system

Abstract

We provide the system. [Solution] A communication means for the user to input travel conditions, A computational means that uses a model to analyze input conditions and generate a travel plan, A display means that presents the generated travel plan to the user and receives feedback from the user, A means of adjusting the travel plan based on feedback and presenting it again, A booking method in which users make reservations based on their confirmed travel plans, 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 method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

[0006] A "user" refers to a person who uses the system to create a travel plan.

[0007] "Travel conditions" refer to the user's desired destination, budget, activities, accommodation, and other preferences.

[0008] "Communication methods" refer to the means by which users input travel conditions and exchange information with the system, and primarily include online chat interfaces.

[0009] "Analysis means" refers to a function that analyzes the travel conditions entered by the user using natural language processing technology and understands their meaning.

[0010] A "generative AI model" refers to an artificial intelligence model that generates the optimal travel plan based on the user's travel conditions.

[0011] "Computational means" refers to the data processing functions necessary to create travel plans using a generative AI model.

[0012] "Display means" refers to a function for displaying generated travel plans and user feedback on the screen.

[0013] "Feedback" refers to suggestions for improvements or additional requests that users submit regarding the proposed travel plan.

[0014] "Adjustment mechanism" refers to a function that readjusts travel plans using a generative AI model based on user feedback and re-presents a plan optimized for the user.

[0015] "Reservation method" refers to a function that automatically makes reservations for accommodations, transportation, etc., based on a confirmed travel plan. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 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 Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Embodiments for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] 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.

[0022] 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).

[0023] 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."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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".

[0037] The system of this invention is built as a digital platform for users to easily plan their trips. Users access the system using a device (e.g., a smartphone or computer) and input their travel conditions. These conditions include destination, budget, activities of interest, and preferred type of accommodation. These conditions are transmitted to the server via communication means.

[0038] The server analyzes the received conditions using natural language processing technology and extracts important elements. The analyzed information is input into a generative AI model by a computational means that generates travel plans. The generative AI model generates the optimal plan for the user's conditions while referring to the accumulated travel database.

[0039] The generated travel plan is presented to the user through the terminal's display mechanism. This allows the user to review the details of the proposed plan and submit feedback as needed. For example, if the user adds requests such as "I want to lower the budget" or "I want to add tourist destinations I want to visit," the server processes this feedback through its adjustment mechanism and readjusts the travel plan based on the new conditions.

[0040] For example, if a user inputs, "I want to go to Kyoto. I'd like a tour that visits historical tourist spots. My budget is under 50,000 yen," the server analyzes this information, and the AI ​​model generates a suggested plan based on the input. This plan includes visits to famous temples and shrines in Kyoto and a list of affordable accommodations. If the user then provides feedback that they would like to enjoy local cuisine, the server will readjust the plan and present a new one that incorporates reservations at local restaurants.

[0041] If the user is satisfied with the final plan, the server automatically arranges accommodation and transportation through the booking system. Once all booking procedures are complete, confirmation information is sent to the user, and the travel plan is officially completed.

[0042] This invention is a system that enables the rapid planning of travel plans that meet user requirements and simplifies the booking process.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] Users access the system using a terminal and enter their travel requirements. These include their desired destination, budget, itinerary, activities of interest, and type of accommodation.

[0046] Step 2:

[0047] The terminal transmits the travel conditions entered by the user to the server via a communication method.

[0048] Step 3:

[0049] The server analyzes the received conditions using natural language processing technology and extracts the important elements. This analysis forms the basis for a clear travel plan tailored to the conditions.

[0050] Step 4:

[0051] The server inputs data into the AI ​​model based on the analysis results. The model generates the optimal travel plan based on these conditions and combines it with information from the internal database.

[0052] Step 5:

[0053] The server sends the generated travel plan to the user via the terminal's display. The plan includes details of the destination, accommodation, transportation, and planned activities.

[0054] Step 6:

[0055] Users review the displayed travel plan and send feedback, such as additional requests or corrections, to the server via their device.

[0056] Step 7:

[0057] The server uses user feedback to readjust the travel plan using a generated AI model. The adjusted plan is then presented to the user again, providing an optimized itinerary.

[0058] Step 8:

[0059] If the user is satisfied with the plan, they will indicate their decision to confirm it through their device.

[0060] Step 9:

[0061] Based on the confirmed travel plan, the server automatically arranges various reservations, such as accommodations and transportation, using booking methods.

[0062] Step 10:

[0063] After the reservation is complete, the server sends confirmation information to the user's terminal and terminates the travel planning process.

[0064] (Example 1)

[0065] 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."

[0066] Planning a trip involves complex tasks such as gathering information, organizing criteria, and making reservations, making it time-consuming and cumbersome for users. Furthermore, it is difficult to quickly present the optimal travel plan tailored to the user's needs and accurately handle the associated reservation procedures. Therefore, there is a need for a system that generates travel plans reflecting user requests and simplifies and streamlines the reservation process based on those plans.

[0067] 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.

[0068] In this invention, the server includes an information transmission means for the user to input travel conditions, an information processing means for analyzing the input conditions using natural language processing technology and generating a travel plan using an AI model, an information display means for presenting the generated travel plan to the user and receiving feedback from the user, an information adjustment means for readjusting the travel plan based on the feedback and presenting it again, and an information processing means for automatically performing reservation procedures based on the travel plan confirmed by the user. This enables the rapid generation of an optimal travel plan that reflects the user's wishes and the automation of related reservation procedures.

[0069] "Information transmission means" refers to a means that provides a function for users to input travel conditions and transmit this information to other components within the system.

[0070] "Natural language processing technology" is a technology that enables machines to understand and analyze the language that humans use on a daily basis.

[0071] A "generative AI model" is an artificial intelligence model that generates the optimal results related to a specific task based on past data and user input.

[0072] An "information processing means" is a means that has processing functions to perform calculations and analyses based on received information and generate results that meet the user's requirements.

[0073] "Information display means" refers to a means of visually presenting the generated travel plan and other related information to the user.

[0074] An "information adjustment mechanism" is a means of providing a function that modifies existing information based on user feedback and generates new information.

[0075] "Booking procedures" refer to a series of steps taken to secure reservations for accommodations and transportation based on a confirmed travel plan.

[0076] "Automated booking methods" refer to means that booking based on travel plans is performed automatically without manual intervention.

[0077] The system of this invention is a digital platform designed to help users efficiently plan their trips. Specifically, it begins with the user accessing the system using a device such as a smartphone or computer and entering their travel conditions. These conditions include details such as destination, budget, activities of interest, and preferred type of accommodation.

[0078] The information entered is transmitted from the terminal to the server via a data transmission method. The server analyzes this information using natural language processing technology and performs preprocessing to generate a travel plan. This analysis extracts important elements that are relevant to the user's requirements. For example, suppose the user enters specific requirements such as "I want to visit historical sites" or "I want to travel within a budget of 50,000 yen."

[0079] Based on the analyzed information, the server uses a generative AI model to generate the optimal travel plan for the user's conditions. This AI model takes into account past travel data and trend information, and has the ability to construct plans while referring to an accumulated database.

[0080] The generated travel plan is sent from the server to the terminal and presented to the user through an information display device. The user can review this plan and send feedback on aspects that do not meet their expectations, such as "I would like to find cheaper restaurants" or "I would like to add places to visit."

[0081] Upon receiving feedback, the server uses information adjustment tools to readjust the plan and regenerate a plan based on the new conditions. Finally, if the user is satisfied with the proposed travel plan, the server automatically executes the booking process via automated booking tools and notifies the user of confirmation information once all procedures are complete.

[0082] For example, if a user enters a prompt such as, "I want to plan a trip to Kyoto, including visiting historical sites and experiencing local cuisine, and I want to generate a program that suggests the best plan within a budget," the system is immediately ready to execute it. This entire process allows users to easily and quickly plan and book their trips.

[0083] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0084] Step 1:

[0085] Users enter their travel preferences using devices such as smartphones or computers. This information includes destination, budget, activities of interest, and type of accommodation. This input data is used as foundational information for planning the trip.

[0086] Step 2:

[0087] The terminal transmits the entered travel conditions to the server via an information transmission system. This process centralizes the travel information requested by the user, preparing it for subsequent processing.

[0088] Step 3:

[0089] The server analyzes the user's travel conditions using natural language processing technology. During the analysis, it extracts important keywords and phrases from the input information, structuring the data. The results of this analysis are then used to generate a travel plan.

[0090] Step 4:

[0091] The server inputs the analyzed information into a generating AI model. This AI model references past travel databases and trend information to calculate the optimal travel plan for the user's conditions. Data processing here includes optimizing the plan based on high-priority conditions.

[0092] Step 5:

[0093] The generated travel plan is transmitted from the server to the terminal via an information display device. The terminal then presents this plan to the user, allowing the user to review the details of the planned itinerary.

[0094] Step 6:

[0095] Users can provide feedback on the displayed travel plan, including further requests or changes. This could include budget revisions or adding places to visit. This feedback will be used to readjust the plan.

[0096] Step 7:

[0097] The server uses information adjustment mechanisms to readjust the travel plan based on the feedback received. It performs data calculations based on the new conditions and generates a newly optimized plan. This process involves updating and recalculating data based on the feedback conditions.

[0098] Step 8:

[0099] Once the user agrees to the final plan, the server automatically executes the booking process using automated booking methods. Accommodation and transportation are secured, and once all procedures are complete, confirmation information is sent to the device. This ensures that all travel plans are in place, allowing the user to travel with peace of mind.

[0100] (Application Example 1)

[0101] 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."

[0102] Modern travelers want to plan their trips smoothly, but they lack the means to obtain appropriate real-time information regarding sightseeing and dining choices after arriving at their destination. To allow travelers to efficiently enjoy sightseeing at their destination, flexible, real-time plan changes and guidance are required. There is a need to provide a system that addresses this lack of on-site information and guidance.

[0103] 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.

[0104] In this invention, the server includes communication means for the user to input travel conditions, computation means that uses a model to analyze the input conditions and generate a travel plan, and location information guidance means that acquire the user's location information and present local guidance information. This enables travelers to receive real-time information and flexible guidance at their destination.

[0105] "Communication method" refers to the interface that allows users to input travel conditions and send them to the server.

[0106] A "computational means" is a processor or system equipped with a model used to analyze input conditions and generate a travel plan.

[0107] "Display means" refers to a device or interface for presenting the generated travel plan to the user and receiving feedback from the user.

[0108] "Adjustment measures" refer to a process or system for readjusting and re-presenting travel plans based on user feedback.

[0109] A "booking method" refers to a function or system that automatically makes reservations for accommodation, transportation, and other services based on a travel plan confirmed by the user.

[0110] A "location information guidance means" is a function or device that acquires a user's real-time location information and provides local tourist information and facility information.

[0111] A system implementing this invention includes a communication device with an interface for the user to input travel conditions, a computing device equipped with a generative AI model for analyzing the input travel conditions and generating an optimal travel plan, a display device that presents the travel plan to the user and receives feedback, an adjustment device for adjusting the travel plan based on the user's feedback, and a reservation device that automatically provides local sightseeing information and makes reservations based on the travel plan confirmed by the user. These components operate in conjunction with a server on the cloud.

[0112] The server analyzes the user's travel conditions using natural language processing technology and extracts key elements. This analysis can utilize machine learning libraries such as TENSORFLOW®. The extracted information is then used by a generative AI model to generate a travel plan optimized for the user, referencing various travel databases.

[0113] On the terminal's display device, the generated travel plan is presented to the user, and user feedback is collected. If the user is using smart glasses, the glasses have a built-in location information guidance device that obtains the user's real-time location information. Then, tourist information and the next destination are displayed on the glasses' screen.

[0114] In this system, users can input prompts such as, "List major tourist attractions near my current location and suggest activities I can enjoy within my budget," and the server will provide information in real time in response to those requests. Users can check information on tourist spots and restaurants on the spot through their smart glasses and flexibly adapt their travel plans. For example, if a user is sightseeing in the Higashiyama area of ​​Kyoto and requests, "Tell me about activities I can enjoy around here," the server can analyze the information and display appropriate tourist spots and restaurant options on the glasses.

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The user enters travel conditions using the communication device on their terminal. These conditions include destination, budget, and activities of interest. This information is sent to the server. The output is a dataset containing the user's travel conditions.

[0118] Step 2:

[0119] The server analyzes the travel conditions it receives using natural language processing (NLP) techniques. Specifically, it uses an NLP library (e.g., spaCy or NLTK) to extract important elements from the conditions. The input is a user's travel condition dataset, and the output is a list of the analyzed condition elements.

[0120] Step 3:

[0121] The server generates the optimal travel plan using a generative AI model based on the analyzed elements. Here, machine learning frameworks such as TensorFlow are used to calculate plans that meet the conditions, referencing an accumulated travel database. The input is a list of condition elements, and the output is a dataset of generated travel plans.

