System

Abstract

A system is provided.SOLUTION: A system comprising: means for providing a user interface for a user to enter travel preferences; means for analyzing the entered data and extracting traveler preferences; means for generating an optimal travel plan based on the extracted preferences; means for presenting the generated travel plan to the user; and means for modifying and regenerating the travel plan based on user feedback.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Travel plans must be customized to meet individual needs, requiring a great deal of time and effort from users. Language barriers and a lack of local information can be significant challenges, especially when traveling abroad or to unfamiliar destinations, making it difficult for many users to enjoy their trip. The purpose of this invention is to eliminate the complexity of travel plans and the difficulty of obtaining information, thereby providing users with efficient and optimal travel plans. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by including the following components: a system that includes a means for providing a user interface through which a user inputs desired travel conditions; an analysis means for analyzing the input data and extracting conditions that match the traveler's preferences; a generation means for generating an optimal travel plan based on the extracted conditions; a means for presenting the generated travel plan to the user; and a means for modifying and regenerating the travel plan based on user feedback. The system is characterized in that databases of information on accommodations, transportation, restaurants, tourist spots, and events are used to generate the travel plan. The system also includes a means for providing a user interface that allows the user to modify and resubmit the conditions if the user is not satisfied with the presented travel plan. This allows the user to obtain an efficient and optimal travel plan, thereby making their trip even more enjoyable.

[0006] A "user interface" is a means of providing a screen or input form for users to input desired conditions into a system.

[0007] The "analysis means" is a part of the system that has the function of analyzing the data entered by the user and extracting conditions that match the traveler's preferences.

[0008] The "generation means" is a system function that automatically generates an optimal travel plan based on the conditions extracted by the analysis means.

[0009] The "presentation means" is a system function that displays the generated travel plan to the user.

[0010] "Modification" refers to the system's ability to modify and regenerate travel plans based on user feedback.

[0011] "Database" means a digital storage system for storing and managing related information such as accommodation, transportation, restaurants, tourist attractions, and event information. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0013] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0014] First, the terms used in the following description will be explained.

[0015] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0016] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0017] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0018] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0020] [First embodiment]

[0021] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0022] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0025] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0028] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0029] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0032] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0033] MODE FOR CARRYING OUT THE INVENTION

[0034] The system of the present invention provides comprehensive support for efficient travel planning, and specific embodiments thereof will be described below.

[0035] Basic system configuration

[0036] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[0037] 1. User Interface

[0038] The device provides a screen and input form for users to enter their travel preferences, including interfaces for inputting items such as departure point, budget, dates, events they would like to attend, and language restrictions.

[0039] 2. Analysis method

[0040] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[0041] 3. Generation means

[0042] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[0043] 4. Presentation means

[0044] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[0045] 5. Corrective measures

[0046] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0047] Program processing overview

[0048] The system operates as follows.

[0049] 1. Enter conditions via terminal

[0050] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[0051] 2. Data Transmission

[0052] The input data is transmitted from the terminal to the server.

[0053] 3. Data Analysis

[0054] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0055] 4. Travel plan generation

[0056] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0057] Transportation: Plane to New Chitose Airport

[0058] Accommodation: Budget-friendly hotels in Sapporo

[0059] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0060] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0061] Event: Fireworks display held on the second night of the trip

[0062] 5. Plan presentation

[0063] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[0064] 6. Feedback and Regeneration

[0065] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0066] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] The user inputs the desired travel conditions (place of departure, budget, dates, events to attend, language restrictions, etc.) on the terminal.

[0070] Step 2:

[0071] The terminal temporarily stores the travel conditions entered by the user and waits for the user to click the "Submit" button.

[0072] Step 3:

[0073] The user clicks the "Submit" button.

[0074] Step 4:

[0075] The terminal packages the entered travel condition data in a format such as JSON and sends it to the server.

[0076] Step 5:

[0077] The server begins analyzing the received data. Specifically, it uses natural language processing technology to interpret the data entered by the user and stores the data in variables.

[0078] Step 6:

[0079] The server extracts the user's desired conditions based on the analysis results and retrieves related information from the database based on these, including data on accommodation, transportation, restaurants, tourist spots, and event information necessary for generating a travel plan.

[0080] Step 7:

[0081] The server then uses the generative AI model to automatically generate an optimal travel plan based on the extracted preferences, including details such as transportation, accommodation, dining options, tourist spots, and event participation.

[0082] Step 8:

[0083] The server transmits the generated travel plan to the terminal.

[0084] Step 9:

[0085] The device displays the received itinerary on the user's screen, including the ability to clearly display each element of the itinerary (transportation, accommodation, meals, sightseeing spots, and events) in list and timeline format.

[0086] Step 10:

[0087] The user can review the proposed itinerary and make any necessary modifications or final approval, for example, if they want to change certain elements.

[0088] Step 11:

[0089] When the user modifies the plan, the modified conditions are retransmitted from the terminal to the server.

[0090] Step 12:

[0091] The server re-analyzes the modified conditions from the user and regenerates a new travel plan.

[0092] Step 13:

[0093] The server transmits the regenerated itinerary back to the terminal.

[0094] Step 14:

[0095] The terminal presents the regenerated travel plan to the user again, who then reviews it and makes a final confirmation.

[0096] Step 15:

[0097] When the user has finally decided on a plan that satisfies him, he clicks on the "Confirm" button.

[0098] Step 16:

[0099] The terminal transmits final plan confirmation information to the server.

[0100] Step 17:

[0101] The server stores the confirmed travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[0102] This is the specific flow of the process, which allows users to efficiently and stress-free obtain the optimal travel plan.

