System

Abstract

An object of a system according to an embodiment is to enable a user to easily find an optimal plan for a trip or a business trip and make a reservation.SOLUTION: A system according to an embodiment includes a user information input unit, a plan suggestion unit, and a reservation unit. The user information input unit inputs user information. The plan proposal unit proposes an optimal plan on the basis of the user information input by the user information input unit. The reservation unit reserves the transportation facility or the accommodation facility based on the plan proposed by the plan proposal unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] With conventional technology, when planning a trip or business trip, users had to personally search through multiple pieces of information to find the optimal plan, which was a time-consuming process.

[0005] The system according to the embodiment aims to enable users to easily find and book the most suitable travel or business trip plan. [Means for solving the problem]

[0006] The system according to the embodiment includes a user information input unit, a plan proposal unit, and a reservation unit. The user information input unit inputs user information. The plan proposal unit proposes an optimal plan based on the user information input by the user information input unit. The reservation unit makes reservations for transportation and accommodations based on the plan proposed by the plan proposal unit. [Effects of the Invention]

[0007] The system according to the embodiment allows users to easily find and book the most suitable travel or business trip plan. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

[0028] (Example 1) The travel plan proposal system according to an embodiment of the present invention is a system that proposes recommended plans when a user plans a trip simply by inputting the necessary information, and also makes all-in-one reservations for transportation, hotels, rental cars, etc. This allows the user to obtain the optimal travel plan without any hassle, and allows all-in-one operations from planning to booking the trip.

[0029] A travel plan proposal system according to an embodiment includes a user information input unit, a plan proposal unit, and a reservation unit. The user information input unit inputs user information. For example, the user inputs information such as desired destinations, dates, number of participants, attributes, preferences, and desired budget. The plan proposal unit proposes an optimal plan based on the user information input by the user information input unit. For example, the generation AI proposes a list of tourist spots and a schedule that matches the date based on the user's input information. The generation AI can also propose activities and facilities based on the participants' attributes. Furthermore, the generation AI proposes a travel style based on the user's preferences and accommodations and transportation options based on the user's desired budget. The reservation unit makes reservations for transportation and accommodations based on the plan proposed by the plan proposal unit. For example, the generation AI automatically reserves airplane and train tickets, hotels and inns, rental cars, and admission tickets and activities for tourist attractions. As a result, the travel plan proposal system according to an embodiment allows users to easily obtain an optimal travel plan and perform everything from travel planning to reservations in one go.

[0030] The user information input unit can automatically acquire the user's past travel history and preferences and propose more personalized plans. The user information input unit, for example, automatically acquires data on travel destinations and accommodations visited by the user in the past and proposes plans that reflect similar preferences. For example, for a user who has previously visited hot springs, plans that include hot springs are preferentially proposed. Furthermore, based on the user's past travel history, favorite activities and tourist spots are automatically extracted and plans are generated based on them. For example, for a user who has previously enjoyed hiking, a plan that includes hiking trails is proposed. Furthermore, from the user's past travel history, the unit automatically acquires the user's favorite accommodation type (e.g., hotel, inn, guesthouse) and proposes accommodation based on that. For example, for a user who has frequently stayed in hotels in the past, a plan centered around a hotel is proposed. This makes it possible to propose more personalized plans based on the user's past travel history and preferences.

[0031] The user information input unit can link with the user's social media account, analyze the user's travel preferences and interests from the posted content and photos, and reflect them in the plan. The user information input unit, for example, analyzes travel photos and comments posted from the user's social media account to identify the user's preferred travel style and interests. For example, for a user with many beach photos, a plan including a beach resort is proposed. The unit also analyzes the content of social media posts to extract tourist spots and activities that the user is interested in. For example, if the user posts many mountain photos, a plan including mountainous areas is proposed. The unit also identifies places visited in the past and preferred travel destinations based on the user's social media check-in history, and generates a plan based on them. For example, if the user has visited many cities, a plan centered on city sightseeing is proposed. In this way, the user's travel preferences and interests can be analyzed from the user's social media account and reflected in the plan.

[0032] The user information input unit uses voice recognition technology to input user information, thereby improving the convenience of voice input. The user information input unit allows a user to input information such as a desired destination, dates, and number of participants by voice, and converts the information into text using voice recognition technology. For example, a user may input "I want to go to Tokyo, the date is next weekend, and there will be four participants" by voice. The voice recognition technology also allows the user to input detailed information such as preferences and budget by voice. For example, a user may input "My budget is within 100,000 yen, and I want to have active fun." In addition, to improve the convenience of voice input, the voice recognition technology is enhanced to support multiple languages ​​and dialects. For example, multilingual support such as English and Chinese is provided. This allows user information to be input using voice recognition technology, thereby improving the convenience of voice input.