[0122] Step 4:

[0123] The generated travel plan is sent to the user's device and presented to the user via a display device. The user reviews the plan details and provides feedback as needed. The input is a dataset of the generated travel plan, and the output is the user's feedback.

[0124] Step 5:

[0125] The server receives user feedback and adjusts the travel plan based on it. The adjustments again utilize an AI model, for example, by adding or adjusting new conditions. The input is the feedback dataset, and the output is the adjusted travel plan dataset.

[0126] Step 6:

[0127] The server obtains the user's location information and generates guidance information based on their current location. This is achieved by acquiring GPS location information, and if the user is wearing smart glasses, it displays guidance for tourist attractions and facilities in real time. The input is the user's real-time location information, and the output is a dataset of guidance information.

[0128] Step 7:

[0129] Based on the travel plan confirmed by the user, the server automatically handles the booking process. It integrates with the booking system to automatically complete arrangements for transportation and accommodation. The input is a dataset of the adjusted travel plan, and the output is booking confirmation information.

[0130] 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.

[0131] The system of this invention is built as a digital platform including an emotion engine to help users efficiently create emotion-based travel plans. Users access the system using a terminal and input their travel preferences and requirements, including destination, budget, desired activities, and itinerary.

[0132] First, the server receives input from the user via a communication method. The server then uses natural language processing technology to analyze this information. Through this analysis, the user's requests are clearly identified.

[0133] Furthermore, this system incorporates an emotion engine to collect emotional data through interaction with the user. Based on this emotional data, the server determines the user's emotional state and generates an optimal travel plan using an AI model that corresponds to those emotions. The emotion engine ensures that the calculation method considers not only the user's feedback but also their current emotions to suggest an optimized plan.

[0134] The generated travel plan is presented to the user through the device's display. The user can review this plan and submit additional requests or modifications as feedback. Furthermore, if the emotion engine detects a change in the user's emotions, elements of the plan, such as activity selections or itinerary, are dynamically adjusted.

[0135] For example, when a user enters "I want to go to Paris. I want to take a trip to enjoy art," the server analyzes the input and generates a plan centered around a Paris museum tour. If the emotion engine detects the user's heightened emotions during this process, it can also incorporate suggestions for enjoying the nightlife. Conversely, if stress is detected, it will suggest visiting a relaxing spa or cafe.

[0136] Once the user confirms the final plan, the server automatically arranges accommodation and transportation through the booking system. After the booking is complete, confirmation information is sent to the user's device, and the travel plan is officially completed.

[0137] By utilizing an emotion engine, it becomes possible to create travel experiences that resonate with users' emotions and tailor trips to their individual needs. This significantly improves the accuracy of planning and customer satisfaction.

[0138] The following describes the processing flow.

[0139] Step 1:

[0140] Users access the system using their devices and enter their travel plans and preferences. Specifically, they enter detailed information such as desired destinations, budget, and duration in the input fields.

[0141] Step 2:

[0142] The terminal transmits the information entered by the user to the server via a communication method.

[0143] Step 3:

[0144] The server receives input information from the user and analyzes the data using natural language processing technology. This extracts and structures the user's wishes and conditions.

[0145] Step 4:

[0146] The server uses an emotion engine to collect data from user input and past interactions to determine the user's emotional state. This includes the content and expression of text.

[0147] Step 5:

[0148] Based on the emotional data collected by the emotion engine, the server inputs the analyzed conditions and emotional state into the generating AI model to create a travel plan that takes the user's emotions into account.

[0149] Step 6:

[0150] The server presents the generated travel plan to the user through the terminal's display. This plan includes activities and sightseeing routes tailored to the user's mood.

[0151] Step 7:

[0152] The user reviews the displayed travel plan and sends feedback to the server via their device if any modifications are needed. Additionally, if the user's emotions change, the emotion engine detects this and notifies the server.

[0153] Step 8:

[0154] Based on feedback and changes in sentiment data, the server readjusts the travel plan. The adjusted plan is then presented to the user's device again, and further modifications are made as needed.

[0155] Step 9:

[0156] If the user is ultimately satisfied with the plan and confirms it, the server automatically processes the booking of accommodations, transportation, and other items through the booking system.

[0157] Step 10:

[0158] The server sends confirmation information about the reservation details to the user's terminal, thereby completing the travel planning process.

[0159] (Example 2)

[0160] 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".

[0161] Conventional travel planning systems struggled to dynamically generate and adjust plans based on user emotions and immediate circumstances. Furthermore, analyzing user input failed to adequately reflect emotions and intuitive requests, making it difficult to provide detailed suggestions tailored to individual needs. This sometimes resulted in decreased user satisfaction.

[0162] 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.

[0163] In this invention, the server includes communication means for the user to input travel conditions and collect data including related intentions; computation means that uses a model that analyzes the input conditions using natural language processing technology, evaluates the user's emotional state using an emotion engine, and generates a travel plan based on that data; and display means that presents the generated travel plan to the user and receives feedback while detecting changes in the user's emotions. This makes it possible to generate and adjust a dynamic and optimal travel plan in accordance with the user's emotions and individual requests.

[0164] "Communication means" refers to a device or interface for users to input travel conditions and for data, including related intentions, to be collected.

[0165] "Natural language processing technology" is a technology that analyzes text information entered by a user and understands its content.

[0166] An "emotion engine" is a program or system that evaluates a user's emotional state based on data collected through user interaction.

[0167] A "generative AI model" is an algorithm or program that generates the optimal travel plan based on user input information and emotional data.

[0168] "Display means" refers to a device or interface that presents the generated travel plan to the user and receives feedback from the user.

[0169] "Adjustment mechanism" refers to a function or process for dynamically updating the travel plan based on user feedback and emotional state.

[0170] A "booking method" refers to a process or system that automatically makes reservations based on a user's confirmed travel plan.

[0171] This invention is a digital system that helps users efficiently create emotion-based travel plans. The system incorporates an emotion engine and includes communication means, calculation means, display means, adjustment means, and booking means. This allows users to obtain an optimal travel plan tailored to their individual emotional state.

[0172] First, the user uses a terminal to input travel conditions such as destination, budget, desired activities, and itinerary via a communication method. The terminal sends this information to the server. Upon receiving this information, the server performs analysis using natural language processing technology. Specifically, the natural language processing software, as the analysis method, tokenizes the input text data and performs syntactic and semantic analysis.

[0173] Next, the server utilizes an emotion engine to extract emotion data from user input and past interactions, and evaluates the user's current emotional state. The emotion engine continuously monitors changes in the user's emotions and supplies this data to a generative AI model for computation. Based on this data, the generative AI model generates an optimal travel plan using prompts. An example of a prompt is, "Create the optimal Paris travel plan based on this user's emotion data."

[0174] The generated travel plan is sent from the server to the terminal and presented to the user via a display device. The user can review this plan, send further feedback, and use it to dynamically adjust the plan. Based on the user's feedback and sentiment data, the server updates the travel plan using an adjustment device.

[0175] Finally, once the user confirms their plan, the server automatically makes reservations for accommodation and transportation through the booking system. This booking process is carried out using a partnered booking system, and the confirmed booking information is sent back to the user's device. This entire process allows the user to have a highly intuitive and personalized travel experience.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The user enters their travel conditions (destination, budget, activities, itinerary, etc.) and sends them to the terminal. The terminal then transmits this input data to the server via a communication method. The input here is text data containing the user's wishes and requirements, and this serves as the starting point for the system's main process.

[0179] Step 2:

[0180] The server analyzes the user's input data using natural language processing techniques. The input for this analysis is text data sent from the terminal. Specifically, the server tokenizes the text data and extracts the user's intent using a language model. The output is a data structure that clearly identifies the user's request.

[0181] Step 3:

[0182] The server uses an emotion engine based on the analysis results to collect and analyze emotion data from user interaction data. The input for this process is the user's past interaction history and current input. The emotion engine evaluates the text data and calculates the user's emotional state. The output is the user's emotion evaluation data.

[0183] Step 4:

[0184] The server supplies emotion data and analysis results to a generating AI model to create a travel plan. The input to this plan generation process includes analyzed user requests and emotion evaluation data. Specifically, the server inputs prompt sentences into the generating AI model, generating a travel plan that reflects the optimal situation based on the user's emotions. The output is the data of the generated travel plan.

[0185] Step 5:

[0186] The server sends the generated travel plan to the terminal, which then presents the plan to the user through a display device. The user can review this plan and enter any additional requests or feedback. The input in this step is the generated travel plan, and the output is the user's feedback data.

[0187] Step 6:

[0188] The server uses user feedback to re-evaluate the travel plan using an emotion engine and dynamically adjust it. The input for this adjustment step is user feedback and the latest emotion data. The server reuses the generated AI model as needed to update the plan. The output is the adjusted travel plan.

[0189] Step 7:

[0190] Once the server receives the user's finalized plan, it automates the booking process for accommodations and transportation using the booking system. This includes access to partner booking systems. The input for this process is the finalized travel plan, and the output is confirmation information for the booked travel services. This confirmation information is sent to the user via the terminal.

[0191] (Application Example 2)

[0192] 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".

[0193] Traditional systems struggled with personalized planning based on user emotions, making it difficult to provide optimal suggestions tailored to the user's emotional state. This limited the potential for improving the user experience.

[0194] 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.

[0195] In this invention, the server includes communication means for the user to input conditions, computation means that use a model to analyze the input conditions and generate a plan, and means that analyze the user's emotions using emotion analysis technology and generate information corresponding to those emotions. This enables dynamic optimization of the plan based on the user's emotions and the provision of a personalized experience.

[0196] A "user" is the entity that uses the system and inputs conditions.

[0197] "Communication means" refers to devices or methods for users to input and transmit conditions.

[0198] A "computational means" refers to a device or method that generates a plan using a generated AI model based on the input conditions.

[0199] "Display means" refers to a device or method for presenting a generated plan to the user.

[0200] "Adjustment means" refers to devices or methods that adjust and re-present a plan based on feedback and emotional data.

[0201] "Emotional analysis technology" is a technology used to analyze a user's emotional state.

[0202] "Information" refers to various data and suggestions related to the plan presented to the user.

[0203] A "reservation method" refers to a device or method that allows a user to make a reservation based on a confirmed plan.

[0204] The server provides a means of communication for users to input conditions, and users access the system using their own devices. The conditions entered by the user are sent to the server via the communication means. The server has a computing means to analyze these conditions, and this computing means utilizes a generative AI model. The natural language processing technology used here is the foundational technology for efficiently analyzing the input conditions and generating the optimal plan that meets the user's needs.

[0205] The generated plan is presented to the user's device via a display device. The user can review this plan and provide feedback as needed. The server dynamically adjusts the plan based on the user's feedback and sentiment data collected using sentiment analysis technology, and then presents the newly optimized plan to the user again.

[0206] For example, when a user enters a department store and observes products through smart glasses, if an emotion indicating "excitement" is detected, the server can present the user with the latest product information and coupons that can be used immediately. Furthermore, by using an emotion engine, it is possible to provide personalized information tailored to the user's mood.

[0207] Examples of prompt statements include the following:

[0208] Current user sentiment: Happy

[0209] Store conditions: Many sale items, famous brands on display.

[0210] Recommended actions: Focus on browsing sale items + take advantage of brand product coupons.

[0211] This enables the generation of dynamic plans that are tailored to the user's emotions and significantly improves the user experience.

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] Users enter travel details using their device and send them to the server. This information includes destination, budget, and desired activities, which are then transmitted to the server via communication channels.

[0215] Step 2:

[0216] The server analyzes the received conditions using natural language processing technology. Here, the conditions are text-based, and specific information such as destination and budget is extracted. The extracted information is then sent to the computing system.

[0217] Step 3:

[0218] The server uses computational means to leverage a generative AI model and generate the optimal plan based on the analyzed information. In this step, data is input into the model, and the travel plan best suited to the user is output. The results are recorded and used by the display means.

[0219] Step 4:

[0220] The server sends the generated plan to the terminal and presents it to the user. The user can review this plan and request adjustments to suit their needs by providing feedback.

[0221] Step 5:

[0222] The server collects emotional data using sentiment analysis technology, along with user feedback. This data, along with the feedback, is input into adjustment mechanisms and used to modify the plan.

[0223] Step 6:

[0224] The server uses adjustment mechanisms to optimize the plan based on feedback and sentiment data, generating a new plan. This dynamically modifies the plan, which is then presented to the user again.

[0225] Step 7:

[0226] Once the user finalizes their plan, the server automatically uses the reservation method to perform the necessary reservation procedures through the partnered reservation system. The completed reservation information is sent to the terminal and notified to the user.

[0227] 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.

[0228] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), 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.

[0229] 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.

[0230] [Second Embodiment]

[0231] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0232] 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.

[0233] 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).

[0234] 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.

[0235] 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.

[0236] 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).

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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".