[0103] Example 1

[0104] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0105] Conventional travel planning systems require users to manually gather information on accommodations, transportation options, tourist attractions, and other topics by browsing multiple websites, which is a cumbersome process. It is also difficult to quickly and efficiently generate an optimal travel plan that reflects the user's requirements and preferences. Furthermore, when a user wants to provide feedback on a presented travel plan and change the requirements, it is difficult to instantly generate a new plan that reflects that feedback.

[0106] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0107] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, a generation means using a generative AI model to generate an optimal travel plan based on the extracted conditions, a means for presenting the generated travel plan to the user, and a means for modifying and regenerating the travel plan based on feedback from the user. This allows users to efficiently and easily create travel plans within a single system and to instantly adjust the plans based on the feedback.

[0108] "User" means any individual or entity that uses the System to plan a trip.

[0109] "Travel preferences" refer to the requirements and wishes that travelers want to include in their travel plans, such as departure point, budget, dates, events they would like to attend, and language preference.

[0110] "User interface" refers to the means by which users can interact with a system, such as a screen or input form for entering travel preferences.

[0111] "Entered Data" means travel preference information provided by a User to the System through the User Interface.

[0112] "Analysis means" refers to a function or system that analyzes input data and extracts conditions that match the traveler's preferences.

[0113] The "generation means" refers to a function or system that generates an optimal travel plan based on the extracted conditions.

[0114] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to automatically generate optimal travel plans.

[0115] "Presentation means" refers to a function or system that visually or electronically presents the generated itinerary to the user.

[0116] "Feedback" refers to information that a user inputs into the system, such as opinions or requests for modifications to a presented travel plan.

[0117] "Modification" refers to a function or system that modifies and regenerates a travel plan based on user feedback.

[0118] "Accommodation" refers to a place of lodging such as a hotel, inn, or guesthouse where travelers can stay.

[0119] "Transportation" refers to the means of transportation used by travelers to travel to their destinations, such as airplanes, trains, buses, etc.

[0120] "Eating and drinking establishments" refer to places such as restaurants, cafes, and izakayas where travelers can eat.

[0121] A "tourist attraction" is a place for tourists to visit and see, such as a park, temple, or museum.

[0122] "Event information" refers to information about various events that can be participated in during a trip, such as concerts, festivals, and fireworks displays.

[0123] MODE FOR CARRYING OUT THE INVENTION

[0124] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system will be described below.

[0125] Basic system configuration

[0126] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[0127] 1. User Interface

[0128] The device provides a screen and input form for users to enter their desired travel conditions. Specifically, it includes an interface for entering items such as departure point, budget, dates, events they would like to attend, and language restrictions. The device can be a personal computer, smartphone, tablet, or other device.

[0129] 2. Analysis method

[0130] The server receives the input data sent from the device and analyzes it using natural language processing technology. This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables. The software used includes a Python natural language processing library and API.

[0131] 3. Generation means

[0132] The server retrieves the necessary information from a database based on the analyzed data. This includes information on accommodations, transportation options, restaurants, tourist attractions, and event information. It then uses a generative AI model to automatically generate an optimal travel plan. The system uses high-performance servers as hardware and software such as TensorFlow and PyTorch.

[0133] 4. Presentation means

[0134] The server sends the generated travel plan to the terminal, which then displays the detailed plan to the user. The user can then check the specific schedule of the trip based on this. The display interface can be a web browser or a dedicated application.

[0135] 5. Corrective measures

[0136] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0137] Program processing overview

[0138] The system operates as follows.

[0139] 1. Enter conditions via terminal

[0140] The user inputs the desired conditions for the trip into an input form on the terminal. For example, the user might input a prompt such as, "The departure point is Tokyo, the budget is up to 100,000 yen, I would like to travel for three days, I would like to attend a fireworks festival, and I would like to go somewhere where I can speak Japanese."

[0141] 2. Data Transmission

[0142] The input data is transmitted from the terminal to the server.

[0143] 3. Data Analysis

[0144] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0145] 4. Travel plan generation

[0146] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0147] Transportation: Fly from Tokyo to New Chitose Airport

[0148] Accommodation: Budget-friendly hotels in Sapporo

[0149] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0150] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0151] Event: Fireworks display held on the second night of the trip

[0152] 5. Plan presentation

[0153] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[0154] 6. Feedback and Regeneration

[0155] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0156] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[0157] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0158] Step 1:

[0159] The user inputs desired travel conditions. Specifically, they input specific conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Place where Japanese is spoken" into the input form on the device. This input becomes the "prompt sentence." The input data is temporarily stored in the device's memory.

[0160] Step 2:

[0161] The device sends the entered travel conditions to the server. When sending the data, the input data is converted to JSON format. The input at this time is the user's desired conditions, and the output is JSON format data sent to the server.

[0162] Step 3:

[0163] The server receives JSON format data from the terminal. The received data is stored in the server's memory. The input is JSON data, and the output indicates that the data was received successfully.

[0164] Step 4:

[0165] The server analyzes the received data using natural language processing technology. Specifically, it uses a Python natural language processing library to convert JSON-formatted data into variables. This analysis extracts conditions such as "departure point," "budget," "schedule," "event," and "language." In this step, the input data is the received JSON data, and the output is the analyzed condition data.

[0166] Step 5:

[0167] The server retrieves the necessary information from a database based on the analyzed data. The database in this case includes information on accommodations, transportation, restaurants, tourist attractions, and events. The specific operation of retrieving data is performed using SQL queries. The input is the analyzed condition data, and the output is the retrieved database information.