[0033] The user information input unit can display reviews and ratings from other users in real time for the information entered by the user, allowing the user to refer to them. For example, when a user enters a place they want to go, the user information input unit displays reviews and ratings from other users for that place in real time. For example, a review such as "This tourist spot is recommended for families" is displayed. Furthermore, when a user selects accommodation, other users' ratings and comments are displayed in real time for the user's reference. For example, a rating such as "This hotel is clean and has good service" is displayed. Furthermore, when a user selects an activity, other users' experiences and ratings are displayed in real time for the user's reference. For example, a rating such as "The guide on this tour was kind and fun" is displayed. In this way, other users' reviews and ratings can be displayed in real time for the information entered by the user, allowing the user to refer to them.

[0034] The plan proposal unit can reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, the plan proposal unit allows users to input real-time feedback on plans proposed by the generation AI, and instantly modify and optimize the plans based on that feedback. For example, if the user provides feedback such as "I'm not interested in this tourist destination," the unit will suggest a different tourist destination. The system also collects user feedback in real time and builds a system in which the generation AI optimizes plans based on that data. For example, if the user provides feedback such as "I would prefer a more active plan," the system will increase activity. The system also provides a function to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, if the user provides feedback such as "I'm over budget, please suggest cheaper accommodations," the system will suggest accommodations within the user's budget. This allows the system to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans.

[0035] The plan suggestion unit can display ratings for proposed plans based on past user satisfaction data to increase reliability. The plan suggestion unit, for example, displays ratings for plans proposed by the generation AI based on past user satisfaction data. For example, it displays a rating such as "90% of users were satisfied with this plan in the past." It also displays a satisfaction score for proposed plans based on past user feedback and ratings to increase reliability. For example, it displays information such as "This accommodation has received high ratings in the past." It also displays ratings for plans proposed by the generation AI based on past user satisfaction data to allow users to make selections with confidence. For example, it displays a rating such as "Many users have enjoyed this activity in the past." This allows ratings for proposed plans based on past user satisfaction data to increase reliability.

[0036] The plan proposal unit can present multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options. For example, the plan proposal unit presents multiple variations of the plan proposed by the generation AI according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a relaxed plan, an active plan, and a balanced plan, are presented. In addition, a system is constructed that displays multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a budget-oriented plan, a time-oriented plan, and an experience-oriented plan, are presented. In addition, a function is provided that presents multiple variations of the plan proposed by the generation AI according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a plan for families, a plan for couples, and a plan for friends, are presented. This makes it possible to present multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options.

[0037] The plan proposal unit can reflect local weather and event information in real time in the plans proposed by the generation AI. The plan proposal unit, for example, reflects local weather information in real time in the plans proposed by the generation AI. For example, it proposes indoor activities when it rains, and outdoor activities when it is sunny. It also collects local event information in real time and reflects it in the plans proposed by the generation AI. For example, it incorporates local festivals and concerts into the plans. It also builds a system that reflects local weather and event information in real time in the plans proposed by the generation AI. For example, it automatically adjusts the plans according to changes in weather and events. This makes it possible to reflect local weather and event information in real time in the plans proposed by the generation AI.

[0038] The reservation unit can automatically suggest optimal options during the reservation process, taking into account the user's past reservation history and preferences. The reservation unit, for example, automatically suggests preferred means of transportation and accommodation based on the user's past reservation history. For example, it prioritizes suggestions of airlines and hotel chains that have been used in the past. It also automatically obtains preferred seat types and room types from the user's past reservation history and suggests options based on them. For example, it suggests business class seats to a user who has used business class in the past. It also builds a system that automatically suggests optimal options taking into account the user's past reservation history. For example, it suggests similar options based on rental car companies and car models that have been used in the past. This makes it possible to automatically suggest optimal options during the reservation process, taking into account the user's past reservation history and preferences.

[0039] The reservation unit can search across multiple reservation sites and services when making a reservation and present the most cost-effective option. The reservation unit builds a system that, for example, searches across multiple reservation sites and services when making a reservation and presents the most cost-effective option. For example, it compares airfare and hotel prices and presents the lowest price. It also searches across multiple reservation sites and services based on the user's desired conditions and automatically suggests the most cost-effective option. For example, it suggests the most highly rated accommodation within the desired budget. It also provides a function that searches across multiple reservation sites and services during the reservation process and presents the most cost-effective option. For example, it compares rental car prices and conditions and presents the optimal option. This makes it possible to search across multiple reservation sites and services when making a reservation and present the most cost-effective option.

[0040] The reservation unit can display other users' reviews and ratings of the transportation and accommodation selected by the user in real time during the reservation process. The reservation unit, for example, builds a system that displays other users' reviews and ratings of the transportation and accommodation selected by the user in real time. For example, it displays a rating such as "This hotel is clean and has good service." Furthermore, during the reservation process, other users' reviews and ratings of the transportation and accommodation selected by the user can be displayed in real time for reference. For example, it displays a review such as "This airline runs on time." Furthermore, a function is provided that displays other users' reviews and ratings of the transportation and accommodation selected by the user in real time. For example, it displays a rating such as "This rental car company is quick and friendly." This makes it possible to display other users' reviews and ratings of the transportation and accommodation selected by the user in real time during the reservation process.