[0243] The system of this invention is built as a digital platform for users to easily plan their trips. Users access the system using a device (e.g., a smartphone or computer) and input their travel conditions. These conditions include destination, budget, activities of interest, and preferred type of accommodation. These conditions are transmitted to the server via communication means.

[0244] The server analyzes the received conditions using natural language processing technology and extracts important elements. The analyzed information is input into a generative AI model by a computational means that generates travel plans. The generative AI model generates the optimal plan for the user's conditions while referring to the accumulated travel database.

[0245] The generated travel plan is presented to the user through the terminal's display mechanism. This allows the user to review the details of the proposed plan and submit feedback as needed. For example, if the user adds requests such as "I want to lower the budget" or "I want to add tourist destinations I want to visit," the server processes this feedback through its adjustment mechanism and readjusts the travel plan based on the new conditions.

[0246] For example, if a user inputs, "I want to go to Kyoto. I'd like a tour that visits historical tourist spots. My budget is under 50,000 yen," the server analyzes this information, and the AI ​​model generates a suggested plan based on the input. This plan includes visits to famous temples and shrines in Kyoto and a list of affordable accommodations. If the user then provides feedback that they would like to enjoy local cuisine, the server will readjust the plan and present a new one that incorporates reservations at local restaurants.

[0247] If the user is satisfied with the final plan, the server automatically arranges accommodation and transportation through the booking system. Once all booking procedures are complete, confirmation information is sent to the user, and the travel plan is officially completed.

[0248] This invention is a system that enables the rapid planning of travel plans that meet user requirements and simplifies the booking process.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] Users access the system using a terminal and enter their travel requirements. These include their desired destination, budget, itinerary, activities of interest, and type of accommodation.

[0252] Step 2:

[0253] The terminal transmits the travel conditions entered by the user to the server via a communication method.

[0254] Step 3:

[0255] The server analyzes the received conditions using natural language processing technology and extracts the important elements. This analysis forms the basis for a clear travel plan tailored to the conditions.

[0256] Step 4:

[0257] The server inputs data into the AI ​​model based on the analysis results. The model generates the optimal travel plan based on these conditions and combines it with information from the internal database.

[0258] Step 5:

[0259] The server sends the generated travel plan to the user via the terminal's display. The plan includes details of the destination, accommodation, transportation, and planned activities.

[0260] Step 6:

[0261] Users review the displayed travel plan and send feedback, such as additional requests or corrections, to the server via their device.

[0262] Step 7:

[0263] The server uses user feedback to readjust the travel plan using a generated AI model. The adjusted plan is then presented to the user again, providing an optimized itinerary.

[0264] Step 8:

[0265] If the user is satisfied with the plan, they will indicate their decision to confirm it through their device.

[0266] Step 9:

[0267] Based on the confirmed travel plan, the server automatically arranges various reservations, such as accommodations and transportation, using booking methods.

[0268] Step 10:

[0269] After the reservation is complete, the server sends confirmation information to the user's terminal and terminates the travel planning process.

[0270] (Example 1)

[0271] 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."

[0272] Planning a trip involves complex tasks such as gathering information, organizing criteria, and making reservations, making it time-consuming and cumbersome for users. Furthermore, it is difficult to quickly present the optimal travel plan tailored to the user's needs and accurately handle the associated reservation procedures. Therefore, there is a need for a system that generates travel plans reflecting user requests and simplifies and streamlines the reservation process based on those plans.

[0273] 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.

[0274] In this invention, the server includes an information transmission means for the user to input travel conditions, an information processing means for analyzing the input conditions using natural language processing technology and generating a travel plan using an AI model, an information display means for presenting the generated travel plan to the user and receiving feedback from the user, an information adjustment means for readjusting the travel plan based on the feedback and presenting it again, and an information processing means for automatically performing reservation procedures based on the travel plan confirmed by the user. This enables the rapid generation of an optimal travel plan that reflects the user's wishes and the automation of related reservation procedures.

[0275] "Information transmission means" refers to a means that provides a function for users to input travel conditions and transmit this information to other components within the system.

[0276] "Natural language processing technology" is a technology that enables machines to understand and analyze the language that humans use on a daily basis.

[0277] A "generative AI model" is an artificial intelligence model that generates the optimal results related to a specific task based on past data and user input.

[0278] An "information processing means" is a means that has processing functions to perform calculations and analyses based on received information and generate results that meet the user's requirements.

[0279] "Information display means" refers to a means of visually presenting the generated travel plan and other related information to the user.

[0280] An "information adjustment mechanism" is a means of providing a function that modifies existing information based on user feedback and generates new information.

[0281] "Booking procedures" refer to a series of steps taken to secure reservations for accommodations and transportation based on a confirmed travel plan.

[0282] The "reservation automation means" is a means for automatically performing reservation operations based on a travel plan without manual intervention.

[0283] The system of this invention is a digital platform for assisting users in efficiently making travel plans. Specifically, it begins with the user accessing through a terminal such as a smartphone or computer and inputting travel conditions. This includes details such as the destination, budget, interesting activities, and the type of accommodation desired.

[0284] The input information is transmitted from the terminal to the server through the information transmission means. The server analyzes this information using natural language processing technology and performs preprocessing for generating a travel plan. Through this analysis, important elements that meet the user's requirements are extracted. For example, assume the user inputs specific requirements such as "want to visit historical sites" or "want to travel within a budget of 50,000 yen".

[0285] Based on the analyzed information, the server uses a generation AI model to generate a travel plan that is optimal for the user's conditions. This AI model takes into account past travel data and trend information and has the ability to construct a plan while referring to the accumulated database.

[0286] The generated travel plan is transmitted from the server to the terminal and presented to the user through the information display means. The user can check this plan and send feedback about points that do not meet their wishes, such as "want to find a more affordable dining place" or "want to add places to visit".

[0287] Upon receiving the feedback, the server readjusts the plan using the information adjustment means and regenerates a plan based on the new conditions. And finally, when the user is satisfied with the proposed travel plan, the server automatically executes the reservation procedure through the reservation automation means and notifies the user of the confirmation information when all procedures are completed.

[0288] For example, if a user enters a prompt such as, "I want to plan a trip to Kyoto, including visiting historical sites and experiencing local cuisine, and I want to generate a program that suggests the best plan within a budget," the system is immediately ready to execute it. This entire process allows users to easily and quickly plan and book their trips.

[0289] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0290] Step 1:

[0291] Users enter their travel preferences using devices such as smartphones or computers. This information includes destination, budget, activities of interest, and type of accommodation. This input data is used as foundational information for planning the trip.

[0292] Step 2:

[0293] The terminal transmits the entered travel conditions to the server via an information transmission system. This process centralizes the travel information requested by the user, preparing it for subsequent processing.

[0294] Step 3:

[0295] The server analyzes the user's travel conditions using natural language processing technology. During the analysis, it extracts important keywords and phrases from the input information, structuring the data. The results of this analysis are then used to generate a travel plan.

[0296] Step 4:

[0297] The server inputs the analyzed information into a generating AI model. This AI model references past travel databases and trend information to calculate the optimal travel plan for the user's conditions. Data processing here includes optimizing the plan based on high-priority conditions.

[0298] Step 5:

[0299] The generated travel plan is transmitted from the server to the terminal through the information display means. By presenting this plan to the user, the user can check the details of the planned itinerary.

[0300] Step 6:

[0301] The user can input further wishes and changes as feedback for the displayed travel plan. For example, it includes reviewing the budget and adding places to visit. This feedback is used for readjusting the plan.

[0302] Step 7:

[0303] The server readjusts the travel plan using the information adjustment means based on the received feedback. Data calculations are performed based on the new conditions to generate a newly optimized plan. In this process, data updates and recalculations are performed according to the feedback conditions.

[0304] Step 8:

[0305] When the user agrees to the final plan, the server automatically executes the reservation procedure using the reservation automation means. Ensuring accommodation facilities and transportation means is carried out, and when all procedures are completed, confirmation information is notified to the terminal. As a result, all preparations for the travel plan are completed, and the user can embark on the journey with confidence.

[0306] (Application Example 1)

[0307] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0308] Modern travelers want to plan their trips smoothly, but they lack the means to obtain appropriate real-time information regarding sightseeing and dining choices after arriving at their destination. To allow travelers to efficiently enjoy sightseeing at their destination, flexible, real-time plan changes and guidance are required. There is a need to provide a system that addresses this lack of on-site information and guidance.

[0309] 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.

[0310] In this invention, the server includes communication means for the user to input travel conditions, computation means that uses a model to analyze the input conditions and generate a travel plan, and location information guidance means that acquire the user's location information and present local guidance information. This enables travelers to receive real-time information and flexible guidance at their destination.

[0311] "Communication method" refers to the interface that allows users to input travel conditions and send them to the server.

[0312] A "computational means" is a processor or system equipped with a model used to analyze input conditions and generate a travel plan.

[0313] "Display means" refers to a device or interface for presenting the generated travel plan to the user and receiving feedback from the user.

[0314] "Adjustment mechanism" refers to a process or system for readjusting and re-presenting travel plans based on user feedback.

[0315] A "booking method" refers to a function or system that automatically makes reservations for accommodation, transportation, and other services based on a travel plan confirmed by the user.

[0316] A "location information guidance means" is a function or device that acquires a user's real-time location information and provides local tourist information and facility information.

[0317] A system implementing this invention includes a communication device with an interface for the user to input travel conditions, a computing device equipped with a generative AI model for analyzing the input travel conditions and generating an optimal travel plan, a display device that presents the travel plan to the user and receives feedback, an adjustment device for adjusting the travel plan based on the user's feedback, and a reservation device that automatically provides local sightseeing information and makes reservations based on the travel plan confirmed by the user. These components operate in conjunction with a server on the cloud.

[0318] The server analyzes the user's travel conditions using natural language processing techniques and extracts key elements. Machine learning libraries such as TensorFlow can be used for this analysis. The extracted information is then used by a generative AI model to generate a travel plan optimized for the user, referencing various travel databases.

[0319] On the terminal's display device, the generated travel plan is presented to the user, and user feedback is collected. If the user is using smart glasses, the glasses have a built-in location information guidance device that obtains the user's real-time location information. Then, tourist information and the next destination are displayed on the glasses' screen.

[0320] In this system, users can input prompts such as, "List major tourist attractions near my current location and suggest activities I can enjoy within my budget," and the server will provide information in real time in response to those requests. Users can check information on tourist spots and restaurants on the spot through their smart glasses and flexibly adapt their travel plans. For example, if a user is sightseeing in the Higashiyama area of ​​Kyoto and requests, "Tell me about activities I can enjoy around here," the server can analyze the information and display appropriate tourist spots and restaurant options on the glasses.

[0321] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0322] Step 1:

[0323] The user enters travel conditions using the communication device on their terminal. These conditions include destination, budget, and activities of interest. This information is sent to the server. The output is a dataset containing the user's travel conditions.

[0324] Step 2:

[0325] The server analyzes the travel conditions it receives using natural language processing (NLP) techniques. Specifically, it uses an NLP library (e.g., spaCy or NLTK) to extract important elements from the conditions. The input is a user's travel condition dataset, and the output is a list of the analyzed condition elements.

[0326] Step 3:

[0327] The server generates the optimal travel plan using a generative AI model based on the analyzed elements. Here, machine learning frameworks such as TensorFlow are used to calculate plans that meet the conditions, referencing an accumulated travel database. The input is a list of condition elements, and the output is a dataset of generated travel plans.

[0328] Step 4:

[0329] The generated travel plan is sent to the user's device and presented to the user via a display device. The user reviews the plan details and provides feedback as needed. The input is a dataset of the generated travel plan, and the output is the user's feedback.

[0330] Step 5:

[0331] The server receives user feedback and adjusts the travel plan based on it. The adjustments again utilize an AI model, for example, by adding or adjusting new conditions. The input is the feedback dataset, and the output is the adjusted travel plan dataset.

[0332] Step 6:

[0333] The server obtains the user's location information and generates guidance information based on their current location. This is achieved by acquiring GPS location information, and if the user is wearing smart glasses, it displays guidance for tourist attractions and facilities in real time. The input is the user's real-time location information, and the output is a dataset of guidance information.

[0334] Step 7:

[0335] Based on the travel plan confirmed by the user, the server automatically handles the booking process. It integrates with the booking system to automatically complete arrangements for transportation and accommodation. The input is a dataset of the adjusted travel plan, and the output is booking confirmation information.

[0336] 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.

[0337] The system of this invention is built as a digital platform including an emotion engine to help users efficiently create emotion-based travel plans. Users access the system using a terminal and input their travel preferences and requirements, including destination, budget, desired activities, and itinerary.

[0338] First, the server receives input from the user via a communication method. The server then uses natural language processing technology to analyze this information. Through this analysis, the user's requests are clearly identified.