[0168] Step 6:

[0169] The server uses a generative AI model based on the acquired information and analysis results to generate an optimal travel plan. The AI ​​model (built with TensorFlow and PyTorch) automatically generates an optimal plan that meets the user's requirements. For example, it includes accommodation, transportation, tourist spots, and event participation schedules. The input is information acquired from the database, and the output is the generated travel plan.

[0170] Step 7:

[0171] The server converts the generated travel plan into JSON format and sends it to the terminal. The input here is the generated travel plan, and the output is JSON format data sent to the terminal.

[0172] Step 8:

[0173] The terminal displays the received itinerary to the user. Specifically, it displays a detailed itinerary using a GUI, allowing the user to check each element. In this step, the input data is the JSON-formatted itinerary received from the server, and the output is a visually displayed itinerary for the user.

[0174] Step 9:

[0175] The user inputs feedback about the presented travel plan into the terminal. Specifically, the user inputs a request for modification, such as "I would like the accommodation to be more luxurious." The input is the user's feedback, and the output is the feedback data stored on the terminal.

[0176] Step 10:

[0177] The terminal sends feedback data to the server. The feedback content is converted to JSON format and sent to the server. The input of this step is feedback data, and the output is JSON-formatted feedback data sent to the server.

[0178] Step 11:

[0179] The server re-analyzes the received feedback data and re-generates the itinerary based on the modification requests, again using a generative AI model. The input for the re-analysis and re-generation is the feedback data, and the output is the re-generated itinerary.

[0180] Step 12:

[0181] The server sends the regenerated itinerary to the terminal, and the terminal displays the regenerated itinerary to the user. The input of this step is the regenerated itinerary, and the output is the itinerary that is resent and displayed to the user.

[0182] This allows users to plan their trip efficiently and stress-free.

[0183] (Application example 1)

[0184] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0185] Conventional travel planning systems require users to manually create travel plans, which takes a lot of time and effort, making the planning process itself cumbersome. Furthermore, it is difficult to automatically generate an optimal plan that meets the user's desired conditions, and it is not easy to regenerate the plan to reflect feedback. These issues also make it difficult to keep the information up-to-date and optimal.

[0186] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0187] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for extracting conditions using natural language processing technology to analyze the input data, and a generation means for generating an optimal travel plan using a generative AI model. This makes it possible to automatically and efficiently generate an optimal travel plan based on the desired conditions input by the user, and to regenerate it based on user feedback.

[0188] A "user interface" is an operating means such as a screen or input form that allows a user to input or give instructions to a system.

[0189] "Natural language processing technology" is a technology that allows a server to understand and analyze the language that people use on a daily basis.

[0190] The "analysis means for extracting conditions" is a means for analyzing input data using natural language processing technology and extracting predetermined conditions.

[0191] A "generative AI model" is an artificial intelligence model that automatically generates optimal travel plans based on given conditions.

[0192] An "optimal travel plan" is a travel schedule and proposal that takes into maximum consideration the user's desired conditions.

[0193] The "generation means" is a means for creating a travel plan based on the extracted conditions using a generative AI model.

[0194] "Feedback" refers to evaluations and requests for modifications to the generated travel plan provided by the user.

[0195] "Regeneration" refers to recreating a travel plan based on feedback.

[0196] MODE FOR CARRYING OUT THE INVENTION

[0197] Basic system configuration

[0198] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system are described below.

[0199] Hardware and software used

[0200] Hardware: Smartphones, servers

[0201] Software: smartphone apps, server-side programs (e.g., Python, Node.js), databases (e.g., MySQL, PostgreSQL), natural language processing libraries (e.g., spaCy, NLTK), generative AI models (e.g., GPT-3)

[0202] User Interface

[0203] The user interface provides a screen and input form for users to enter their desired travel conditions. Specifically, it is designed to allow users to easily enter items such as "place of departure," "budget," "date," "events they want to attend," and "language restrictions" on their smartphones.

[0204] Data transmission and analysis

[0205] When a user enters travel conditions, the data is sent from the smartphone to a server. The server then analyzes the received data using natural language processing technology to extract conditions. This analysis is performed using natural language processing libraries such as spaCy and NLTK. For example, related event information can be extracted from the condition "events I want to attend."

[0206] Generate a travel plan

[0207] Based on the analysis results, the server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from a database. Based on the retrieved data, the server automatically generates an optimal travel plan using a generative AI model (such as GPT-3). This generation method provides a travel plan that best suits the user's requirements.

[0208] Examples of prompt statements

[0209] "Departure point: Tokyo

[0210] Budget: 100,000 yen

[0211] Duration: 3 days

[0212] Events I'd like to attend: Fireworks displays

[0213] Language restrictions: Avoid places where Japanese is not available

[0214] Generate the best itinerary for you.

[0215] Plan presentation and feedback

[0216] The generated travel plan is sent from the server to a smartphone app and presented to the user, who can then review the plan, which includes a detailed schedule and suggestions.

[0217] If a user is not satisfied with the travel plan presented to them, they can modify the conditions and resubmit them from their smartphone to the server. The server then analyzes the data and generates a new plan based on the modified data received. By repeating this process, the optimal travel plan is provided to the user.

[0218] Specific examples

[0219] As an example, consider the case where a user inputs the following conditions:

[0220] "Departure point: Tokyo

[0221] Budget: 100,000 yen

[0222] Duration: 3 days

[0223] Events I'd like to attend: Fireworks displays

[0224] Language restrictions: Avoid places where Japanese is not available

[0225] The server analyzes this information and generates a travel plan that includes, for example, a flight to New Chitose Airport, a hotel in Sapporo, sightseeing at Odori Park and Asahiyama Zoo, and information about the fireworks display.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] The user uses the device to input their travel preferences, including their departure point, budget, dates, events they want to attend, language restrictions, etc. The device then collects the input data and prepares it.

