System

Abstract

An object of a system according to an embodiment is to easily create a travel plan suitable for a user's preference and update the travel plan in real time.SOLUTION: A system according to an embodiment includes a user attribute input unit, an itinerary generation unit, a proposal unit, a change update unit, a list-up unit, an information provision unit, and an information storage unit. The user attribute input unit inputs attributes and preferences of the user. The itinerary generation unit generates an itinerary on the basis of information input by the user attribute input unit. The proposal unit proposes the itinerary generated by the itinerary generation unit to the user. The change updating unit updates the itinerary in real time in response to a change request from the user. The list-up section lists up what is necessary by the day and what is necessary on the day. The information providing unit provides information on a travel destination before a travel. The information storage unit stores information after the travel.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] Conventional technologies have had the problem that it is difficult for users to easily create travel plans that suit their preferences and update them in real time.

[0005] The system according to the embodiment aims to enable a user to easily create a travel plan that matches their preferences and update it in real time. [Means for solving the problem]

[0006] The system according to the embodiment includes a user attribute input unit, an itinerary generation unit, a proposal unit, a change / update unit, a list unit, an information provision unit, and an information storage unit. The user attribute input unit inputs the user's attributes and preferences. The itinerary generation unit generates an itinerary based on the information input by the user attribute input unit. The proposal unit proposes the itinerary generated by the itinerary generation unit to the user. The change / update unit updates the itinerary in real time in response to a change request from the user. The list unit lists things that need to be done by the day of travel and things that need to be done on the day of travel. The information provision unit provides information about the travel destination before the trip. The information storage unit stores information after the trip. [Effects of the Invention]

[0007] The system according to the embodiment allows a user to easily create a travel plan that matches their preferences and update it in real time. [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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[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 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[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 suggestion system according to the embodiment of the present invention is a system that proposes optimal itineraries based on the attributes and preferences of users and updates them in real time, thereby enabling the travel suggestion system to provide travel plans that meet the needs of users.

[0029] A travel suggestion system according to an embodiment includes a user attribute input unit, an itinerary generation unit, a suggestion unit, a change / update unit, a list unit, an information provision unit, and an information storage unit. The user attribute input unit inputs a user's attributes and preferences. For example, the user can input age, gender, hobbies, interests, etc. The user attribute input unit can also analyze the user's past travel history and social media posts to automatically extract detailed preferences and interests. For example, it can collect data on previously visited tourist spots and accommodations and analyze the user's travel patterns. The itinerary generation unit generates an itinerary based on the information input by the user attribute input unit. For example, the generation AI can suggest an itinerary that includes tourist spots and accommodations that match the user's preferences. The itinerary generation unit can also analyze the user's past travel satisfaction and prioritize itineraries that include elements that generated high satisfaction. The suggestion unit suggests the itinerary generated by the itinerary generation unit to the user. For example, the generation AI can tentatively compile multiple itineraries and suggest them with catchy titles. The change update unit updates the itinerary in real time in response to a user's change request. For example, if a user requests, "I want to add this tourist attraction," the generation AI recalculates the optimal route including the new tourist attraction and updates the itinerary. The list unit lists things that need to be done before and on the day of the trip. For example, it creates a list such as "Don't forget your passport" and "Prepare local currency" and notifies the user. The information provision unit provides information about the travel destination before the trip. For example, it provides the user with information such as "The history of the area" and "Recommended local cuisine." The information storage unit stores information after the trip and suggests a new itinerary based on the satisfaction level of past trips. For example, it suggests "a new itinerary including tourist attractions that were highly satisfying on the previous trip." This allows the travel suggestion system according to the embodiment to provide travel plans that meet the user's needs. For example, users can enjoy trips that suit their preferences and easily prepare for their trip. In addition, since the information remains even after the trip, it can be used as a reference for the next trip.

[0030] The user attribute input unit can analyze past travel history and social media posts to automatically extract detailed preferences and interests. The user attribute input unit, for example, analyzes the user's past travel history to extract preferences and interests based on places visited and activities participated in. For example, it collects data on tourist spots and accommodations visited in the past and analyzes the user's travel patterns. The user attribute input unit also analyzes social media posts to extract the user's interests and concerns. For example, it can understand the user's preferences based on the content of the post, the number of likes, comments, etc. By analyzing the user's past travel history and social media posts, it is possible to understand more detailed preferences and interests and propose optimal itineraries.

[0031] The user attribute input unit can suggest appropriate activities and tourist spots by taking into account the user's health condition and physical condition. The user attribute input unit, for example, analyzes the user's health data (e.g., fitness tracker data) and suggests activities that suit their physical condition. For example, based on heart rate and step count data, it suggests light hikes and relaxing tourist spots. The user attribute input unit also builds a system for suggesting appropriate activities and tourist spots by taking into account the user's health condition and physical condition. For example, based on blood pressure and body temperature data, it suggests tourist spots and activities that suit their physical condition. Furthermore, the user attribute input unit develops an algorithm for suggesting appropriate activities and tourist spots by taking into account the user's health condition and physical condition. For example, it suggests tourist spots and activities that suit their physical condition based on the user's health data. In this way, appropriate activities and tourist spots can be suggested by taking into account the user's health condition and physical condition.

[0032] The user attribute input unit also inputs the attributes and preferences of friends and family, and can generate an itinerary that is optimal for a group trip. The user attribute input unit inputs, for example, the attributes (age, gender, hobbies, etc.) of the user's friends and family, and generates an itinerary that suits the preferences of everyone. For example, for a family trip with children, the unit suggests an itinerary that includes activities for the children. The user attribute input unit also inputs the preferences of friends and family, and builds a system for generating an itinerary that is optimal for the entire group. For example, it suggests tourist spots and accommodations that suit the preferences of everyone. Furthermore, the user attribute input unit inputs the attributes and preferences of friends and family, and develops an algorithm for generating an itinerary that is optimal for a group trip. For example, it suggests tourist spots and activities that suit the preferences of everyone. In this way, the optimal itinerary for a group trip can be generated by taking into account the attributes and preferences of the user's friends and family.

[0033] The user attribute input unit can input information about a pet and propose travel plans that allow pets. The user attribute input unit can input, for example, the type, size, and characteristics of the user's pet and propose accommodations and tourist spots that allow pets. For example, for a user who owns a dog, the unit can propose itineraries that include hotels and dog runs that allow dogs. The user attribute input unit can also input information about a pet and build a system for proposing travel plans that allow pets. For example, the unit can propose tourist spots and activities that allow pets. The user attribute input unit can also input information about a pet and develop an algorithm for proposing travel plans that allow pets. For example, the unit can propose accommodations and tourist spots that allow pets. In this way, travel plans that allow pets can be proposed by taking into account the information about the user's pet.

[0034] The itinerary generation unit can analyze past travel satisfaction levels and prioritize itineraries that include elements that generated high satisfaction. The itinerary generation unit, for example, analyzes the user's past travel reviews and ratings and extracts elements that generated high satisfaction. For example, it preferentially proposes itineraries that include elements such as "beautiful scenery" and "delicious food." The itinerary generation unit also analyzes the user's past travel satisfaction levels and builds a system for proposing itineraries that include elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on past travel data and reflects them in the itinerary. Furthermore, the itinerary generation unit analyzes the user's past travel satisfaction levels and develops an algorithm for proposing itineraries that include elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on past travel data and reflects them in the itinerary. In this way, it is possible to prioritize itineraries that include elements that generated high satisfaction by analyzing the user's past travel satisfaction levels.

