system

Abstract

We provide the system. [Solution] A means of receiving user attribute information and image information, and analyzing that data to infer user preferences and travel requests, A means for automatically generating multiple travel plans based on the aforementioned analysis and assigning titles to the generated travel plans, A means for customizing and updating the aforementioned travel plan according to the user's request, A means for generating a preparation list that presents necessary items and actions based on a travel plan, A means of receiving user feedback after their trip and updating a database to use for future travel planning suggestions, A system that includes this.

Description

Technical Field

[0005] ,

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When planning a trip, information collection and reservation arrangements required are diverse and difficult for beginners. Also, using a travel agency is costly and it is difficult to provide a flexible plan based on individual preferences. Therefore, there is a need to provide a means for users to easily generate and customize a special travel plan according to their preferences.

Means for Solving the Problems

[0005] This invention provides means for receiving user attribute information and image information and analyzing them to infer individual preferences and travel requests. It also provides means for automatically generating multiple travel plans based on the analysis results and assigning titles to them. Furthermore, it includes a function to customize travel plans according to user requests and automatically reschedule accommodations and transportation as needed. It also provides means for users to list necessary items and procedures before traveling, and to update a database after the trip through feedback to be used for future plan suggestions.

[0006] "Users" refers to individual people who use this system.

[0007] "Attribute information" refers to information about a user's personal characteristics, such as their age, gender, and travel experience.

[0008] "Image information" refers to image data related to the travel destination preferences entered by the user.

[0009] "Analyzing" refers to the act of processing information provided by users, understanding its content, and grasping their intentions.

[0010] "Preferences" refer to the travel style and activities that users enjoy.

[0011] "Travel requirements" refer to the purpose of travel and the experiences that users desire.

[0012] A "travel plan" refers to a detailed plan that includes the itinerary, destinations, activities, means of transportation, accommodations, and other details of a trip.

[0013] "Title" refers to an identifiable and engaging name associated with the generated travel plan.

[0014] "Customization" refers to the act of changing or adjusting a travel plan according to the user's wishes.

[0015] "Re-allocation" refers to changing the existing allocation content and making a new allocation.

[0016] "Preparation list" refers to a list of items and procedures necessary for a trip.

[0017] "Feedback" refers to information provided by users to the app regarding the satisfaction and improvement points felt after a trip.

[0018] "Database" refers to a system that organizes and stores information for use in generating future travel plans.

Brief Explanation of Drawings

[0019] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [[ID=)) [Figure 11]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0020] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0021] First, the language used in the following description will be explained.

[0022] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0023] In the following embodiments, the labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0024] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0025] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0026] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0030] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0031] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0032] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0033] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0034] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0037] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0038] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0039] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0040] This invention provides a system that automatically generates travel plans tailored to the individual preferences of users and allows for easy customization. This system is designed to enhance the convenience of users in creating their preferred travel plans without any hassle. An embodiment of this system is described below.

[0041] server

[0042] The server provides a platform for analyzing attribute and image data received from users. Based on the analyzed data, it uses a generative AI to generate multiple travel plans combining various tourist destinations, modes of transportation, and accommodations. This ensures that multiple plans tailored to the user's preferences are proposed. In addition, the generated travel plans are given titles that are likely to attract the user's interest. These titles help users choose a plan.

[0043] Furthermore, the server has the ability to learn and update its database by analyzing user feedback and using it to suggest future travel plans. This feedback includes not only satisfaction and excitement during the trip, but also hopes for future trips.

[0044] terminal

[0045] The terminal provides an interface for users to input information. It has the functionality to send attribute information and images to the server and displays multiple received travel plans for the user to review. Each travel plan includes a detailed itinerary and related activity information. Furthermore, when a user customizes part of the itinerary, the terminal sends that information to the server and receives a new itinerary. In addition, it displays a list of necessary preparations and items to pack before the trip, helping users to complete their travel preparations without forgetting anything.

[0046] user

[0047] Users begin interacting with the system by entering attribute information and images related to their desired trip within the application. They select the travel plan that interests them most from several presented options and review its details. They customize the travel plan as needed and finalize their itinerary. After the trip, they provide feedback through the app, recording their travel experience and contributing to improving the quality of future travel planning.

[0048] As a concrete example, suppose a user wants to travel to a summer resort and uploads images of beaches in that area to the app. The server analyzes the images and the user's preferences and generates multiple travel plans, including nearby beach resorts, activities (e.g., diving, beach parties), and transportation options. After the user makes adjustments based on these plans, the device displays a packing list and a detailed checklist to support the user's travel preparations.

[0049] The following describes the processing flow.

[0050] Step 1:

[0051] Users access the app via their device and enter their personal information (e.g., age, travel style) and images related to their desired travel destinations.

[0052] Step 2:

[0053] The terminal transmits user-entered information and images to the server. This is done using data communication technology.

[0054] Step 3:

[0055] The server analyzes the received attribute information using natural language processing technology to extract the user's preferences and travel objectives. It also analyzes uploaded images using image recognition technology to identify relevant tourist destinations and activities.

[0056] Step 4:

[0057] Based on the analysis results, the server automatically generates multiple travel plans using a generation AI. These plans include combinations of tourist destinations, accommodations, transportation, and activities. Each travel plan is also given a catchy title.

[0058] Step 5:

[0059] The server sends the generated travel plan to the terminal.

[0060] Step 6:

[0061] The terminal visually displays multiple travel plans received from the server to the user. The user can then view the details of each plan.

[0062] Step 7:

[0063] The user selects the most suitable travel plan from the presented options and enters requests into the terminal to customize parts of the itinerary as needed.

[0064] Step 8:

[0065] The terminal sends the user's customization requests to the server.

[0066] Step 9:

[0067] The server regenerates the travel plan selected based on the user's request and rearranges accommodations and transportation if necessary.

[0068] Step 10:

[0069] The server sends the completed travel plan and the accompanying preparation list to the terminal.

[0070] Step 11:

[0071] The device displays the user's latest travel plans and a list of necessary preparations and packing lists before the trip.

[0072] Step 12:

[0073] After completing their trip, users will enter their travel impressions and feedback through the app.

[0074] Step 13:

[0075] The server analyzes user feedback and updates its database to use it for suggesting future travel plans.

[0076] (Example 1)

[0077] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0078] Planning a trip involves gathering a lot of information and manual adjustments, and planning according to individual preferences is particularly complex and time-consuming. Users want a system that can automatically and easily create trips that match their preferences. They also want a system that uses post-trip feedback to improve future plans. Furthermore, it is necessary to use images and language information to precisely understand user needs and provide the optimal travel plan.

[0079] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0080] This invention includes a server that receives attribute data and image data from a user and interprets this information to estimate the user's preferences and travel itinerary desires; a server that utilizes a generative AI model to provide an optimal plan tailored to the user's preferences; and an image recognition technology that extracts relevant tourist destinations and activities from images input by the user. This enables users to easily and automatically generate travel plans that suit their preferences and to proceed with planning efficiently.

[0081] "Attribute data" refers to personal information such as the user's age, hobbies, and budget, and is basic information used to customize travel plans.

[0082] "Image data" refers to image information provided by users for reference in their travel planning, and includes visual data related to tourist destinations and preferences.

[0083] A "generative AI model" is a general term for algorithms that use artificial intelligence technology to generate optimal travel plans based on the user's preferences and requests.

[0084] A "prompt message" is a sentence that describes the user's wishes and requests to the system, and it provides initial input information for creating a travel plan.

[0085] "Interpreting" refers to the process of analyzing data received from users and understanding its meaning and intent.

[0086] A "travel itinerary" refers to a proposed itinerary for a trip, created by combining tourist destinations, activities, transportation, accommodations, and other elements.

[0087] "Image recognition technology" is a technology used to identify and interpret objects and features in images, and is utilized to optimize travel planning.

[0088] A "preparation list" refers to a list that organizes and presents to the user the necessary items and procedures for traveling.

[0089] "Information records" refer to a database that stores user feedback and related information to help generate future travel plans.

[0090] This invention provides a system that automatically generates travel plans tailored to the user's preferences and allows for easy customization. An example of this system is described below.

[0091] server

[0092] The server receives attribute and image data sent by users and provides a platform for interpreting this information. The received data is analyzed using a generative AI model to generate an optimal travel plan tailored to the user's preferences and requests. This generative AI model uses natural language processing and image recognition technologies to evaluate the attribute and image data and precisely understand the user's needs. Through this process, the server creates multiple travel plans, including tourist destinations, activities, transportation, and accommodations, and each plan is given a title designed to attract the user's interest.

[0093] For example, if a user uploads a beach image along with the prompt message, "I want to relax on the beach during my summer vacation. Please suggest some recommended resorts and activities I can do there. I've attached a photo of a beach," the server will use that information to generate a travel plan that includes activities and transportation options at nearby resorts.

[0094] terminal

[0095] The terminal provides an interface for users to input information into the system. This transmits attribute and image data to the server. Furthermore, the terminal displays multiple received travel plans on its screen, allowing users to compare and select them. Each plan includes detailed itinerary and associated activity information. When users customize a plan, the changes are resent to the server via the terminal, providing an updated travel plan. The terminal also displays packing lists and preparation checklists to assist with travel preparations.

[0096] user

[0097] This system allows users to input their personal information and travel preferences to receive personalized travel plan suggestions. Users can then select plans that interest them, review their details, and adjust them as needed to create the optimal travel plan. Furthermore, by providing feedback after their trip and recording their experiences, users can contribute to improving future travel plans.

[0098] This system enables users to quickly and efficiently create travel plans tailored to their individual needs. By utilizing a generative AI model and prompt messages, the system achieves highly accurate automatic generation and customization of travel plans.

[0099] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0100] Step 1:

[0101] Users input attribute data (e.g., age, hobbies, budget) and image data related to their travel destination through the application. This input is sent to the server via the terminal. More specific data is provided when users explicitly state their travel requests using prompts, such as "I want to relax on the beach."

[0102] Step 2:

[0103] The server interprets the received attribute and image data. Using a generative AI model, it analyzes the prompt text and image data to infer the user's preferences. For example, it extracts features from beach image data and selects related tourist destinations and activities. This results in the output of information based on the user's wishes.

[0104] Step 3:

[0105] The server automatically generates multiple travel plans based on the analysis results. The generation AI model creates plans by combining tourist destinations, accommodations, and modes of transportation, and assigns an appealing name to each. The generated plans are configured to be customizable according to the user's requests.

[0106] Step 4:

[0107] The device displays multiple travel plans provided by the server to the user. The user can review these options and access detailed itinerary and activity information for each plan. Specifically, the device interface provides a function to compare and select each plan.

[0108] Step 5:

[0109] Users select a travel plan that interests them from the displayed options and customize it as needed. The user's customization requests are resent to the server via their device, and a more accurate travel plan is updated. During this process, details of the plan and itinerary are adjusted.

[0110] Step 6:

[0111] The server creates a regenerated travel plan based on the user's customization information. The regenerated plan is optimized based on the user's preferences, and any additions or modifications the user requests are reflected.

[0112] Step 7:

[0113] The device displays a packing list and preparation checklist for the trip to the user. It provides the necessary information appropriately to ensure smooth travel preparations.

[0114] Step 8:

[0115] After the trip, users provide feedback through the application. The server receives this feedback information and updates its database. The feedback is used to create future travel plans, contributing to improving the accuracy of the system's suggestions.

[0116] (Application Example 1)

[0117] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0118] Conventional travel planning systems have suffered from insufficient customization based on user preferences and a lack of ability to provide real-time information during travel. Furthermore, they lacked mechanisms to utilize user feedback to improve future plans, making it difficult to improve user satisfaction. In this situation, there is a need for a system that accurately reflects user preferences and provides comprehensive support throughout the entire travel experience.

[0119] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0120] In this invention, the server includes means for receiving user attribute information and image information and analyzing that data to infer the user's preferences and travel requests; means for automatically generating multiple travel plans based on the analysis and assigning titles to the generated travel plans; means for customizing and updating the travel plans according to the user's requests; means for generating a preparation list that presents necessary items and activities based on the travel plans; means for providing content that delivers various relevant information based on the user's travel data; and means for receiving the user's post-trip feedback and updating a database for use in future plan suggestions. This makes it possible to provide flexible travel plans tailored to the user's preferences, as well as a system for real-time support during travel and for utilizing feedback in future plans.

[0121] "User attribute information" refers to data that represents the unique characteristics and interests of each user, and is used to personalize travel plans.

[0122] "Image information" refers to visual materials provided by users, which are analyzed to gain a more concrete understanding of their preferences and needs.

[0123] "Means for inferring preferences and travel requests" refers to methods for predicting user preferences and requests based on input information and presenting the most suitable travel plan.

[0124] "Methods for automatically generating multiple travel plans" refer to methods for mechanically constructing diverse travel possibilities based on the user's preferences and requests.

[0125] "Method of assigning a title" refers to a method of giving a generated travel plan a name that succinctly expresses its content.

[0126] "Means of customization and updating" refers to methods of adjusting existing travel plans and changing information to accommodate new user requests.

[0127] "Means of generating a preparation list" refers to a method of creating a list of necessary items and activities in accordance with a travel plan.

[0128] "Content delivery methods" refer to methods for automatically providing users with various relevant information while they are traveling.

[0129] "Means of receiving feedback and updating the database" refers to a method of organizing and storing information in order to incorporate feedback from users after their trip and reflect it in future travel planning.

[0130] To implement this invention, the interaction between the server, the terminal, and the user is key.

[0131] The server first receives user attribute information and image information from the cloud and has the function to analyze it. This analysis uses natural language processing technology and image recognition technology to accurately predict the user's preferences and travel requests. Using the analyzed data, a generative AI model is utilized to automatically generate multiple travel plans. The plans are given user-friendly titles to pique the user's interest.

[0132] The terminal is a device that provides an interface with the user. Users input information via a terminal such as a smartphone and receive multiple travel plans generated by the server. From the displayed plans, users can select the one that interests them most and further customize it. For example, they can add specific tourist attractions or change the dates, and these changes are sent to the server in real time, and an updated travel plan is sent back immediately.

[0133] Users manage all aspects of their travel planning through this system. Before their trip, they can receive assistance creating a list of necessary items using their device, and during their trip, they receive real-time content from the server. This content includes recommendations for destinations and information on special events. After their trip, users provide feedback on their experience, and this information is stored in the server's database, which helps improve the quality of future travel suggestions.

[0134] For example, if a user inputs images of "adventure travel" and "mountain scenery," the server will generate multiple travel plans, including hiking and rock climbing. These plans are sent to the user's device to help them choose the best one. An example of a prompt would be, "The user prefers an adventurous travel style and has provided images of mountainous terrain. Please generate the best travel plan."

[0135] This allows for the efficient provision of individually customized travel plans, making it easy for users to realize the travel experience they desire.