[0041] The reservation unit can suggest additional options (e.g., travel insurance, local tours) related to the plan selected by the user during the reservation process. The reservation unit, for example, builds a system that suggests additional options related to the plan selected by the user during the reservation process. For example, it displays options for travel insurance and local tours. It also suggests additional options related to the plan selected by the user to improve travel convenience. For example, it suggests options for car navigation systems and child seats when reserving a rental car. It also provides a function that suggests additional options related to the plan selected by the user during the reservation process. For example, it displays options for breakfast plans and spa services when reserving a hotel. This makes it possible to suggest additional options related to the plan selected by the user during the reservation process.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The user information input unit can also suggest travel plans based on the user's health condition and physical condition. For example, the user can link with a health management app to obtain data on their current health condition and physical condition. As a result, if the user easily gets tired, a relaxing plan can be suggested. If the user prefers an active lifestyle, a plan including hiking or sports activities can be suggested. Furthermore, if the user has specific dietary restrictions, restaurants and meal plans that accommodate those restrictions can be suggested. This makes it possible to provide more personalized travel plans based on the user's health condition and physical condition.

[0044] The user information input unit can also suggest travel plans based on the user's hobbies and interests. For example, if the user likes music, a plan including local music festivals and live events can be suggested. If the user is interested in history, a plan including historical tourist spots and museums can be suggested. Furthermore, if the user likes outdoor activities, a plan including camping and trekking can be suggested. This makes it possible to provide more attractive travel plans based on the user's hobbies and interests.

[0045] The user information input unit can also suggest travel plans based on the user's family structure and life stage. For example, if the user is a family with small children, a plan including activities and facilities for children can be suggested. If the user is planning a honeymoon, a plan including romantic destinations and activities for couples can be suggested. Furthermore, if the user is a senior citizen, a plan including tourist spots and accommodations that can be enjoyed at a leisurely pace can be suggested. This makes it possible to provide more appropriate travel plans based on the user's family structure and life stage.

[0046] The user information input unit can automatically acquire the user's past travel history and preferences and propose more personalized plans. For example, the unit can automatically acquire data on travel destinations and accommodations visited by the user in the past and propose plans that reflect similar preferences. For example, for a user who has previously enjoyed hot springs, plans that include hot springs are preferentially proposed. In addition, the unit can automatically extract preferred activities and tourist spots based on the user's past travel history and generate plans based on them. For example, for a user who has previously enjoyed hiking, a plan that includes hiking trails is proposed. In addition, the unit can automatically acquire the user's preferred accommodation type (e.g., hotel, inn, or guesthouse) from the user's past travel history and propose accommodations based on that. For example, for a user who has frequently stayed in hotels in the past, a plan centered around a hotel is proposed. This makes it possible to propose more personalized plans based on the user's past travel history and preferences.

[0047] The user information input unit can link with the user's social media account, analyze the user's travel preferences and interests from the posted content and photos, and reflect them in the plan. For example, the unit can analyze travel photos and comments posted from the user's social media account to identify the user's preferred travel style and interests. For example, for a user with many beach photos, a plan including a beach resort can be suggested. The unit can also analyze the content of social media posts to extract tourist spots and activities that the user is interested in. For example, if the user posts many mountain photos, a plan including mountainous areas can be suggested. The unit can also identify places visited in the past and preferred travel destinations based on the user's social media check-in history and generate a plan based on that. For example, if the user has visited many cities, a plan centered on city sightseeing can be suggested. In this way, the user's travel preferences and interests can be analyzed from the user's social media account and reflected in the plan.

[0048] The plan proposal unit can reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, the system allows users to input real-time feedback on plans proposed by the generation AI, and the plans are instantly modified and optimized based on that feedback. For example, if the user provides feedback such as "I'm not interested in this tourist destination," the system will suggest a different tourist destination. The system also collects user feedback in real time and builds a system in which the generation AI optimizes plans based on that data. For example, if the user provides feedback such as "I would prefer a more active plan," the system will increase activity. The system also provides a function to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, if the user provides feedback such as "I'm over budget, please suggest cheaper accommodations," the system will suggest accommodations within the user's budget. This allows the system to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans.