[0035] The itinerary generation unit can suggest optimal travel times and tourist spots based on seasonal and weather data. The itinerary generation unit, for example, analyzes weather data for each season and suggests optimal travel times. For example, it suggests times that avoid the rainy season or times when the temperature is comfortable. The itinerary generation unit can also suggest optimal tourist spots based on weather data. For example, it suggests outdoor activities during times when there is a lot of sunny weather. Furthermore, the itinerary generation unit builds a system for suggesting optimal travel times and tourist spots based on seasonal and weather data. For example, it suggests optimal travel times and tourist spots based on weather data. In this way, it is possible to suggest optimal travel times and tourist spots based on seasonal and weather data.

[0036] The itinerary generation unit can propose an itinerary that includes appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, the itinerary generation unit inputs the user's dietary restrictions and allergy information and proposes appropriate restaurants and meal plans based on the input. For example, it selects restaurants that have vegetarian or gluten-free options. The itinerary generation unit also builds a system for proposing appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, it proposes appropriate restaurants and meal plans based on the user's dietary restrictions and allergy information. Furthermore, the itinerary generation unit develops an algorithm for proposing appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, it proposes appropriate restaurants and meal plans based on the user's dietary restrictions and allergy information. This makes it possible to propose an itinerary that includes appropriate restaurants and meal plans by taking into account the user's dietary restrictions and allergy information.

[0037] The change update unit can analyze past change history and propose optimal change proposals in response to change requests. The change update unit, for example, analyzes the user's past change history and proposes optimal change proposals. For example, it proposes change proposals that suit the user's preferences based on data on tourist attractions and activities that have been changed in the past. The change update unit also analyzes past change history and builds a system for proposing optimal change proposals. For example, it proposes optimal change proposals based on the user's past change history. Furthermore, the change update unit develops an algorithm for analyzing past change history and proposing optimal change proposals. For example, it proposes optimal change proposals based on the user's past change history. In this way, it is possible to propose optimal change proposals in response to a user's change request by analyzing past change history.

[0038] The change / update unit can recalculate optimal routes and tourist attractions based on real-time location information. The change / update unit, for example, builds a system that recalculates optimal routes and tourist attractions based on the user's real-time location information. For example, it proposes the tourist attraction closest to the current location. The change / update unit also develops an algorithm for recalculating optimal routes and tourist attractions based on real-time location information. For example, it proposes optimal routes and tourist attractions based on the user's current location. This makes it possible to recalculate optimal routes and tourist attractions based on the user's real-time location information.

[0039] The change update unit can reflect the opinions of friends and family in real time and propose optimal change proposals for the entire group. The change update unit, for example, builds a system that collects the opinions of the user's friends and family in real time and proposes optimal change proposals for the entire group. For example, it collects opinions using a group chat function. The change update unit also develops an algorithm that reflects the opinions of friends and family in real time and proposes optimal change proposals for the entire group. For example, it proposes optimal change proposals based on the opinions of everyone. In this way, it is possible to propose optimal change proposals for the entire group by reflecting the opinions of the user's friends and family in real time.

[0040] The change update unit can propose appropriate change proposals in response to changes in the user's health condition or physical condition. The change update unit, for example, builds a system that monitors changes in the user's health condition or physical condition in real time and proposes appropriate change proposals. For example, it uses data from a fitness tracker. The change update unit also develops an algorithm for proposing appropriate change proposals in response to changes in the user's health condition or physical condition. For example, it proposes appropriate change proposals based on the user's health data. This makes it possible to propose appropriate change proposals in response to changes in the user's health condition or physical condition.

[0041] The list-up unit can include necessary medications and health management items in the list, taking into account the user's health condition and physical condition. The list-up unit, for example, analyzes the user's health data (e.g., fitness tracker data) and includes necessary medications and health management items in the list. For example, medications and supplements for chronic illnesses are added to the list. The list-up unit also builds a system for including necessary medications and health management items in the list, taking into account the user's health condition and physical condition. For example, necessary medications and health management items are included in the list based on the user's health data. Furthermore, the list-up unit develops an algorithm for including necessary medications and health management items in the list, taking into account the user's health condition and physical condition. For example, necessary medications and health management items are included in the list based on the user's health data. In this way, necessary medications and health management items can be included in the list by taking into account the user's health condition and physical condition.

[0042] The list-up unit can reflect the opinions of friends and family and create a list of things that are necessary for the entire group. For example, the list-up unit builds a system that collects the opinions of the user's friends and family and creates a list of things that are necessary for the entire group. For example, it uses a group chat function to collect opinions. The list-up unit also develops an algorithm for reflecting the opinions of friends and family and creating a list of things that are necessary for the entire group. For example, it creates a list of things that are necessary based on everyone's opinions. This makes it possible to create a list of things that are necessary for the entire group by reflecting the opinions of the user's friends and family.

[0043] The list-up unit can include items necessary for traveling with a pet in the list by taking into account information about the pet. The list-up unit, for example, inputs the type, size, and characteristics of the user's pet and includes items necessary for traveling with a pet in the list. For example, dog leashes and carrier bags are added to the list. The list-up unit also builds a system for including items necessary for traveling with a pet in the list by taking into account information about the pet. For example, accommodations and activities that allow pets are included in the list. Furthermore, the list-up unit develops an algorithm for including items necessary for traveling with a pet in the list by taking into account information about the pet. For example, accommodations and activities that allow pets are included in the list. In this way, items necessary for traveling with a pet can be included in the list by taking into account information about the user's pet.

[0044] The information providing unit can analyze the user's past travel history and interests and provide the most interesting information. The information providing unit, for example, analyzes the user's past travel history and provides the most interesting information. For example, information is provided based on tourist spots visited in the past and activities participated in. The information providing unit also analyzes the user's interests and builds a system for providing the most interesting information. For example, the most interesting information is provided based on the user's interests. Furthermore, the information providing unit analyzes the user's past travel history and interests and develops an algorithm for providing the most interesting information. For example, the most interesting information is provided based on the user's past travel data and interests. In this way, the most interesting information can be provided by analyzing the user's past travel history and interests.

[0045] The information providing unit can provide appropriate health management information by taking into account the user's health condition and physical condition. The information providing unit, for example, analyzes the user's health data (e.g., fitness tracker data) and provides appropriate health management information. For example, it provides advice on how to manage chronic illnesses and how to maintain health. The information providing unit also builds a system for providing appropriate health management information by taking into account the user's health condition and physical condition. For example, it provides appropriate health management information based on the user's health data. Furthermore, the information providing unit develops an algorithm for providing appropriate health management information by taking into account the user's health condition and physical condition. For example, it provides appropriate health management information based on the user's health data. In this way, it is possible to provide appropriate health management information by taking into account the user's health condition and physical condition.

[0046] The information providing unit can reflect the opinions of friends and family and provide information that is useful to the entire group. The information providing unit, for example, collects the opinions of the user's friends and family and builds a system that provides information that is useful to the entire group. For example, the information providing unit collects opinions using a group chat function. The information providing unit also develops an algorithm for reflecting the opinions of friends and family and providing information that is useful to the entire group. For example, information that is useful to the entire group is provided based on the opinions of everyone. In this way, information that is useful to the entire group can be provided by reflecting the opinions of the user's friends and family.