[0136] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0137] Step 1:

[0138] The user inputs travel preference information and image data through the terminal. This prepares the terminal to send the input data to the server. The input in this step consists of text information indicating the user's preferences and associated image data, while the output is raw data sent to the server for further analysis.

[0139] Step 2:

[0140] The server analyzes the information received from the user. It uses natural language processing techniques to analyze text information and image recognition techniques to analyze image data. This allows it to infer the user's preferences and travel requests, and then uses a generative AI model to create travel plan generation prompts. The input for this step is user data, and the output is a travel plan generation prompt that is considered to match the user's expectations.

[0141] Step 3:

[0142] The server uses a generative AI model to automatically generate multiple travel plans based on the prompts created in the previous step. Each plan is given a title designed to attract the user's attention. The input for this step is prompt data, and the output is multiple travel plan proposals.

[0143] Step 4:

[0144] The terminal displays travel plans received from the server to the user. The user selects the plan that interests them most from the presented options and can further customize it. In this case, the input is travel plan data from the server, and the output is the user's selected plan and customization information.

[0145] Step 5:

[0146] The user sends their customization information to the server, which receives this information and updates the travel plan. It generates a new plan and sends it to the user's terminal. The input for this step is the customization data, and the output is the updated travel plan.

[0147] Step 6:

[0148] During travel, the server delivers relevant content in real time based on the user's location and schedule. This includes information on tourist attractions and events. The input for this step is the user's real-time data, and the output is the generated content information.

[0149] Step 7:

[0150] After a trip, users enter feedback about their trip via their device. This information is sent to a server and stored in a database. It is then used to improve the quality of future travel planning. The input for this step is user feedback data, and the output is an updated database.

[0151] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0152] This invention is a system that, in addition to suggesting travel plans based on user preferences, provides more appropriate and personalized travel plans by using an emotion engine. The aim of this system is to accurately provide the travel experience that the user desires by analyzing the user's input information and emotions.

[0153] server

[0154] The server has the capability to comprehensively analyze attribute information, image information, and emotion data received from users. First, it uses natural language processing and image recognition technologies to analyze the user's text input and images. In addition, it uses an emotion engine to estimate the emotions the user expresses while selecting or inputting travel plans. These emotions can be inferred from text or obtained through facial expression analysis. From this data, the server comprehensively analyzes the user's preferences and state and automatically generates the optimal travel plan.

[0155] Each travel plan is given a catchy title tailored to the user's situation, and these titles are adjusted accordingly. This process allows us to receive feedback that reflects the user's emotions when they selected a plan, enabling us to continuously learn how to propose plans in the future.

[0156] terminal

[0157] The terminal provides an intuitive interface, allowing users to smoothly input information and select and customize travel plans. If the server determines that emotionally-based adjustments are needed during the travel plan selection process, new suggestions will be presented through the terminal.

[0158] The terminal displays multiple travel plans received from the server in an easily viewable format for the user, providing detailed itinerary information and related activities. Based on the displayed information, users can select a plan that meets specific criteria. Furthermore, it displays a preparation list to help users confirm necessary procedures and items to pack before their trip.

[0159] User

[0160] Users input their travel wishes and preferences as information through the application. Adding images helps to concretize the travel image, but at the same time, important data is collected, including how the application is used and the emotions experienced when selecting travel plans. The emotion engine infers emotions from the user's facial expressions and input content during this process and uses this information to adjust the plan.

[0161] As a concrete example, suppose a user wants to take a shopping trip to a major city and inputs an image of the city's scenery. If the user shows an enthusiastic reaction on the travel plan selection screen, the server analyzes the data received from the device and generates a travel plan that incorporates not only tourist attractions but also recommended shopping spots. When the user selects the optimal plan, the plan is fine-tuned accordingly. After the trip, the user's satisfaction level and impressions are provided as feedback and used to improve future suggestions.

[0162] In this way, this system promotes a more fulfilling travel experience by accurately reflecting the user's preferences and emotions.

[0163] The following describes the processing flow.

[0164] Step 1:

[0165] Users operate their devices to open the app and enter attribute information about their trip (e.g., purpose of travel, preferences) and related images. They can also enter their travel expectations and hopes in text format.

[0166] Step 2:

[0167] The terminal sends attribute information, image information, and text information obtained from the user to the server. At this time, it is also possible to capture the user's facial expressions with a camera during input operations and include them as emotion data.

[0168] Step 3:

[0169] The server receives the transmitted data and analyzes the attribute information using natural language processing technology. This analysis clarifies the user's travel preferences and requests. Image information is analyzed using image recognition technology to extract highly relevant tourist destinations and activities.

[0170] Step 4:

[0171] The server's emotion engine analyzes emotion data and estimates the user's emotional state. Based on these results, it considers travel plans that the user is more likely to find enjoyable.

[0172] Step 5:

[0173] The server uses generative AI to create multiple customized travel plans based on attribute, image, and sentiment analysis results. Each plan is given a catchy title to attract the user's attention.

[0174] Step 6:

[0175] The server sends the generated travel plan to the terminal.

[0176] Step 7:

[0177] The device displays multiple received travel plans to the user. The user can review the details of each travel plan and select one that suits their preferences and circumstances. The user's reaction is monitored in real time as they make their selection.

[0178] Step 8:

[0179] The user selects the most suitable travel plan from the suggested options and enters customization requests into the terminal, adjusting parts of the itinerary as needed.

[0180] Step 9:

[0181] The terminal sends the user's adjustment request to the server.

[0182] Step 10:

[0183] The server re-analyzes the user's emotional data to create the optimal travel plan. If necessary, it automatically rebooks accommodations and transportation.

[0184] Step 11:

[0185] The server sends the finalized travel plan and packing list back to the terminal.

[0186] Step 12:

[0187] The device displays the user's finalized travel plan and a list of necessary preparations before the trip, prompting them to confirm them.

[0188] Step 13:

[0189] After their trip ends, users enter their thoughts and feedback about the trip through the app. This includes providing emotional feedback based on their experiences during the trip.

[0190] Step 14:

[0191] The server receives feedback from users, analyzes it, and updates the database. This data is used to improve future travel planning suggestions.

[0192] (Example 2)

[0193] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0194] Modern travel planning presents a challenge in accurately reflecting the individual preferences and emotions of travelers. Furthermore, traditional travel planning systems often offer fixed itineraries, lacking the flexibility to adapt to changing traveler needs. Therefore, there is a growing need for more personalized plans that fulfill the travel experiences travelers desire.

[0195] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0196] In this invention, the server includes means for receiving and analyzing user attribute information, image information, and emotion data; means for automatically generating multiple travel plans using a generative AI model; and means for assigning titles to the travel plans and customizing them according to the user's emotional state. This makes it possible to dynamically adjust travel plans according to the user's individual preferences and emotions, and to provide an optimal experience.

[0197] "Attribute information" refers to data that indicates a user's personal characteristics and preferences.

[0198] "Image information" refers to visual data, including photographs and diagrams provided by users.

[0199] "Emotional data" refers to information that indicates the emotional state of a user, and is obtained through text analysis and facial recognition.

[0200] A "generative AI model" refers to a technology that uses algorithms to generate new information from data, and is used in natural language processing and data analysis.

[0201] "Natural language processing technology" is a technology that enables computers to understand and generate human language, making text analysis and semantic comprehension possible.

[0202] "Image recognition technology" is a technique that uses computer vision to analyze images and extract useful information from them.

[0203] "Emotion estimation technology" is a technique that analyzes a user's emotions from their text and facial expressions to infer their emotional state.

[0204] A "preparation list" is a list of necessary items and actions based on a travel plan, intended to help travelers prepare for their trip efficiently.

[0205] This invention is a system that provides travel plans based on the individual preferences and emotions of users. This system operates through the interaction of a server, a terminal, and a user, with each component playing the following roles.

[0206] server

[0207] The server comprehensively analyzes attribute information, image information, and sentiment data submitted by the user. This analysis utilizes natural language processing technologies (e.g., Python libraries spaCy and NLTK), image recognition technologies (e.g., OpenCV and TENSORFLOW®), and sentiment estimation technologies (e.g., Hume AI and Affectiva). The server leverages generative AI models (e.g., ChatGPT® and BERT) to automatically generate multiple travel plans based on the acquired data. The generated travel plans are assigned titles that reflect the user's emotional state and are customized according to the user's needs.

[0208] terminal

[0209] The device has the functionality to intuitively display travel plans received from the server to the user. The device provides an interface for viewing detailed information on each travel plan and generates a preparation list outlining necessary items and activities for the trip. Furthermore, the device utilizes notification functions to send reminders to the user, helping to ensure the plan proceeds smoothly.

[0210] User

[0211] Users begin by inputting their individual wishes and preferences through an intuitive application. For example, they might want a shopping trip to a major city and upload photos of cityscapes. This input is presented as prompts such as, "I want to enjoy shopping in a major city," or "I want to visit places that match this image." Once a travel plan is displayed, the user selects the plan that interests them and provides feedback, contributing to improving the accuracy of future suggestions.

[0212] In this way, the interconnectedness of each component makes it possible to provide personalized travel plans that reflect the individual needs and emotions of the user. This system continuously learns to improve the user's travel experience.

[0213] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0214] Step 1:

[0215] Users input information about their travel preferences and desires through the application. Specifically, they upload information about places they want to visit, their preferred activities, and images that represent their travel image. During this process, they may enter prompts such as "I'm interested in hiking in the mountains" or "I want to see this beautiful scenery," and provide relevant image files.

[0216] Step 2:

[0217] The server receives attribute and image information entered by the user and begins analysis. During this process, natural language processing techniques are used to analyze the text data and extract relevant keywords and structures. Image recognition techniques are also used to analyze the uploaded images and identify the locations and activities they represent. The output consists of features and labels derived from the analyzed text and image data.

[0218] Step 3:

[0219] The server uses emotion estimation technology to infer emotional data from user input and provided images. This combines linguistic emotional expressions obtained through text analysis with facial expression analysis within the images. As a result, the user's emotional state (e.g., "excited" or "relaxed") is output as numerical data.

[0220] Step 4:

[0221] The server applies a generative AI model to automatically generate multiple travel plans based on the analyzed data. Here, it considers the user's preferences, emotional state, and past feedback information to create the optimal travel plan and its associated title. The output is provided as a set of selectable travel plans.

[0222] Step 5:

[0223] The device displays multiple travel plans sent from the server in an easy-to-read format. Each travel plan includes detailed itinerary, places to visit, and recommended activities. Users can compare these plans and select the one that interests them. Further details can also be adjusted according to the user's preferences.

[0224] Step 6:

[0225] The user reviews the presented travel plan and makes a selection. Based on the selection, the device displays a preparation list to help the user confirm necessary procedures and items to pack before the trip. The device also uses a notification function to support the user in smoothly carrying out their preparations.

[0226] Step 7:

[0227] When users return from a trip, they provide feedback via their device, sharing their satisfaction level and specific impressions of the trip. The server receives this feedback and updates its database, which is then used to improve future travel plans. Through this process, the system continuously learns and enhances the user experience.

[0228] (Application Example 2)

[0229] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0230] Modern consumers have diverse preferences and demand product suggestions that cater to their moods and feelings. However, existing food delivery services often fail to offer suggestions based on the user's emotions or mood on any given day, instead providing only generic options, which can lead to decreased customer satisfaction.

[0231] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0232] In this invention, the server includes means for analyzing the user's attribute information, image information, and emotional information to infer their preferences and consumption requests; means for generating multiple consumption plans based on the analysis and assigning names to them; and means for customizing the consumption plans according to the user's requests. This makes it possible to provide personalized consumption plans that are tailored to the user's emotions and psychological state on that day.

[0233] "Attribute information" refers to information that identifies an individual or indicates their preferences, such as the user's basic characteristics, tastes, and past consumption history.

[0234] "Image information" refers to photographs and visual data provided by users, which are used as material to infer emotions and preferences through analysis.

[0235] "Emotional information" refers to data that indicates the user's psychological state and emotions, and is estimated through facial recognition and text analysis.

[0236] "Consumption demand" refers to information that represents the consumption behavior and desires that users currently wish to have, and is inferred through analysis.

[0237] A "consumer plan" is a proposal plan for products and services that is automatically generated based on the user's preferences and emotions.

[0238] A "preparation list" is a list of items and actions that a user will need, based on their consumption plan.

[0239] "Feedback" refers to data that shows the level of satisfaction and opinions that consumers provide after using a product or experiencing a service, and it is an important source of information for future proposals.

[0240] A "recording device" is a database that stores user feedback and consumption history to be used for future suggestions.

[0241] This invention comprises a system for providing personalized consumption plans based on user emotional information. This system mainly includes a server, terminals, and a user interface.

[0242] First, the device acquires user attribute information, image information, and current emotional information through a smartphone application. The acquired data is sent to a server in the cloud. The server uses natural language processing and image recognition technologies to analyze the user's emotions and preferences. Specifically, this involves using Google® Cloud Natural Language API and Face API, among other things.

[0243] Based on the analyzed information, a generative AI model automatically generates an optimal consumption plan for the user. This consumption plan is customized according to the user's mood and psychological state on that day, listing multiple options and giving them attractive names. The generated plan is presented to the user via their device.

[0244] Users can select or customize plans presented on their devices and link them to their actual consumption behavior. Feedback after selection is also sent from the device to the server and stored in a recording device. This feedback information is used to improve future suggestions.

[0245] For example, if a user enters a prompt such as, "Today I want something spicy and energizing," the server will suggest menu items that match their desired level of energy and vitality. If the server detects that the user's expression is slightly tired, it can also suggest refreshing beverages.

[0246] An example of a prompt message would be: "The user seems to be in the mood for spicy food and looks a little sleepy. Suggest a dish that will give them energy and consider side options."

[0247] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0248] Step 1:

[0249] The terminal acquires user attribute information, image information, and sentiment information and sends it to the server. The input here is basic data provided by the user through a smartphone application. The output sent to the server is the user's attributes, digital image data, and real-time sentiment estimation data.

[0250] Step 2:

[0251] The server analyzes the received data. In this analysis step, natural language processing technology (Google Cloud Natural Language API) is used to analyze text data, and image recognition technology (Face API) is used to infer emotions and facial expressions from image data. The output obtained from this process reflects the user's preferences and current psychological state.

[0252] Step 3:

[0253] Based on the analyzed information, the server automatically generates an optimal consumption plan for the user using a generative AI model. The input for this process is the preference and emotional data obtained in step 2. As output, multiple personalized consumption plans reflecting the user's emotions and preferences are generated.

[0254] Step 4:

[0255] The server assigns a name to the generated consumption plan and displays it on the terminal. The input is the consumption plan generated in step 3, and the output is a list of plans that the user can select on the terminal.

[0256] Step 5:

[0257] Users select or customize a consumption plan presented via the terminal. Input here includes the user's selection information and facial expressions during selection, and the specific selected consumption plan is displayed on the terminal as output.