[0049] The plan suggestion unit can display ratings for proposed plans based on past user satisfaction data to increase reliability. For example, for plans proposed by the generation AI, ratings based on past user satisfaction data are displayed. For example, a rating such as "90% of users were satisfied with this plan in the past" is displayed. In addition, a satisfaction score based on past user feedback and ratings is displayed for proposed plans to increase reliability. For example, information such as "This accommodation has received high ratings in the past" is displayed. In addition, ratings based on past user satisfaction data are displayed for plans proposed by the generation AI to allow users to make selections with confidence. For example, a rating such as "Many users have enjoyed this activity in the past" is displayed. In this way, ratings based on past user satisfaction data are displayed for proposed plans to increase reliability.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The user information input unit inputs user information, such as the desired destination, schedule, number of participants, attributes, preferences, and desired budget. Step 2: The plan suggestion unit proposes the optimal plan based on the user information entered by the user information input unit. For example, the generation AI proposes a list of tourist spots and a schedule that matches the date based on the information entered by the user. The generation AI can also suggest activities and facilities based on the attributes of the participants. Furthermore, the generation AI suggests a travel style that matches the user's preferences, as well as accommodation and transportation options that match the desired budget. Step 3: The reservation unit makes reservations for transportation and accommodation based on the plan proposed by the plan proposal unit. For example, the generation AI automatically makes reservations for plane and train tickets, hotels and inns, rental cars, and admission tickets and activities at tourist attractions.

[0052] (Example 2) The travel plan proposal system according to an embodiment of the present invention is a system that proposes recommended plans when a user plans a trip simply by inputting the necessary information, and also makes all-in-one reservations for transportation, hotels, rental cars, etc. This allows the user to obtain the optimal travel plan without any hassle, and allows all-in-one operations from planning to booking the trip.

[0053] A travel plan proposal system according to an embodiment includes a user information input unit, a plan proposal unit, and a reservation unit. The user information input unit inputs user information. For example, the user inputs information such as desired destinations, dates, number of participants, attributes, preferences, and desired budget. The plan proposal unit proposes an optimal plan based on the user information input by the user information input unit. For example, the generation AI proposes a list of tourist spots and a schedule that matches the date based on the user's input information. The generation AI can also propose activities and facilities based on the participants' attributes. Furthermore, the generation AI proposes a travel style based on the user's preferences and accommodations and transportation options based on the user's desired budget. The reservation unit makes reservations for transportation and accommodations based on the plan proposed by the plan proposal unit. For example, the generation AI automatically reserves airplane and train tickets, hotels and inns, rental cars, and admission tickets and activities for tourist attractions. As a result, the travel plan proposal system according to an embodiment allows users to easily obtain an optimal travel plan and perform everything from travel planning to reservations in one go.

[0054] The user information input unit can automatically acquire the user's past travel history and preferences and propose more personalized plans. The user information input unit, for example, automatically acquires data on travel destinations and accommodations visited by the user in the past and proposes plans that reflect similar preferences. For example, for a user who has previously visited hot springs, plans that include hot springs are preferentially proposed. Furthermore, based on the user's past travel history, favorite activities and tourist spots are automatically extracted and plans are generated based on them. For example, for a user who has previously enjoyed hiking, a plan that includes hiking trails is proposed. Furthermore, from the user's past travel history, the unit automatically acquires the user's favorite accommodation type (e.g., hotel, inn, guesthouse) and proposes accommodation based on that. For example, for a user who has frequently stayed in hotels in the past, a plan centered around a hotel is proposed. This makes it possible to propose more personalized plans based on the user's past travel history and preferences.

[0055] The user information input unit can link with the user's social media account, analyze the user's travel preferences and interests from the posted content and photos, and reflect them in the plan. The user information input unit, for example, analyzes travel photos and comments posted from the user's social media account to identify the user's preferred travel style and interests. For example, for a user with many beach photos, a plan including a beach resort is proposed. The unit also analyzes the content of social media posts to extract tourist spots and activities that the user is interested in. For example, if the user posts many mountain photos, a plan including mountainous areas is proposed. The unit also identifies places visited in the past and preferred travel destinations based on the user's social media check-in history, and generates a plan based on them. For example, if the user has visited many cities, a plan centered on city sightseeing is proposed. In this way, the user's travel preferences and interests can be analyzed from the user's social media account and reflected in the plan.

[0056] The user information input unit uses the emotion estimation function to analyze the emotions felt by the user while inputting information in real time, and can make suggestions to simplify input if the user is feeling stressed. The user information input unit, for example, analyzes facial expressions and voice tones when the user is inputting information, and can make suggestions to reduce the number of input items if the user is feeling stressed. For example, a simplified mode is provided in which only the minimum amount of information is input. The emotion estimation function is also used to analyze the emotions felt by the user while inputting information in real time, and can enhance the auto-completion function if the user is feeling stressed. For example, auto-completion is performed based on past input history. Furthermore, if the user is feeling stressed while inputting information, the interface is changed based on the emotion estimation data, and suggestions to simplify input are made. For example, by narrowing down and displaying options, the effort required for input is reduced. This makes it possible to analyze the emotions felt by the user while inputting information in real time, and can make suggestions to simplify input if the user is feeling stressed.