[0229] Input: Travel conditions data entered by the user (origin, budget, schedule, events, language restrictions)

[0230] Output: Collected travel condition data

[0231] Step 2:

[0232] The terminal transmits the collected travel condition data to the server, which stores the received data and prepares it for analysis.

[0233] Input: Collected travel condition data

[0234] Output: Travel conditions data sent to the server

[0235] Step 3:

[0236] The server analyzes the received data using natural language processing technology, extracting each condition and storing it in the appropriate variable.

[0237] Input: Travel conditions data sent to the server

[0238] Output: Parsed condition variable data (departure point, budget, schedule, events, language constraints)

[0239] Specific operation: Using spaCy or NLTK, natural language processing techniques are used to extract conditions such as event information from input data.

[0240] Step 4:

[0241] The server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from the database based on the analysis results, stores the retrieved data, and prepares it for use in the next step.

[0242] Input: Variable data for the parsed condition

[0243] Output: Travel-related information obtained from the database (accommodation, transportation, restaurants, tourist spots, event information)

[0244] Specific operation: The server uses MySQL or PostgreSQL to query the database to obtain the relevant information.

[0245] Step 5:

[0246] The server generates an optimal travel plan using a generative AI model (such as GPT-3) based on the acquired data, stores the generated plan, and prepares it for presentation to the user.

[0247] Input: Acquired travel-related information

[0248] Output: Optimal travel plan

[0249] Specific operation: Input conditions into the generative AI model in the form of a prompt sentence to generate the optimal plan. For example,

[0250] "Departure point: Tokyo

[0251] Budget: 100,000 yen

[0252] Duration: 3 days

[0253] Events I'd like to attend: Fireworks displays

[0254] Language restrictions: Avoid places where Japanese is not available

[0255] Generate the best itinerary for you.

[0256] Step 6:

[0257] The server sends the generated travel plan to the terminal, which then displays the received plan to the user.

[0258] Input: Generated itinerary

[0259] Output: Trip plan sent to the device

[0260] Specific operation: The server sends the generated travel plan to the terminal in JSON format, etc., and the terminal parses it and displays it on the user interface.

[0261] Step 7:

[0262] If the user is not satisfied with the presented travel plan, he / she can modify the conditions and resend them from the terminal to the server. The server will then analyze the data and generate a new plan based on the modified data received.

[0263] Input: User feedback and revised conditions

[0264] Output: Regenerated itinerary

[0265] Specific operation: The device sends the re-entered condition data to the server, which analyzes it and regenerates a new plan using the AI ​​model.

[0266] This series of steps allows users to plan their trip efficiently and optimally.

[0267] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0268] MODE FOR CARRYING OUT THE INVENTION

[0269] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. Specific embodiments of the system will be described below.

[0270] Basic system configuration

[0271] The system includes a user interface, an analysis means, a generation means, a presentation means, a modification means, and an emotion engine.

[0272] 1. User Interface

[0273] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[0274] 2. Analysis method

[0275] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[0276] 3. Generation means

[0277] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[0278] 4. Presentation means

[0279] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[0280] 5. Corrective measures

[0281] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0282] 6. Emotion Engine

[0283] The device will have sensors and software to recognize the user's emotional state, using facial recognition and voice analysis technology, as well as analyzing input data and user operation patterns.

[0284] The server analyzes the emotional data sent from the emotion engine and evaluates the user's positive or negative emotions. Based on the user's emotional state, the server adjusts the content and method of presenting the plan to the user.

[0285] Program processing overview

[0286] The system operates as follows.

[0287] 1. Enter conditions via terminal

[0288] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[0289] 2. Data Transmission

[0290] The input data is transmitted from the terminal to the server.

[0291] 3. Data Analysis

[0292] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0293] 4. Travel plan generation

[0294] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0295] Transportation: Plane to New Chitose Airport

[0296] Accommodation: Budget-friendly hotels in Sapporo

[0297] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0298] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0299] Event: Fireworks display held on the second night of the trip

[0300] 5. Plan presentation

[0301] The server sends the generated plan to the terminal, and the terminal displays the detailed plan to the user, who can then check the detailed schedule and each element.

[0302] 6. Feedback and Regeneration

[0303] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0304] 7. Emotional Recognition and Regulation

[0305] The emotion engine recognizes the user's emotional state from their face, voice, and operation patterns, extracting positive and negative emotions.

[0306] The server evaluates the user's emotional state based on data from the emotion engine and adjusts the itinerary and its presentation accordingly, for example, highlighting the itinerary if the user is expressing positive emotions, or quickly presenting alternatives if the user is expressing negative emotions.

[0307] The above embodiments allow users to plan their trips efficiently and stress-free. Furthermore, by recognizing the user's emotional state and optimizing the plan, a more personalized user experience is realized. The entire system is designed to be user-friendly and can quickly and accurately respond to the user's needs and emotions.

[0308] The processing flow will be explained below.

[0309] Step 1:

[0310] The user inputs desired travel conditions (place of departure, budget, schedule, events to attend, language restrictions, etc.) on the terminal. For example, the user inputs the departure place "Tokyo," the budget "100,000 yen," the schedule "3 days," the event to attend "fireworks display," and the language restriction "avoid places where Japanese cannot be used."

[0311] Step 2:

[0312] The terminal temporarily stores the entered data and waits for the user to click the "Submit" button.

[0313] Step 3:

[0314] The user clicks the "Submit" button.

[0315] Step 4:

[0316] The terminal packages the input data in JSON format or similar and sends it to the server.