[0258] Step 6:

[0259] The device collects user feedback and sends it to the server. The input is user feedback and satisfaction data after consumption, and the output is feedback information stored in the server's recording device.

[0260] Step 7:

[0261] The server uses feedback information stored in the recording device to improve the next proposal. The input is feedback data, and the output is the updated proposal method and content based on the feedback.

[0262] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0263] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0264] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0265] [Second Embodiment]

[0266] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0267] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0268] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0269] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0270] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0271] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0272] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0273] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0274] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0275] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0276] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0277] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0278] This invention provides a system that automatically generates travel plans tailored to the individual preferences of users and allows for easy customization. This system is designed to enhance the convenience of users in creating their preferred travel plans without any hassle. An embodiment of this system is described below.

[0279] server

[0280] The server provides a foundation for analyzing data such as attribute information and image information received from users. Based on the analyzed data, it utilizes generative AI to generate multiple travel plans that combine various tourist destinations, means of transportation, and accommodation facilities. As a result, multiple plans that meet the user's expectations are proposed. In addition, a title that attracts the user's interest is assigned to the generated travel plans. This title helps the user when choosing a plan.

[0281] Furthermore, the server has a function to analyze feedback from users and learn and update the database for use in proposing future travel plans. This feedback includes not only satisfaction and exciting points during the trip but also the user's wishes for future trips.

[0282] Terminal

[0283] The terminal provides an interface for the user to input information. It has the function to send attribute information and images to the server and displays the received multiple travel plans for the user to view. Each travel plan includes a detailed itinerary and related activity information. Also, when the user customizes a part of the itinerary, the terminal can send that information to the server and receive a new itinerary. Furthermore, it displays a preparation list and items needed before the trip to assist the user in making thorough travel preparations.

[0284] User

[0285] The user starts interacting with the system by inputting attribute information and images related to the desired trip on the application. The user selects the most interesting one from the presented multiple travel plans and checks its details. Customizes the travel plan if necessary and finalizes the ultimate plan. After the trip, the user provides feedback through the app, records their travel experience, and contributes to improving the quality of future travel plans.

[0286] As a specific example, assume that a user hopes to travel to a summer resort area and uploads an image of a beach in that area to the app. The server analyzes the image and the user's preferences, and generates multiple travel plans that include nearby beach resorts, activities (such as diving, beach parties), and transportation options. After the user makes adjustments based on these plans, the terminal displays the items needed for the trip and a detailed checklist to support the user's travel preparation.

[0287] The following describes the processing flow.

[0288] Step 1:

[0289] The user accesses the app via the terminal and inputs their attribute information (e.g., age, travel style) and an image related to the travel destination they want to go to.

[0290] Step 2:

[0291] The terminal sends the information and image input by the user to the server. This is done using data communication technology.

[0292] Step 3:

[0293] The server analyzes the received attribute information using natural language processing technology to extract the user's preferences and travel purposes. Also, it analyzes the uploaded image using image recognition technology to identify related tourist attractions and activities.

[0294] Step 4:

[0295] Based on the analysis results, the server uses a generation AI to automatically generate multiple travel plans. This includes combinations of tourist attractions, accommodation facilities, means of transportation, and activities. Also, each travel plan is given a catchy title.

[0296] Step 5:

[0297] The server sends the generated travel plan to the terminal.

[0298] Step 6:

[0299] The terminal visually displays the multiple travel plans received from the server to the user. The user can check the details of each plan.

[0300] Step 7:

[0301] The user selects the optimal one from the presented travel plans and inputs a request to the terminal to customize a part of the itinerary if necessary.

[0302] Step 8:

[0303] The terminal sends the user's customization request to the server.

[0304] Step 9:

[0305] The server regenerates the travel plan selected based on the user's request and rearranges accommodation facilities and transportation means if necessary.

[0306] Step 10:

[0307] The server sends the completed travel plan and the accompanying preparation list to the terminal.

[0308] Step 11:

[0309] The terminal displays the latest travel plan and the preparation list and items list required before the trip to the user.

[0310] Step 12:

[0311] After the user finishes the trip, the user inputs the feelings and feedback of the trip through the app.

[0312] Step 13:

[0313] The server analyzes user feedback and updates its database to use it for suggesting future travel plans.

[0314] (Example 1)

[0315] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0316] Planning a trip involves gathering a lot of information and manual adjustments, and planning according to individual preferences is particularly complex and time-consuming. Users want a system that can automatically and easily create trips that match their preferences. They also want a system that uses post-trip feedback to improve future plans. Furthermore, it is necessary to use images and language information to precisely understand user needs and provide the optimal travel plan.

[0317] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0318] This invention includes a server that receives attribute data and image data from a user and interprets this information to estimate the user's preferences and travel itinerary desires; a server that utilizes a generative AI model to provide an optimal plan tailored to the user's preferences; and an image recognition technology that extracts relevant tourist destinations and activities from images input by the user. This enables users to easily and automatically generate travel plans that suit their preferences and to proceed with planning efficiently.

[0319] "Attribute data" refers to personal information such as the user's age, hobbies, and budget, and is basic information used to customize travel plans.

[0320] "Image data" refers to image information provided by users for reference in their travel planning, and includes visual data related to tourist destinations and preferences.

[0321] A "generative AI model" is a general term for algorithms that use artificial intelligence technology to generate optimal travel plans based on the user's preferences and requests.

[0322] A "prompt message" is a sentence that describes the user's wishes and requests to the system, and it provides initial input information for creating a travel plan.

[0323] "Interpreting" refers to the process of analyzing data received from users and understanding its meaning and intent.

[0324] A "travel itinerary" refers to a proposed itinerary for a trip, created by combining tourist destinations, activities, transportation, accommodations, and other elements.

[0325] "Image recognition technology" is a technology used to identify and interpret objects and features in images, and is utilized to optimize travel planning.

[0326] A "preparation list" refers to a list that organizes and presents to the user the necessary items and procedures for traveling.

[0327] "Information records" refer to a database that stores user feedback and related information to help generate future travel plans.

[0328] This invention provides a system that automatically generates travel plans tailored to the user's preferences and allows for easy customization. An example of this system is described below.

[0329] server

[0330] The server receives attribute and image data sent by users and provides a platform for interpreting this information. The received data is analyzed using a generative AI model to generate an optimal travel plan tailored to the user's preferences and requests. This generative AI model uses natural language processing and image recognition technologies to evaluate the attribute and image data and precisely understand the user's needs. Through this process, the server creates multiple travel plans, including tourist destinations, activities, transportation, and accommodations, and each plan is given a title designed to attract the user's interest.

[0331] For example, if a user uploads a beach image along with the prompt message, "I want to relax on the beach during my summer vacation. Please suggest some recommended resorts and activities I can do there. I've attached a photo of a beach," the server will use that information to generate a travel plan that includes activities and transportation options at nearby resorts.

[0332] terminal

[0333] The terminal provides an interface for users to input information into the system. This transmits attribute and image data to the server. Furthermore, the terminal displays multiple received travel plans on its screen, allowing users to compare and select them. Each plan includes detailed itinerary and associated activity information. When users customize a plan, the changes are resent to the server via the terminal, providing an updated travel plan. The terminal also displays packing lists and preparation checklists to assist with travel preparations.

[0334] user

[0335] This system allows users to input their personal information and travel preferences to receive personalized travel plan suggestions. Users can then select plans that interest them, review their details, and adjust them as needed to create the optimal travel plan. Furthermore, by providing feedback after their trip and recording their experiences, users can contribute to improving future travel plans.

[0336] This system enables users to quickly and efficiently create travel plans tailored to their individual needs. By utilizing a generative AI model and prompt messages, the system achieves highly accurate automatic generation and customization of travel plans.

[0337] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0338] Step 1:

[0339] Users input attribute data (e.g., age, hobbies, budget) and image data related to their travel destination through the application. This input is sent to the server via the terminal. More specific data is provided when users explicitly state their travel requests using prompts, such as "I want to relax on the beach."

[0340] Step 2:

[0341] The server interprets the received attribute and image data. Using a generative AI model, it analyzes the prompt text and image data to infer the user's preferences. For example, it extracts features from beach image data and selects related tourist destinations and activities. This results in the output of information based on the user's wishes.

[0342] Step 3:

[0343] The server automatically generates multiple travel plans based on the analysis results. The generation AI model creates plans by combining tourist destinations, accommodations, and modes of transportation, and assigns an appealing name to each. The generated plans are configured to be customizable according to the user's requests.

[0344] Step 4:

[0345] The device displays multiple travel plans provided by the server to the user. The user can review these options and access detailed itinerary and activity information for each plan. Specifically, the device interface provides a function to compare and select each plan.

[0346] Step 5:

[0347] Users select a travel plan that interests them from the displayed options and customize it as needed. The user's customization requests are resent to the server via their device, and a more accurate travel plan is updated. During this process, details of the plan and itinerary are adjusted.

[0348] Step 6:

[0349] The server creates a regenerated travel plan based on the user's customization information. The regenerated plan is optimized based on the user's preferences, and any additions or modifications the user requests are reflected.

[0350] Step 7:

[0351] The device displays a packing list and preparation checklist for the trip to the user. It provides the necessary information appropriately to ensure smooth travel preparations.

[0352] Step 8:

[0353] After the trip, users provide feedback through the application. The server receives this feedback information and updates its database. The feedback is used to create future travel plans, contributing to improving the accuracy of the system's suggestions.

[0354] (Application Example 1)

[0355] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0356] Conventional travel planning systems have suffered from insufficient customization based on user preferences and a lack of ability to provide real-time information during travel. Furthermore, they lacked mechanisms to utilize user feedback to improve future plans, making it difficult to improve user satisfaction. In this situation, there is a need for a system that accurately reflects user preferences and provides comprehensive support throughout the entire travel experience.

[0357] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0358] In this invention, the server includes means for receiving user attribute information and image information and analyzing that data to infer the user's preferences and travel requests; means for automatically generating multiple travel plans based on the analysis and assigning titles to the generated travel plans; means for customizing and updating the travel plans according to the user's requests; means for generating a preparation list that presents necessary items and activities based on the travel plans; means for providing content that delivers various relevant information based on the user's travel data; and means for receiving the user's post-trip feedback and updating a database for use in future plan suggestions. This makes it possible to provide flexible travel plans tailored to the user's preferences, as well as a system for real-time support during travel and for utilizing feedback in future plans.

[0359] "User attribute information" refers to data that represents the unique characteristics and interests of each user, and is used to personalize travel plans.

[0360] "Image information" refers to visual materials provided by users, which are analyzed to gain a more concrete understanding of their preferences and needs.

[0361] "Means for inferring preferences and travel requests" refers to methods for predicting user preferences and requests based on input information and presenting the most suitable travel plan.

[0362] "Methods for automatically generating multiple travel plans" refer to methods for mechanically constructing diverse travel possibilities based on the user's preferences and requests.

[0363] "Method of assigning a title" refers to a method of giving a generated travel plan a name that succinctly expresses its content.

[0364] "Means of customization and updating" refers to methods of adjusting existing travel plans and changing information to accommodate new user requests.

[0365] "Means of generating a preparation list" refers to a method of creating a list of necessary items and activities in accordance with a travel plan.

[0366] "Content delivery methods" refer to methods for automatically providing users with various relevant information while they are traveling.

[0367] "Means of receiving feedback and updating the database" refers to a method of organizing and storing information in order to incorporate feedback from users after their trip and reflect it in future travel planning.

[0368] To implement this invention, the interaction between the server, the terminal, and the user is key.

[0369] The server first receives user attribute information and image information from the cloud and has the function to analyze it. This analysis uses natural language processing technology and image recognition technology to accurately predict the user's preferences and travel requests. Using the analyzed data, a generative AI model is utilized to automatically generate multiple travel plans. The plans are given user-friendly titles to pique the user's interest.

[0370] The terminal is a device that provides an interface with the user. Users input information via a terminal such as a smartphone and receive multiple travel plans generated by the server. From the displayed plans, users can select the one that interests them most and further customize it. For example, they can add specific tourist attractions or change the dates, and these changes are sent to the server in real time, and an updated travel plan is sent back immediately.

[0371] Users manage all aspects of their travel planning through this system. Before their trip, they can receive assistance creating a list of necessary items using their device, and during their trip, they receive real-time content from the server. This content includes recommendations for destinations and information on special events. After their trip, users provide feedback on their experience, and this information is stored in the server's database, which helps improve the quality of future travel suggestions.

[0372] For example, if a user inputs images of "adventure travel" and "mountain scenery," the server will generate multiple travel plans, including hiking and rock climbing. These plans are sent to the user's device to help them choose the best one. An example of a prompt would be, "The user prefers an adventurous travel style and has provided images of mountainous terrain. Please generate the best travel plan."

[0373] This allows for the efficient provision of individually customized travel plans, making it easy for users to realize the travel experience they desire.

[0374] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0375] Step 1:

[0376] The user inputs travel preference information and image data through the terminal. This prepares the terminal to send the input data to the server. The input in this step consists of text information indicating the user's preferences and associated image data, while the output is raw data sent to the server for further analysis.

[0377] Step 2:

[0378] The server analyzes the information received from the user. It uses natural language processing techniques to analyze text information and image recognition techniques to analyze image data. This allows it to infer the user's preferences and travel requests, and then uses a generative AI model to create travel plan generation prompts. The input for this step is user data, and the output is a travel plan generation prompt that is considered to match the user's expectations.

[0379] Step 3:

[0380] The server uses a generative AI model to automatically generate multiple travel plans based on the prompts created in the previous step. Each plan is given a title designed to attract the user's attention. The input for this step is prompt data, and the output is multiple travel plan proposals.

[0381] Step 4:

[0382] The terminal displays travel plans received from the server to the user. The user selects the plan that interests them most from the presented options and can further customize it. In this case, the input is travel plan data from the server, and the output is the user's selected plan and customization information.

[0383] Step 5:

[0384] The user sends their customization information to the server, which receives this information and updates the travel plan. It generates a new plan and sends it to the user's terminal. The input for this step is the customization data, and the output is the updated travel plan.

[0385] Step 6:

[0386] During travel, the server delivers relevant content in real time based on the user's location and schedule. This includes information on tourist attractions and events. The input for this step is the user's real-time data, and the output is the generated content information.

[0387] Step 7:

[0388] After a trip, users enter feedback about their trip via their device. This information is sent to a server and stored in a database. It is then used to improve the quality of future travel planning. The input for this step is user feedback data, and the output is an updated database.

[0389] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0390] This invention is a system that, in addition to suggesting travel plans based on user preferences, provides more appropriate and personalized travel plans by using an emotion engine. The aim of this system is to accurately provide the travel experience that the user desires by analyzing the user's input information and emotions.