[0057] The user information input unit uses voice recognition technology to input user information, thereby improving the convenience of voice input. The user information input unit allows a user to input information such as a desired destination, dates, and number of participants by voice, and converts the information into text using voice recognition technology. For example, a user may input "I want to go to Tokyo, the date is next weekend, and there will be four participants" by voice. The voice recognition technology also allows the user to input detailed information such as preferences and budget by voice. For example, a user may input "My budget is within 100,000 yen, and I want to have active fun." In addition, to improve the convenience of voice input, the voice recognition technology is enhanced to support multiple languages ​​and dialects. For example, multilingual support such as English and Chinese is provided. This allows user information to be input using voice recognition technology, thereby improving the convenience of voice input.

[0058] The user information input unit can display reviews and ratings from other users in real time for the information entered by the user, allowing the user to refer to them. For example, when a user enters a place they want to go, the user information input unit displays reviews and ratings from other users for that place in real time. For example, a review such as "This tourist spot is recommended for families" is displayed. Furthermore, when a user selects accommodation, other users' ratings and comments are displayed in real time for the user's reference. For example, a rating such as "This hotel is clean and has good service" is displayed. Furthermore, when a user selects an activity, other users' experiences and ratings are displayed in real time for the user's reference. For example, a rating such as "The guide on this tour was kind and fun" is displayed. In this way, other users' reviews and ratings can be displayed in real time for the information entered by the user, allowing the user to refer to them.

[0059] The user information input unit can use the emotion estimation function to analyze the emotions felt by the user when entering data and propose an interface design that elicits positive emotions. The user information input unit, for example, uses the emotion estimation function to analyze the emotions felt by the user while entering data in real time and propose an interface design that elicits positive emotions. For example, it displays bright colors and encouraging messages. It also adjusts the interface layout and design based on the emotion estimation data so that the user feels positive emotions while entering data. For example, it provides customizable themes tailored to the user's preferences. It also uses the emotion estimation function to propose an interface design that reduces the stress felt by the user while entering data and elicits positive emotions. For example, it displays a guide message to ensure smooth entry. This makes it possible to analyze the emotions felt by the user when entering data and propose an interface design that elicits positive emotions.

[0060] The plan proposal unit can reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, the plan proposal unit allows users to input real-time feedback on plans proposed by the generation AI, and instantly modify and optimize the plans based on that feedback. For example, if the user provides feedback such as "I'm not interested in this tourist destination," the unit will suggest a different tourist destination. The system also collects user feedback in real time and builds a system in which the generation AI optimizes plans based on that data. For example, if the user provides feedback such as "I would prefer a more active plan," the system will increase activity. The system also provides a function to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, if the user provides feedback such as "I'm over budget, please suggest cheaper accommodations," the system will suggest accommodations within the user's budget. This allows the system to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans.

[0061] The plan suggestion unit can display ratings for proposed plans based on past user satisfaction data to increase reliability. The plan suggestion unit, for example, displays ratings for plans proposed by the generation AI based on past user satisfaction data. For example, it displays a rating such as "90% of users were satisfied with this plan in the past." It also displays a satisfaction score for proposed plans based on past user feedback and ratings to increase reliability. For example, it displays information such as "This accommodation has received high ratings in the past." It also displays ratings for plans proposed by the generation AI based on past user satisfaction data to allow users to make selections with confidence. For example, it displays a rating such as "Many users have enjoyed this activity in the past." This allows ratings for proposed plans based on past user satisfaction data to increase reliability.

[0062] The plan proposal unit can use the emotion estimation function to analyze the user's emotional response to the proposed plan and adjust the plan to obtain a positive response. The plan proposal unit, for example, uses the emotion estimation function to analyze the user's emotional response to the proposed plan in real time and adjust the plan to obtain a positive response. For example, if the user is excited, the plan proposal unit increases the number of activities. Furthermore, the proposed plan is adjusted based on the user's emotional response data to obtain a positive response. For example, if the user feels like relaxing, a relaxing activity is added. Furthermore, a system is constructed that uses the emotion estimation function to analyze the user's emotional response to the proposed plan and adjust the plan to obtain a positive response. For example, if the user feels like having fun, similar activities are increased. In this way, the user's emotional response to the proposed plan can be analyzed and the plan can be adjusted to obtain a positive response.

[0063] The plan proposal unit can present multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options. For example, the plan proposal unit presents multiple variations of the plan proposed by the generation AI according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a relaxed plan, an active plan, and a balanced plan, are presented. In addition, a system is constructed that displays multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a budget-oriented plan, a time-oriented plan, and an experience-oriented plan, are presented. In addition, a function is provided that presents multiple variations of the plan proposed by the generation AI according to the user's preferences, thereby increasing the number of options. For example, three variations, namely, a plan for families, a plan for couples, and a plan for friends, are presented. This makes it possible to present multiple variations of the proposed plan according to the user's preferences, thereby increasing the number of options.

[0064] The plan proposal unit can reflect local weather and event information in real time in the plans proposed by the generation AI. The plan proposal unit, for example, reflects local weather information in real time in the plans proposed by the generation AI. For example, it proposes indoor activities when it rains, and outdoor activities when it is sunny. It also collects local event information in real time and reflects it in the plans proposed by the generation AI. For example, it incorporates local festivals and concerts into the plans. It also builds a system that reflects local weather and event information in real time in the plans proposed by the generation AI. For example, it automatically adjusts the plans according to changes in weather and events. This makes it possible to reflect local weather and event information in real time in the plans proposed by the generation AI.