[0317] Step 5:

[0318] The server analyzes the received data, uses natural language processing technology to interpret the user's desired conditions, and stores the data in appropriate variables.

[0319] Step 6:

[0320] Based on the analysis results, the server retrieves relevant information from a database, including information on accommodation, transportation, restaurants, tourist attractions, and events.

[0321] Step 7:

[0322] The server uses a generative AI model to generate an optimal travel plan based on the acquired information, including details of flights to New Chitose Airport, hotels in Sapporo, dining options, tourist attractions, and events.

[0323] Step 8:

[0324] The server transmits the generated travel plan to the terminal.

[0325] Step 9:

[0326] The device displays the received travel plan on the user's screen, clearly showing each element in a list or timeline format.

[0327] Step 10:

[0328] The emotion engine evaluates the user's emotional state when a plan is presented, using facial recognition technology, voice analysis, and analysis of operation patterns to assess the user's emotions in real time.

[0329] Step 11:

[0330] The emotion engine sends the acquired emotion data to the server, such as whether the user is smiling or frowning when looking at the plan.

[0331] Step 12:

[0332] The server adjusts the presentation and content of the plan in real time based on the emotional data, for example, highlighting the plan if it detects positive emotions, or presenting alternatives if it detects negative emotions.

[0333] Step 13:

[0334] The user reviews the proposed itinerary and provides any necessary corrections or feedback, for example, if they want to change their accommodation.

[0335] Step 14:

[0336] The user enters the desired modifications into the terminal and resubmits.

[0337] Step 15:

[0338] The terminal transmits the modified data to the server.

[0339] Step 16:

[0340] The server then analyzes the retransmitted data again and generates a new itinerary based on the revised conditions, taking into account the evaluation results of the emotion engine.

[0341] Step 17:

[0342] The server transmits the regenerated itinerary back to the terminal.

[0343] Step 18:

[0344] The device will then present the regenerated plan to the user, who will then confirm it again.

[0345] Step 19:

[0346] The user makes a final confirmation and clicks the "Confirm" button to confirm the final plan.

[0347] Step 20:

[0348] The terminal transmits final plan confirmation information to the server.

[0349] Step 21:

[0350] The server stores the finalized travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[0351] These are the specific processing steps of the system combined with the emotion engine, which allows users to obtain efficient and individually optimized travel plans, and adjusts the plans according to their emotional state, improving the user experience.

[0352] Example 2

[0353] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0354] Current travel planning support systems can generate plans that reflect travelers' desired conditions, but they lack the ability to optimize plans based on user emotions or adjust them to meet individual needs. This can lead to lower user satisfaction and make travel planning stressful. Furthermore, the lack of a mechanism for effectively incorporating user feedback creates the problem of cumbersome, repeated plan revisions. The objective of the present invention is to solve these problems and improve the efficiency of travel planning and user satisfaction.

[0355] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0356] In this invention, the server includes means for providing a user interface through which a user inputs desired travel conditions, analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, generation means for generating an optimal travel plan based on the extracted conditions, means for presenting the generated travel plan to the user, means including an emotion engine for recognizing the user's emotions, means for adjusting the travel plan and presentation method based on emotion data transmitted from the emotion engine, and means for correcting and regenerating the travel plan based on feedback from the user. This makes it possible to optimize the travel plan based on the user's desired conditions as well as their emotional state, and provide a highly satisfying travel plan.

[0357] "User Interface" means the means by which a user interacts directly with the system and inputs travel preferences.

[0358] "Analysis means" refers to a means that has the function of analyzing input data and extracting conditions that match the traveler's preferences.

[0359] "Generation means" refers to a means having the function of generating an optimal travel plan based on the extracted conditions.

[0360] "Presentation means" refers to a means that has the function of displaying and sharing the generated travel plan to the user.

[0361] An "emotion engine" refers to a system that includes sensors and analytical software to recognize user emotions and processes that data.

[0362] "Feedback" refers to the user's evaluation or opinion on the presented travel plan, and includes information that the system uses to revise the plan.

[0363] "Regeneration means" refers to a means that has the function of revising and generating a new travel plan based on user feedback and revision conditions.

[0364] "Database" refers to a system that stores and manages information necessary to generate travel plans, such as information on accommodations, transportation, restaurants, tourist attractions, and events.

[0365] MODE FOR CARRYING OUT THE INVENTION

[0366] Basic system configuration

[0367] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. To provide a superior user experience, the system is configured as follows:

[0368] 1. User Interface

[0369] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[0370] 2. Analysis method

[0371] The server receives the input data sent from the device and analyzes it using natural language processing technology (NLTK or similar technology). This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables.

[0372] 3. Generation means

[0373] The server generates a travel plan based on the analyzed data. It retrieves information on accommodation, transportation, restaurants, tourist attractions, and events from an internal database. It uses a generative AI model (e.g., GPT-3) to generate the optimal travel plan. Examples of prompts for the generative AI model include:

[0374] "Create a travel plan for the user. The conditions are: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend fireworks festivals, avoid places where Japanese is not spoken."

[0375] 4. Presentation means

[0376] The server sends the generated travel plan to the device, which then displays the detailed plan to the user, allowing the user to check the specific itinerary, including information on flights to New Chitose Airport, accommodations in Sapporo, tourist spots such as Odori Park and Sapporo TV Tower, and fireworks displays.

[0377] 5. Corrective measures

[0378] If the user is not satisfied with the proposed itinerary, he or she can modify the conditions and resubmit them from the terminal to the server, which will then analyze the modified conditions again and generate a new itinerary.

[0379] 6. Emotion Engine

[0380] The device is equipped with sensors and software to recognize the user's emotions, specifically using facial recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text API) to determine the user's emotional state.