[0391] server

[0392] The server has the capability to comprehensively analyze attribute information, image information, and emotion data received from users. First, it uses natural language processing and image recognition technologies to analyze the user's text input and images. In addition, it uses an emotion engine to estimate the emotions the user expresses while selecting or inputting travel plans. These emotions can be inferred from text or obtained through facial expression analysis. From this data, the server comprehensively analyzes the user's preferences and state and automatically generates the optimal travel plan.

[0393] Each travel plan is given a catchy title tailored to the user's situation, and these titles are adjusted accordingly. This process allows us to receive feedback that reflects the user's emotions when they selected a plan, enabling us to continuously learn how to propose plans in the future.

[0394] terminal

[0395] The terminal provides an intuitive interface, allowing users to smoothly input information and select and customize travel plans. If the server determines that emotionally-based adjustments are needed during the travel plan selection process, new suggestions will be presented through the terminal.

[0396] The terminal displays multiple travel plans received from the server in an easily viewable format for the user, providing detailed itinerary information and related activities. Based on the displayed information, users can select a plan that meets specific criteria. Furthermore, it displays a preparation list to help users confirm necessary procedures and items to pack before their trip.

[0397] User

[0398] Users input their travel wishes and preferences as information through the application. Adding images helps to concretize the travel image, but at the same time, important data is collected, including how the application is used and the emotions experienced when selecting travel plans. The emotion engine infers emotions from the user's facial expressions and input content during this process and uses this information to adjust the plan.

[0399] As a concrete example, suppose a user wants to take a shopping trip to a major city and inputs an image of the city's scenery. If the user shows an enthusiastic reaction on the travel plan selection screen, the server analyzes the data received from the device and generates a travel plan that incorporates not only tourist attractions but also recommended shopping spots. When the user selects the optimal plan, the plan is fine-tuned accordingly. After the trip, the user's satisfaction level and impressions are provided as feedback and used to improve future suggestions.

[0400] In this way, this system promotes a more fulfilling travel experience by accurately reflecting the user's preferences and emotions.

[0401] The following describes the processing flow.

[0402] Step 1:

[0403] Users operate their devices to open the app and enter attribute information about their trip (e.g., purpose of travel, preferences) and related images. They can also enter their travel expectations and hopes in text format.

[0404] Step 2:

[0405] The terminal sends attribute information, image information, and text information obtained from the user to the server. At this time, it is also possible to capture the user's facial expressions with a camera during input operations and include them as emotion data.

[0406] Step 3:

[0407] The server receives the transmitted data and analyzes the attribute information using natural language processing technology. This analysis clarifies the user's travel preferences and requests. Image information is analyzed using image recognition technology to extract highly relevant tourist destinations and activities.

[0408] Step 4:

[0409] The server's emotion engine analyzes emotion data and estimates the user's emotional state. Based on these results, it considers travel plans that the user is more likely to find enjoyable.

[0410] Step 5:

[0411] The server uses generative AI to create multiple customized travel plans based on attribute, image, and sentiment analysis results. Each plan is given a catchy title to attract the user's attention.

[0412] Step 6:

[0413] The server sends the generated travel plan to the terminal.

[0414] Step 7:

[0415] The device displays multiple received travel plans to the user. The user can review the details of each travel plan and select one that suits their preferences and circumstances. The user's reaction is monitored in real time as they make their selection.

[0416] Step 8:

[0417] The user selects the most suitable travel plan from the suggested options and enters customization requests into the terminal, adjusting parts of the itinerary as needed.

[0418] Step 9:

[0419] The terminal sends the user's adjustment request to the server.

[0420] Step 10:

[0421] The server re-analyzes the user's emotional data to create the optimal travel plan. If necessary, it automatically rebooks accommodations and transportation.

[0422] Step 11:

[0423] The server sends the finalized travel plan and packing list back to the terminal.

[0424] Step 12:

[0425] The device displays the user's finalized travel plan and a list of necessary preparations before the trip, prompting them to confirm them.

[0426] Step 13:

[0427] After their trip ends, users enter their thoughts and feedback about the trip through the app. This includes providing emotional feedback based on their experiences during the trip.

[0428] Step 14:

[0429] The server receives feedback from users, analyzes it, and updates the database. This data is used to improve future travel planning suggestions.

[0430] (Example 2)

[0431] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0432] Modern travel planning presents a challenge in accurately reflecting the individual preferences and emotions of travelers. Furthermore, traditional travel planning systems often offer fixed itineraries, lacking the flexibility to adapt to changing traveler needs. Therefore, there is a growing need for more personalized plans that fulfill the travel experiences travelers desire.

[0433] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0434] In this invention, the server includes means for receiving and analyzing user attribute information, image information, and emotion data; means for automatically generating multiple travel plans using a generative AI model; and means for assigning titles to the travel plans and customizing them according to the user's emotional state. This makes it possible to dynamically adjust travel plans according to the user's individual preferences and emotions, and to provide an optimal experience.

[0435] "Attribute information" refers to data that indicates a user's personal characteristics and preferences.

[0436] "Image information" refers to visual data, including photographs and diagrams provided by users.

[0437] "Emotional data" refers to information that indicates the emotional state of a user, and is obtained through text analysis and facial recognition.

[0438] A "generative AI model" refers to a technology that uses algorithms to generate new information from data, and is used in natural language processing and data analysis.

[0439] "Natural language processing technology" is a technology that enables computers to understand and generate human language, making text analysis and semantic comprehension possible.

[0440] "Image recognition technology" is a technique that uses computer vision to analyze images and extract useful information from them.

[0441] "Emotion estimation technology" is a technique that analyzes a user's emotions from their text and facial expressions to infer their emotional state.

[0442] A "preparation list" is a list of necessary items and actions based on a travel plan, intended to help travelers prepare for their trip efficiently.

[0443] This invention is a system that provides travel plans based on the individual preferences and emotions of users. This system operates through the interaction of a server, a terminal, and a user, with each component playing the following roles.

[0444] server

[0445] The server comprehensively analyzes attribute information, image information, and sentiment data submitted by the user. This analysis utilizes natural language processing technologies (e.g., Python libraries such as spaCy and NLTK), image recognition technologies (e.g., OpenCV and TensorFlow), and sentiment estimation technologies (e.g., Hume AI and Affectiva). The server leverages generative AI models (e.g., ChatGPT and BERT) to automatically generate multiple travel plans based on the acquired data. The generated travel plans are assigned titles that reflect the user's emotional state and are customized according to the user's needs.

[0446] terminal

[0447] The device has the functionality to intuitively display travel plans received from the server to the user. The device provides an interface for viewing detailed information on each travel plan and generates a preparation list outlining necessary items and activities for the trip. Furthermore, the device utilizes notification functions to send reminders to the user, helping to ensure the plan proceeds smoothly.

[0448] User

[0449] Users begin by inputting their individual wishes and preferences through an intuitive application. For example, they might want a shopping trip to a major city and upload photos of cityscapes. This input is presented as prompts such as, "I want to enjoy shopping in a major city," or "I want to visit places that match this image." Once a travel plan is displayed, the user selects the plan that interests them and provides feedback, contributing to improving the accuracy of future suggestions.

[0450] In this way, the interconnectedness of each component makes it possible to provide personalized travel plans that reflect the individual needs and emotions of the user. This system continuously learns to improve the user's travel experience.

[0451] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0452] Step 1:

[0453] Users input information about their travel preferences and desires through the application. Specifically, they upload information about places they want to visit, their preferred activities, and images that represent their travel image. During this process, they may enter prompts such as "I'm interested in hiking in the mountains" or "I want to see this beautiful scenery," and provide relevant image files.

[0454] Step 2:

[0455] The server receives attribute and image information entered by the user and begins analysis. During this process, natural language processing techniques are used to analyze the text data and extract relevant keywords and structures. Image recognition techniques are also used to analyze the uploaded images and identify the locations and activities they represent. The output consists of features and labels derived from the analyzed text and image data.

[0456] Step 3:

[0457] The server uses emotion estimation technology to infer emotional data from user input and provided images. This combines linguistic emotional expressions obtained through text analysis with facial expression analysis within the images. As a result, the user's emotional state (e.g., "excited" or "relaxed") is output as numerical data.

[0458] Step 4:

[0459] The server applies a generative AI model to automatically generate multiple travel plans based on the analyzed data. Here, it considers the user's preferences, emotional state, and past feedback information to create the optimal travel plan and its associated title. The output is provided as a set of selectable travel plans.

[0460] Step 5:

[0461] The device displays multiple travel plans sent from the server in an easy-to-read format. Each travel plan includes detailed itinerary, places to visit, and recommended activities. Users can compare these plans and select the one that interests them. Further details can also be adjusted according to the user's preferences.

[0462] Step 6:

[0463] The user reviews the presented travel plan and makes a selection. Based on the selection, the device displays a preparation list to help the user confirm necessary procedures and items to pack before the trip. The device also uses a notification function to support the user in smoothly carrying out their preparations.

[0464] Step 7:

[0465] When users return from a trip, they provide feedback via their device, sharing their satisfaction level and specific impressions of the trip. The server receives this feedback and updates its database, which is then used to improve future travel plans. Through this process, the system continuously learns and enhances the user experience.

[0466] (Application Example 2)

[0467] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0468] Modern consumers have diverse preferences and demand product suggestions that cater to their moods and feelings. However, existing food delivery services often fail to offer suggestions based on the user's emotions or mood on any given day, instead providing only generic options, which can lead to decreased customer satisfaction.

[0469] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0470] In this invention, the server includes means for analyzing the user's attribute information, image information, and emotional information to infer their preferences and consumption requests; means for generating multiple consumption plans based on the analysis and assigning names to them; and means for customizing the consumption plans according to the user's requests. This makes it possible to provide personalized consumption plans that are tailored to the user's emotions and psychological state on that day.

[0471] "Attribute information" refers to information that identifies an individual or indicates their preferences, such as the user's basic characteristics, tastes, and past consumption history.

[0472] "Image information" refers to photographs and visual data provided by users, which are used as material to infer emotions and preferences through analysis.

[0473] "Emotional information" refers to data that indicates the user's psychological state and emotions, and is estimated through facial recognition and text analysis.

[0474] "Consumption demand" refers to information that represents the consumption behavior and desires that users currently wish to have, and is inferred through analysis.

[0475] A "consumer plan" is a proposal plan for products and services that is automatically generated based on the user's preferences and emotions.

[0476] A "preparation list" is a list of items and actions that a user will need, based on their consumption plan.

[0477] "Feedback" refers to data that shows the level of satisfaction and opinions that consumers provide after using a product or experiencing a service, and it is an important source of information for future proposals.

[0478] A "recording device" is a database that stores user feedback and consumption history to be used for future suggestions.

[0479] This invention comprises a system for providing personalized consumption plans based on user emotional information. This system mainly includes a server, terminals, and a user interface.

[0480] First, the device acquires user attribute information, image information, and current emotional information through a smartphone application. The acquired data is sent to a server in the cloud. The server uses natural language processing and image recognition technologies to analyze the user's emotions and preferences. Specifically, this might involve using Google Cloud Natural Language API or Face API.

[0481] Based on the analyzed information, a generative AI model automatically generates an optimal consumption plan for the user. This consumption plan is customized according to the user's mood and psychological state on that day, listing multiple options and giving them attractive names. The generated plan is presented to the user via their device.

[0482] Users can select or customize plans presented on their devices and link them to their actual consumption behavior. Feedback after selection is also sent from the device to the server and stored in a recording device. This feedback information is used to improve future suggestions.

[0483] For example, if a user enters a prompt such as, "Today I want something spicy and energizing," the server will suggest menu items that match their desired level of energy and vitality. If the server detects that the user's expression is slightly tired, it can also suggest refreshing beverages.

[0484] An example of a prompt message would be: "The user seems to be in the mood for spicy food and looks a little sleepy. Suggest a dish that will give them energy and consider side options."

[0485] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0486] Step 1:

[0487] The terminal acquires user attribute information, image information, and sentiment information and sends it to the server. The input here is basic data provided by the user through a smartphone application. The output sent to the server is the user's attributes, digital image data, and real-time sentiment estimation data.

[0488] Step 2:

[0489] The server analyzes the received data. In this analysis step, natural language processing technology (Google Cloud Natural Language API) is used to analyze text data, and image recognition technology (Face API) is used to infer emotions and facial expressions from image data. The output obtained from this process reflects the user's preferences and current psychological state.

[0490] Step 3:

[0491] Based on the analyzed information, the server automatically generates an optimal consumption plan for the user using a generative AI model. The input for this process is the preference and emotional data obtained in step 2. As output, multiple personalized consumption plans reflecting the user's emotions and preferences are generated.

[0492] Step 4:

[0493] The server assigns a name to the generated consumption plan and displays it on the terminal. The input is the consumption plan generated in step 3, and the output is a list of plans that the user can select on the terminal.

[0494] Step 5:

[0495] Users select or customize a consumption plan presented via the terminal. Input here includes the user's selection information and facial expressions during selection, and the specific selected consumption plan is displayed on the terminal as output.

[0496] Step 6:

[0497] The device collects user feedback and sends it to the server. The input is user feedback and satisfaction data after consumption, and the output is feedback information stored in the server's recording device.

[0498] Step 7:

[0499] The server uses feedback information stored in the recording device to improve the next proposal. The input is feedback data, and the output is the updated proposal method and content based on the feedback.

[0500] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0501] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0502] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0503] [Third Embodiment]

[0504] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0505] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0506] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0507] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0508] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0509] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0510] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0511] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0512] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0513] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0514] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0515] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0516] This invention provides a system that automatically generates travel plans tailored to the individual preferences of users and allows for easy customization. This system is designed to enhance the convenience of users in creating their preferred travel plans without any hassle. An embodiment of this system is described below.

[0517] server

[0518] The server provides a platform for analyzing attribute and image data received from users. Based on the analyzed data, it uses a generative AI to generate multiple travel plans combining various tourist destinations, modes of transportation, and accommodations. This ensures that multiple plans tailored to the user's preferences are proposed. In addition, the generated travel plans are given titles that are likely to attract the user's interest. These titles help users choose a plan.

[0519] Furthermore, the server has the ability to learn and update its database by analyzing user feedback and using it to suggest future travel plans. This feedback includes not only satisfaction and excitement during the trip, but also hopes for future trips.

[0520] terminal

[0521] The terminal provides an interface for users to input information. It has the functionality to send attribute information and images to the server and displays multiple received travel plans for the user to review. Each travel plan includes a detailed itinerary and related activity information. Furthermore, when a user customizes part of the itinerary, the terminal sends that information to the server and receives a new itinerary. In addition, it displays a list of necessary preparations and items to pack before the trip, helping users to complete their travel preparations without forgetting anything.

[0522] user

[0523] Users begin interacting with the system by entering attribute information and images related to their desired trip within the application. They select the travel plan that interests them most from several presented options and review its details. They customize the travel plan as needed and finalize their itinerary. After the trip, they provide feedback through the app, recording their travel experience and contributing to improving the quality of future travel planning.