[0047] The information providing unit can provide information useful for traveling with pets by taking into account information about the pet. The information providing unit, for example, inputs the type, size, and characteristics of the user's pet and provides information useful for traveling with pets. For example, it provides information about accommodations and activities that allow pets. The information providing unit also builds a system for providing information useful for traveling with pets by taking into account information about the pet. For example, it provides information about tourist spots and activities that allow pets. Furthermore, the information providing unit develops an algorithm for providing information useful for traveling with pets by taking into account information about the pet. For example, it provides information about accommodations and activities that allow pets. In this way, it is possible to provide information useful for traveling with pets by taking into account information about the user's pet.

[0048] The information storage unit can analyze the user's past travel history in detail and propose a new itinerary that includes elements that generated high satisfaction. The information storage unit, for example, analyzes the user's past travel history in detail and extracts elements that generated high satisfaction. For example, it proposes a new itinerary that includes tourist spots and activities that have been highly rated in the past. The information storage unit also builds a system for analyzing the user's past travel history in detail and proposing a new itinerary that includes elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on the user's past travel data and reflects them in a new itinerary. Furthermore, the information storage unit develops an algorithm for analyzing the user's past travel history in detail and proposing a new itinerary that includes elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on the user's past travel data and reflects them in a new itinerary. In this way, it is possible to propose a new itinerary that includes elements that generated high satisfaction by analyzing the user's past travel history in detail.

[0049] The information storage unit can propose new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. The information storage unit, for example, analyzes the user's health data (e.g., data from a fitness tracker) and proposes new itineraries that include appropriate activities and tourist attractions. For example, it proposes an itinerary that includes methods for managing chronic illnesses and activities for maintaining health. The information storage unit also builds a system for proposing new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. For example, it proposes new itineraries that include appropriate activities and tourist attractions based on the user's health data. Furthermore, the information storage unit develops an algorithm for proposing new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. For example, it proposes new itineraries that include appropriate activities and tourist attractions based on the user's health data. In this way, it is possible to propose new itineraries that include appropriate activities and tourist attractions by taking into account the user's health condition and physical condition.

[0050] The information storage unit can propose a new itinerary that is optimal for the entire group based on the travel histories of friends and family. The information storage unit, for example, collects the travel histories of the user's friends and family and builds a system that proposes a new itinerary that is optimal for the entire group. For example, it proposes optimal tourist spots and activities based on the travel histories of everyone. The information storage unit also develops an algorithm for proposing a new itinerary that is optimal for the entire group based on the travel histories of friends and family. For example, it proposes optimal tourist spots and activities based on the travel histories of everyone. In this way, it is possible to propose a new itinerary that is optimal for the entire group based on the travel histories of the user's friends and family.

[0051] The information storage unit can take into account information about the pet and propose a new itinerary that is optimal for traveling with a pet. The information storage unit, for example, inputs the type, size, and characteristics of the user's pet and proposes a new itinerary that is optimal for traveling with a pet. For example, it adds a dog leash or a carrier bag to the list. The information storage unit also builds a system for taking into account information about the pet and proposing a new itinerary that is optimal for traveling with a pet. For example, it proposes accommodations and activities that allow pets. The information storage unit also develops an algorithm for taking into account information about the pet and proposing a new itinerary that is optimal for traveling with a pet. For example, it proposes accommodations and activities that allow pets. In this way, it is possible to propose a new itinerary that is optimal for traveling with a pet by taking into account information about the user's pet.

[0052] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0053] The user attribute input unit can also suggest related events and festivals based on the user's hobbies and interests. For example, a music-loving user can be suggested a music festival held at the travel destination. A food-loving user can be suggested an event where they can experience the local food culture. A user interested in history and culture can be suggested a historical event or cultural festival at the travel destination. This makes it possible to provide a special experience at the travel destination based on the user's hobbies and interests.

[0054] The user attribute input unit not only analyzes a user's past travel history and social media posts, but can also extract preferences and interests based on the user's purchasing history. For example, it can analyze the products and services the user has purchased online and suggest shopping spots and related activities at the travel destination. It can also suggest similar events at the travel destination based on data on events and workshops the user has previously attended. It can also analyze the contents of magazines and newsletters the user subscribes to and suggest tourist spots and activities that match the user's interests. This makes it possible to utilize the user's purchasing history to provide more personalized travel plans.

[0055] The user attribute input unit can suggest appropriate activities and tourist spots taking into account the user's health condition and physical condition. For example, if the user uses a fitness tracker, the data can be analyzed to suggest hiking trails and cycling routes that provide moderate exercise. If the user has a chronic illness, the unit can suggest itineraries that include facilities and services that are useful for managing the illness. Furthermore, if the user is looking to relax, the unit can suggest itineraries that include spas and yoga retreats. This makes it possible to provide optimal travel plans based on the user's health condition and physical condition.

[0056] The user attribute input unit can also input the attributes and preferences of friends and family members to generate an itinerary optimized for group trips. For example, for a family trip with children, it can suggest an itinerary that includes activities and tourist spots for children. For a group of friends traveling, it can also suggest activities and restaurants that everyone can enjoy. Furthermore, for a senior traveler, it can suggest tourist spots and accommodations that are less strenuous on the body. This makes it possible to provide the optimal travel plan based on the attributes and preferences of the entire group.

[0057] The user attribute input unit can input pet information and suggest travel plans that allow pets. For example, for a user who owns a dog, it can suggest itineraries that include hotels and dog runs that allow dogs. For a user who owns a cat, it can also suggest accommodations and cat cafes that allow cats. Furthermore, it can also suggest pet-friendly tourist spots and activities taking into account the health and characteristics of the pet. This makes it possible to provide the best plans for enjoying travel with pets.

[0058] The itinerary generation unit can suggest optimal travel times and tourist spots based on seasonal and weather data. For example, it analyzes weather data for each season and suggests optimal travel times. For example, it suggests times that avoid the rainy season or times when the temperature is comfortable. The itinerary generation unit can also suggest optimal tourist spots based on weather data. For example, it suggests outdoor activities during times with a lot of sunny weather. Furthermore, the itinerary generation unit builds a system for suggesting optimal travel times and tourist spots based on seasonal and weather data. For example, it suggests optimal travel times and tourist spots based on weather data. In this way, it is possible to suggest optimal travel times and tourist spots based on seasonal and weather data.

[0059] The itinerary generation unit can consider dietary restrictions and allergy information and propose an itinerary that includes appropriate restaurants and meal plans. For example, the user's dietary restrictions and allergy information is input, and appropriate restaurants and meal plans are proposed based on the input. For example, a restaurant with vegetarian or gluten-free options is selected. The itinerary generation unit also considers dietary restrictions and allergy information and builds a system for considering dietary restrictions and allergy information and proposing appropriate restaurants and meal plans. For example, appropriate restaurants and meal plans are proposed based on the user's dietary restrictions and allergy information. Furthermore, the itinerary generation unit develops an algorithm for considering dietary restrictions and allergy information and proposing appropriate restaurants and meal plans. For example, appropriate restaurants and meal plans are proposed based on the user's dietary restrictions and allergy information. This makes it possible to propose an itinerary that includes appropriate restaurants and meal plans by considering the user's dietary restrictions and allergy information.

[0060] The processing flow of the first embodiment will be briefly explained below.