[0065] The plan suggestion unit can use the emotion estimation function to identify the plan in which the user is most interested and suggest additional information and options related to the plan. For example, the plan suggestion unit uses the emotion estimation function to identify the plan in which the user is most interested and suggest additional information and options related to the plan. For example, it suggests special tours and events related to tourist destinations in which the user has shown interest. Furthermore, a system is constructed that identifies the plan in which the user is most interested and provides additional information and options related to the plan based on the user's emotional response data. For example, it suggests equipment and guide services related to activities in which the user has shown interest. Furthermore, a function is provided that uses the emotion estimation function to identify the plan in which the user is most interested and suggest additional information and options related to the plan. For example, it suggests special dinners and spa services related to accommodations in which the user has shown interest. In this way, it is possible to identify the plan in which the user is most interested and suggest additional information and options related to the plan.

[0066] The reservation unit can automatically suggest optimal options during the reservation process, taking into account the user's past reservation history and preferences. The reservation unit, for example, automatically suggests preferred means of transportation and accommodation based on the user's past reservation history. For example, it prioritizes suggestions of airlines and hotel chains that have been used in the past. It also automatically obtains preferred seat types and room types from the user's past reservation history and suggests options based on them. For example, it suggests business class seats to a user who has used business class in the past. It also builds a system that automatically suggests optimal options taking into account the user's past reservation history. For example, it suggests similar options based on rental car companies and car models that have been used in the past. This makes it possible to automatically suggest optimal options during the reservation process, taking into account the user's past reservation history and preferences.

[0067] The reservation unit can search across multiple reservation sites and services when making a reservation and present the most cost-effective option. The reservation unit builds a system that, for example, searches across multiple reservation sites and services when making a reservation and presents the most cost-effective option. For example, it compares airfare and hotel prices and presents the lowest price. It also searches across multiple reservation sites and services based on the user's desired conditions and automatically suggests the most cost-effective option. For example, it suggests the most highly rated accommodation within the desired budget. It also provides a function that searches across multiple reservation sites and services during the reservation process and presents the most cost-effective option. For example, it compares rental car prices and conditions and presents the optimal option. This makes it possible to search across multiple reservation sites and services when making a reservation and present the most cost-effective option.

[0068] The reservation unit can use the emotion estimation function to analyze the user's emotions during the reservation procedure and make suggestions to simplify the procedure if the user is feeling stressed. The reservation unit, for example, uses the emotion estimation function to analyze the user's emotions during the reservation procedure in real time and make suggestions to simplify the procedure if the user is feeling stressed. For example, a simplified mode is provided in which only the minimum necessary information is entered. Furthermore, if the user is feeling stressed during the reservation procedure, the interface is changed based on the emotion estimation data to make suggestions to simplify the procedure. For example, by narrowing down and displaying options, the effort required for input is reduced. Furthermore, the emotion estimation function is used to analyze the user's emotions during the reservation procedure and enhance the auto-complete function if the user is feeling stressed. For example, auto-complete is performed based on past reservation history. In this way, the reservation unit can analyze the user's emotions during the reservation procedure and make suggestions to simplify the procedure if the user is feeling stressed.

[0069] The reservation unit can display other users' reviews and ratings of the transportation and accommodation selected by the user in real time during the reservation process. The reservation unit, for example, builds a system that displays other users' reviews and ratings of the transportation and accommodation selected by the user in real time. For example, it displays a rating such as "This hotel is clean and has good service." Furthermore, during the reservation process, other users' reviews and ratings of the transportation and accommodation selected by the user can be displayed in real time for reference. For example, it displays a review such as "This airline runs on time." Furthermore, a function is provided that displays other users' reviews and ratings of the transportation and accommodation selected by the user in real time. For example, it displays a rating such as "This rental car company is quick and friendly." This makes it possible to display other users' reviews and ratings of the transportation and accommodation selected by the user in real time during the reservation process.

[0070] The reservation unit can suggest additional options (e.g., travel insurance, local tours) related to the plan selected by the user during the reservation process. The reservation unit, for example, builds a system that suggests additional options related to the plan selected by the user during the reservation process. For example, it displays options for travel insurance and local tours. It also suggests additional options related to the plan selected by the user to improve travel convenience. For example, it suggests options for car navigation systems and child seats when reserving a rental car. It also provides a function that suggests additional options related to the plan selected by the user during the reservation process. For example, it displays options for breakfast plans and spa services when reserving a hotel. This makes it possible to suggest additional options related to the plan selected by the user during the reservation process.