[0524] As a concrete example, suppose a user wants to travel to a summer resort and uploads images of beaches in that area to the app. The server analyzes the images and the user's preferences and generates multiple travel plans, including nearby beach resorts, activities (e.g., diving, beach parties), and transportation options. After the user makes adjustments based on these plans, the device displays a packing list and a detailed checklist to support the user's travel preparations.

[0525] The following describes the processing flow.

[0526] Step 1:

[0527] Users access the app via their device and enter their personal information (e.g., age, travel style) and images related to their desired travel destinations.

[0528] Step 2:

[0529] The terminal transmits user-entered information and images to the server. This is done using data communication technology.

[0530] Step 3:

[0531] The server analyzes the received attribute information using natural language processing technology to extract the user's preferences and travel objectives. It also analyzes uploaded images using image recognition technology to identify relevant tourist destinations and activities.

[0532] Step 4:

[0533] Based on the analysis results, the server automatically generates multiple travel plans using a generation AI. These plans include combinations of tourist destinations, accommodations, transportation, and activities. Each travel plan is also given a catchy title.

[0534] Step 5:

[0535] The server sends the generated travel plan to the terminal.

[0536] Step 6:

[0537] The terminal visually displays multiple travel plans received from the server to the user. The user can then view the details of each plan.

[0538] Step 7:

[0539] The user selects the most suitable travel plan from the presented options and enters requests into the terminal to customize parts of the itinerary as needed.

[0540] Step 8:

[0541] The terminal sends the user's customization requests to the server.

[0542] Step 9:

[0543] The server regenerates the travel plan selected based on the user's request and rearranges accommodations and transportation if necessary.

[0544] Step 10:

[0545] The server sends the completed travel plan and the accompanying preparation list to the terminal.

[0546] Step 11:

[0547] The device displays the user's latest travel plans and a list of necessary preparations and packing lists before the trip.

[0548] Step 12:

[0549] After completing their trip, users will enter their travel impressions and feedback through the app.

[0550] Step 13:

[0551] The server analyzes user feedback and updates its database to use it for suggesting future travel plans.

[0552] (Example 1)

[0553] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0554] Planning a trip involves gathering a lot of information and manual adjustments, and planning according to individual preferences is particularly complex and time-consuming. Users want a system that can automatically and easily create trips that match their preferences. They also want a system that uses post-trip feedback to improve future plans. Furthermore, it is necessary to use images and language information to precisely understand user needs and provide the optimal travel plan.

[0555] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0556] This invention includes a server that receives attribute data and image data from a user and interprets this information to estimate the user's preferences and travel itinerary desires; a server that utilizes a generative AI model to provide an optimal plan tailored to the user's preferences; and an image recognition technology that extracts relevant tourist destinations and activities from images input by the user. This enables users to easily and automatically generate travel plans that suit their preferences and to proceed with planning efficiently.

[0557] "Attribute data" refers to personal information such as the user's age, hobbies, and budget, and is basic information used to customize travel plans.

[0558] "Image data" refers to image information provided by users for reference in their travel planning, and includes visual data related to tourist destinations and preferences.

[0559] A "generative AI model" is a general term for algorithms that use artificial intelligence technology to generate optimal travel plans based on the user's preferences and requests.

[0560] A "prompt message" is a sentence that describes the user's wishes and requests to the system, and it provides initial input information for creating a travel plan.

[0561] "Interpreting" refers to the process of analyzing data received from users and understanding its meaning and intent.

[0562] A "travel itinerary" refers to a proposed itinerary for a trip, created by combining tourist destinations, activities, transportation, accommodations, and other elements.

[0563] "Image recognition technology" is a technology used to identify and interpret objects and features in images, and is utilized to optimize travel planning.

[0564] A "preparation list" refers to a list that organizes and presents to the user the necessary items and procedures for traveling.

[0565] "Information records" refer to a database that stores user feedback and related information to help generate future travel plans.

[0566] This invention provides a system that automatically generates travel plans tailored to the user's preferences and allows for easy customization. An example of this system is described below.

[0567] server

[0568] The server receives attribute and image data sent by users and provides a platform for interpreting this information. The received data is analyzed using a generative AI model to generate an optimal travel plan tailored to the user's preferences and requests. This generative AI model uses natural language processing and image recognition technologies to evaluate the attribute and image data and precisely understand the user's needs. Through this process, the server creates multiple travel plans, including tourist destinations, activities, transportation, and accommodations, and each plan is given a title designed to attract the user's interest.

[0569] For example, if a user uploads a beach image along with the prompt message, "I want to relax on the beach during my summer vacation. Please suggest some recommended resorts and activities I can do there. I've attached a photo of a beach," the server will use that information to generate a travel plan that includes activities and transportation options at nearby resorts.

[0570] terminal

[0571] The terminal provides an interface for users to input information into the system. This transmits attribute and image data to the server. Furthermore, the terminal displays multiple received travel plans on its screen, allowing users to compare and select them. Each plan includes detailed itinerary and associated activity information. When users customize a plan, the changes are resent to the server via the terminal, providing an updated travel plan. The terminal also displays packing lists and preparation checklists to assist with travel preparations.

[0572] user

[0573] This system allows users to input their personal information and travel preferences to receive personalized travel plan suggestions. Users can then select plans that interest them, review their details, and adjust them as needed to create the optimal travel plan. Furthermore, by providing feedback after their trip and recording their experiences, users can contribute to improving future travel plans.

[0574] This system enables users to quickly and efficiently create travel plans tailored to their individual needs. By utilizing a generative AI model and prompt messages, the system achieves highly accurate automatic generation and customization of travel plans.

[0575] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0576] Step 1:

[0577] Users input attribute data (e.g., age, hobbies, budget) and image data related to their travel destination through the application. This input is sent to the server via the terminal. More specific data is provided when users explicitly state their travel requests using prompts, such as "I want to relax on the beach."

[0578] Step 2:

[0579] The server interprets the received attribute and image data. Using a generative AI model, it analyzes the prompt text and image data to infer the user's preferences. For example, it extracts features from beach image data and selects related tourist destinations and activities. This results in the output of information based on the user's wishes.

[0580] Step 3:

[0581] The server automatically generates multiple travel plans based on the analysis results. The generation AI model creates plans by combining tourist destinations, accommodations, and modes of transportation, and assigns an appealing name to each. The generated plans are configured to be customizable according to the user's requests.

[0582] Step 4:

[0583] The device displays multiple travel plans provided by the server to the user. The user can review these options and access detailed itinerary and activity information for each plan. Specifically, the device interface provides a function to compare and select each plan.

[0584] Step 5:

[0585] Users select a travel plan that interests them from the displayed options and customize it as needed. The user's customization requests are resent to the server via their device, and a more accurate travel plan is updated. During this process, details of the plan and itinerary are adjusted.

[0586] Step 6:

[0587] The server creates a regenerated travel plan based on the user's customization information. The regenerated plan is optimized based on the user's preferences, and any additions or modifications the user requests are reflected.

[0588] Step 7:

[0589] The device displays a packing list and preparation checklist for the trip to the user. It provides the necessary information appropriately to ensure smooth travel preparations.

[0590] Step 8:

[0591] After the trip, users provide feedback through the application. The server receives this feedback information and updates its database. The feedback is used to create future travel plans, contributing to improving the accuracy of the system's suggestions.

[0592] (Application Example 1)

[0593] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0594] Conventional travel planning systems have suffered from insufficient customization based on user preferences and a lack of ability to provide real-time information during travel. Furthermore, they lacked mechanisms to utilize user feedback to improve future plans, making it difficult to improve user satisfaction. In this situation, there is a need for a system that accurately reflects user preferences and provides comprehensive support throughout the entire travel experience.

[0595] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0596] In this invention, the server includes means for receiving user attribute information and image information and analyzing that data to infer the user's preferences and travel requests; means for automatically generating multiple travel plans based on the analysis and assigning titles to the generated travel plans; means for customizing and updating the travel plans according to the user's requests; means for generating a preparation list that presents necessary items and activities based on the travel plans; means for providing content that delivers various relevant information based on the user's travel data; and means for receiving the user's post-trip feedback and updating a database for use in future plan suggestions. This makes it possible to provide flexible travel plans tailored to the user's preferences, as well as a system for real-time support during travel and for utilizing feedback in future plans.

[0597] "User attribute information" refers to data that represents the unique characteristics and interests of each user, and is used to personalize travel plans.

[0598] "Image information" refers to visual materials provided by users, which are analyzed to gain a more concrete understanding of their preferences and needs.

[0599] "Means for inferring preferences and travel requests" refers to methods for predicting user preferences and requests based on input information and presenting the most suitable travel plan.

[0600] "Methods for automatically generating multiple travel plans" refer to methods for mechanically constructing diverse travel possibilities based on the user's preferences and requests.

[0601] "Method of assigning a title" refers to a method of giving a generated travel plan a name that succinctly expresses its content.

[0602] "Means of customization and updating" refers to methods of adjusting existing travel plans and changing information to accommodate new user requests.

[0603] "Means of generating a preparation list" refers to a method of creating a list of necessary items and activities in accordance with a travel plan.

[0604] "Content delivery methods" refer to methods for automatically providing users with various relevant information while they are traveling.

[0605] "Means of receiving feedback and updating the database" refers to a method of organizing and storing information in order to incorporate feedback from users after their trip and reflect it in future travel planning.

[0606] To implement this invention, the interaction between the server, the terminal, and the user is key.

[0607] The server first receives user attribute information and image information from the cloud and has the function to analyze it. This analysis uses natural language processing technology and image recognition technology to accurately predict the user's preferences and travel requests. Using the analyzed data, a generative AI model is utilized to automatically generate multiple travel plans. The plans are given user-friendly titles to pique the user's interest.

[0608] The terminal is a device that provides an interface with the user. Users input information via a terminal such as a smartphone and receive multiple travel plans generated by the server. From the displayed plans, users can select the one that interests them most and further customize it. For example, they can add specific tourist attractions or change the dates, and these changes are sent to the server in real time, and an updated travel plan is sent back immediately.

[0609] Users manage all aspects of their travel planning through this system. Before their trip, they can receive assistance creating a list of necessary items using their device, and during their trip, they receive real-time content from the server. This content includes recommendations for destinations and information on special events. After their trip, users provide feedback on their experience, and this information is stored in the server's database, which helps improve the quality of future travel suggestions.

[0610] For example, if a user inputs images of "adventure travel" and "mountain scenery," the server will generate multiple travel plans, including hiking and rock climbing. These plans are sent to the user's device to help them choose the best one. An example of a prompt would be, "The user prefers an adventurous travel style and has provided images of mountainous terrain. Please generate the best travel plan."

[0611] This allows for the efficient provision of individually customized travel plans, making it easy for users to realize the travel experience they desire.

[0612] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0613] Step 1:

[0614] The user inputs travel preference information and image data through the terminal. This prepares the terminal to send the input data to the server. The input in this step consists of text information indicating the user's preferences and associated image data, while the output is raw data sent to the server for further analysis.

[0615] Step 2:

[0616] The server analyzes the information received from the user. It uses natural language processing techniques to analyze text information and image recognition techniques to analyze image data. This allows it to infer the user's preferences and travel requests, and then uses a generative AI model to create travel plan generation prompts. The input for this step is user data, and the output is a travel plan generation prompt that is considered to match the user's expectations.

[0617] Step 3:

[0618] The server uses a generative AI model to automatically generate multiple travel plans based on the prompts created in the previous step. Each plan is given a title designed to attract the user's attention. The input for this step is prompt data, and the output is multiple travel plan proposals.

[0619] Step 4:

[0620] The terminal displays travel plans received from the server to the user. The user selects the plan that interests them most from the presented options and can further customize it. In this case, the input is travel plan data from the server, and the output is the user's selected plan and customization information.

[0621] Step 5:

[0622] The user sends their customization information to the server, which receives this information and updates the travel plan. It generates a new plan and sends it to the user's terminal. The input for this step is the customization data, and the output is the updated travel plan.

[0623] Step 6:

[0624] During travel, the server delivers relevant content in real time based on the user's location and schedule. This includes information on tourist attractions and events. The input for this step is the user's real-time data, and the output is the generated content information.

[0625] Step 7:

[0626] After a trip, users enter feedback about their trip via their device. This information is sent to a server and stored in a database. It is then used to improve the quality of future travel planning. The input for this step is user feedback data, and the output is an updated database.

[0627] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0628] This invention is a system that, in addition to suggesting travel plans based on user preferences, provides more appropriate and personalized travel plans by using an emotion engine. The aim of this system is to accurately provide the travel experience that the user desires by analyzing the user's input information and emotions.

[0629] server

[0630] The server has the capability to comprehensively analyze attribute information, image information, and emotion data received from users. First, it uses natural language processing and image recognition technologies to analyze the user's text input and images. In addition, it uses an emotion engine to estimate the emotions the user expresses while selecting or inputting travel plans. These emotions can be inferred from text or obtained through facial expression analysis. From this data, the server comprehensively analyzes the user's preferences and state and automatically generates the optimal travel plan.

[0631] Each travel plan is given a catchy title tailored to the user's situation, and these titles are adjusted accordingly. This process allows us to receive feedback that reflects the user's emotions when they selected a plan, enabling us to continuously learn how to propose plans in the future.

[0632] terminal

[0633] The terminal provides an intuitive interface, allowing users to smoothly input information and select and customize travel plans. If the server determines that emotionally-based adjustments are needed during the travel plan selection process, new suggestions will be presented through the terminal.

[0634] The terminal displays multiple travel plans received from the server in an easily viewable format for the user, providing detailed itinerary information and related activities. Based on the displayed information, users can select a plan that meets specific criteria. Furthermore, it displays a preparation list to help users confirm necessary procedures and items to pack before their trip.

[0635] User

[0636] Users input their travel wishes and preferences as information through the application. Adding images helps to concretize the travel image, but at the same time, important data is collected, including how the application is used and the emotions experienced when selecting travel plans. The emotion engine infers emotions from the user's facial expressions and input content during this process and uses this information to adjust the plan.

[0637] As a concrete example, suppose a user wants to take a shopping trip to a major city and inputs an image of the city's scenery. If the user shows an enthusiastic reaction on the travel plan selection screen, the server analyzes the data received from the device and generates a travel plan that incorporates not only tourist attractions but also recommended shopping spots. When the user selects the optimal plan, the plan is fine-tuned accordingly. After the trip, the user's satisfaction level and impressions are provided as feedback and used to improve future suggestions.

[0638] In this way, this system promotes a more fulfilling travel experience by accurately reflecting the user's preferences and emotions.

[0639] The following describes the processing flow.

[0640] Step 1:

[0641] Users operate their devices to open the app and enter attribute information about their trip (e.g., purpose of travel, preferences) and related images. They can also enter their travel expectations and hopes in text format.