[0339] Furthermore, this system incorporates an emotion engine to collect emotional data through interaction with the user. Based on this emotional data, the server determines the user's emotional state and generates an optimal travel plan using an AI model that corresponds to those emotions. The emotion engine ensures that the calculation method considers not only the user's feedback but also their current emotions to suggest an optimized plan.

[0340] The generated travel plan is presented to the user through the device's display. The user can review this plan and submit additional requests or modifications as feedback. Furthermore, if the emotion engine detects a change in the user's emotions, elements of the plan, such as activity selections or itinerary, are dynamically adjusted.

[0341] For example, when a user enters "I want to go to Paris. I want to take a trip to enjoy art," the server analyzes the input and generates a plan centered around a Paris museum tour. If the emotion engine detects the user's heightened emotions during this process, it can also incorporate suggestions for enjoying the nightlife. Conversely, if stress is detected, it will suggest visiting a relaxing spa or cafe.

[0342] Once the user confirms the final plan, the server automatically arranges accommodation and transportation through the booking system. After the booking is complete, confirmation information is sent to the user's device, and the travel plan is officially completed.

[0343] By utilizing an emotion engine, it becomes possible to create travel experiences that resonate with users' emotions and tailor trips to their individual needs. This significantly improves the accuracy of planning and customer satisfaction.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] Users access the system using their devices and enter their travel plans and preferences. Specifically, they enter detailed information such as desired destinations, budget, and duration in the input fields.

[0347] Step 2:

[0348] The terminal transmits the information entered by the user to the server via a communication method.

[0349] Step 3:

[0350] The server receives input information from the user and analyzes the data using natural language processing technology. This extracts and structures the user's wishes and conditions.

[0351] Step 4:

[0352] The server uses an emotion engine to collect data from user input and past interactions to determine the user's emotional state. This includes the content and expression of text.

[0353] Step 5:

[0354] Based on the emotional data collected by the emotion engine, the server inputs the analyzed conditions and emotional state into the generating AI model to create a travel plan that takes the user's emotions into account.

[0355] Step 6:

[0356] The server presents the generated travel plan to the user through the terminal's display. This plan includes activities and sightseeing routes tailored to the user's mood.

[0357] Step 7:

[0358] The user reviews the displayed travel plan and sends feedback to the server via their device if any modifications are needed. Additionally, if the user's emotions change, the emotion engine detects this and notifies the server.

[0359] Step 8:

[0360] Based on feedback and changes in sentiment data, the server readjusts the travel plan. The adjusted plan is then presented to the user's device again, and further modifications are made as needed.

[0361] Step 9:

[0362] If the user is ultimately satisfied with the plan and confirms it, the server automatically processes the booking of accommodations, transportation, and other items through the booking system.

[0363] Step 10:

[0364] The server sends confirmation information about the reservation details to the user's terminal, thereby completing the travel planning process.

[0365] (Example 2)

[0366] 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".

[0367] Conventional travel planning systems struggled to dynamically generate and adjust plans based on user emotions and immediate circumstances. Furthermore, analyzing user input failed to adequately reflect emotions and intuitive requests, making it difficult to provide detailed suggestions tailored to individual needs. This sometimes resulted in decreased user satisfaction.

[0368] 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.

[0369] In this invention, the server includes communication means for the user to input travel conditions and collect data including related intentions; computation means that uses a model that analyzes the input conditions using natural language processing technology, evaluates the user's emotional state using an emotion engine, and generates a travel plan based on that data; and display means that presents the generated travel plan to the user and receives feedback while detecting changes in the user's emotions. This makes it possible to generate and adjust a dynamic and optimal travel plan in accordance with the user's emotions and individual requests.

[0370] "Communication means" refers to a device or interface for users to input travel conditions and for data, including related intentions, to be collected.

[0371] "Natural language processing technology" is a technology that analyzes text information entered by a user and understands its content.

[0372] An "emotion engine" is a program or system that evaluates a user's emotional state based on data collected through user interaction.

[0373] A "generative AI model" is an algorithm or program that generates the optimal travel plan based on user input information and emotional data.

[0374] "Display means" refers to a device or interface that presents the generated travel plan to the user and receives feedback from the user.

[0375] "Adjustment mechanism" refers to a function or process for dynamically updating the travel plan based on user feedback and emotional state.

[0376] A "booking method" refers to a process or system that automatically makes reservations based on a user's confirmed travel plan.

[0377] This invention is a digital system that helps users efficiently create emotion-based travel plans. The system incorporates an emotion engine and includes communication means, calculation means, display means, adjustment means, and booking means. This allows users to obtain an optimal travel plan tailored to their individual emotional state.

[0378] First, the user uses a terminal to input travel conditions such as destination, budget, desired activities, and itinerary via a communication method. The terminal sends this information to the server. Upon receiving this information, the server performs analysis using natural language processing technology. Specifically, the natural language processing software, as the analysis method, tokenizes the input text data and performs syntactic and semantic analysis.

[0379] Next, the server utilizes an emotion engine to extract emotion data from user input and past interactions, and evaluates the user's current emotional state. The emotion engine continuously monitors changes in the user's emotions and supplies this data to a generative AI model for computation. Based on this data, the generative AI model generates an optimal travel plan using prompts. An example of a prompt is, "Create the optimal Paris travel plan based on this user's emotion data."

[0380] The generated travel plan is sent from the server to the terminal and presented to the user via a display device. The user can review this plan, send further feedback, and use it to dynamically adjust the plan. Based on the user's feedback and sentiment data, the server updates the travel plan using an adjustment device.

[0381] Finally, once the user confirms their plan, the server automatically makes reservations for accommodation and transportation through the booking system. This booking process is carried out using a partnered booking system, and the confirmed booking information is sent back to the user's device. This entire process allows the user to have a highly intuitive and personalized travel experience.

[0382] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0383] Step 1:

[0384] The user enters their travel conditions (destination, budget, activities, itinerary, etc.) and sends them to the terminal. The terminal then transmits this input data to the server via a communication method. The input here is text data containing the user's wishes and requirements, and this serves as the starting point for the system's main process.

[0385] Step 2:

[0386] The server analyzes the user's input data using natural language processing techniques. The input for this analysis is text data sent from the terminal. Specifically, the server tokenizes the text data and extracts the user's intent using a language model. The output is a data structure that clearly identifies the user's request.

[0387] Step 3:

[0388] The server uses an emotion engine based on the analysis results to collect and analyze emotion data from user interaction data. The input for this process is the user's past interaction history and current input. The emotion engine evaluates the text data and calculates the user's emotional state. The output is the user's emotion evaluation data.

[0389] Step 4:

[0390] The server supplies emotion data and analysis results to a generating AI model to create a travel plan. The input to this plan generation process includes analyzed user requests and emotion evaluation data. Specifically, the server inputs prompt sentences into the generating AI model, generating a travel plan that reflects the optimal situation based on the user's emotions. The output is the data of the generated travel plan.

[0391] Step 5:

[0392] The server sends the generated travel plan to the terminal, which then presents the plan to the user through a display device. The user can review this plan and enter any additional requests or feedback. The input in this step is the generated travel plan, and the output is the user's feedback data.

[0393] Step 6:

[0394] The server uses user feedback to re-evaluate the travel plan using an emotion engine and dynamically adjust it. The input for this adjustment step is user feedback and the latest emotion data. The server reuses the generated AI model as needed to update the plan. The output is the adjusted travel plan.

[0395] Step 7:

[0396] Once the server receives the user's finalized plan, it automates the booking process for accommodations and transportation using the booking system. This includes access to partner booking systems. The input for this process is the finalized travel plan, and the output is confirmation information for the booked travel services. This confirmation information is sent to the user via the terminal.

[0397] (Application Example 2)

[0398] 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."

[0399] Traditional systems struggled with personalized planning based on user emotions, making it difficult to provide optimal suggestions tailored to the user's emotional state. This limited the potential for improving the user experience.

[0400] 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.

[0401] In this invention, the server includes communication means for the user to input conditions, computation means that use a model to analyze the input conditions and generate a plan, and means that analyze the user's emotions using emotion analysis technology and generate information corresponding to those emotions. This enables dynamic optimization of the plan based on the user's emotions and the provision of a personalized experience.

[0402] A "user" is the entity that uses the system and inputs conditions.

[0403] "Communication means" refers to devices or methods for users to input and transmit conditions.

[0404] A "computational means" refers to a device or method that generates a plan using a generated AI model based on the input conditions.

[0405] "Display means" refers to a device or method for presenting a generated plan to the user.

[0406] "Adjustment means" refers to devices or methods that adjust and re-present a plan based on feedback and emotional data.

[0407] "Emotional analysis technology" is a technology used to analyze a user's emotional state.

[0408] "Information" refers to various data and suggestions related to the plan presented to the user.

[0409] A "reservation method" refers to a device or method that allows a user to make a reservation based on a confirmed plan.

[0410] The server provides a means of communication for users to input conditions, and users access the system using their own devices. The conditions entered by the user are sent to the server via the communication means. The server has a computing means to analyze these conditions, and this computing means utilizes a generative AI model. The natural language processing technology used here is the foundational technology for efficiently analyzing the input conditions and generating the optimal plan that meets the user's needs.

[0411] The generated plan is presented to the user's device via a display device. The user can review this plan and provide feedback as needed. The server dynamically adjusts the plan based on the user's feedback and sentiment data collected using sentiment analysis technology, and then presents the newly optimized plan to the user again.

[0412] For example, when a user enters a department store and observes products through smart glasses, if an emotion indicating "excitement" is detected, the server can present the user with the latest product information and coupons that can be used immediately. Furthermore, by using an emotion engine, it is possible to provide personalized information tailored to the user's mood.

[0413] Examples of prompt statements include the following:

[0414] Current user sentiment: Happy

[0415] Store conditions: Many sale items, famous brands on display.

[0416] Recommended actions: Focus on browsing sale items + take advantage of brand product coupons.

[0417] This enables the generation of dynamic plans that are tailored to the user's emotions and significantly improves the user experience.

[0418] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0419] Step 1:

[0420] Users enter travel details using their device and send them to the server. This information includes destination, budget, and desired activities, which are then transmitted to the server via communication channels.

[0421] Step 2:

[0422] The server analyzes the received conditions using natural language processing technology. Here, the conditions are text-based, and specific information such as destination and budget is extracted. The extracted information is then sent to the computing system.

[0423] Step 3:

[0424] The server uses computational means to leverage a generative AI model and generate the optimal plan based on the analyzed information. In this step, data is input into the model, and the travel plan best suited to the user is output. The results are recorded and used for display purposes.

[0425] Step 4:

[0426] The server sends the generated plan to the terminal and presents it to the user. The user can review this plan and request adjustments to suit their needs by providing feedback.

[0427] Step 5:

[0428] The server collects emotional data using sentiment analysis technology, along with user feedback. This data, along with the feedback, is input into adjustment mechanisms and used to modify the plan.

[0429] Step 6:

[0430] The server uses adjustment mechanisms to optimize the plan based on feedback and sentiment data, generating a new plan. This dynamically modifies the plan, which is then presented to the user again.

[0431] Step 7:

[0432] Once the user finalizes their plan, the server automatically performs the necessary booking procedures through a partner booking system using the booking method. The completed booking information is sent to the terminal and notified to the user.

[0433] 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.

[0434] 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.

[0435] 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.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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".

[0449] The system of this invention is built as a digital platform for users to easily plan their trips. Users access the system using a device (e.g., a smartphone or computer) and input their travel conditions. These conditions include destination, budget, activities of interest, and preferred type of accommodation. These conditions are transmitted to the server via communication means.

[0450] The server analyzes the received conditions using natural language processing technology and extracts important elements. The analyzed information is input into a generative AI model by a computational means that generates travel plans. The generative AI model generates the optimal plan for the user's conditions while referring to the accumulated travel database.

[0451] The generated travel plan is presented to the user through the terminal's display mechanism. This allows the user to review the details of the proposed plan and submit feedback as needed. For example, if the user adds requests such as "I want to lower the budget" or "I want to add tourist destinations I want to visit," the server processes this feedback through its adjustment mechanism and readjusts the travel plan based on the new conditions.

[0452] For example, if a user inputs, "I want to go to Kyoto. I'd like a tour that visits historical tourist spots. My budget is under 50,000 yen," the server analyzes this information, and the AI ​​model generates a suggested plan based on the input. This plan includes visits to famous temples and shrines in Kyoto and a list of affordable accommodations. If the user then provides feedback that they would like to enjoy local cuisine, the server will readjust the plan and present a new one that incorporates reservations at local restaurants.

[0453] If the user is satisfied with the final plan, the server automatically arranges accommodation and transportation through the booking system. Once all booking procedures are complete, confirmation information is sent to the user, and the travel plan is officially completed.

[0454] This invention is a system that enables the rapid planning of travel plans that meet user requirements and simplifies the booking process.

[0455] The following describes the processing flow.

[0456] Step 1:

[0457] Users access the system using a terminal and enter their travel requirements. These include their desired destination, budget, itinerary, activities of interest, and type of accommodation.