[0071] The reservation unit can use the emotion estimation function to analyze the user's emotions during the reservation procedure and propose an interface design that elicits positive emotions. The reservation unit, for example, uses the emotion estimation function to analyze the user's emotions during the reservation procedure in real time and propose an interface design that elicits positive emotions. For example, it displays bright colors and encouraging messages. It also adjusts the interface layout and design based on the emotion estimation data so that the user feels positive emotions during the reservation procedure. For example, it provides customizable themes that match the user's preferences. It also uses the emotion estimation function to build a system that analyzes the user's emotions during the reservation procedure and proposes an interface design that elicits positive emotions. For example, it displays a guide message to ensure smooth input. This makes it possible to analyze the user's emotions during the reservation procedure and propose an interface design that elicits positive emotions.

[0072] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0073] The user information input unit can also suggest travel plans based on the user's health condition and physical condition. For example, the user can link with a health management app to obtain data on their current health condition and physical condition. As a result, if the user easily gets tired, a relaxing plan can be suggested. If the user prefers an active lifestyle, a plan including hiking or sports activities can be suggested. Furthermore, if the user has specific dietary restrictions, restaurants and meal plans that accommodate those restrictions can be suggested. This makes it possible to provide more personalized travel plans based on the user's health condition and physical condition.

[0074] The user information input unit can also suggest travel plans based on the user's hobbies and interests. For example, if the user likes music, a plan including local music festivals and live events can be suggested. If the user is interested in history, a plan including historical tourist spots and museums can be suggested. Furthermore, if the user likes outdoor activities, a plan including camping and trekking can be suggested. This makes it possible to provide more attractive travel plans based on the user's hobbies and interests.

[0075] The user information input unit can also suggest travel plans based on the user's family structure and life stage. For example, if the user is a family with small children, a plan including activities and facilities for children can be suggested. If the user is planning a honeymoon, a plan including romantic destinations and activities for couples can be suggested. Furthermore, if the user is a senior citizen, a plan including tourist spots and accommodations that can be enjoyed at a leisurely pace can be suggested. This makes it possible to provide more appropriate travel plans based on the user's family structure and life stage.

[0076] The user information input unit can automatically acquire the user's past travel history and preferences and propose more personalized plans. For example, the unit can automatically acquire data on travel destinations and accommodations visited by the user in the past and propose plans that reflect similar preferences. For example, for a user who has previously enjoyed hot springs, plans that include hot springs are preferentially proposed. In addition, the unit can automatically extract preferred activities and tourist spots based on the user's past travel history and generate plans based on them. For example, for a user who has previously enjoyed hiking, a plan that includes hiking trails is proposed. In addition, the unit can automatically acquire the user's preferred accommodation type (e.g., hotel, inn, or guesthouse) from the user's past travel history and propose accommodations based on that. For example, for a user who has frequently stayed in hotels in the past, a plan centered around a hotel is proposed. This makes it possible to propose more personalized plans based on the user's past travel history and preferences.

[0077] The user information input unit can link with the user's social media account, analyze the user's travel preferences and interests from the posted content and photos, and reflect them in the plan. For example, the unit can analyze travel photos and comments posted from the user's social media account to identify the user's preferred travel style and interests. For example, for a user with many beach photos, a plan including a beach resort can be suggested. The unit can also analyze the content of social media posts to extract tourist spots and activities that the user is interested in. For example, if the user posts many mountain photos, a plan including mountainous areas can be suggested. The unit can also identify places visited in the past and preferred travel destinations based on the user's social media check-in history and generate a plan based on that. For example, if the user has visited many cities, a plan centered on city sightseeing can be suggested. In this way, the user's travel preferences and interests can be analyzed from the user's social media account and reflected in the plan.

[0078] The user information input unit can use the emotion estimation function to analyze the emotions felt by the user while inputting information in real time, and make suggestions to simplify input if the user is feeling stressed. For example, when the user is inputting information, the unit analyzes facial expressions and voice tone, and makes suggestions to reduce the number of input items if the user is feeling stressed. For example, a simplified mode is provided in which only the minimum amount of information is input. The emotion estimation function can also be used to analyze the emotions felt by the user while inputting information in real time, and if the user is feeling stressed, the unit enhances the auto-completion function. For example, auto-completion is performed based on past input history. Furthermore, if the user is feeling stressed while inputting information, the unit changes the interface based on the emotion estimation data and makes suggestions to simplify input. For example, by narrowing down and displaying options, the effort required for input is reduced. This makes it possible to analyze the emotions felt by the user while inputting information in real time, and make suggestions to simplify input if the user is feeling stressed.

[0079] The user information input unit can use the emotion estimation function to analyze the emotions felt by the user when entering text and propose an interface design that elicits positive emotions. For example, the emotion estimation function can be used to analyze the emotions felt by the user while entering text in real time and propose an interface design that elicits positive emotions. For example, bright colors or encouraging messages can be displayed. The interface layout and design can also be adjusted based on the emotion estimation data so that the user feels positive emotions while entering text. For example, customizable themes can be provided to suit the user's preferences. The emotion estimation function can also be used to propose an interface design that reduces the stress felt by the user while entering text and elicits positive emotions. For example, a guide message can be displayed to ensure smooth entry. This makes it possible to analyze the emotions felt by the user when entering text and propose an interface design that elicits positive emotions.