[0642] Step 2:

[0643] The terminal sends attribute information, image information, and text information obtained from the user to the server. At this time, it is also possible to capture the user's facial expressions with a camera during input operations and include them as emotion data.

[0644] Step 3:

[0645] The server receives the transmitted data and analyzes the attribute information using natural language processing technology. This analysis clarifies the user's travel preferences and requests. Image information is analyzed using image recognition technology to extract highly relevant tourist destinations and activities.

[0646] Step 4:

[0647] The server's emotion engine analyzes emotion data and estimates the user's emotional state. Based on these results, it considers travel plans that the user is more likely to find enjoyable.

[0648] Step 5:

[0649] The server uses generative AI to create multiple customized travel plans based on attribute, image, and sentiment analysis results. Each plan is given a catchy title to attract the user's attention.

[0650] Step 6:

[0651] The server sends the generated travel plan to the terminal.

[0652] Step 7:

[0653] The device displays multiple received travel plans to the user. The user can review the details of each travel plan and select one that suits their preferences and circumstances. The user's reaction is monitored in real time as they make their selection.

[0654] Step 8:

[0655] The user selects the most suitable travel plan from the suggested options and enters customization requests into the terminal, adjusting parts of the itinerary as needed.

[0656] Step 9:

[0657] The terminal sends the user's adjustment request to the server.

[0658] Step 10:

[0659] The server re-analyzes the user's emotional data to create the optimal travel plan. If necessary, it automatically rebooks accommodations and transportation.

[0660] Step 11:

[0661] The server sends the finalized travel plan and packing list back to the terminal.

[0662] Step 12:

[0663] The device displays the user's finalized travel plan and a list of necessary preparations before the trip, prompting them to confirm them.

[0664] Step 13:

[0665] After their trip ends, users enter their thoughts and feedback about the trip through the app. This includes providing emotional feedback based on their experiences during the trip.

[0666] Step 14:

[0667] The server receives feedback from users, analyzes it, and updates the database. This data is used to improve future travel planning suggestions.

[0668] (Example 2)

[0669] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0670] Modern travel planning presents a challenge in accurately reflecting the individual preferences and emotions of travelers. Furthermore, traditional travel planning systems often offer fixed itineraries, lacking the flexibility to adapt to changing traveler needs. Therefore, there is a growing need for more personalized plans that fulfill the travel experiences travelers desire.

[0671] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0672] In this invention, the server includes means for receiving and analyzing user attribute information, image information, and emotion data; means for automatically generating multiple travel plans using a generative AI model; and means for assigning titles to the travel plans and customizing them according to the user's emotional state. This makes it possible to dynamically adjust travel plans according to the user's individual preferences and emotions, and to provide an optimal experience.

[0673] "Attribute information" refers to data that indicates a user's personal characteristics and preferences.

[0674] "Image information" refers to visual data, including photographs and diagrams provided by users.

[0675] "Emotional data" refers to information that indicates the emotional state of a user, and is obtained through text analysis and facial recognition.

[0676] A "generative AI model" refers to a technology that uses algorithms to generate new information from data, and is used in natural language processing and data analysis.

[0677] "Natural language processing technology" is a technology that enables computers to understand and generate human language, making text analysis and semantic comprehension possible.

[0678] "Image recognition technology" is a technique that uses computer vision to analyze images and extract useful information from them.

[0679] "Emotion estimation technology" is a technique that analyzes a user's emotions from their text and facial expressions to infer their emotional state.

[0680] A "preparation list" is a list of necessary items and actions based on a travel plan, intended to help travelers prepare for their trip efficiently.

[0681] This invention is a system that provides travel plans based on the individual preferences and emotions of users. This system operates through the interaction of a server, a terminal, and a user, with each component playing the following roles.

[0682] server

[0683] The server comprehensively analyzes attribute information, image information, and sentiment data submitted by the user. This analysis utilizes natural language processing technologies (e.g., Python libraries such as spaCy and NLTK), image recognition technologies (e.g., OpenCV and TensorFlow), and sentiment estimation technologies (e.g., Hume AI and Affectiva). The server leverages generative AI models (e.g., ChatGPT and BERT) to automatically generate multiple travel plans based on the acquired data. The generated travel plans are assigned titles that reflect the user's emotional state and are customized according to the user's needs.

[0684] terminal

[0685] The device has the functionality to intuitively display travel plans received from the server to the user. The device provides an interface for viewing detailed information on each travel plan and generates a preparation list outlining necessary items and activities for the trip. Furthermore, the device utilizes notification functions to send reminders to the user, helping to ensure the plan proceeds smoothly.

[0686] User

[0687] Users begin by inputting their individual wishes and preferences through an intuitive application. For example, they might want a shopping trip to a major city and upload photos of cityscapes. This input is presented as prompts such as, "I want to enjoy shopping in a major city," or "I want to visit places that match this image." Once a travel plan is displayed, the user selects the plan that interests them and provides feedback, contributing to improving the accuracy of future suggestions.

[0688] In this way, the interconnectedness of each component makes it possible to provide personalized travel plans that reflect the individual needs and emotions of the user. This system continuously learns to improve the user's travel experience.

[0689] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0690] Step 1:

[0691] Users input information about their travel preferences and desires through the application. Specifically, they upload information about places they want to visit, their preferred activities, and images that represent their travel image. During this process, they may enter prompts such as "I'm interested in hiking in the mountains" or "I want to see this beautiful scenery," and provide relevant image files.

[0692] Step 2:

[0693] The server receives attribute and image information entered by the user and begins analysis. During this process, natural language processing techniques are used to analyze the text data and extract relevant keywords and structures. Image recognition techniques are also used to analyze the uploaded images and identify the locations and activities they represent. The output consists of features and labels derived from the analyzed text and image data.

[0694] Step 3:

[0695] The server uses emotion estimation technology to infer emotional data from user input and provided images. This combines linguistic emotional expressions obtained through text analysis with facial expression analysis within the images. As a result, the user's emotional state (e.g., "excited" or "relaxed") is output as numerical data.

[0696] Step 4:

[0697] The server applies a generative AI model to automatically generate multiple travel plans based on the analyzed data. Here, it considers the user's preferences, emotional state, and past feedback information to create the optimal travel plan and its associated title. The output is provided as a set of selectable travel plans.

[0698] Step 5:

[0699] The device displays multiple travel plans sent from the server in an easy-to-read format. Each travel plan includes detailed itinerary, places to visit, and recommended activities. Users can compare these plans and select the one that interests them. Further details can also be adjusted according to the user's preferences.

[0700] Step 6:

[0701] The user reviews the presented travel plan and makes a selection. Based on the selection, the device displays a preparation list to help the user confirm necessary procedures and items to pack before the trip. The device also uses a notification function to support the user in smoothly carrying out their preparations.

[0702] Step 7:

[0703] When users return from a trip, they provide feedback via their device, sharing their satisfaction level and specific impressions of the trip. The server receives this feedback and updates its database, which is then used to improve future travel plans. Through this process, the system continuously learns and enhances the user experience.

[0704] (Application Example 2)

[0705] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0706] Modern consumers have diverse preferences and demand product suggestions that cater to their moods and feelings. However, existing food delivery services often fail to offer suggestions based on the user's emotions or mood on any given day, instead providing only generic options, which can lead to decreased customer satisfaction.

[0707] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0708] In this invention, the server includes means for analyzing the user's attribute information, image information, and emotional information to infer their preferences and consumption requests; means for generating multiple consumption plans based on the analysis and assigning names to them; and means for customizing the consumption plans according to the user's requests. This makes it possible to provide personalized consumption plans that are tailored to the user's emotions and psychological state on that day.

[0709] "Attribute information" refers to information that identifies an individual or indicates their preferences, such as the user's basic characteristics, tastes, and past consumption history.

[0710] "Image information" refers to photographs and visual data provided by users, which are used as material to infer emotions and preferences through analysis.

[0711] "Emotional information" refers to data that indicates the user's psychological state and emotions, and is estimated through facial recognition and text analysis.

[0712] "Consumption demand" refers to information that represents the consumption behavior and desires that users currently wish to have, and is inferred through analysis.

[0713] A "consumer plan" is a proposal plan for products and services that is automatically generated based on the user's preferences and emotions.

[0714] A "preparation list" is a list of items and actions that a user will need, based on their consumption plan.

[0715] "Feedback" refers to data that shows the level of satisfaction and opinions that consumers provide after using a product or experiencing a service, and it is an important source of information for future proposals.

[0716] A "recording device" is a database that stores user feedback and consumption history to be used for future suggestions.

[0717] This invention comprises a system for providing personalized consumption plans based on user emotional information. This system mainly includes a server, terminals, and a user interface.

[0718] First, the device acquires user attribute information, image information, and current emotional information through a smartphone application. The acquired data is sent to a server in the cloud. The server uses natural language processing and image recognition technologies to analyze the user's emotions and preferences. Specifically, this might involve using Google Cloud Natural Language API or Face API.

[0719] Based on the analyzed information, a generative AI model automatically generates an optimal consumption plan for the user. This consumption plan is customized according to the user's mood and psychological state on that day, listing multiple options and giving them attractive names. The generated plan is presented to the user via their device.

[0720] Users can select or customize plans presented on their devices and link them to their actual consumption behavior. Feedback after selection is also sent from the device to the server and stored in a recording device. This feedback information is used to improve future suggestions.

[0721] For example, if a user enters a prompt such as, "Today I want something spicy and energizing," the server will suggest menu items that match their desired level of energy and vitality. If the server detects that the user's expression is slightly tired, it can also suggest refreshing beverages.

[0722] An example of a prompt message would be: "The user seems to be in the mood for spicy food and looks a little sleepy. Suggest a dish that will give them energy and consider side options."

[0723] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0724] Step 1:

[0725] The terminal acquires user attribute information, image information, and sentiment information and sends it to the server. The input here is basic data provided by the user through a smartphone application. The output sent to the server is the user's attributes, digital image data, and real-time sentiment estimation data.

[0726] Step 2:

[0727] The server analyzes the received data. In this analysis step, natural language processing technology (Google Cloud Natural Language API) is used to analyze text data, and image recognition technology (Face API) is used to infer emotions and facial expressions from image data. The output obtained from this process reflects the user's preferences and current psychological state.

[0728] Step 3:

[0729] Based on the analyzed information, the server automatically generates an optimal consumption plan for the user using a generative AI model. The input for this process is the preference and emotional data obtained in step 2. As output, multiple personalized consumption plans reflecting the user's emotions and preferences are generated.

[0730] Step 4:

[0731] The server assigns a name to the generated consumption plan and displays it on the terminal. The input is the consumption plan generated in step 3, and the output is a list of plans that the user can select on the terminal.

[0732] Step 5:

[0733] Users select or customize a consumption plan presented via the terminal. Input here includes the user's selection information and facial expressions during selection, and the specific selected consumption plan is displayed on the terminal as output.

[0734] Step 6:

[0735] The device collects user feedback and sends it to the server. The input is user feedback and satisfaction data after consumption, and the output is feedback information stored in the server's recording device.

[0736] Step 7:

[0737] The server uses feedback information stored in the recording device to improve the next proposal. The input is feedback data, and the output is the updated proposal method and content based on the feedback.

[0738] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0739] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0740] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0741] [Fourth Embodiment]

[0742] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0743] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0744] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0745] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0746] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0747] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0748] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0749] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0750] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0751] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0752] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0753] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0754] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0755] This invention provides a system that automatically generates travel plans tailored to the individual preferences of users and allows for easy customization. This system is designed to enhance the convenience of users in creating their preferred travel plans without any hassle. An embodiment of this system is described below.

[0756] server

[0757] The server provides a platform for analyzing attribute and image data received from users. Based on the analyzed data, it uses a generative AI to generate multiple travel plans combining various tourist destinations, modes of transportation, and accommodations. This ensures that multiple plans tailored to the user's preferences are proposed. In addition, the generated travel plans are given titles that are likely to attract the user's interest. These titles help users choose a plan.

[0758] Furthermore, the server has the ability to learn and update its database by analyzing user feedback and using it to suggest future travel plans. This feedback includes not only satisfaction and excitement during the trip, but also hopes for future trips.

[0759] terminal

[0760] The terminal provides an interface for users to input information. It has the functionality to send attribute information and images to the server and displays multiple received travel plans for the user to review. Each travel plan includes a detailed itinerary and related activity information. Furthermore, when a user customizes part of the itinerary, the terminal sends that information to the server and receives a new itinerary. In addition, it displays a list of necessary preparations and items to pack before the trip, helping users to complete their travel preparations without forgetting anything.

[0761] user

[0762] Users begin interacting with the system by entering attribute information and images related to their desired trip within the application. They select the travel plan that interests them most from several presented options and review its details. They customize the travel plan as needed and finalize their itinerary. After the trip, they provide feedback through the app, recording their travel experience and contributing to improving the quality of future travel planning.

[0763] As a concrete example, suppose a user wants to travel to a summer resort and uploads images of beaches in that area to the app. The server analyzes the images and the user's preferences and generates multiple travel plans, including nearby beach resorts, activities (e.g., diving, beach parties), and transportation options. After the user makes adjustments based on these plans, the device displays a packing list and a detailed checklist to support the user's travel preparations.

[0764] The following describes the processing flow.

[0765] Step 1:

[0766] Users access the app via their device and enter their personal information (e.g., age, travel style) and images related to their desired travel destinations.

[0767] Step 2:

[0768] The terminal transmits user-entered information and images to the server. This is done using data communication technology.

[0769] Step 3:

[0770] The server analyzes the received attribute information using natural language processing technology to extract the user's preferences and travel objectives. It also analyzes uploaded images using image recognition technology to identify relevant tourist destinations and activities.

[0771] Step 4:

[0772] Based on the analysis results, the server automatically generates multiple travel plans using a generation AI. These plans include combinations of tourist destinations, accommodations, transportation, and activities. Each travel plan is also given a catchy title.

[0773] Step 5:

[0774] The server sends the generated travel plan to the terminal.

[0775] Step 6:

[0776] The terminal visually displays multiple travel plans received from the server to the user. The user can then view the details of each plan.

[0777] Step 7:

[0778] The user selects the most suitable travel plan from the presented options and enters requests into the terminal to customize parts of the itinerary as needed.

[0779] Step 8:

[0780] The terminal sends the user's customization requests to the server.

[0781] Step 9:

[0782] The server regenerates the travel plan selected based on the user's request and rearranges accommodations and transportation if necessary.

[0783] Step 10:

[0784] The server sends the completed travel plan and the accompanying preparation list to the terminal.

[0785] Step 11:

[0786] The device displays the user's latest travel plans and a list of necessary preparations and packing lists before the trip.

[0787] Step 12:

[0788] After completing their trip, users will enter their travel impressions and feedback through the app.

[0789] Step 13:

[0790] The server analyzes user feedback and updates its database to use it for suggesting future travel plans.