[0061] Step 1: The user attribute input unit inputs the user's attributes and preferences. For example, the user can input their age, gender, hobbies, interests, etc. The user attribute input unit can also analyze the user's past travel history and social media posts to automatically extract detailed preferences and interests. Step 2: The itinerary generation unit generates an itinerary based on the information input by the user attribute input unit. For example, the generation AI proposes an itinerary that includes tourist spots and accommodations that match the user's preferences. The itinerary generation unit can also analyze the user's past travel satisfaction and prioritize proposing itineraries that include elements that generated high satisfaction. Step 3: The suggestion unit proposes the itinerary generated by the itinerary generation unit to the user. For example, the generation AI creates multiple itineraries and suggests them with catchy titles. Step 4: The change update unit updates the itinerary in real time according to the user's change requests. For example, if the user requests "I want to add this tourist attraction," the generation AI recalculates the optimal route including the new tourist attraction and updates the itinerary. Step 5: The list-up section creates a list of things that need to be done before and on the day of the trip. For example, it creates a list such as "Don't forget your passport" and "Prepare local currency" and notifies the user. Step 6: The information provider provides information about the travel destination before the trip. For example, the information provider provides the user with information such as "the history of the region" and "recommended local cuisine." Step 7: The information storage unit stores the post-trip information and suggests a new itinerary based on the satisfaction level of the past trip. For example, it suggests a new itinerary that includes tourist spots that were highly satisfying on the previous trip.

[0062] (Example 2) The travel suggestion system according to the embodiment of the present invention is a system that proposes optimal itineraries based on the attributes and preferences of users and updates them in real time, thereby enabling the travel suggestion system to provide travel plans that meet the needs of users.

[0063] A travel suggestion system according to an embodiment includes a user attribute input unit, an itinerary generation unit, a suggestion unit, a change / update unit, a list unit, an information provision unit, and an information storage unit. The user attribute input unit inputs a user's attributes and preferences. For example, the user can input age, gender, hobbies, interests, etc. The user attribute input unit can also analyze the user's past travel history and social media posts to automatically extract detailed preferences and interests. For example, it can collect data on previously visited tourist spots and accommodations and analyze the user's travel patterns. The itinerary generation unit generates an itinerary based on the information input by the user attribute input unit. For example, the generation AI can suggest an itinerary that includes tourist spots and accommodations that match the user's preferences. The itinerary generation unit can also analyze the user's past travel satisfaction and prioritize itineraries that include elements that generated high satisfaction. The suggestion unit suggests the itinerary generated by the itinerary generation unit to the user. For example, the generation AI can tentatively compile multiple itineraries and suggest them with catchy titles. The change update unit updates the itinerary in real time in response to a user's change request. For example, if a user requests, "I want to add this tourist attraction," the generation AI recalculates the optimal route including the new tourist attraction and updates the itinerary. The list unit lists things that need to be done before and on the day of the trip. For example, it creates a list such as "Don't forget your passport" and "Prepare local currency" and notifies the user. The information provision unit provides information about the travel destination before the trip. For example, it provides the user with information such as "The history of the area" and "Recommended local cuisine." The information storage unit stores information after the trip and suggests a new itinerary based on the satisfaction level of past trips. For example, it suggests "a new itinerary including tourist attractions that were highly satisfying on the previous trip." This allows the travel suggestion system according to the embodiment to provide travel plans that meet the user's needs. For example, users can enjoy trips that suit their preferences and easily prepare for their trip. In addition, since the information remains even after the trip, it can be used as a reference for the next trip.

[0064] The user attribute input unit can analyze past travel history and social media posts to automatically extract detailed preferences and interests. The user attribute input unit, for example, analyzes the user's past travel history to extract preferences and interests based on places visited and activities participated in. For example, it collects data on tourist spots and accommodations visited in the past and analyzes the user's travel patterns. The user attribute input unit also analyzes social media posts to extract the user's interests and concerns. For example, it can understand the user's preferences based on the content of the post, the number of likes, comments, etc. By analyzing the user's past travel history and social media posts, it is possible to understand more detailed preferences and interests and propose optimal itineraries.

[0065] The user attribute input unit can analyze the user's real-time emotional state using an emotion estimation function and suggest an itinerary that matches the user's mood at that time. For example, the user attribute input unit can analyze the user's real-time emotional state using facial expression recognition technology and suggest an itinerary that matches the user's mood at that time. For example, the user attribute input unit can read the user's facial expression through a camera and suggest a hot spring trip if the user is in the mood to relax. The user attribute input unit can also analyze the user's emotional state using voice analysis technology and suggest an itinerary that matches the user's mood at that time. For example, the user attribute input unit can analyze the user's tone and speed of voice and suggest outdoor activities if the user is in the mood to be active. The user attribute input unit can also analyze the user's emotional state using text analysis technology and suggest an itinerary that matches the user's mood at that time. For example, the user attribute input unit can analyze a text message entered by the user and suggest tourist spots where the user can relax if the user is in the mood to relax. In this way, by analyzing the user's real-time emotional state, it is possible to suggest an itinerary that matches the user's mood at that time.

[0066] The user attribute input unit can suggest appropriate activities and tourist spots by taking into account the user's health condition and physical condition. The user attribute input unit, for example, analyzes the user's health data (e.g., fitness tracker data) and suggests activities that suit their physical condition. For example, based on heart rate and step count data, it suggests light hikes and relaxing tourist spots. The user attribute input unit also builds a system for suggesting appropriate activities and tourist spots by taking into account the user's health condition and physical condition. For example, based on blood pressure and body temperature data, it suggests tourist spots and activities that suit their physical condition. Furthermore, the user attribute input unit develops an algorithm for suggesting appropriate activities and tourist spots by taking into account the user's health condition and physical condition. For example, it suggests tourist spots and activities that suit their physical condition based on the user's health data. In this way, appropriate activities and tourist spots can be suggested by taking into account the user's health condition and physical condition.

[0067] The user attribute input unit also inputs the attributes and preferences of friends and family, and can generate an itinerary that is optimal for a group trip. The user attribute input unit inputs, for example, the attributes (age, gender, hobbies, etc.) of the user's friends and family, and generates an itinerary that suits the preferences of everyone. For example, for a family trip with children, the unit suggests an itinerary that includes activities for the children. The user attribute input unit also inputs the preferences of friends and family, and builds a system for generating an itinerary that is optimal for the entire group. For example, it suggests tourist spots and accommodations that suit the preferences of everyone. Furthermore, the user attribute input unit inputs the attributes and preferences of friends and family, and develops an algorithm for generating an itinerary that is optimal for a group trip. For example, it suggests tourist spots and activities that suit the preferences of everyone. In this way, the optimal itinerary for a group trip can be generated by taking into account the attributes and preferences of the user's friends and family.

[0068] The user attribute input unit can input information about a pet and propose travel plans that allow pets. The user attribute input unit can input, for example, the type, size, and characteristics of the user's pet and propose accommodations and tourist spots that allow pets. For example, for a user who owns a dog, the unit can propose itineraries that include hotels and dog runs that allow dogs. The user attribute input unit can also input information about a pet and build a system for proposing travel plans that allow pets. For example, the unit can propose tourist spots and activities that allow pets. The user attribute input unit can also input information about a pet and develop an algorithm for proposing travel plans that allow pets. For example, the unit can propose accommodations and tourist spots that allow pets. In this way, travel plans that allow pets can be proposed by taking into account the information about the user's pet.

[0069] The user attribute input unit can use an emotion estimation function to analyze the user's emotions in real time when inputting information and provide input support that elicits positive emotions. For example, when a user inputs attributes or preferences, the user attribute input unit can use facial expression recognition technology to analyze the user's emotions in real time and display a message that elicits positive emotions. For example, when a smile is detected, the unit can display "Great choice!". The user attribute input unit can also use voice analysis technology to analyze the user's emotions in real time and provide input support that elicits positive emotions. For example, the unit can analyze the tone and speed of the user's voice and display a positive message. The user attribute input unit can also use text analysis technology to analyze the user's emotions in real time and provide input support that elicits positive emotions. For example, the unit can analyze a text message input by the user and display a positive message. This allows the user's emotions in real time when inputting information to be analyzed and elicits positive emotions, thereby providing a better input experience.