[0080] The plan proposal unit can reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, the system allows users to input real-time feedback on plans proposed by the generation AI, and the plans are instantly modified and optimized based on that feedback. For example, if the user provides feedback such as "I'm not interested in this tourist destination," the system will suggest a different tourist destination. The system also collects user feedback in real time and builds a system in which the generation AI optimizes plans based on that data. For example, if the user provides feedback such as "I would prefer a more active plan," the system will increase activity. The system also provides a function to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans. For example, if the user provides feedback such as "I'm over budget, please suggest cheaper accommodations," the system will suggest accommodations within the user's budget. This allows the system to reflect real-time user feedback on plans proposed by the generation AI and instantly modify and optimize the plans.

[0081] The plan suggestion unit can display ratings for proposed plans based on past user satisfaction data to increase reliability. For example, for plans proposed by the generation AI, ratings based on past user satisfaction data are displayed. For example, a rating such as "90% of users were satisfied with this plan in the past" is displayed. In addition, a satisfaction score based on past user feedback and ratings is displayed for proposed plans to increase reliability. For example, information such as "This accommodation has received high ratings in the past" is displayed. In addition, ratings based on past user satisfaction data are displayed for plans proposed by the generation AI to allow users to make selections with confidence. For example, a rating such as "Many users have enjoyed this activity in the past" is displayed. In this way, ratings based on past user satisfaction data are displayed for proposed plans to increase reliability.

[0082] The plan suggestion unit can use the emotion estimation function to analyze the user's emotional response to the proposed plan and adjust the plan to obtain a positive response. For example, the emotion estimation function can be used to analyze the user's emotional response to the proposed plan in real time and adjust the plan to obtain a positive response. For example, if the user is excited, the system can increase the number of activities. Furthermore, the system can adjust the proposed plan based on the user's emotional response data to obtain a positive response. For example, if the user feels like relaxing, the system can add a relaxing activity. Furthermore, the system can use the emotion estimation function to analyze the user's emotional response to the proposed plan and adjust the plan to obtain a positive response. For example, if the user feels like having fun, the system can increase similar activities. In this way, the system can analyze the user's emotional response to the proposed plan and adjust the plan to obtain a positive response.

[0083] The processing flow of the second embodiment will be briefly explained below.

[0084] Step 1: The user information input unit inputs user information, such as the desired destination, schedule, number of participants, attributes, preferences, and desired budget. Step 2: The plan suggestion unit proposes the optimal plan based on the user information entered by the user information input unit. For example, the generation AI proposes a list of tourist spots and a schedule that matches the date based on the information entered by the user. The generation AI can also suggest activities and facilities based on the attributes of the participants. Furthermore, the generation AI suggests a travel style that matches the user's preferences, as well as accommodation and transportation options that match the desired budget. Step 3: The reservation unit makes reservations for transportation and accommodation based on the plan proposed by the plan proposal unit. For example, the generation AI automatically makes reservations for plane and train tickets, hotels and inns, rental cars, and admission tickets and activities at tourist attractions.

[0085] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0086] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0087] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0088] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0089] 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.

[0090] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0091] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0092] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0093] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0094] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0095] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0096] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0097] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0098] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0099] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0100] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0101] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0102] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0103] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0104] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0106] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0107] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0110] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0111] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0113] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0114] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0115] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0118] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0119] 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.

[0120] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0121] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0122] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0124] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0125] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0126] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0127] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0129] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0130] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0131] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0132] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0133] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0134] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0135] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0136] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0137] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0138] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0139] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0140] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0141] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0142] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0143] 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.

[0144] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0145] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0146] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0147] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0148] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0149] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0150] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0151] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0152] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. a user information input unit for inputting user information; a plan proposal unit that proposes an optimal plan based on the user information input by the user information input unit; a reservation unit that makes reservations for transportation and accommodation facilities based on the plan proposed by the plan proposal unit. A system characterized by:

2. The user information input unit Automatically captures users' past travel history and preferences to suggest more personalized plans 2. The system of claim 1.

3. The user information input unit Linking with users' social media accounts, analyzing travel preferences and interests from posts and photos and reflecting them in plans 2. The system of claim 1.

4. The user information input unit Analyzes the user's emotions in real time while they are typing, and suggests ways to simplify input if they are feeling stressed.

2. The system of claim 1.

5. The user information input unit Use voice recognition technology to input user information, improving convenience through voice input 2. The system of claim 1.

6. The user information input unit For the information entered by the user, reviews and ratings from other users are displayed in real time for reference.

2. The system of claim 1.

7. The user information input unit Analyzing the emotions users feel when typing and proposing interface designs that elicit positive emotions 2. The system of claim 1.

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