[0381] The server analyzes the emotion data sent from the emotion engine and evaluates the user's emotional state. Based on the evaluation results, the server adjusts the travel plan and how it is presented. For example, if the user is expressing positive emotions, the server will emphasize the plan and present it, and if the user is expressing dissatisfaction, the server will quickly present alternative plans.

[0382] Specific examples

[0383] Let's say a user enters the following information into the input form on their device: "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken."

[0384] 1. Data transmission and analysis

[0385] This data is sent from the terminal to a server, where it is analyzed using natural language processing technology.

[0386] 2. Travel plan generation

[0387] Based on the analysis results, the server retrieves information from the database and generates a travel plan using a generative AI model. For example, the following results may be generated: a flight to New Chitose Airport, accommodation in Sapporo, Odori Park, Sapporo TV Tower, and a fireworks display to be held on the night of the second day of the trip.

[0388] 3. Plan Presentation and Emotion Recognition

[0389] The generated plan is sent to the device and displayed to the user. At the same time, the device's sensors recognize the user's emotions and transmit them to the server.

[0390] The server analyzes the emotion data to assess the user's positive or negative reaction, and adjusts the way the plan is presented depending on the emotion, offering alternatives if necessary.

[0391] In this way, the system provides optimal travel plans that take into account the user's desired conditions and emotional state, enabling users to plan their trips efficiently and stress-free.

[0392] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0393] Specific explanation of processing steps

[0394] Step 1:

[0395] The user enters desired travel conditions into an input form on the terminal, such as the departure point, budget, dates, events to attend, and language restrictions.

[0396] Input: User's desired conditions (e.g., departure point: Tokyo, budget: 100,000 yen, dates: 3 days, event to attend: fireworks festival, language: avoid places where Japanese is not spoken).

[0397] Output: Sending input data from the terminal to the server.

[0398] Step 2:

[0399] The device sends the user's input data to the server, using the secure HTTPS protocol.

[0400] Input: The user's desired conditions entered into the terminal.

[0401] Output: The user's preference data sent to the server.

[0402] Step 3:

[0403] The server receives the data sent from the device and analyzes it using natural language processing technology (e.g., Python's NLTK).

[0404] Data processing: The received data is processed as text and conditions are extracted.

[0405] Input: User preference data received by the server.

[0406] Output: Parsed condition data (e.g., departure location='Tokyo', budget=100,000 yen, date=3 days, event='fireworks festival', language constraint='Japanese only').

[0407] Step 4:

[0408] The server retrieves travel-related information from an internal database based on the extracted condition data, including information on accommodations, transportation, restaurants, tourist attractions, and events.

[0409] Data processing: Performing database queries to retrieve relevant information.

[0410] Input: Parsed condition data.

[0411] Output: Travel-related information retrieved from the database.

[0412] Step 5:

[0413] The server uses a generative AI model (e.g., GPT-3) to generate an optimal travel plan, using a prompt.

[0414] Generative AI model: An example of a prompt sentence is, "Please create a travel plan for the user. The conditions are as follows: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend the fireworks festival, avoid places where Japanese is not spoken."

[0415] Data calculation: Input the prompt sentence and condition data into the generative AI model to generate a plan.

[0416] Input: Travel-related information retrieved from the database and a prompt statement.

[0417] Output: Generated itinerary (e.g., flight to New Chitose Airport, accommodation in Sapporo city, Odori Park, Sapporo TV Tower, and fireworks festival on the second night of the trip).

[0418] Step 6:

[0419] The server transmits the generated travel plan to the terminal, which displays the detailed plan to the user.

[0420] Input: The generated itinerary.

[0421] Output: The itinerary presented to the user.

[0422] Step 7:

[0423] The user inputs feedback on the presented travel plan through the terminal. If the user is not satisfied, he / she can modify the conditions and resubmit the plan.

[0424] Input: User feedback and correction criteria.

[0425] Output: Corrected data resent from the terminal.

[0426] Step 8:

[0427] The server re-analyzes the retransmitted data and presents the regenerated itinerary to the user.

[0428] Input: Resubmitted corrected data.

[0429] Data processing and calculation: Regenerate plans using data analysis and AI models.

[0430] Output: The regenerated itinerary.

[0431] Step 9:

[0432] The device uses sensors and software (e.g., facial recognition technology and voice analysis technology) to recognize the user's emotions, determines their emotional state, and sends the data to a server.

[0433] Input: User operations, facial expressions, and voice data.

[0434] Output: Parsed emotion data.

[0435] Step 10:

[0436] The server analyzes the emotional data sent by the emotion engine and adjusts the travel plan and presentation accordingly: if the emotion is positive, the plan is emphasized, and if the emotion is negative, alternatives are presented.

[0437] Input: Parsed emotion data.

[0438] Data processing: Plan adjustment based on the results of the emotional state assessment.

[0439] Output: Adjusted travel plan or alternatives.

[0440] The above is the specific processing flow of this system.

[0441] (Application example 2)

[0442] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0443] Conventional food delivery systems have difficulty providing optimal food plans based on a user's emotional state. Furthermore, generating a plan that matches a user's preferences requires considering many factors, which makes the process complicated and burdensome for users. Therefore, there is a need for the development of a food delivery system that is easy for users to use and provides optimal plans based on their emotional state.

[0444] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for providing a user interface through which the user inputs desired conditions regarding food type, budget, and delivery time; an analysis means for analyzing the input data and extracting conditions that match the user's preferences; an emotion recognition means for recognizing the user's emotional state using facial recognition technology; a generation means for generating an optimal food plan based on the extracted conditions and emotional state; a means for presenting the generated food plan to the user; and a means for modifying and regenerating the food plan based on feedback from the user. This makes it possible to provide a fast and appropriate food delivery plan that also takes into account the user's emotional state.