[0070] The itinerary generation unit can analyze past travel satisfaction levels and prioritize itineraries that include elements that generated high satisfaction. The itinerary generation unit, for example, analyzes the user's past travel reviews and ratings and extracts elements that generated high satisfaction. For example, it preferentially proposes itineraries that include elements such as "beautiful scenery" and "delicious food." The itinerary generation unit also analyzes the user's past travel satisfaction levels and builds a system for proposing itineraries that include elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on past travel data and reflects them in the itinerary. Furthermore, the itinerary generation unit analyzes the user's past travel satisfaction levels and develops an algorithm for proposing itineraries that include elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on past travel data and reflects them in the itinerary. In this way, it is possible to prioritize itineraries that include elements that generated high satisfaction by analyzing the user's past travel satisfaction levels.

[0071] The itinerary generation unit can use the emotion estimation function to predict the user's emotions toward the proposed itinerary and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can predict the user's emotions toward the proposed itinerary using facial expression recognition technology and propose an itinerary that will elicit the most positive response. For example, if a smile is detected, the itinerary can be preferentially proposed. The itinerary generation unit can also predict the user's emotions using voice analysis technology and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can analyze the tone and speed of the user's voice and propose an itinerary that will elicit the most positive response. Furthermore, the itinerary generation unit can predict the user's emotions using text analysis technology and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can analyze a text message entered by the user and propose an itinerary that will elicit the most positive response. In this way, the itinerary generation unit can predict the user's emotions toward the proposed itinerary and propose an itinerary that will elicit the most positive response.

[0072] The itinerary generation unit can suggest optimal travel times and tourist spots based on seasonal and weather data. The itinerary generation unit, for example, analyzes weather data for each season and suggests optimal travel times. For example, it suggests times that avoid the rainy season or times when the temperature is comfortable. The itinerary generation unit can also suggest optimal tourist spots based on weather data. For example, it suggests outdoor activities during times when there is a lot of sunny weather. Furthermore, the itinerary generation unit builds a system for suggesting optimal travel times and tourist spots based on seasonal and weather data. For example, it suggests optimal travel times and tourist spots based on weather data. In this way, it is possible to suggest optimal travel times and tourist spots based on seasonal and weather data.

[0073] The itinerary generation unit can propose an itinerary that includes appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, the itinerary generation unit inputs the user's dietary restrictions and allergy information and proposes appropriate restaurants and meal plans based on the input. For example, it selects restaurants that have vegetarian or gluten-free options. The itinerary generation unit also builds a system for proposing appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, it proposes appropriate restaurants and meal plans based on the user's dietary restrictions and allergy information. Furthermore, the itinerary generation unit develops an algorithm for proposing appropriate restaurants and meal plans by taking into account dietary restrictions and allergy information. For example, it proposes appropriate restaurants and meal plans based on the user's dietary restrictions and allergy information. This makes it possible to propose an itinerary that includes appropriate restaurants and meal plans by taking into account the user's dietary restrictions and allergy information.

[0074] The itinerary generation unit can use the emotion estimation function to provide real-time feedback on the user's emotions regarding the proposed itinerary, thereby assisting in selecting an optimal itinerary. For example, the itinerary generation unit can provide real-time feedback on the user's emotions regarding the proposed itinerary, thereby assisting in selecting an optimal itinerary. For example, facial expression recognition technology can be used to analyze emotions and propose an itinerary that elicits a positive response. The itinerary generation unit can also provide real-time feedback on the user's emotions using voice analysis technology, thereby assisting in selecting an optimal itinerary. For example, the itinerary generation unit can analyze the tone and speed of the user's voice and propose an itinerary that elicits a positive response. Furthermore, the itinerary generation unit can provide real-time feedback on the user's emotions using text analysis technology, thereby assisting in selecting an optimal itinerary. For example, the itinerary generation unit can analyze a text message entered by the user and propose an itinerary that elicits a positive response. In this way, real-time feedback on the user's emotions regarding the proposed itinerary can assist in selecting an optimal itinerary.

[0075] The change update unit can analyze past change history and propose optimal change proposals in response to change requests. The change update unit, for example, analyzes the user's past change history and proposes optimal change proposals. For example, it proposes change proposals that suit the user's preferences based on data on tourist attractions and activities that have been changed in the past. The change update unit also analyzes past change history and builds a system for proposing optimal change proposals. For example, it proposes optimal change proposals based on the user's past change history. Furthermore, the change update unit develops an algorithm for analyzing past change history and proposing optimal change proposals. For example, it proposes optimal change proposals based on the user's past change history. In this way, it is possible to propose optimal change proposals in response to a user's change request by analyzing past change history.

[0076] The change / update unit can recalculate optimal routes and tourist attractions based on real-time location information. The change / update unit, for example, builds a system that recalculates optimal routes and tourist attractions based on the user's real-time location information. For example, it proposes the tourist attraction closest to the current location. The change / update unit also develops an algorithm for recalculating optimal routes and tourist attractions based on real-time location information. For example, it proposes optimal routes and tourist attractions based on the user's current location. This makes it possible to recalculate optimal routes and tourist attractions based on the user's real-time location information.

[0077] The change update unit can use the emotion estimation function to predict the user's emotions regarding the changed itinerary and propose the most positive change proposal. For example, the change update unit can predict the user's emotions regarding the changed itinerary using facial expression recognition technology and propose the most positive change proposal. For example, if a smile is detected, the change update unit can preferentially propose that change proposal. The change update unit can also predict the user's emotions using voice analysis technology and propose the most positive change proposal. For example, the change update unit can analyze the tone and speed of the user's voice and propose change proposals that will elicit a positive response. The change update unit can also predict the user's emotions using text analysis technology and propose the most positive change proposal. For example, the change update unit can analyze a text message entered by the user and propose change proposals that will elicit a positive response. In this way, the most positive change proposal can be proposed by predicting the user's emotions regarding the changed itinerary.

[0078] The change update unit can reflect the opinions of friends and family in real time and propose optimal change proposals for the entire group. The change update unit, for example, builds a system that collects the opinions of the user's friends and family in real time and proposes optimal change proposals for the entire group. For example, it collects opinions using a group chat function. The change update unit also develops an algorithm that reflects the opinions of friends and family in real time and proposes optimal change proposals for the entire group. For example, it proposes optimal change proposals based on the opinions of everyone. In this way, it is possible to propose optimal change proposals for the entire group by reflecting the opinions of the user's friends and family in real time.

[0079] The change update unit can propose appropriate change proposals in response to changes in the user's health condition or physical condition. The change update unit, for example, builds a system that monitors changes in the user's health condition or physical condition in real time and proposes appropriate change proposals. For example, it uses data from a fitness tracker. The change update unit also develops an algorithm for proposing appropriate change proposals in response to changes in the user's health condition or physical condition. For example, it proposes appropriate change proposals based on the user's health data. This makes it possible to propose appropriate change proposals in response to changes in the user's health condition or physical condition.