[0458] Step 2:

[0459] The terminal transmits the travel conditions entered by the user to the server via a communication method.

[0460] Step 3:

[0461] The server analyzes the received conditions using natural language processing technology and extracts the important elements. This analysis forms the basis for a clear travel plan tailored to the conditions.

[0462] Step 4:

[0463] The server inputs data into the AI ​​model based on the analysis results. The model generates the optimal travel plan based on these conditions and combines it with information from the internal database.

[0464] Step 5:

[0465] The server sends the generated travel plan to the user via the terminal's display. The plan includes details of the destination, accommodation, transportation, and planned activities.

[0466] Step 6:

[0467] Users review the displayed travel plan and send feedback, such as additional requests or corrections, to the server via their device.

[0468] Step 7:

[0469] The server uses user feedback to readjust the travel plan using a generated AI model. The adjusted plan is then presented to the user again, providing an optimized itinerary.

[0470] Step 8:

[0471] If the user is satisfied with the plan, they will indicate their decision to confirm it through their device.

[0472] Step 9:

[0473] Based on the confirmed travel plan, the server automatically arranges various reservations, such as accommodations and transportation, using booking methods.

[0474] Step 10:

[0475] After the reservation is complete, the server sends confirmation information to the user's terminal and terminates the travel planning process.

[0476] (Example 1)

[0477] 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."

[0478] Planning a trip involves complex tasks such as gathering information, organizing criteria, and making reservations, making it time-consuming and cumbersome for users. Furthermore, it is difficult to quickly present the optimal travel plan tailored to the user's needs and accurately handle the associated reservation procedures. Therefore, there is a need for a system that generates travel plans reflecting user requests and simplifies and streamlines the reservation process based on those plans.

[0479] 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.

[0480] In this invention, the server includes an information transmission means for the user to input travel conditions, an information processing means for analyzing the input conditions using natural language processing technology and generating a travel plan using an AI model, an information display means for presenting the generated travel plan to the user and receiving feedback from the user, an information adjustment means for readjusting the travel plan based on the feedback and presenting it again, and an information processing means for automatically performing reservation procedures based on the travel plan confirmed by the user. This enables the rapid generation of an optimal travel plan that reflects the user's wishes and the automation of related reservation procedures.

[0481] "Information transmission means" refers to a means that provides a function for users to input travel conditions and transmit this information to other components within the system.

[0482] "Natural language processing technology" is a technology that enables machines to understand and analyze the language that humans use on a daily basis.

[0483] A "generative AI model" is an artificial intelligence model that generates the optimal results related to a specific task based on past data and user input.

[0484] An "information processing means" is a means that has processing functions to perform calculations and analyses based on received information and generate results that meet the user's requirements.

[0485] "Information display means" refers to a means of visually presenting the generated travel plan and other related information to the user.

[0486] An "information adjustment mechanism" is a means of providing a function that modifies existing information based on user feedback and generates new information.

[0487] "Booking procedures" refer to a series of steps taken to secure reservations for accommodations and transportation based on a confirmed travel plan.

[0488] "Automated booking methods" refer to means that booking based on travel plans is performed automatically without manual intervention.

[0489] The system of this invention is a digital platform designed to help users efficiently plan their trips. Specifically, it begins with the user accessing the system using a device such as a smartphone or computer and entering their travel conditions. These conditions include details such as destination, budget, activities of interest, and preferred type of accommodation.

[0490] The information entered is transmitted from the terminal to the server via a data transmission method. The server analyzes this information using natural language processing technology and performs preprocessing to generate a travel plan. This analysis extracts important elements that are relevant to the user's requirements. For example, suppose the user enters specific requirements such as "I want to visit historical sites" or "I want to travel within a budget of 50,000 yen."

[0491] Based on the analyzed information, the server uses a generative AI model to generate the optimal travel plan for the user's conditions. This AI model takes into account past travel data and trend information, and has the ability to construct plans while referring to an accumulated database.

[0492] The generated travel plan is sent from the server to the terminal and presented to the user through an information display device. The user can review this plan and send feedback on aspects that do not meet their expectations, such as "I would like to find cheaper restaurants" or "I would like to add places to visit."

[0493] Upon receiving feedback, the server uses information adjustment tools to readjust the plan and regenerate a plan based on the new conditions. Finally, if the user is satisfied with the proposed travel plan, the server automatically executes the booking process via automated booking tools and notifies the user of confirmation information once all procedures are complete.

[0494] For example, if a user enters a prompt such as, "I want to plan a trip to Kyoto, including visiting historical sites and experiencing local cuisine, and I want to generate a program that suggests the best plan within a budget," the system is immediately ready to execute it. This entire process allows users to easily and quickly plan and book their trips.

[0495] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0496] Step 1:

[0497] Users enter their travel preferences using devices such as smartphones or computers. This information includes destination, budget, activities of interest, and type of accommodation. This input data is used as foundational information for planning the trip.

[0498] Step 2:

[0499] The terminal transmits the entered travel conditions to the server via an information transmission system. This process centralizes the travel information requested by the user, preparing it for subsequent processing.

[0500] Step 3:

[0501] The server analyzes the user's travel conditions using natural language processing technology. During the analysis, it extracts important keywords and phrases from the input information, structuring the data. The results of this analysis are then used to generate a travel plan.

[0502] Step 4:

[0503] The server inputs the analyzed information into a generating AI model. This AI model references past travel databases and trend information to calculate the optimal travel plan for the user's conditions. Data processing here includes optimizing the plan based on high-priority conditions.

[0504] Step 5:

[0505] The generated travel plan is transmitted from the server to the terminal via an information display device. The terminal then presents this plan to the user, allowing the user to review the details of the planned itinerary.

[0506] Step 6:

[0507] Users can provide feedback on the displayed travel plan, including further requests or changes. This could include budget revisions or adding places to visit. This feedback will be used to readjust the plan.

[0508] Step 7:

[0509] The server uses information adjustment mechanisms to readjust the travel plan based on the feedback received. It performs data calculations based on the new conditions and generates a newly optimized plan. This process involves updating and recalculating data based on the feedback conditions.

[0510] Step 8:

[0511] Once the user agrees to the final plan, the server automatically executes the booking process using automated booking methods. Accommodation and transportation are secured, and once all procedures are complete, confirmation information is sent to the device. This ensures that all travel plans are in place, allowing the user to travel with peace of mind.

[0512] (Application Example 1)

[0513] 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."

[0514] Modern travelers want to plan their trips smoothly, but they lack the means to obtain appropriate real-time information regarding sightseeing and dining choices after arriving at their destination. To allow travelers to efficiently enjoy sightseeing at their destination, flexible, real-time plan changes and guidance are required. There is a need to provide a system that addresses this lack of on-site information and guidance.

[0515] 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.

[0516] In this invention, the server includes communication means for the user to input travel conditions, computation means that uses a model to analyze the input conditions and generate a travel plan, and location information guidance means that acquire the user's location information and present local guidance information. This enables travelers to receive real-time information and flexible guidance at their destination.

[0517] "Communication method" refers to the interface that allows users to input travel conditions and send them to the server.

[0518] A "computational means" is a processor or system equipped with a model used to analyze input conditions and generate a travel plan.

[0519] "Display means" refers to a device or interface for presenting the generated travel plan to the user and receiving feedback from the user.

[0520] "Adjustment measures" refer to a process or system for readjusting and re-presenting travel plans based on user feedback.

[0521] A "booking method" refers to a function or system that automatically makes reservations for accommodation, transportation, and other services based on a travel plan confirmed by the user.

[0522] A "location information guidance means" is a function or device that acquires a user's real-time location information and provides local tourist information and facility information.

[0523] A system implementing this invention includes a communication device with an interface for the user to input travel conditions, a computing device equipped with a generative AI model for analyzing the input travel conditions and generating an optimal travel plan, a display device that presents the travel plan to the user and receives feedback, an adjustment device for adjusting the travel plan based on the user's feedback, and a reservation device that automatically provides local sightseeing information and makes reservations based on the travel plan confirmed by the user. These components operate in conjunction with a server on the cloud.

[0524] The server analyzes the user's travel conditions using natural language processing techniques and extracts key elements. Machine learning libraries such as TensorFlow can be used for this analysis. The extracted information is then used by a generative AI model to generate a travel plan optimized for the user, referencing various travel databases.

[0525] On the terminal's display device, the generated travel plan is presented to the user, and user feedback is collected. If the user is using smart glasses, the glasses have a built-in location information guidance device that obtains the user's real-time location information. Then, tourist information and the next destination are displayed on the glasses' screen.

[0526] In this system, users can input prompts such as, "List major tourist attractions near my current location and suggest activities I can enjoy within my budget," and the server will provide information in real time in response to those requests. Users can check information on tourist spots and restaurants on the spot through their smart glasses and flexibly adapt their travel plans. For example, if a user is sightseeing in the Higashiyama area of ​​Kyoto and requests, "Tell me about activities I can enjoy around here," the server can analyze the information and display appropriate tourist spots and restaurant options on the glasses.

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] The user enters travel conditions using the communication device on their terminal. These conditions include destination, budget, and activities of interest. This information is sent to the server. The output is a dataset containing the user's travel conditions.

[0530] Step 2:

[0531] The server analyzes the travel conditions it receives using natural language processing (NLP) techniques. Specifically, it uses an NLP library (e.g., spaCy or NLTK) to extract important elements from the conditions. The input is a user's travel condition dataset, and the output is a list of the analyzed condition elements.

[0532] Step 3:

[0533] The server generates the optimal travel plan using a generative AI model based on the analyzed elements. Here, machine learning frameworks such as TensorFlow are used to calculate plans that meet the conditions, referencing an accumulated travel database. The input is a list of condition elements, and the output is a dataset of generated travel plans.

[0534] Step 4:

[0535] The generated travel plan is sent to the user's device and presented to the user via a display device. The user reviews the plan details and provides feedback as needed. The input is a dataset of the generated travel plan, and the output is the user's feedback.

[0536] Step 5:

[0537] The server receives user feedback and adjusts the travel plan based on it. The adjustments again utilize an AI model, for example, by adding or adjusting new conditions. The input is the feedback dataset, and the output is the adjusted travel plan dataset.

[0538] Step 6:

[0539] The server obtains the user's location information and generates guidance information based on their current location. This is achieved by acquiring GPS location information, and if the user is wearing smart glasses, it displays guidance for tourist attractions and facilities in real time. The input is the user's real-time location information, and the output is a dataset of guidance information.

[0540] Step 7:

[0541] Based on the travel plan confirmed by the user, the server automatically handles the booking process. It integrates with the booking system to automatically complete arrangements for transportation and accommodation. The input is a dataset of the adjusted travel plan, and the output is booking confirmation information.

[0542] 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.

[0543] The system of this invention is built as a digital platform including an emotion engine to help users efficiently create emotion-based travel plans. Users access the system using a terminal and input their travel preferences and requirements, including destination, budget, desired activities, and itinerary.

[0544] First, the server receives input from the user via a communication method. The server then uses natural language processing technology to analyze this information. Through this analysis, the user's requests are clearly identified.

[0545] Furthermore, this system incorporates an emotion engine to collect emotional data through interaction with the user. Based on this emotional data, the server determines the user's emotional state and generates an optimal travel plan using an AI model that corresponds to those emotions. The emotion engine ensures that the calculation method considers not only the user's feedback but also their current emotions to suggest an optimized plan.

[0546] The generated travel plan is presented to the user through the device's display. The user can review this plan and submit additional requests or modifications as feedback. Furthermore, if the emotion engine detects a change in the user's emotions, elements of the plan, such as activity selections or itinerary, are dynamically adjusted.

[0547] For example, when a user enters "I want to go to Paris. I want to take a trip to enjoy art," the server analyzes the input and generates a plan centered around a Paris museum tour. If the emotion engine detects the user's heightened emotions during this process, it can also incorporate suggestions for enjoying the nightlife. Conversely, if stress is detected, it will suggest visiting a relaxing spa or cafe.

[0548] Once the user confirms the final plan, the server automatically arranges accommodation and transportation through the booking system. After the booking is complete, confirmation information is sent to the user's device, and the travel plan is officially completed.

[0549] By utilizing an emotion engine, it becomes possible to create travel experiences that resonate with users' emotions and tailor trips to their individual needs. This significantly improves the accuracy of planning and customer satisfaction.

[0550] The following describes the processing flow.

[0551] Step 1:

[0552] Users access the system using their devices and enter their travel plans and preferences. Specifically, they enter detailed information such as desired destinations, budget, and duration in the input fields.

[0553] Step 2:

[0554] The terminal transmits the information entered by the user to the server via a communication method.

[0555] Step 3:

[0556] The server receives input information from the user and analyzes the data using natural language processing technology. This extracts and structures the user's wishes and conditions.