[0791] (Example 1)

[0792] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0793] Planning a trip involves gathering a lot of information and manual adjustments, and planning according to individual preferences is particularly complex and time-consuming. Users want a system that can automatically and easily create trips that match their preferences. They also want a system that uses post-trip feedback to improve future plans. Furthermore, it is necessary to use images and language information to precisely understand user needs and provide the optimal travel plan.

[0794] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0795] This invention includes a server that receives attribute data and image data from a user and interprets this information to estimate the user's preferences and travel itinerary desires; a server that utilizes a generative AI model to provide an optimal plan tailored to the user's preferences; and an image recognition technology that extracts relevant tourist destinations and activities from images input by the user. This enables users to easily and automatically generate travel plans that suit their preferences and to proceed with planning efficiently.

[0796] "Attribute data" refers to personal information such as the user's age, hobbies, and budget, and is basic information used to customize travel plans.

[0797] "Image data" refers to image information provided by users for reference in their travel planning, and includes visual data related to tourist destinations and preferences.

[0798] A "generative AI model" is a general term for algorithms that use artificial intelligence technology to generate optimal travel plans based on the user's preferences and requests.

[0799] A "prompt message" is a sentence that describes the user's wishes and requests to the system, and it provides initial input information for creating a travel plan.

[0800] "Interpreting" refers to the process of analyzing data received from users and understanding its meaning and intent.

[0801] A "travel itinerary" refers to a proposed itinerary for a trip, created by combining tourist destinations, activities, transportation, accommodations, and other elements.

[0802] "Image recognition technology" is a technology used to identify and interpret objects and features in images, and is utilized to optimize travel planning.

[0803] A "preparation list" refers to a list that organizes and presents to the user the necessary items and procedures for traveling.

[0804] "Information records" refer to a database that stores user feedback and related information to help generate future travel plans.

[0805] This invention provides a system that automatically generates travel plans tailored to the user's preferences and allows for easy customization. An example of this system is described below.

[0806] server

[0807] The server receives attribute and image data sent by users and provides a platform for interpreting this information. The received data is analyzed using a generative AI model to generate an optimal travel plan tailored to the user's preferences and requests. This generative AI model uses natural language processing and image recognition technologies to evaluate the attribute and image data and precisely understand the user's needs. Through this process, the server creates multiple travel plans, including tourist destinations, activities, transportation, and accommodations, and each plan is given a title designed to attract the user's interest.

[0808] For example, if a user uploads a beach image along with the prompt message, "I want to relax on the beach during my summer vacation. Please suggest some recommended resorts and activities I can do there. I've attached a photo of a beach," the server will use that information to generate a travel plan that includes activities and transportation options at nearby resorts.

[0809] terminal

[0810] The terminal provides an interface for users to input information into the system. This transmits attribute and image data to the server. Furthermore, the terminal displays multiple received travel plans on its screen, allowing users to compare and select them. Each plan includes detailed itinerary and associated activity information. When users customize a plan, the changes are resent to the server via the terminal, providing an updated travel plan. The terminal also displays packing lists and preparation checklists to assist with travel preparations.

[0811] user

[0812] This system allows users to input their personal information and travel preferences to receive personalized travel plan suggestions. Users can then select plans that interest them, review their details, and adjust them as needed to create the optimal travel plan. Furthermore, by providing feedback after their trip and recording their experiences, users can contribute to improving future travel plans.

[0813] This system enables users to quickly and efficiently create travel plans tailored to their individual needs. By utilizing a generative AI model and prompt messages, the system achieves highly accurate automatic generation and customization of travel plans.

[0814] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0815] Step 1:

[0816] Users input attribute data (e.g., age, hobbies, budget) and image data related to their travel destination through the application. This input is sent to the server via the terminal. More specific data is provided when users explicitly state their travel requests using prompts, such as "I want to relax on the beach."

[0817] Step 2:

[0818] The server interprets the received attribute and image data. Using a generative AI model, it analyzes the prompt text and image data to infer the user's preferences. For example, it extracts features from beach image data and selects related tourist destinations and activities. This results in the output of information based on the user's wishes.

[0819] Step 3:

[0820] The server automatically generates multiple travel plans based on the analysis results. The generation AI model creates plans by combining tourist destinations, accommodations, and modes of transportation, and assigns an appealing name to each. The generated plans are configured to be customizable according to the user's requests.

[0821] Step 4:

[0822] The device displays multiple travel plans provided by the server to the user. The user can review these options and access detailed itinerary and activity information for each plan. Specifically, the device interface provides a function to compare and select each plan.

[0823] Step 5:

[0824] Users select a travel plan that interests them from the displayed options and customize it as needed. The user's customization requests are resent to the server via their device, and a more accurate travel plan is updated. During this process, details of the plan and itinerary are adjusted.

[0825] Step 6:

[0826] The server creates a regenerated travel plan based on the user's customization information. The regenerated plan is optimized based on the user's preferences, and any additions or modifications the user requests are reflected.

[0827] Step 7:

[0828] The device displays a packing list and preparation checklist for the trip to the user. It provides the necessary information appropriately to ensure smooth travel preparations.

[0829] Step 8:

[0830] After the trip, users provide feedback through the application. The server receives this feedback information and updates its database. The feedback is used to create future travel plans, contributing to improving the accuracy of the system's suggestions.

[0831] (Application Example 1)

[0832] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0833] Conventional travel planning systems have suffered from insufficient customization based on user preferences and a lack of ability to provide real-time information during travel. Furthermore, they lacked mechanisms to utilize user feedback to improve future plans, making it difficult to improve user satisfaction. In this situation, there is a need for a system that accurately reflects user preferences and provides comprehensive support throughout the entire travel experience.

[0834] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0835] In this invention, the server includes means for receiving user attribute information and image information and analyzing that data to infer the user's preferences and travel requests; means for automatically generating multiple travel plans based on the analysis and assigning titles to the generated travel plans; means for customizing and updating the travel plans according to the user's requests; means for generating a preparation list that presents necessary items and activities based on the travel plans; means for providing content that delivers various relevant information based on the user's travel data; and means for receiving the user's post-trip feedback and updating a database for use in future plan suggestions. This makes it possible to provide flexible travel plans tailored to the user's preferences, as well as a system for real-time support during travel and for utilizing feedback in future plans.

[0836] "User attribute information" refers to data that represents the unique characteristics and interests of each user, and is used to personalize travel plans.

[0837] "Image information" refers to visual materials provided by users, which are analyzed to gain a more concrete understanding of their preferences and needs.

[0838] "Means for inferring preferences and travel requests" refers to methods for predicting user preferences and requests based on input information and presenting the most suitable travel plan.

[0839] "Methods for automatically generating multiple travel plans" refer to methods for mechanically constructing diverse travel possibilities based on the user's preferences and requests.

[0840] "Method of assigning a title" refers to a method of giving a generated travel plan a name that succinctly expresses its content.

[0841] "Means of customization and updating" refers to methods of adjusting existing travel plans and changing information to accommodate new user requests.

[0842] "Means of generating a preparation list" refers to a method of creating a list of necessary items and activities in accordance with a travel plan.

[0843] "Content delivery methods" refer to methods for automatically providing users with various relevant information while they are traveling.

[0844] "Means of receiving feedback and updating the database" refers to a method of organizing and storing information in order to incorporate feedback from users after their trip and reflect it in future travel planning.

[0845] To implement this invention, the interaction between the server, the terminal, and the user is key.

[0846] The server first receives user attribute information and image information from the cloud and has the function to analyze it. This analysis uses natural language processing technology and image recognition technology to accurately predict the user's preferences and travel requests. Using the analyzed data, a generative AI model is utilized to automatically generate multiple travel plans. The plans are given user-friendly titles to pique the user's interest.

[0847] The terminal is a device that provides an interface with the user. Users input information via a terminal such as a smartphone and receive multiple travel plans generated by the server. From the displayed plans, users can select the one that interests them most and further customize it. For example, they can add specific tourist attractions or change the dates, and these changes are sent to the server in real time, and an updated travel plan is sent back immediately.

[0848] Users manage all aspects of their travel planning through this system. Before their trip, they can receive assistance creating a list of necessary items using their device, and during their trip, they receive real-time content from the server. This content includes recommendations for destinations and information on special events. After their trip, users provide feedback on their experience, and this information is stored in the server's database, which helps improve the quality of future travel suggestions.

[0849] For example, if a user inputs images of "adventure travel" and "mountain scenery," the server will generate multiple travel plans, including hiking and rock climbing. These plans are sent to the user's device to help them choose the best one. An example of a prompt would be, "The user prefers an adventurous travel style and has provided images of mountainous terrain. Please generate the best travel plan."

[0850] This allows for the efficient provision of individually customized travel plans, making it easy for users to realize the travel experience they desire.

[0851] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0852] Step 1:

[0853] The user inputs travel preference information and image data through the terminal. This prepares the terminal to send the input data to the server. The input in this step consists of text information indicating the user's preferences and associated image data, while the output is raw data sent to the server for further analysis.

[0854] Step 2:

[0855] The server analyzes the information received from the user. It uses natural language processing techniques to analyze text information and image recognition techniques to analyze image data. This allows it to infer the user's preferences and travel requests, and then uses a generative AI model to create travel plan generation prompts. The input for this step is user data, and the output is a travel plan generation prompt that is considered to match the user's expectations.

[0856] Step 3:

[0857] The server uses a generative AI model to automatically generate multiple travel plans based on the prompts created in the previous step. Each plan is given a title designed to attract the user's attention. The input for this step is prompt data, and the output is multiple travel plan proposals.

[0858] Step 4:

[0859] The terminal displays travel plans received from the server to the user. The user selects the plan that interests them most from the presented options and can further customize it. In this case, the input is travel plan data from the server, and the output is the user's selected plan and customization information.

[0860] Step 5:

[0861] The user sends their customization information to the server, which receives this information and updates the travel plan. It generates a new plan and sends it to the user's terminal. The input for this step is the customization data, and the output is the updated travel plan.

[0862] Step 6:

[0863] During travel, the server delivers relevant content in real time based on the user's location and schedule. This includes information on tourist attractions and events. The input for this step is the user's real-time data, and the output is the generated content information.

[0864] Step 7:

[0865] After a trip, users enter feedback about their trip via their device. This information is sent to a server and stored in a database. It is then used to improve the quality of future travel planning. The input for this step is user feedback data, and the output is an updated database.

[0866] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0867] This invention is a system that, in addition to suggesting travel plans based on user preferences, provides more appropriate and personalized travel plans by using an emotion engine. The aim of this system is to accurately provide the travel experience that the user desires by analyzing the user's input information and emotions.

[0868] server

[0869] The server has the capability to comprehensively analyze attribute information, image information, and emotion data received from users. First, it uses natural language processing and image recognition technologies to analyze the user's text input and images. In addition, it uses an emotion engine to estimate the emotions the user expresses while selecting or inputting travel plans. These emotions can be inferred from text or obtained through facial expression analysis. From this data, the server comprehensively analyzes the user's preferences and state and automatically generates the optimal travel plan.

[0870] Each travel plan is given a catchy title tailored to the user's situation, and these titles are adjusted accordingly. This process allows us to receive feedback that reflects the user's emotions when they selected a plan, enabling us to continuously learn how to propose plans in the future.

[0871] terminal

[0872] The terminal provides an intuitive interface, allowing users to smoothly input information and select and customize travel plans. If the server determines that emotionally-based adjustments are needed during the travel plan selection process, new suggestions will be presented through the terminal.

[0873] The terminal displays multiple travel plans received from the server in an easily viewable format for the user, providing detailed itinerary information and related activities. Based on the displayed information, users can select a plan that meets specific criteria. Furthermore, it displays a preparation list to help users confirm necessary procedures and items to pack before their trip.

[0874] User

[0875] Users input their travel wishes and preferences as information through the application. Adding images helps to concretize the travel image, but at the same time, important data is collected, including how the application is used and the emotions experienced when selecting travel plans. The emotion engine infers emotions from the user's facial expressions and input content during this process and uses this information to adjust the plan.

[0876] As a concrete example, suppose a user wants to take a shopping trip to a major city and inputs an image of the city's scenery. If the user shows an enthusiastic reaction on the travel plan selection screen, the server analyzes the data received from the device and generates a travel plan that incorporates not only tourist attractions but also recommended shopping spots. When the user selects the optimal plan, the plan is fine-tuned accordingly. After the trip, the user's satisfaction level and impressions are provided as feedback and used to improve future suggestions.

[0877] In this way, this system promotes a more fulfilling travel experience by accurately reflecting the user's preferences and emotions.

[0878] The following describes the processing flow.

[0879] Step 1:

[0880] Users operate their devices to open the app and enter attribute information about their trip (e.g., purpose of travel, preferences) and related images. They can also enter their travel expectations and hopes in text format.

[0881] Step 2:

[0882] The terminal sends attribute information, image information, and text information obtained from the user to the server. At this time, it is also possible to capture the user's facial expressions with a camera during input operations and include them as emotion data.

[0883] Step 3:

[0884] The server receives the transmitted data and analyzes the attribute information using natural language processing technology. This analysis clarifies the user's travel preferences and requests. Image information is analyzed using image recognition technology to extract highly relevant tourist destinations and activities.

[0885] Step 4:

[0886] The server's emotion engine analyzes emotion data and estimates the user's emotional state. Based on these results, it considers travel plans that the user is more likely to find enjoyable.

[0887] Step 5:

[0888] The server uses generative AI to create multiple customized travel plans based on attribute, image, and sentiment analysis results. Each plan is given a catchy title to attract the user's attention.

[0889] Step 6:

[0890] The server sends the generated travel plan to the terminal.

[0891] Step 7:

[0892] The device displays multiple received travel plans to the user. The user can review the details of each travel plan and select one that suits their preferences and circumstances. The user's reaction is monitored in real time as they make their selection.

[0893] Step 8:

[0894] The user selects the most suitable travel plan from the suggested options and enters customization requests into the terminal, adjusting parts of the itinerary as needed.

[0895] Step 9:

[0896] The terminal sends the user's adjustment request to the server.

[0897] Step 10:

[0898] The server re-analyzes the user's emotional data to create the optimal travel plan. If necessary, it automatically rebooks accommodations and transportation.

[0899] Step 11:

[0900] The server sends the finalized travel plan and packing list back to the terminal.

[0901] Step 12:

[0902] The device displays the user's finalized travel plan and a list of necessary preparations before the trip, prompting them to confirm them.

[0903] Step 13:

[0904] After their trip ends, users enter their thoughts and feedback about the trip through the app. This includes providing emotional feedback based on their experiences during the trip.

[0905] Step 14:

[0906] The server receives feedback from users, analyzes it, and updates the database. This data is used to improve future travel planning suggestions.