[0080] The change update unit can use the emotion estimation function to provide real-time feedback on the user's emotions regarding the changed itinerary, thereby assisting in selecting the optimal change plan. For example, the change update unit can provide real-time feedback on the user's emotions regarding the changed itinerary, thereby assisting in selecting the optimal change plan. For example, facial expression recognition technology can be used to analyze emotions and propose change plans that will elicit a positive response. The change update unit can also provide real-time feedback on the user's emotions using voice analysis technology, thereby assisting in selecting the optimal change plan. For example, the change update unit can analyze the tone and speed of the user's voice and propose change plans that will elicit a positive response. Furthermore, the change update unit can provide real-time feedback on the user's emotions using text analysis technology, thereby assisting in selecting the optimal change plan. For example, the change update unit can analyze text messages entered by the user and propose change plans that will elicit a positive response. In this way, real-time feedback on the user's emotions regarding the changed itinerary can be used to assist in selecting the optimal change plan.

[0081] The list-up unit can analyze the user's real-time emotional state using an emotion estimation function and suggest a preparation list for reducing stress. For example, the list-up unit can analyze the user's real-time emotional state using facial expression recognition technology and suggest a preparation list for reducing stress. For example, when stress is high, items that help to relax are included in the list. The list-up unit can also analyze the user's emotional state in real time using voice analysis technology and suggest a preparation list for reducing stress. For example, the list-up unit can analyze the user's tone and speed of voice and suggest items that help to relax. Furthermore, the list-up unit can analyze the user's emotional state in real time using text analysis technology and suggest a preparation list for reducing stress. For example, the list-up unit can analyze text messages entered by the user and suggest items that help to relax in the list. In this way, a preparation list for reducing stress can be suggested by analyzing the user's real-time emotional state.

[0082] The list-up unit can include necessary medications and health management items in the list, taking into account the user's health condition and physical condition. The list-up unit, for example, analyzes the user's health data (e.g., fitness tracker data) and includes necessary medications and health management items in the list. For example, medications and supplements for chronic illnesses are added to the list. The list-up unit also builds a system for including necessary medications and health management items in the list, taking into account the user's health condition and physical condition. For example, necessary medications and health management items are included in the list based on the user's health data. Furthermore, the list-up unit develops an algorithm for including necessary medications and health management items in the list, taking into account the user's health condition and physical condition. For example, necessary medications and health management items are included in the list based on the user's health data. In this way, necessary medications and health management items can be included in the list by taking into account the user's health condition and physical condition.

[0083] The list-up unit can reflect the opinions of friends and family and create a list of things that are necessary for the entire group. For example, the list-up unit builds a system that collects the opinions of the user's friends and family and creates a list of things that are necessary for the entire group. For example, it uses a group chat function to collect opinions. The list-up unit also develops an algorithm for reflecting the opinions of friends and family and creating a list of things that are necessary for the entire group. For example, it creates a list of things that are necessary based on everyone's opinions. This makes it possible to create a list of things that are necessary for the entire group by reflecting the opinions of the user's friends and family.

[0084] The list-up unit can include items necessary for traveling with a pet in the list by taking into account information about the pet. The list-up unit, for example, inputs the type, size, and characteristics of the user's pet and includes items necessary for traveling with a pet in the list. For example, dog leashes and carrier bags are added to the list. The list-up unit also builds a system for including items necessary for traveling with a pet in the list by taking into account information about the pet. For example, accommodations and activities that allow pets are included in the list. Furthermore, the list-up unit develops an algorithm for including items necessary for traveling with a pet in the list by taking into account information about the pet. For example, accommodations and activities that allow pets are included in the list. In this way, items necessary for traveling with a pet can be included in the list by taking into account information about the user's pet.

[0085] The list-up unit can use an emotion estimation function to provide feedback on the emotions the user has toward the list in real time, thereby assisting in creating an optimal list. For example, the list-up unit can provide feedback on the emotions the user has toward the list in real time, thereby assisting in creating an optimal list. For example, facial expression recognition technology can be used to analyze emotions and suggest a list that elicits a positive response. The list-up unit can also provide feedback on the user's emotions in real time using voice analysis technology, thereby assisting in creating an optimal list. For example, the list-up unit can analyze the tone and speed of the user's voice and suggest a list that elicits a positive response. Furthermore, the list-up unit can provide feedback on the user's emotions in real time using text analysis technology, thereby assisting in creating an optimal list. For example, the list-up unit can analyze a text message entered by the user and suggest a list that elicits a positive response. In this way, real-time feedback on the emotions the user has toward the list can assist in creating an optimal list.

[0086] The information providing unit can analyze the user's past travel history and interests and provide the most interesting information. The information providing unit, for example, analyzes the user's past travel history and provides the most interesting information. For example, information is provided based on tourist spots visited in the past and activities participated in. The information providing unit also analyzes the user's interests and builds a system for providing the most interesting information. For example, the most interesting information is provided based on the user's interests. Furthermore, the information providing unit analyzes the user's past travel history and interests and develops an algorithm for providing the most interesting information. For example, the most interesting information is provided based on the user's past travel data and interests. In this way, the most interesting information can be provided by analyzing the user's past travel history and interests.

[0087] The information providing unit can analyze the user's real-time emotional state using an emotion estimation function and provide information that matches the user's mood at that time. For example, the information providing unit can analyze the user's real-time emotional state using facial expression recognition technology and provide information that matches the user's mood at that time. For example, if the user wants to relax, the information providing unit can provide information about tourist spots where the user can relax. The information providing unit can also analyze the user's emotional state in real time using voice analysis technology and provide information that matches the user's mood at that time. For example, the information providing unit can analyze the user's tone and speed of voice to provide information about tourist spots where the user can relax. The information providing unit can also analyze the user's emotional state in real time using text analysis technology and provide information that matches the user's mood at that time. For example, the information providing unit can analyze a text message entered by the user to provide information about tourist spots where the user can relax. In this way, the information providing unit can provide information that matches the user's mood at that time by analyzing the user's real-time emotional state.

[0088] The information providing unit can provide appropriate health management information by taking into account the user's health condition and physical condition. The information providing unit, for example, analyzes the user's health data (e.g., fitness tracker data) and provides appropriate health management information. For example, it provides advice on how to manage chronic illnesses and how to maintain health. The information providing unit also builds a system for providing appropriate health management information by taking into account the user's health condition and physical condition. For example, it provides appropriate health management information based on the user's health data. Furthermore, the information providing unit develops an algorithm for providing appropriate health management information by taking into account the user's health condition and physical condition. For example, it provides appropriate health management information based on the user's health data. In this way, it is possible to provide appropriate health management information by taking into account the user's health condition and physical condition.

[0089] The information providing unit can reflect the opinions of friends and family and provide information that is useful to the entire group. The information providing unit, for example, collects the opinions of the user's friends and family and builds a system that provides information that is useful to the entire group. For example, the information providing unit collects opinions using a group chat function. The information providing unit also develops an algorithm for reflecting the opinions of friends and family and providing information that is useful to the entire group. For example, information that is useful to the entire group is provided based on the opinions of everyone. In this way, information that is useful to the entire group can be provided by reflecting the opinions of the user's friends and family.

[0090] The information providing unit can provide information useful for traveling with pets by taking into account information about the pet. The information providing unit, for example, inputs the type, size, and characteristics of the user's pet and provides information useful for traveling with pets. For example, it provides information about accommodations and activities that allow pets. The information providing unit also builds a system for providing information useful for traveling with pets by taking into account information about the pet. For example, it provides information about tourist spots and activities that allow pets. Furthermore, the information providing unit develops an algorithm for providing information useful for traveling with pets by taking into account information about the pet. For example, it provides information about accommodations and activities that allow pets. In this way, it is possible to provide information useful for traveling with pets by taking into account information about the user's pet.