[0557] Step 4:

[0558] The server uses an emotion engine to collect data from user input and past interactions to determine the user's emotional state. This includes the content and expression of text.

[0559] Step 5:

[0560] Based on the emotional data collected by the emotion engine, the server inputs the analyzed conditions and emotional state into the generating AI model to create a travel plan that takes the user's emotions into account.

[0561] Step 6:

[0562] The server presents the generated travel plan to the user through the terminal's display. This plan includes activities and sightseeing routes tailored to the user's mood.

[0563] Step 7:

[0564] The user reviews the displayed travel plan and sends feedback to the server via their device if any modifications are needed. Additionally, if the user's emotions change, the emotion engine detects this and notifies the server.

[0565] Step 8:

[0566] Based on feedback and changes in sentiment data, the server readjusts the travel plan. The adjusted plan is then presented to the user's device again, and further modifications are made as needed.

[0567] Step 9:

[0568] If the user is ultimately satisfied with the plan and confirms it, the server automatically processes the booking of accommodations, transportation, and other items through the booking system.

[0569] Step 10:

[0570] The server sends confirmation information about the reservation details to the user's terminal, thereby completing the travel planning process.

[0571] (Example 2)

[0572] 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."

[0573] Conventional travel planning systems struggled to dynamically generate and adjust plans based on user emotions and immediate circumstances. Furthermore, analyzing user input failed to adequately reflect emotions and intuitive requests, making it difficult to provide detailed suggestions tailored to individual needs. This sometimes resulted in decreased user satisfaction.

[0574] 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.

[0575] In this invention, the server includes communication means for the user to input travel conditions and collect data including related intentions; computation means that uses a model that analyzes the input conditions using natural language processing technology, evaluates the user's emotional state using an emotion engine, and generates a travel plan based on that data; and display means that presents the generated travel plan to the user and receives feedback while detecting changes in the user's emotions. This makes it possible to generate and adjust a dynamic and optimal travel plan in accordance with the user's emotions and individual requests.

[0576] "Communication means" refers to a device or interface for users to input travel conditions and for data, including related intentions, to be collected.

[0577] "Natural language processing technology" is a technology that analyzes text information entered by a user and understands its content.

[0578] An "emotion engine" is a program or system that evaluates a user's emotional state based on data collected through user interaction.

[0579] A "generative AI model" is an algorithm or program that generates the optimal travel plan based on user input information and emotional data.

[0580] "Display means" refers to a device or interface that presents the generated travel plan to the user and receives feedback from the user.

[0581] "Adjustment mechanism" refers to a function or process for dynamically updating the travel plan based on user feedback and emotional state.

[0582] A "booking method" refers to a process or system that automatically makes reservations based on a user's confirmed travel plan.

[0583] This invention is a digital system that helps users efficiently create emotion-based travel plans. The system incorporates an emotion engine and includes communication means, calculation means, display means, adjustment means, and booking means. This allows users to obtain an optimal travel plan tailored to their individual emotional state.

[0584] First, the user uses a terminal to input travel conditions such as destination, budget, desired activities, and itinerary via a communication method. The terminal sends this information to the server. Upon receiving this information, the server performs analysis using natural language processing technology. Specifically, the natural language processing software, as the analysis method, tokenizes the input text data and performs syntactic and semantic analysis.

[0585] Next, the server utilizes an emotion engine to extract emotion data from user input and past interactions, and evaluates the user's current emotional state. The emotion engine continuously monitors changes in the user's emotions and supplies this data to a generative AI model for computation. Based on this data, the generative AI model generates an optimal travel plan using prompts. An example of a prompt is, "Create the optimal Paris travel plan based on this user's emotion data."

[0586] The generated travel plan is sent from the server to the terminal and presented to the user via a display device. The user can review this plan, send further feedback, and use it to dynamically adjust the plan. Based on the user's feedback and sentiment data, the server updates the travel plan using an adjustment device.

[0587] Finally, once the user confirms their plan, the server automatically makes reservations for accommodation and transportation through the booking system. This booking process is carried out using a partnered booking system, and the confirmed booking information is sent back to the user's device. This entire process allows the user to have a highly intuitive and personalized travel experience.

[0588] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0589] Step 1:

[0590] The user enters their travel conditions (destination, budget, activities, itinerary, etc.) and sends them to the terminal. The terminal then transmits this input data to the server via a communication method. The input here is text data containing the user's wishes and requirements, and this serves as the starting point for the system's main process.

[0591] Step 2:

[0592] The server analyzes the user's input data using natural language processing techniques. The input for this analysis is text data sent from the terminal. Specifically, the server tokenizes the text data and extracts the user's intent using a language model. The output is a data structure that clearly identifies the user's request.

[0593] Step 3:

[0594] The server uses an emotion engine based on the analysis results to collect and analyze emotion data from user interaction data. The input for this process is the user's past interaction history and current input. The emotion engine evaluates the text data and calculates the user's emotional state. The output is the user's emotion evaluation data.

[0595] Step 4:

[0596] The server supplies emotion data and analysis results to a generating AI model to create a travel plan. The input to this plan generation process includes analyzed user requests and emotion evaluation data. Specifically, the server inputs prompt sentences into the generating AI model, generating a travel plan that reflects the optimal situation based on the user's emotions. The output is the data of the generated travel plan.

[0597] Step 5:

[0598] The server sends the generated travel plan to the terminal, which then presents the plan to the user through a display device. The user can review this plan and enter any additional requests or feedback. The input in this step is the generated travel plan, and the output is the user's feedback data.

[0599] Step 6:

[0600] The server uses user feedback to re-evaluate the travel plan using an emotion engine and dynamically adjust it. The input for this adjustment step is user feedback and the latest emotion data. The server reuses the generated AI model as needed to update the plan. The output is the adjusted travel plan.

[0601] Step 7:

[0602] Once the server receives the user's finalized plan, it automates the booking process for accommodations and transportation using the booking system. This includes access to partner booking systems. The input for this process is the finalized travel plan, and the output is confirmation information for the booked travel services. This confirmation information is sent to the user via the terminal.

[0603] (Application Example 2)

[0604] 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."

[0605] Traditional systems struggled with personalized planning based on user emotions, making it difficult to provide optimal suggestions tailored to the user's emotional state. This limited the potential for improving the user experience.

[0606] 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.

[0607] In this invention, the server includes communication means for the user to input conditions, computation means that use a model to analyze the input conditions and generate a plan, and means that analyze the user's emotions using emotion analysis technology and generate information corresponding to those emotions. This enables dynamic optimization of the plan based on the user's emotions and the provision of a personalized experience.

[0608] A "user" is the entity that uses the system and inputs conditions.

[0609] "Communication means" refers to devices or methods for users to input and transmit conditions.

[0610] A "computational means" refers to a device or method that generates a plan using a generated AI model based on the input conditions.

[0611] "Display means" refers to a device or method for presenting a generated plan to the user.

[0612] "Adjustment means" refers to devices or methods that adjust and re-present a plan based on feedback and emotional data.

[0613] "Emotional analysis technology" is a technology used to analyze a user's emotional state.

[0614] "Information" refers to various data and suggestions related to the plan presented to the user.

[0615] A "reservation method" refers to a device or method that allows a user to make a reservation based on a confirmed plan.

[0616] The server provides a means of communication for users to input conditions, and users access the system using their own devices. The conditions entered by the user are sent to the server via the communication means. The server has a computing means to analyze these conditions, and this computing means utilizes a generative AI model. The natural language processing technology used here is the foundational technology for efficiently analyzing the input conditions and generating the optimal plan that meets the user's needs.

[0617] The generated plan is presented to the user's device via a display device. The user can review this plan and provide feedback as needed. The server dynamically adjusts the plan based on the user's feedback and sentiment data collected using sentiment analysis technology, and then presents the newly optimized plan to the user again.

[0618] For example, when a user enters a department store and observes products through smart glasses, if an emotion indicating "excitement" is detected, the server can present the user with the latest product information and coupons that can be used immediately. Furthermore, by using an emotion engine, it is possible to provide personalized information tailored to the user's mood.

[0619] Examples of prompt statements include the following:

[0620] Current user sentiment: Happy

[0621] Store conditions: Many sale items, famous brands on display.

[0622] Recommended actions: Focus on browsing sale items + take advantage of brand product coupons.

[0623] This enables the generation of dynamic plans that are tailored to the user's emotions and significantly improves the user experience.

[0624] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0625] Step 1:

[0626] Users enter travel details using their device and send them to the server. This information includes destination, budget, and desired activities, which are then transmitted to the server via communication channels.

[0627] Step 2:

[0628] The server analyzes the received conditions using natural language processing technology. Here, the conditions are text-based, and specific information such as destination and budget is extracted. The extracted information is then sent to the computing system.

[0629] Step 3:

[0630] The server uses computational means to leverage a generative AI model and generate the optimal plan based on the analyzed information. In this step, data is input into the model, and the travel plan best suited to the user is output. The results are recorded and used by the display means.

[0631] Step 4:

[0632] The server sends the generated plan to the terminal and presents it to the user. The user can review this plan and request adjustments to suit their needs by providing feedback.

[0633] Step 5:

[0634] The server collects emotional data using sentiment analysis technology, along with user feedback. This data, along with the feedback, is input into adjustment mechanisms and used to modify the plan.

[0635] Step 6:

[0636] The server uses adjustment mechanisms to optimize the plan based on feedback and sentiment data, generating a new plan. This dynamically modifies the plan, which is then presented to the user again.

[0637] Step 7:

[0638] Once the user finalizes their plan, the server automatically uses the reservation method to perform the necessary reservation procedures through the partnered reservation system. The completed reservation information is sent to the terminal and notified to the user.

[0639] 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.

[0640] 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.

[0641] 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.

[0642] [Fourth Embodiment]

[0643] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0644] 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.

[0645] 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).

[0646] 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.

[0647] 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.

[0648] 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).

[0649] 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.

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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".

[0656] The system of this invention is built as a digital platform for users to easily plan their trips. Users access the system using a device (e.g., a smartphone or computer) and input their travel conditions. These conditions include destination, budget, activities of interest, and preferred type of accommodation. These conditions are transmitted to the server via communication means.

[0657] The server analyzes the received conditions using natural language processing technology and extracts important elements. The analyzed information is input into a generative AI model by a computational means that generates travel plans. The generative AI model generates the optimal plan for the user's conditions while referring to the accumulated travel database.

[0658] The generated travel plan is presented to the user through the terminal's display mechanism. This allows the user to review the details of the proposed plan and submit feedback as needed. For example, if the user adds requests such as "I want to lower the budget" or "I want to add tourist destinations I want to visit," the server processes this feedback through its adjustment mechanism and readjusts the travel plan based on the new conditions.

[0659] For example, if a user inputs, "I want to go to Kyoto. I'd like a tour that visits historical tourist spots. My budget is under 50,000 yen," the server analyzes this information, and the AI ​​model generates a suggested plan based on the input. This plan includes visits to famous temples and shrines in Kyoto and a list of affordable accommodations. If the user then provides feedback that they would like to enjoy local cuisine, the server will readjust the plan and present a new one that incorporates reservations at local restaurants.

[0660] If the user is satisfied with the final plan, the server automatically arranges accommodation and transportation through the booking system. Once all booking procedures are complete, confirmation information is sent to the user, and the travel plan is officially completed.

[0661] This invention is a system that enables the rapid planning of travel plans that meet user requirements and simplifies the booking process.

[0662] The following describes the processing flow.

[0663] Step 1:

[0664] Users access the system using a terminal and enter their travel requirements. These include their desired destination, budget, itinerary, activities of interest, and type of accommodation.

[0665] Step 2:

[0666] The terminal transmits the travel conditions entered by the user to the server via a communication method.

[0667] Step 3:

[0668] The server analyzes the received conditions using natural language processing technology and extracts the important elements. This analysis forms the basis for a clear travel plan tailored to the conditions.

[0669] Step 4:

[0670] The server inputs data into the AI ​​model based on the analysis results. The model generates the optimal travel plan based on these conditions and combines it with information from the internal database.

[0671] Step 5:

[0672] The server sends the generated travel plan to the user via the terminal's display. The plan includes details of the destination, accommodation, transportation, and planned activities.

[0673] Step 6:

[0674] Users review the displayed travel plan and send feedback, such as additional requests or corrections, to the server via their device.

[0675] Step 7:

[0676] The server uses user feedback to readjust the travel plan using a generated AI model. The adjusted plan is then presented to the user again, providing an optimized itinerary.

[0677] Step 8:

[0678] If the user is satisfied with the plan, they will indicate their decision to confirm it through their device.

[0679] Step 9:

[0680] Based on the confirmed travel plan, the server automatically arranges various reservations, such as accommodations and transportation, using booking methods.

[0681] Step 10:

[0682] After the reservation is complete, the server sends confirmation information to the user's terminal and terminates the travel planning process.

[0683] (Example 1)

[0684] 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".