[0445] A "user interface" is a means of providing a screen or input form for users to perform operations.

[0446] The "analysis means" is a function that analyzes the input data and extracts conditions that match the user's preferences.

[0447] "Emotion recognition means" is a technology for recognizing the emotional state of a user using face recognition technology.

[0448] The "generator" is a function that generates an optimal food plan based on the extracted conditions and emotional state.

[0449] "Presentation means" refers to a function that presents the generated food plan to the user.

[0450] A "modification tool" is a tool that has the ability to modify and regenerate a food plan based on user feedback.

[0451] A "food plan" is a selection of food and dining options generated based on a user's preferences and emotional state.

[0452] A "database" is an information storage system that stores information such as restaurant and event information and uses it as needed.

[0453] "Emotional state" refers to the user's emotional state, and is information detected using technologies such as facial recognition and voice analysis.

[0454] "Feedback" refers to the evaluation or opinion that a user gives regarding the information or plans provided.

[0455] A novel system for implementing this invention is designed to provide food delivery services to users. The system combines a user interface, an analysis means, an emotion recognition means, a generation means, a presentation means, and a modification means.

[0456] User Interface

[0457] The terminal provides an interface for users to input their desired conditions regarding food type, budget, and delivery time. Specifically, users can input their food delivery preferences through an input form displayed on the smartphone application screen.

[0458] Analysis means

[0459] The server receives the input data sent from the device and analyzes it using natural language processing technology. This allows it to understand the desired conditions entered by the user and store each condition, such as food type and budget, in the appropriate variables. The software used is Hugging Face Transformers, a natural language processing software.

[0460] emotion recognition means

[0461] The device uses a webcam or smartphone camera to recognize the user's emotions. It uses facial recognition technology to capture the user's face in real time and analyzes their emotional state using Hugging Face's emotion analysis model. This allows it to recognize the user's emotions as states such as "happy" or "unhappy."

[0462] generation means

[0463] The server generates an optimal meal plan based on the analyzed data and emotion recognition results. To do this, it references a database of restaurant and event information and uses a generative AI model to suggest the most suitable foods and restaurants for the user. The generative AI model receives prompts based on the user's desired conditions and emotional state, and customizes the suggestions accordingly.

[0464] Presentation means

[0465] The server sends the generated meal plan to the device, which displays it to the user, who can then check the proposed meal plan and detailed information about the selected restaurant through a smartphone application.

[0466] Correction means

[0467] The user can provide feedback on the presented meal plan. For example, they can input their opinion such as, "This restaurant doesn't suit my mood." Based on that feedback, the server analyzes the data again and regenerates a new meal plan that matches their conditions and emotional state.

[0468] Specific examples

[0469] For example, if a user inputs "My budget is under 2,000 yen and I want to eat pizza," and the facial image captured by the webcam is recognized as "happy," the server will consider the user's positive emotional state and suggest restaurants that offer the best pizza within their budget. Examples of prompt sentences are as follows:

[0470] Prompt statement:

[0471] A user enters "I want to eat pizza within 2,000 yen." Emotion analysis is performed on the facial image captured by the webcam, and the result is recognized as "happy." Based on this, what is the best food and restaurant for the user?

[0472] This system allows users to easily receive the optimal food delivery plan that takes their emotional state into consideration.

[0473] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0474] Step 1:

[0475] The terminal provides an interface for the user to input desired conditions regarding food type, budget, and delivery time. When the user inputs these conditions, the data is sent from the terminal to the server. The input here includes food type (e.g., pizza), budget (e.g., 2,000 yen), and delivery time (e.g., within 30 minutes). This input data is passed to the next processing step.

[0476] Step 2:

[0477] The server receives the input data sent from the terminal and analyzes the data using analytical means. Through this analysis, the user's desired conditions are understood and stored in the appropriate variables. For example, natural language processing is used to extract "food_type: pizza" from the input "pizza," and to obtain "budget: 2000" from "budget: 2,000 yen." The analysis results are passed to the next processing step.

[0478] Step 3:

[0479] To recognize the user's emotions, the device activates the webcam and captures a facial image. The captured facial image is analyzed by an emotion recognition means, and the user's emotional state is recognized as "happy" or "unhappy." For example, the facial image is analyzed using the Hugging Face emotion analysis model, and the result is "Emotional state: happy." This emotional state data is passed to the next processing step.

[0480] Step 4:

[0481] The server uses a generative means to generate an optimal meal plan based on the analysis results and the user's emotional state. The server sends the input desired conditions and emotional state as prompts to the generative AI model, which retrieves relevant restaurant and menu information from the database and proposes a meal plan that suits the user. For example, based on "food_type: pizza," "budget: 2000," and "emotional state: happy," the generative AI model recommends the optimal pizza restaurant and specific menu (e.g., Margherita pizza). This generated result is passed to the next processing step.

[0482] Step 5:

[0483] The server sends the generated food plan to the terminal through the presentation means, and the terminal displays the detailed plan to the user on the screen. The user can check the presented food plan (e.g., Margherita pizza, XX pizza restaurant), select and rate it. This displayed information is passed to the next processing step.

[0484] Step 6:

[0485] The user provides feedback on the presented food plan, and that feedback is sent from the device to the server. For example, if the user enters an opinion such as "I don't feel like going to this restaurant," that data is passed to the server. This feedback data is then passed to the next processing step.