[0091] The information storage unit can analyze the user's past travel history in detail and propose a new itinerary that includes elements that generated high satisfaction. The information storage unit, for example, analyzes the user's past travel history in detail and extracts elements that generated high satisfaction. For example, it proposes a new itinerary that includes tourist spots and activities that have been highly rated in the past. The information storage unit also builds a system for analyzing the user's past travel history in detail and proposing a new itinerary that includes elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on the user's past travel data and reflects them in a new itinerary. Furthermore, the information storage unit develops an algorithm for analyzing the user's past travel history in detail and proposing a new itinerary that includes elements that generated high satisfaction. For example, it extracts elements that generated high satisfaction based on the user's past travel data and reflects them in a new itinerary. In this way, it is possible to propose a new itinerary that includes elements that generated high satisfaction by analyzing the user's past travel history in detail.

[0092] The information storage unit can analyze the user's real-time emotional state using an emotion estimation function and suggest a new itinerary that matches the user's mood at that time. For example, the information storage unit can analyze the user's real-time emotional state using facial expression recognition technology and suggest a new itinerary that matches the user's mood at that time. For example, if the user is in a relaxed mood, the information storage unit can suggest an itinerary that includes relaxing tourist spots. The information storage unit can also analyze the user's emotional state in real time using voice analysis technology and suggest a new itinerary that matches the user's mood at that time. For example, the information storage unit can analyze the user's tone and speed of voice and suggest an itinerary that includes relaxing tourist spots. The information storage unit can also analyze the user's emotional state in real time using text analysis technology and suggest a new itinerary that matches the user's mood at that time. For example, the information storage unit can analyze a text message entered by the user and suggest an itinerary that includes relaxing tourist spots. In this way, by analyzing the user's real-time emotional state, a new itinerary that matches the user's mood at that time can be suggested.

[0093] The information storage unit can propose new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. The information storage unit, for example, analyzes the user's health data (e.g., data from a fitness tracker) and proposes new itineraries that include appropriate activities and tourist attractions. For example, it proposes an itinerary that includes methods for managing chronic illnesses and activities for maintaining health. The information storage unit also builds a system for proposing new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. For example, it proposes new itineraries that include appropriate activities and tourist attractions based on the user's health data. Furthermore, the information storage unit develops an algorithm for proposing new itineraries that include appropriate activities and tourist attractions, taking into account the user's health condition and physical condition. For example, it proposes new itineraries that include appropriate activities and tourist attractions based on the user's health data. In this way, it is possible to propose new itineraries that include appropriate activities and tourist attractions by taking into account the user's health condition and physical condition.

[0094] The information storage unit can propose a new itinerary that is optimal for the entire group based on the travel histories of friends and family. The information storage unit, for example, collects the travel histories of the user's friends and family and builds a system that proposes a new itinerary that is optimal for the entire group. For example, it proposes optimal tourist spots and activities based on the travel histories of everyone. The information storage unit also develops an algorithm for proposing a new itinerary that is optimal for the entire group based on the travel histories of friends and family. For example, it proposes optimal tourist spots and activities based on the travel histories of everyone. In this way, it is possible to propose a new itinerary that is optimal for the entire group based on the travel histories of the user's friends and family.

[0095] The information storage unit can take into account information about the pet and propose a new itinerary that is optimal for traveling with a pet. The information storage unit, for example, inputs the type, size, and characteristics of the user's pet and proposes a new itinerary that is optimal for traveling with a pet. For example, it adds a dog leash or a carrier bag to the list. The information storage unit also builds a system for taking into account information about the pet and proposing a new itinerary that is optimal for traveling with a pet. For example, it proposes accommodations and activities that allow pets. The information storage unit also develops an algorithm for taking into account information about the pet and proposing a new itinerary that is optimal for traveling with a pet. For example, it proposes accommodations and activities that allow pets. In this way, it is possible to propose a new itinerary that is optimal for traveling with a pet by taking into account information about the user's pet.

[0096] The information storage unit can use the emotion estimation function to provide real-time feedback on the user's emotions regarding a new itinerary and assist in proposing an optimal itinerary. For example, the information storage unit can provide real-time feedback on the user's emotions regarding a new itinerary and assist in proposing an optimal itinerary. For example, facial expression recognition technology can be used to analyze emotions and propose an itinerary that elicits a positive response. The information storage unit can also provide real-time feedback on the user's emotions using voice analysis technology and assist in proposing an optimal itinerary. For example, the information storage unit can analyze the tone and speed of the user's voice and propose an itinerary that elicits a positive response. Furthermore, the information storage unit can provide real-time feedback on the user's emotions using text analysis technology and assist in proposing an optimal itinerary. For example, text messages entered by the user can be analyzed and an itinerary that elicits a positive response can be proposed. In this way, real-time feedback on the user's emotions regarding a new itinerary can be provided to assist in proposing an optimal itinerary.

[0097] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0098] The user attribute input unit can also suggest related events and festivals based on the user's hobbies and interests. For example, a music-loving user can be suggested a music festival held at the travel destination. A food-loving user can be suggested an event where they can experience the local food culture. A user interested in history and culture can be suggested a historical event or cultural festival at the travel destination. This makes it possible to provide a special experience at the travel destination based on the user's hobbies and interests.

[0099] The user attribute input unit not only analyzes a user's past travel history and social media posts, but can also extract preferences and interests based on the user's purchasing history. For example, it can analyze the products and services the user has purchased online and suggest shopping spots and related activities at the travel destination. It can also suggest similar events at the travel destination based on data on events and workshops the user has previously attended. It can also analyze the contents of magazines and newsletters the user subscribes to and suggest tourist spots and activities that match the user's interests. This makes it possible to utilize the user's purchasing history to provide more personalized travel plans.

[0100] The user attribute input unit can analyze the user's real-time emotional state using the emotion estimation function and suggest itineraries that match their mood at that time. For example, if the user is feeling stressed, it can suggest a relaxing hot spring trip or a nature walk. If the user is excited, it can suggest active sports or adventure activities. Furthermore, if the user is sad, it can suggest an art gallery or a quiet place to soothe the soul. This allows the system to provide the optimal itinerary according to the user's real-time emotional state.

[0101] The user attribute input unit can suggest appropriate activities and tourist spots taking into account the user's health condition and physical condition. For example, if the user uses a fitness tracker, the data can be analyzed to suggest hiking trails and cycling routes that provide moderate exercise. If the user has a chronic illness, the unit can suggest itineraries that include facilities and services that are useful for managing the illness. Furthermore, if the user is looking to relax, the unit can suggest itineraries that include spas and yoga retreats. This makes it possible to provide optimal travel plans based on the user's health condition and physical condition.

[0102] The user attribute input unit can also input the attributes and preferences of friends and family members to generate an itinerary optimized for group trips. For example, for a family trip with children, it can suggest an itinerary that includes activities and tourist spots for children. For a group of friends traveling, it can also suggest activities and restaurants that everyone can enjoy. Furthermore, for a senior traveler, it can suggest tourist spots and accommodations that are less strenuous on the body. This makes it possible to provide the optimal travel plan based on the attributes and preferences of the entire group.

[0103] The user attribute input unit can input pet information and suggest travel plans that allow pets. For example, for a user who owns a dog, it can suggest itineraries that include hotels and dog runs that allow dogs. For a user who owns a cat, it can also suggest accommodations and cat cafes that allow cats. Furthermore, it can also suggest pet-friendly tourist spots and activities taking into account the health and characteristics of the pet. This makes it possible to provide the best plans for enjoying travel with pets.