[0685] Planning a trip involves complex tasks such as gathering information, organizing criteria, and making reservations, making it time-consuming and cumbersome for users. Furthermore, it is difficult to quickly present the optimal travel plan tailored to the user's needs and accurately handle the associated reservation procedures. Therefore, there is a need for a system that generates travel plans reflecting user requests and simplifies and streamlines the reservation process based on those plans.

[0686] 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.

[0687] In this invention, the server includes an information transmission means for the user to input travel conditions, an information processing means for analyzing the input conditions using natural language processing technology and generating a travel plan using an AI model, an information display means for presenting the generated travel plan to the user and receiving feedback from the user, an information adjustment means for readjusting the travel plan based on the feedback and presenting it again, and an information processing means for automatically performing reservation procedures based on the travel plan confirmed by the user. This enables the rapid generation of an optimal travel plan that reflects the user's wishes and the automation of related reservation procedures.

[0688] "Information transmission means" refers to a means that provides a function for users to input travel conditions and transmit this information to other components within the system.

[0689] "Natural language processing technology" is a technology that enables machines to understand and analyze the language that humans use on a daily basis.

[0690] A "generative AI model" is an artificial intelligence model that generates the optimal results related to a specific task based on past data and user input.

[0691] An "information processing means" is a means that has processing functions to perform calculations and analyses based on received information and generate results that meet the user's requirements.

[0692] "Information display means" refers to a means of visually presenting the generated travel plan and other related information to the user.

[0693] An "information adjustment mechanism" is a means of providing a function that modifies existing information based on user feedback and generates new information.

[0694] "Booking procedures" refer to a series of steps taken to secure reservations for accommodations and transportation based on a confirmed travel plan.

[0695] "Automated booking methods" refer to means that booking based on travel plans is performed automatically without manual intervention.

[0696] The system of this invention is a digital platform designed to help users efficiently plan their trips. Specifically, it begins with the user accessing the system using a device such as a smartphone or computer and entering their travel conditions. These conditions include details such as destination, budget, activities of interest, and preferred type of accommodation.

[0697] The information entered is transmitted from the terminal to the server via a data transmission method. The server analyzes this information using natural language processing technology and performs preprocessing to generate a travel plan. This analysis extracts important elements that are relevant to the user's requirements. For example, suppose the user enters specific requirements such as "I want to visit historical sites" or "I want to travel within a budget of 50,000 yen."

[0698] Based on the analyzed information, the server uses a generative AI model to generate the optimal travel plan for the user's conditions. This AI model takes into account past travel data and trend information, and has the ability to construct plans while referring to an accumulated database.

[0699] The generated travel plan is sent from the server to the terminal and presented to the user through an information display device. The user can review this plan and send feedback on aspects that do not meet their expectations, such as "I would like to find cheaper restaurants" or "I would like to add places to visit."

[0700] Upon receiving feedback, the server uses information adjustment tools to readjust the plan and regenerate a plan based on the new conditions. Finally, if the user is satisfied with the proposed travel plan, the server automatically executes the booking process via automated booking tools and notifies the user of confirmation information once all procedures are complete.

[0701] For example, if a user enters a prompt such as, "I want to plan a trip to Kyoto, including visiting historical sites and experiencing local cuisine, and I want to generate a program that suggests the best plan within a budget," the system is immediately ready to execute it. This entire process allows users to easily and quickly plan and book their trips.

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] Users enter their travel preferences using devices such as smartphones or computers. This information includes destination, budget, activities of interest, and type of accommodation. This input data is used as foundational information for planning the trip.

[0705] Step 2:

[0706] The terminal transmits the entered travel conditions to the server via an information transmission system. This process centralizes the travel information requested by the user, preparing it for subsequent processing.

[0707] Step 3:

[0708] The server analyzes the user's travel conditions using natural language processing technology. During the analysis, it extracts important keywords and phrases from the input information, structuring the data. The results of this analysis are then used to generate a travel plan.

[0709] Step 4:

[0710] The server inputs the analyzed information into a generating AI model. This AI model references past travel databases and trend information to calculate the optimal travel plan for the user's conditions. Data processing here includes optimizing the plan based on high-priority conditions.

[0711] Step 5:

[0712] The generated travel plan is transmitted from the server to the terminal via an information display device. The terminal then presents this plan to the user, allowing the user to review the details of the planned itinerary.

[0713] Step 6:

[0714] Users can provide feedback on the displayed travel plan, including further requests or changes. This could include budget revisions or adding places to visit. This feedback will be used to readjust the plan.

[0715] Step 7:

[0716] The server uses information adjustment mechanisms to readjust the travel plan based on the feedback received. It performs data calculations based on the new conditions and generates a newly optimized plan. This process involves updating and recalculating data based on the feedback conditions.

[0717] Step 8:

[0718] Once the user agrees to the final plan, the server automatically executes the booking process using automated booking methods. Accommodation and transportation are secured, and once all procedures are complete, confirmation information is sent to the device. This ensures that all travel plans are in place, allowing the user to travel with peace of mind.

[0719] (Application Example 1)

[0720] 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".

[0721] Modern travelers want to plan their trips smoothly, but they lack the means to obtain appropriate real-time information regarding sightseeing and dining choices after arriving at their destination. To allow travelers to efficiently enjoy sightseeing at their destination, flexible, real-time plan changes and guidance are required. There is a need to provide a system that addresses this lack of on-site information and guidance.

[0722] 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.

[0723] In this invention, the server includes communication means for the user to input travel conditions, computation means that uses a model to analyze the input conditions and generate a travel plan, and location information guidance means that acquire the user's location information and present local guidance information. This enables travelers to receive real-time information and flexible guidance at their destination.

[0724] "Communication method" refers to the interface that allows users to input travel conditions and send them to the server.

[0725] A "computational means" is a processor or system equipped with a model used to analyze input conditions and generate a travel plan.

[0726] "Display means" refers to a device or interface for presenting the generated travel plan to the user and receiving feedback from the user.

[0727] "Adjustment measures" refer to a process or system for readjusting and re-presenting travel plans based on user feedback.

[0728] A "booking method" refers to a function or system that automatically makes reservations for accommodation, transportation, and other services based on a travel plan confirmed by the user.

[0729] A "location information guidance means" is a function or device that acquires a user's real-time location information and provides local tourist information and facility information.

[0730] A system implementing this invention includes a communication device with an interface for the user to input travel conditions, a computing device equipped with a generative AI model for analyzing the input travel conditions and generating an optimal travel plan, a display device that presents the travel plan to the user and receives feedback, an adjustment device for adjusting the travel plan based on the user's feedback, and a reservation device that automatically provides local sightseeing information and makes reservations based on the travel plan confirmed by the user. These components operate in conjunction with a server on the cloud.

[0731] The server analyzes the user's travel conditions using natural language processing techniques and extracts key elements. Machine learning libraries such as TensorFlow can be used for this analysis. The extracted information is then used by a generative AI model to generate a travel plan optimized for the user, referencing various travel databases.

[0732] On the terminal's display device, the generated travel plan is presented to the user, and user feedback is collected. If the user is using smart glasses, the glasses have a built-in location information guidance device that obtains the user's real-time location information. Then, tourist information and the next destination are displayed on the glasses' screen.

[0733] In this system, users can input prompts such as, "List major tourist attractions near my current location and suggest activities I can enjoy within my budget," and the server will provide information in real time in response to those requests. Users can check information on tourist spots and restaurants on the spot through their smart glasses and flexibly adapt their travel plans. For example, if a user is sightseeing in the Higashiyama area of ​​Kyoto and requests, "Tell me about activities I can enjoy around here," the server can analyze the information and display appropriate tourist spots and restaurant options on the glasses.

[0734] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0735] Step 1:

[0736] The user enters travel conditions using the communication device on their terminal. These conditions include destination, budget, and activities of interest. This information is sent to the server. The output is a dataset containing the user's travel conditions.

[0737] Step 2:

[0738] The server analyzes the travel conditions it receives using natural language processing (NLP) techniques. Specifically, it uses an NLP library (e.g., spaCy or NLTK) to extract important elements from the conditions. The input is a user's travel condition dataset, and the output is a list of the analyzed condition elements.

[0739] Step 3:

[0740] The server generates the optimal travel plan using a generative AI model based on the analyzed elements. Here, machine learning frameworks such as TensorFlow are used to calculate plans that meet the conditions, referencing an accumulated travel database. The input is a list of condition elements, and the output is a dataset of generated travel plans.

[0741] Step 4:

[0742] The generated travel plan is sent to the user's device and presented to the user via a display device. The user reviews the plan details and provides feedback as needed. The input is a dataset of the generated travel plan, and the output is the user's feedback.

[0743] Step 5:

[0744] The server receives user feedback and adjusts the travel plan based on it. The adjustments again utilize an AI model, for example, by adding or adjusting new conditions. The input is the feedback dataset, and the output is the adjusted travel plan dataset.

[0745] Step 6:

[0746] The server obtains the user's location information and generates guidance information based on their current location. This is achieved by acquiring GPS location information, and if the user is wearing smart glasses, it displays guidance for tourist attractions and facilities in real time. The input is the user's real-time location information, and the output is a dataset of guidance information.

[0747] Step 7:

[0748] Based on the travel plan confirmed by the user, the server automatically handles the booking process. It integrates with the booking system to automatically complete arrangements for transportation and accommodation. The input is a dataset of the adjusted travel plan, and the output is booking confirmation information.

[0749] 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.

[0750] The system of this invention is built as a digital platform including an emotion engine to help users efficiently create emotion-based travel plans. Users access the system using a terminal and input their travel preferences and requirements, including destination, budget, desired activities, and itinerary.

[0751] First, the server receives input from the user via a communication method. The server then uses natural language processing technology to analyze this information. Through this analysis, the user's requests are clearly identified.

[0752] Furthermore, this system incorporates an emotion engine to collect emotional data through interaction with the user. Based on this emotional data, the server determines the user's emotional state and generates an optimal travel plan using an AI model that corresponds to those emotions. The emotion engine ensures that the calculation method considers not only the user's feedback but also their current emotions to suggest an optimized plan.

[0753] The generated travel plan is presented to the user through the device's display. The user can review this plan and submit additional requests or modifications as feedback. Furthermore, if the emotion engine detects a change in the user's emotions, elements of the plan, such as activity selections or itinerary, are dynamically adjusted.

[0754] For example, when a user enters "I want to go to Paris. I want to take a trip to enjoy art," the server analyzes the input and generates a plan centered around a Paris museum tour. If the emotion engine detects the user's heightened emotions during this process, it can also incorporate suggestions for enjoying the nightlife. Conversely, if stress is detected, it will suggest visiting a relaxing spa or cafe.

[0755] Once the user confirms the final plan, the server automatically arranges accommodation and transportation through the booking system. After the booking is complete, confirmation information is sent to the user's device, and the travel plan is officially completed.

[0756] By utilizing an emotion engine, it becomes possible to create travel experiences that resonate with users' emotions and tailor trips to their individual needs. This significantly improves the accuracy of planning and customer satisfaction.

[0757] The following describes the processing flow.

[0758] Step 1:

[0759] Users access the system using their devices and enter their travel plans and preferences. Specifically, they enter detailed information such as desired destinations, budget, and duration in the input fields.

[0760] Step 2:

[0761] The terminal transmits the information entered by the user to the server via a communication method.

[0762] Step 3:

[0763] The server receives input information from the user and analyzes the data using natural language processing technology. This extracts and structures the user's wishes and conditions.

[0764] Step 4:

[0765] The server uses an emotion engine to collect data from user input and past interactions to determine the user's emotional state. This includes the content and expression of text.

[0766] Step 5:

[0767] Based on the emotional data collected by the emotion engine, the server inputs the analyzed conditions and emotional state into the generating AI model to create a travel plan that takes the user's emotions into account.

[0768] Step 6:

[0769] The server presents the generated travel plan to the user through the terminal's display. This plan includes activities and sightseeing routes tailored to the user's mood.

[0770] Step 7:

[0771] The user reviews the displayed travel plan and sends feedback to the server via their device if any modifications are needed. Additionally, if the user's emotions change, the emotion engine detects this and notifies the server.

[0772] Step 8:

[0773] Based on feedback and changes in sentiment data, the server readjusts the travel plan. The adjusted plan is then presented to the user's device again, and further modifications are made as needed.

[0774] Step 9:

[0775] If the user is ultimately satisfied with the plan and confirms it, the server automatically processes the booking of accommodations, transportation, and other items through the booking system.

[0776] Step 10:

[0777] The server sends confirmation information about the reservation details to the user's terminal, thereby completing the travel planning process.

[0778] (Example 2)

[0779] 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".

[0780] Conventional travel planning systems struggled to dynamically generate and adjust plans based on user emotions and immediate circumstances. Furthermore, analyzing user input failed to adequately reflect emotions and intuitive requests, making it difficult to provide detailed suggestions tailored to individual needs. This sometimes resulted in decreased user satisfaction.