[0907] (Example 2)

[0908] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0909] Modern travel planning presents a challenge in accurately reflecting the individual preferences and emotions of travelers. Furthermore, traditional travel planning systems often offer fixed itineraries, lacking the flexibility to adapt to changing traveler needs. Therefore, there is a growing need for more personalized plans that fulfill the travel experiences travelers desire.

[0910] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0911] In this invention, the server includes means for receiving and analyzing user attribute information, image information, and emotion data; means for automatically generating multiple travel plans using a generative AI model; and means for assigning titles to the travel plans and customizing them according to the user's emotional state. This makes it possible to dynamically adjust travel plans according to the user's individual preferences and emotions, and to provide an optimal experience.

[0912] "Attribute information" refers to data that indicates a user's personal characteristics and preferences.

[0913] "Image information" refers to visual data, including photographs and diagrams provided by users.

[0914] "Emotional data" refers to information that indicates the emotional state of a user, and is obtained through text analysis and facial recognition.

[0915] A "generative AI model" refers to a technology that uses algorithms to generate new information from data, and is used in natural language processing and data analysis.

[0916] "Natural language processing technology" is a technology that enables computers to understand and generate human language, making text analysis and semantic comprehension possible.

[0917] "Image recognition technology" is a technique that uses computer vision to analyze images and extract useful information from them.

[0918] "Emotion estimation technology" is a technique that analyzes a user's emotions from their text and facial expressions to infer their emotional state.

[0919] A "preparation list" is a list of necessary items and actions based on a travel plan, intended to help travelers prepare for their trip efficiently.

[0920] This invention is a system that provides travel plans based on the individual preferences and emotions of users. This system operates through the interaction of a server, a terminal, and a user, with each component playing the following roles.

[0921] server

[0922] The server comprehensively analyzes attribute information, image information, and sentiment data submitted by the user. This analysis utilizes natural language processing technologies (e.g., Python libraries such as spaCy and NLTK), image recognition technologies (e.g., OpenCV and TensorFlow), and sentiment estimation technologies (e.g., Hume AI and Affectiva). The server leverages generative AI models (e.g., ChatGPT and BERT) to automatically generate multiple travel plans based on the acquired data. The generated travel plans are assigned titles that reflect the user's emotional state and are customized according to the user's needs.

[0923] terminal

[0924] The device has the functionality to intuitively display travel plans received from the server to the user. The device provides an interface for viewing detailed information on each travel plan and generates a preparation list outlining necessary items and activities for the trip. Furthermore, the device utilizes notification functions to send reminders to the user, helping to ensure the plan proceeds smoothly.

[0925] User

[0926] Users begin by inputting their individual wishes and preferences through an intuitive application. For example, they might want a shopping trip to a major city and upload photos of cityscapes. This input is presented as prompts such as, "I want to enjoy shopping in a major city," or "I want to visit places that match this image." Once a travel plan is displayed, the user selects the plan that interests them and provides feedback, contributing to improving the accuracy of future suggestions.

[0927] In this way, the interconnectedness of each component makes it possible to provide personalized travel plans that reflect the individual needs and emotions of the user. This system continuously learns to improve the user's travel experience.

[0928] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0929] Step 1:

[0930] Users input information about their travel preferences and desires through the application. Specifically, they upload information about places they want to visit, their preferred activities, and images that represent their travel image. During this process, they may enter prompts such as "I'm interested in hiking in the mountains" or "I want to see this beautiful scenery," and provide relevant image files.

[0931] Step 2:

[0932] The server receives attribute and image information entered by the user and begins analysis. During this process, natural language processing techniques are used to analyze the text data and extract relevant keywords and structures. Image recognition techniques are also used to analyze the uploaded images and identify the locations and activities they represent. The output consists of features and labels derived from the analyzed text and image data.

[0933] Step 3:

[0934] The server uses emotion estimation technology to infer emotional data from user input and provided images. This combines linguistic emotional expressions obtained through text analysis with facial expression analysis within the images. As a result, the user's emotional state (e.g., "excited" or "relaxed") is output as numerical data.

[0935] Step 4:

[0936] The server applies a generative AI model to automatically generate multiple travel plans based on the analyzed data. Here, it considers the user's preferences, emotional state, and past feedback information to create the optimal travel plan and its associated title. The output is provided as a set of selectable travel plans.

[0937] Step 5:

[0938] The device displays multiple travel plans sent from the server in an easy-to-read format. Each travel plan includes detailed itinerary, places to visit, and recommended activities. Users can compare these plans and select the one that interests them. Further details can also be adjusted according to the user's preferences.

[0939] Step 6:

[0940] The user reviews the presented travel plan and makes a selection. Based on the selection, the device displays a preparation list to help the user confirm necessary procedures and items to pack before the trip. The device also uses a notification function to support the user in smoothly carrying out their preparations.

[0941] Step 7:

[0942] When users return from a trip, they provide feedback via their device, sharing their satisfaction level and specific impressions of the trip. The server receives this feedback and updates its database, which is then used to improve future travel plans. Through this process, the system continuously learns and enhances the user experience.

[0943] (Application Example 2)

[0944] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0945] Modern consumers have diverse preferences and demand product suggestions that cater to their moods and feelings. However, existing food delivery services often fail to offer suggestions based on the user's emotions or mood on any given day, instead providing only generic options, which can lead to decreased customer satisfaction.

[0946] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0947] In this invention, the server includes means for analyzing the user's attribute information, image information, and emotional information to infer their preferences and consumption requests; means for generating multiple consumption plans based on the analysis and assigning names to them; and means for customizing the consumption plans according to the user's requests. This makes it possible to provide personalized consumption plans that are tailored to the user's emotions and psychological state on that day.

[0948] "Attribute information" refers to information that identifies an individual or indicates their preferences, such as the user's basic characteristics, tastes, and past consumption history.

[0949] "Image information" refers to photographs and visual data provided by users, which are used as material to infer emotions and preferences through analysis.

[0950] "Emotional information" refers to data that indicates the user's psychological state and emotions, and is estimated through facial recognition and text analysis.

[0951] "Consumption demand" refers to information that represents the consumption behavior and desires that users currently wish to have, and is inferred through analysis.

[0952] A "consumer plan" is a proposal plan for products and services that is automatically generated based on the user's preferences and emotions.

[0953] A "preparation list" is a list of items and actions that a user will need, based on their consumption plan.

[0954] "Feedback" refers to data that shows the level of satisfaction and opinions that consumers provide after using a product or experiencing a service, and it is an important source of information for future proposals.

[0955] A "recording device" is a database that stores user feedback and consumption history to be used for future suggestions.

[0956] This invention comprises a system for providing personalized consumption plans based on user emotional information. This system mainly includes a server, terminals, and a user interface.

[0957] First, the device acquires user attribute information, image information, and current emotional information through a smartphone application. The acquired data is sent to a server in the cloud. The server uses natural language processing and image recognition technologies to analyze the user's emotions and preferences. Specifically, this might involve using Google Cloud Natural Language API or Face API.

[0958] Based on the analyzed information, a generative AI model automatically generates an optimal consumption plan for the user. This consumption plan is customized according to the user's mood and psychological state on that day, listing multiple options and giving them attractive names. The generated plan is presented to the user via their device.

[0959] Users can select or customize plans presented on their devices and link them to their actual consumption behavior. Feedback after selection is also sent from the device to the server and stored in a recording device. This feedback information is used to improve future suggestions.

[0960] For example, if a user enters a prompt such as, "Today I want something spicy and energizing," the server will suggest menu items that match their desired level of energy and vitality. If the server detects that the user's expression is slightly tired, it can also suggest refreshing beverages.

[0961] An example of a prompt message would be: "The user seems to be in the mood for spicy food and looks a little sleepy. Suggest a dish that will give them energy and consider side options."

[0962] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0963] Step 1:

[0964] The terminal acquires user attribute information, image information, and sentiment information and sends it to the server. The input here is basic data provided by the user through a smartphone application. The output sent to the server is the user's attributes, digital image data, and real-time sentiment estimation data.

[0965] Step 2:

[0966] The server analyzes the received data. In this analysis step, natural language processing technology (Google Cloud Natural Language API) is used to analyze text data, and image recognition technology (Face API) is used to infer emotions and facial expressions from image data. The output obtained from this process reflects the user's preferences and current psychological state.

[0967] Step 3:

[0968] Based on the analyzed information, the server automatically generates an optimal consumption plan for the user using a generative AI model. The input for this process is the preference and emotional data obtained in step 2. As output, multiple personalized consumption plans reflecting the user's emotions and preferences are generated.

[0969] Step 4:

[0970] The server assigns a name to the generated consumption plan and displays it on the terminal. The input is the consumption plan generated in step 3, and the output is a list of plans that the user can select on the terminal.

[0971] Step 5:

[0972] Users select or customize a consumption plan presented via the terminal. Input here includes the user's selection information and facial expressions during selection, and the specific selected consumption plan is displayed on the terminal as output.

[0973] Step 6:

[0974] The device collects user feedback and sends it to the server. The input is user feedback and satisfaction data after consumption, and the output is feedback information stored in the server's recording device.

[0975] Step 7:

[0976] The server uses feedback information stored in the recording device to improve the next proposal. The input is feedback data, and the output is the updated proposal method and content based on the feedback.

[0977] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0978] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0979] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0980] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0981] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0982] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0983] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0984] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0985] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0986] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0987] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0988] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0989] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0990] 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.

[0991] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0992] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0993] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0994] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0995] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0996] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0997] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0998] The following is further disclosed regarding the embodiments described above.

[0999] (Claim 1)

[1000] A means of receiving user attribute information and image information, and analyzing that data to infer user preferences and travel requests,

[1001] A means for automatically generating multiple travel plans based on the aforementioned analysis and assigning titles to the generated travel plans,

[1002] A means for customizing and updating the aforementioned travel plan according to the user's request,

[1003] A means for generating a preparation list that presents necessary items and actions based on a travel plan,

[1004] A means of receiving user feedback after their trip and updating a database to use for future travel planning suggestions,

[1005] A system that includes this.

[1006] (Claim 2)

[1007] The system according to claim 1, wherein the analysis means uses natural language processing technology and image recognition technology.

[1008] (Claim 3)

[1009] The system according to claim 1, wherein the customization means automatically rearranges accommodation and transportation in response to user input.

[1010] "Example 1"

[1011] (Claim 1)

[1012] A means of receiving attribute data and image data from users and interpreting that information to estimate the user's preferences and travel itinerary desires,

[1013] A means for automatically generating multiple itinerary plans based on the aforementioned interpretation and naming the generated itinerary plans,

[1014] Means for modifying and updating the aforementioned itinerary plan according to the user's wishes,

[1015] A means for generating a preparation list that presents necessary items and actions based on the itinerary plan,

[1016] A means of receiving user feedback after their trip and updating the information record to use in proposing future travel plans,

[1017] A means of providing optimal plans tailored to user preferences by utilizing generative AI models,

[1018] Image recognition technology is used to extract relevant tourist destinations and activities from images input by users.

[1019] A means of presenting users with multiple option plans, allowing them to select one or confirm further details,

[1020] A means of receiving user customization requests and regenerating and providing the plan,

[1021] A means of using prompt statements to facilitate the generation of travel plans that meet the user's preferences,

[1022] A system that includes this.

[1023] (Claim 2)

[1024] The system according to claim 1, wherein the interpretation means uses natural language processing technology and image recognition technology.

[1025] (Claim 3)

[1026] The system according to claim 1, wherein the modification means automatically rearranges accommodation facilities and means of transportation in response to user input.

[1027] "Application Example 1"

[1028] (Claim 1)

[1029] A means of receiving user attribute information and image information, and analyzing that data to infer user preferences and travel requests,

[1030] A means for automatically generating multiple travel plans based on the aforementioned analysis and assigning titles to the generated travel plans,

[1031] A means for customizing and updating the aforementioned travel plan according to the user's request,

[1032] A means for generating a preparation list that presents necessary items and actions based on a travel plan,

[1033] A content delivery method that distributes diverse relevant information based on data collected by users during their travels,

[1034] A means of receiving user feedback after their trip and updating a database to use for future travel planning suggestions,

[1035] A system that includes this.

[1036] (Claim 2)

[1037] The system according to claim 1, wherein the analysis means uses natural language processing technology and image recognition technology.

[1038] (Claim 3)

[1039] The system according to claim 1, wherein the customization means automatically rearranges accommodation and transportation in response to user input.

[1040] "Example 2 of combining an emotion engine"

[1041] (Claim 1)

[1042] A means of receiving user attribute information, image information, and emotional data, and analyzing this data to infer user preferences and travel requests,

[1043] A means for automatically generating multiple travel plans using an AI model based on the aforementioned analysis, and assigning titles to the generated travel plans according to the user's emotional state,

[1044] A means for customizing the aforementioned travel plan based on user requests and emotional data, and for presenting alternative plans that respond to the user's emotions,

[1045] A means of generating a preparation list that presents necessary items and actions based on the travel plan, and notifying the user,

[1046] A means of receiving user feedback after their trip and updating a database to use for future travel planning suggestions,

[1047] A system that includes this.

[1048] (Claim 2)

[1049] The system according to claim 1, wherein the analysis means uses natural language processing technology, image recognition technology, and emotion estimation technology.

[1050] (Claim 3)

[1051] The system according to claim 1, wherein the customization means optimizes the itinerary and activity content in accordance with user input and emotion data.

[1052] "Application example 2 when combining with an emotional engine"

[1053] (Claim 1)

[1054] A means of receiving user attribute information, image information, and emotional information, and analyzing this data to infer user preferences and consumption demands,

[1055] A means for automatically generating multiple consumption plans based on the aforementioned analysis and assigning names to the generated consumption plans,

[1056] A means for customizing and updating the consumption plan according to the user's request,

[1057] A means for generating a preparation list that presents necessary items and actions based on a consumption plan,

[1058] A means of updating a recording device to receive user feedback after consumption and use it for future planning proposals,

[1059] A means of analyzing emotional information and providing suggestions based on the user's psychological state,

[1060] A system that includes this.

[1061] (Claim 2)

[1062] The system according to claim 1, wherein the analysis means uses natural language processing technology and image recognition technology.

[1063] (Claim 3)

[1064] The system according to claim 1, wherein the customization means automatically reconfigures the suggested content in response to user input. [Explanation of Symbols]

[1065] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving user attribute information and image information, and analyzing that data to infer user preferences and travel requests, A means for automatically generating multiple travel plans based on the aforementioned analysis and assigning titles to the generated travel plans, A means for customizing and updating the aforementioned travel plan according to the user's request, A means for generating a preparation list that presents necessary items and actions based on a travel plan, A means of receiving user feedback after their trip and updating a database to use for future travel planning suggestions, A system that includes this.

2. The system according to claim 1, wherein the analysis means uses natural language processing technology and image recognition technology.

3. The system according to claim 1, wherein the customization means automatically rearranges accommodation and transportation in response to user input.

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