[0104] The user attribute input unit can use an emotion estimation function to analyze the user's emotions in real time when entering information and provide input support that elicits positive emotions. For example, when a user enters attributes or preferences, facial expression recognition technology can be used to analyze the user's emotions in real time and display a message that elicits positive emotions. For example, if a smile is detected, "Great choice!" can be displayed. The user attribute input unit can also use voice analysis technology to analyze the user's emotions in real time and provide input support that elicits positive emotions. For example, it can analyze the tone and speed of the user's voice and display a positive message. The user attribute input unit can also use text analysis technology to analyze the user's emotions in real time and provide input support that elicits positive emotions. For example, it can analyze a text message entered by the user and display a positive message. This allows the user's emotions in real time when entering information to be analyzed and elicits positive emotions, thereby providing a better input experience.

[0105] The itinerary generation unit can suggest optimal travel times and tourist spots based on seasonal and weather data. For example, it analyzes weather data for each season and suggests optimal travel times. For example, it suggests times that avoid the rainy season or times when the temperature is comfortable. The itinerary generation unit can also suggest optimal tourist spots based on weather data. For example, it suggests outdoor activities during times with a lot of sunny weather. Furthermore, the itinerary generation unit builds a system for suggesting optimal travel times and tourist spots based on seasonal and weather data. For example, it suggests optimal travel times and tourist spots based on weather data. In this way, it is possible to suggest optimal travel times and tourist spots based on seasonal and weather data.

[0106] The itinerary generation unit can use the emotion estimation function to predict the user's emotions toward the proposed itinerary and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can predict the user's emotions toward the proposed itinerary using facial expression recognition technology and propose an itinerary that will elicit the most positive response. For example, if a smile is detected, the itinerary can be preferentially proposed. The itinerary generation unit can also predict the user's emotions using voice analysis technology and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can analyze the tone and speed of the user's voice and propose an itinerary that will elicit the most positive response. Furthermore, the itinerary generation unit can predict the user's emotions using text analysis technology and propose an itinerary that will elicit the most positive response. For example, the itinerary generation unit can analyze a text message entered by the user and propose an itinerary that will elicit the most positive response. In this way, the itinerary generation unit can propose an itinerary that will elicit the most positive response by predicting the user's emotions toward the proposed itinerary.

[0107] The itinerary generation unit can consider dietary restrictions and allergy information and propose an itinerary that includes appropriate restaurants and meal plans. For example, the user's dietary restrictions and allergy information is input, and appropriate restaurants and meal plans are proposed based on the input. For example, a restaurant with vegetarian or gluten-free options is selected. The itinerary generation unit also considers dietary restrictions and allergy information and builds a system for considering dietary restrictions and allergy information and proposing appropriate restaurants and meal plans. For example, appropriate restaurants and meal plans are proposed based on the user's dietary restrictions and allergy information. Furthermore, the itinerary generation unit develops an algorithm for considering dietary restrictions and allergy information and proposing appropriate restaurants and meal plans. For example, appropriate restaurants and meal plans are proposed based on the user's dietary restrictions and allergy information. This makes it possible to propose an itinerary that includes appropriate restaurants and meal plans by considering the user's dietary restrictions and allergy information.

[0108] The processing flow of the second embodiment will be briefly explained below.

[0109] Step 1: The user attribute input unit inputs the user's attributes and preferences. For example, the user can input their age, gender, hobbies, interests, etc. The user attribute input unit can also analyze the user's past travel history and social media posts to automatically extract detailed preferences and interests. Step 2: The itinerary generation unit generates an itinerary based on the information input by the user attribute input unit. For example, the generation AI proposes an itinerary that includes tourist spots and accommodations that match the user's preferences. The itinerary generation unit can also analyze the user's past travel satisfaction and prioritize proposing itineraries that include elements that generated high satisfaction. Step 3: The suggestion unit proposes the itinerary generated by the itinerary generation unit to the user. For example, the generation AI creates multiple itineraries and suggests them with catchy titles. Step 4: The change update unit updates the itinerary in real time according to the user's change requests. For example, if the user requests "I want to add this tourist attraction," the generation AI recalculates the optimal route including the new tourist attraction and updates the itinerary. Step 5: The list-up section creates a list of things that need to be done before and on the day of the trip. For example, it creates a list such as "Don't forget your passport" and "Prepare local currency" and notifies the user. Step 6: The information provider provides information about the travel destination before the trip. For example, the information provider provides the user with information such as "the history of the region" and "recommended local cuisine." Step 7: The information storage unit stores the post-trip information and suggests a new itinerary based on the satisfaction level of the past trip. For example, it suggests a new itinerary that includes tourist spots that were highly satisfying on the previous trip.

[0110] 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.

[0111] 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.

[0112] 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.

[0113] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0114] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0115] 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.

[0116] 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.

[0117] 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.

[0118] 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).

[0119] 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.

[0120] 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.

[0121] 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.

[0122] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0123] 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. Note that the smart glasses 214 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0124] 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.

[0125] 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.

[0126] 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.

[0127] 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.

[0128] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0129] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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).

[0134] 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.

[0135] 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.

[0136] 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.

[0137] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0138] In the headset type terminal 314, the identification process is performed by the processor 46. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. Note that the headset type terminal 314 may also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0144] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0145] 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.

[0146] 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.

[0147] 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.

[0148] 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).

[0149] 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.

[0150] 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.

[0151] 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.

[0152] 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.

[0153] 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 the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0154] In the robot 414, the processor 46 performs the identification process. A identification program 60 is stored in the storage 50. The processor 46 reads the identification program 60 from the storage 50 and executes the read identification program 60 on the RAM 48. The identification process is realized by the processor 46 operating as a control unit 46A in accordance with the identification program 60 executed on the RAM 48. The robot 414 may have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59.

[0155] 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.

[0156] 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.

[0157] 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.

[0158] 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.

[0159] 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.

[0160] 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.

[0161] 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.

[0162] 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).

[0163] 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.

[0164] 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."

[0165] 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.

[0166] 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.

[0167] 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.

[0168] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0169] 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.

[0170] 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.

[0171] 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.

[0172] 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.

[0173] 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.

[0174] 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.

[0175] 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.

[0176] 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]

[0177] 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 attribute input unit for inputting user attributes and preferences; an itinerary generation unit that generates an itinerary based on the information input by the user attribute input unit; a suggestion unit that suggests the itinerary generated by the itinerary generation unit to a user; a change update unit that updates the itinerary in real time in response to a change request from a user; A list-making department that lists what is needed before and on the day of the event, an information providing unit that provides information about a travel destination before the trip; and an information storage unit for storing post-travel information. A system characterized by:

2. The itinerary generation unit Analyze past travel satisfaction and prioritize proposals for itineraries that include elements that generated high satisfaction.

2. The system of claim 1.

3. The change update unit For the change request, we analyze the past change history and propose the optimal change plan.

2. The system of claim 1.

4. The list-up unit Analyze past travel history and automatically generate a list to prevent forgetting or being unprepared.

2. The system of claim 1.

5. The information providing unit Analyze your past travel history and interests to provide you with the information that is most interesting to you 2. The system of claim 1.

6. The user attribute input unit The real-time emotional state is analyzed using an emotion estimation function, and the itinerary is suggested to suit the mood at that time.

2. The system of claim 1.

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