[0781] 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.

[0782] In this invention, the server includes communication means for the user to input travel conditions and collect data including related intentions; computation means that uses a model that analyzes the input conditions using natural language processing technology, evaluates the user's emotional state using an emotion engine, and generates a travel plan based on that data; and display means that presents the generated travel plan to the user and receives feedback while detecting changes in the user's emotions. This makes it possible to generate and adjust a dynamic and optimal travel plan in accordance with the user's emotions and individual requests.

[0783] "Communication means" refers to a device or interface for users to input travel conditions and for data, including related intentions, to be collected.

[0784] "Natural language processing technology" is a technology that analyzes text information entered by a user and understands its content.

[0785] An "emotion engine" is a program or system that evaluates a user's emotional state based on data collected through user interaction.

[0786] A "generative AI model" is an algorithm or program that generates the optimal travel plan based on user input information and emotional data.

[0787] "Display means" refers to a device or interface that presents the generated travel plan to the user and receives feedback from the user.

[0788] "Adjustment mechanism" refers to a function or process for dynamically updating the travel plan based on user feedback and emotional state.

[0789] A "booking method" refers to a process or system that automatically makes reservations based on a user's confirmed travel plan.

[0790] This invention is a digital system that helps users efficiently create emotion-based travel plans. The system incorporates an emotion engine and includes communication means, calculation means, display means, adjustment means, and booking means. This allows users to obtain an optimal travel plan tailored to their individual emotional state.

[0791] First, the user uses a terminal to input travel conditions such as destination, budget, desired activities, and itinerary via a communication method. The terminal sends this information to the server. Upon receiving this information, the server performs analysis using natural language processing technology. Specifically, the natural language processing software, as the analysis method, tokenizes the input text data and performs syntactic and semantic analysis.

[0792] Next, the server utilizes an emotion engine to extract emotion data from user input and past interactions, and evaluates the user's current emotional state. The emotion engine continuously monitors changes in the user's emotions and supplies this data to a generative AI model for computation. Based on this data, the generative AI model generates an optimal travel plan using prompts. An example of a prompt is, "Create the optimal Paris travel plan based on this user's emotion data."

[0793] The generated travel plan is sent from the server to the terminal and presented to the user via a display device. The user can review this plan, send further feedback, and use it to dynamically adjust the plan. Based on the user's feedback and sentiment data, the server updates the travel plan using an adjustment device.

[0794] Finally, once the user confirms their plan, the server automatically makes reservations for accommodation and transportation through the booking system. This booking process is carried out using a partnered booking system, and the confirmed booking information is sent back to the user's device. This entire process allows the user to have a highly intuitive and personalized travel experience.

[0795] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0796] Step 1:

[0797] The user enters their travel conditions (destination, budget, activities, itinerary, etc.) and sends them to the terminal. The terminal then transmits this input data to the server via a communication method. The input here is text data containing the user's wishes and requirements, and this serves as the starting point for the system's main process.

[0798] Step 2:

[0799] The server analyzes the user's input data using natural language processing techniques. The input for this analysis is text data sent from the terminal. Specifically, the server tokenizes the text data and extracts the user's intent using a language model. The output is a data structure that clearly identifies the user's request.

[0800] Step 3:

[0801] The server uses an emotion engine based on the analysis results to collect and analyze emotion data from user interaction data. The input for this process is the user's past interaction history and current input. The emotion engine evaluates the text data and calculates the user's emotional state. The output is the user's emotion evaluation data.

[0802] Step 4:

[0803] The server supplies emotion data and analysis results to a generating AI model to create a travel plan. The input to this plan generation process includes analyzed user requests and emotion evaluation data. Specifically, the server inputs prompt sentences into the generating AI model, generating a travel plan that reflects the optimal situation based on the user's emotions. The output is the data of the generated travel plan.

[0804] Step 5:

[0805] The server sends the generated travel plan to the terminal, which then presents the plan to the user through a display device. The user can review this plan and enter any additional requests or feedback. The input in this step is the generated travel plan, and the output is the user's feedback data.

[0806] Step 6:

[0807] The server uses user feedback to re-evaluate the travel plan using an emotion engine and dynamically adjust it. The input for this adjustment step is user feedback and the latest emotion data. The server reuses the generated AI model as needed to update the plan. The output is the adjusted travel plan.

[0808] Step 7:

[0809] Once the server receives the user's finalized plan, it automates the booking process for accommodations and transportation using the booking system. This includes access to partner booking systems. The input for this process is the finalized travel plan, and the output is confirmation information for the booked travel services. This confirmation information is sent to the user via the terminal.

[0810] (Application Example 2)

[0811] 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".

[0812] Traditional systems struggled with personalized planning based on user emotions, making it difficult to provide optimal suggestions tailored to the user's emotional state. This limited the potential for improving the user experience.

[0813] 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.

[0814] In this invention, the server includes communication means for the user to input conditions, computation means that use a model to analyze the input conditions and generate a plan, and means that analyze the user's emotions using emotion analysis technology and generate information corresponding to those emotions. This enables dynamic optimization of the plan based on the user's emotions and the provision of a personalized experience.

[0815] A "user" is the entity that uses the system and inputs conditions.

[0816] "Communication means" refers to devices or methods for users to input and transmit conditions.

[0817] A "computational means" refers to a device or method that generates a plan using a generated AI model based on the input conditions.

[0818] "Display means" refers to a device or method for presenting a generated plan to the user.

[0819] "Adjustment means" refers to devices or methods that adjust and re-present a plan based on feedback and emotional data.

[0820] "Emotional analysis technology" is a technology used to analyze a user's emotional state.

[0821] "Information" refers to various data and suggestions related to the plan presented to the user.

[0822] A "reservation method" refers to a device or method that allows a user to make a reservation based on a confirmed plan.

[0823] The server provides a means of communication for users to input conditions, and users access the system using their own devices. The conditions entered by the user are sent to the server via the communication means. The server has a computing means to analyze these conditions, and this computing means utilizes a generative AI model. The natural language processing technology used here is the foundational technology for efficiently analyzing the input conditions and generating the optimal plan that meets the user's needs.

[0824] The generated plan is presented to the user's device via a display device. The user can review this plan and provide feedback as needed. The server dynamically adjusts the plan based on the user's feedback and sentiment data collected using sentiment analysis technology, and then presents the newly optimized plan to the user again.

[0825] For example, when a user enters a department store and observes products through smart glasses, if an emotion indicating "excitement" is detected, the server can present the user with the latest product information and coupons that can be used immediately. Furthermore, by using an emotion engine, it is possible to provide personalized information tailored to the user's mood.

[0826] Examples of prompt statements include the following:

[0827] Current user sentiment: Happy

[0828] Store conditions: Many sale items, famous brands on display.

[0829] Recommended actions: Focus on browsing sale items + take advantage of brand product coupons.

[0830] This enables the generation of dynamic plans that are tailored to the user's emotions and significantly improves the user experience.

[0831] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0832] Step 1:

[0833] Users enter travel details using their device and send them to the server. This information includes destination, budget, and desired activities, which are then transmitted to the server via communication channels.

[0834] Step 2:

[0835] The server analyzes the received conditions using natural language processing technology. Here, the conditions are text-based, and specific information such as destination and budget is extracted. The extracted information is then sent to the computing system.

[0836] Step 3:

[0837] The server uses computational means to leverage a generative AI model and generate the optimal plan based on the analyzed information. In this step, data is input into the model, and the travel plan best suited to the user is output. The results are recorded and used by the display means.

[0838] Step 4:

[0839] The server sends the generated plan to the terminal and presents it to the user. The user can review this plan and request adjustments to suit their needs by providing feedback.

[0840] Step 5:

[0841] The server collects emotional data using sentiment analysis technology, along with user feedback. This data, along with the feedback, is input into adjustment mechanisms and used to modify the plan.

[0842] Step 6:

[0843] The server uses adjustment mechanisms to optimize the plan based on feedback and sentiment data, generating a new plan. This dynamically modifies the plan, which is then presented to the user again.

[0844] Step 7:

[0845] Once the user finalizes their plan, the server automatically uses the reservation method to perform the necessary reservation procedures through the partnered reservation system. The completed reservation information is sent to the terminal and notified to the user.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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."

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0867] The following is further disclosed regarding the embodiments described above.

[0868] (Claim 1)

[0869] A means of communication for the user to enter travel conditions,

[0870] A computational means that uses a model to analyze input conditions and generate a travel plan,

[0871] A display means that presents the generated travel plan to the user and receives feedback from the user,

[0872] A means of adjusting the travel plan based on feedback and presenting it again,

[0873] A booking method in which users make reservations based on their confirmed travel plans,

[0874] A system that includes this.

[0875] (Claim 2)

[0876] The system according to claim 1, comprising an analysis means for analyzing user input using natural language processing technology.

[0877] (Claim 3)

[0878] The system according to claim 1, comprising a reservation automation means that automatically performs reservation procedures based on the generated travel plan via a partner reservation system.

[0879] "Example 1"

[0880] (Claim 1)

[0881] A means of transmitting information for users to input travel conditions,

[0882] An information processing means that analyzes input conditions using natural language processing technology and generates a travel plan using an AI model,

[0883] An information display means that presents the generated travel plan to the user and receives feedback from the user,

[0884] Information adjustments that readjust and re-present travel plans based on feedback,

[0885] A system that includes an information processing mechanism that automatically performs booking procedures based on a travel plan confirmed by the user.

[0886] (Claim 2)

[0887] The system according to claim 1, comprising information analysis means for analyzing user input using natural language processing technology.

[0888] (Claim 3)

[0889] The system according to claim 1, further comprising a reservation automation means for automatically processing reservation procedures based on generated travel plans via a linked reservation system.

[0890] "Application Example 1"

[0891] (Claim 1)

[0892] A means of communication for the user to enter travel conditions,

[0893] A computational means that uses a model to analyze input conditions and generate a travel plan,

[0894] A display means that presents the generated travel plan to the user and receives feedback from the user,

[0895] A means of adjusting the travel plan based on feedback and presenting it again,

[0896] A booking method in which users make reservations based on their confirmed travel plans,

[0897] A location-based guidance system that acquires the user's location information and displays local guidance information,

[0898] A system that includes this.

[0899] (Claim 2)

[0900] The system according to claim 1, comprising an analysis means for analyzing user input using natural language processing technology.

[0901] (Claim 3)

[0902] The system according to claim 1, comprising a reservation automation means that automatically performs reservation procedures based on the generated travel plan via a partner reservation system.

[0903] "Example 2 of combining an emotion engine"

[0904] (Claim 1)

[0905] A means of communication that allows users to input travel conditions and collects data including related intentions,

[0906] A computational means that uses a model that analyzes input conditions using natural language processing technology, evaluates the user's emotional state using an emotion engine, and generates a travel plan based on that data,

[0907] A display means that presents a generated travel plan to the user, detects changes in the user's emotions, and receives feedback,

[0908] A means of adjusting the travel plan based on feedback and the user's emotional state, and re-presenting the generated AI model as needed,

[0909] A booking method that automatically processes reservations through a partnered booking system based on the travel plan confirmed by the user,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, comprising analysis means for analyzing user input using natural language processing technology and evaluating emotional data using an emotion engine.

[0913] (Claim 3)

[0914] The system according to claim 1, comprising a means for automating reservations that generates travel plans that take emotional data into consideration using a generative AI model, and automatically performs reservation procedures based on those plans through a partnered reservation system.

[0915] "Application example 2 when combining with an emotional engine"

[0916] (Claim 1)

[0917] A means of communication for the user to input conditions,

[0918] A computational means that uses a model to analyze the input conditions and generate a plan,

[0919] A display means for presenting the generated plan to the user and receiving feedback from the user,

[0920] A means of adjusting and re-presenting the plan based on feedback and emotional data,

[0921] A means of analyzing a user's emotions using emotion analysis technology and generating information corresponding to those emotions,

[0922] A reservation method in which the user makes a reservation based on a confirmed plan,

[0923] A system that includes this.

[0924] (Claim 2)

[0925] The system according to claim 1, comprising an analysis means for analyzing user input using natural language processing technology.

[0926] (Claim 3)

[0927] The system according to claim 1, comprising a reservation automation means that automatically performs reservation procedures based on the generated plan via a partnered reservation system. [Explanation of Symbols]

[0928] 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 communication for the user to enter travel conditions, A computational means that uses a model to analyze input conditions and generate a travel plan, A display means that presents the generated travel plan to the user and receives feedback from the user, A means of adjusting the travel plan based on feedback and presenting it again, A booking method in which users make reservations based on their confirmed travel plans, A system that includes this.

2. The system according to claim 1, comprising an analysis means for analyzing user input using natural language processing technology.

3. The system according to claim 1, comprising a reservation automation means that automatically performs reservation procedures based on the generated travel plan via a partner reservation system.

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