[0486] Step 7:

[0487] The server analyzes the user's feedback data and uses the corrective measures to regenerate a new meal plan, taking into account the user's original preferences and emotional state. It then incorporates the previous feedback and uses the database and generative AI model again to generate new suggestions, e.g., re-recommend the next best pizza place and menu item based on the user's new feedback. This new meal plan then returns to step 5 and is displayed again for presentation to the user.

[0488] This specific process allows users to conveniently receive food delivery plans that reflect their emotional state in real time.

[0489] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0490] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0491] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0492] [Second embodiment]

[0493] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0494] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0495] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0496] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0497] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0498] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0499] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0500] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0501] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0502] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0503] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0504] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0505] MODE FOR CARRYING OUT THE INVENTION

[0506] The system of the present invention provides comprehensive support for efficient travel planning, and specific embodiments thereof will be described below.

[0507] Basic system configuration

[0508] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[0509] 1. User Interface

[0510] The device provides a screen and input form for users to enter their travel preferences, including interfaces for inputting items such as departure point, budget, dates, events they would like to attend, and language restrictions.

[0511] 2. Analysis method

[0512] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[0513] 3. Generation means

[0514] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[0515] 4. Presentation means

[0516] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[0517] 5. Corrective measures

[0518] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0519] Program processing overview

[0520] The system operates as follows.

[0521] 1. Enter conditions via terminal

[0522] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[0523] 2. Data Transmission

[0524] The input data is transmitted from the terminal to the server.

[0525] 3. Data Analysis

[0526] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0527] 4. Travel plan generation

[0528] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0529] Transportation: Plane to New Chitose Airport

[0530] Accommodation: Budget-friendly hotels in Sapporo

[0531] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0532] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0533] Event: Fireworks display held on the second night of the trip

[0534] 5. Plan presentation

[0535] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[0536] 6. Feedback and Regeneration

[0537] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0538] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[0539] The processing flow will be explained below.

[0540] Step 1:

[0541] The user inputs the desired travel conditions (place of departure, budget, dates, events to attend, language restrictions, etc.) on the terminal.

[0542] Step 2:

[0543] The terminal temporarily stores the travel conditions entered by the user and waits for the user to click the "Submit" button.

[0544] Step 3:

[0545] The user clicks the "Submit" button.

[0546] Step 4:

[0547] The terminal packages the entered travel condition data in a format such as JSON and sends it to the server.

[0548] Step 5:

[0549] The server begins analyzing the received data. Specifically, it uses natural language processing technology to interpret the data entered by the user and stores the data in variables.

[0550] Step 6:

[0551] The server extracts the user's desired conditions based on the analysis results and retrieves related information from the database based on these, including data on accommodation, transportation, restaurants, tourist spots, and event information necessary for generating a travel plan.

[0552] Step 7:

[0553] The server then uses the generative AI model to automatically generate an optimal travel plan based on the extracted preferences, including details such as transportation, accommodation, dining options, tourist spots, and event participation.

[0554] Step 8:

[0555] The server transmits the generated travel plan to the terminal.

[0556] Step 9:

[0557] The device displays the received itinerary on the user's screen, including the ability to clearly display each element of the itinerary (transportation, accommodation, meals, sightseeing spots, and events) in list and timeline format.

[0558] Step 10:

[0559] The user can review the proposed itinerary and make any necessary modifications or final approval, for example, if they want to change certain elements.

[0560] Step 11:

[0561] When the user modifies the plan, the modified conditions are retransmitted from the terminal to the server.

[0562] Step 12:

[0563] The server re-analyzes the modified conditions from the user and regenerates a new travel plan.

[0564] Step 13:

[0565] The server transmits the regenerated itinerary back to the terminal.

[0566] Step 14:

[0567] The terminal presents the regenerated travel plan to the user again, who then reviews it and makes a final confirmation.

[0568] Step 15:

[0569] When the user has finally decided on a plan that satisfies him, he clicks on the "Confirm" button.

[0570] Step 16:

[0571] The terminal transmits final plan confirmation information to the server.

[0572] Step 17:

[0573] The server stores the confirmed travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[0574] This is the specific flow of the process, which allows users to efficiently and stress-free obtain the optimal travel plan.

[0575] Example 1

[0576] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0577] Conventional travel planning systems require users to manually gather information on accommodations, transportation options, tourist attractions, and other topics by browsing multiple websites, which is a cumbersome process. It is also difficult to quickly and efficiently generate an optimal travel plan that reflects the user's requirements and preferences. Furthermore, when a user wants to provide feedback on a presented travel plan and change the requirements, it is difficult to instantly generate a new plan that reflects that feedback.

[0578] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0579] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, a generation means using a generative AI model to generate an optimal travel plan based on the extracted conditions, a means for presenting the generated travel plan to the user, and a means for modifying and regenerating the travel plan based on feedback from the user. This allows users to efficiently and easily create travel plans within a single system and to instantly adjust the plans based on the feedback.

[0580] "User" means any individual or entity that uses the System to plan a trip.

[0581] "Travel preferences" refer to the requirements and wishes that travelers want to include in their travel plans, such as departure point, budget, dates, events they would like to attend, and language preference.

[0582] "User interface" refers to the means by which users can interact with a system, such as a screen or input form for entering travel preferences.

[0583] "Entered Data" means travel preference information provided by a User to the System through the User Interface.

[0584] "Analysis means" refers to a function or system that analyzes input data and extracts conditions that match the traveler's preferences.

[0585] The "generation means" refers to a function or system that generates an optimal travel plan based on the extracted conditions.

[0586] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to automatically generate optimal travel plans.

[0587] "Presentation means" refers to a function or system that visually or electronically presents the generated itinerary to the user.

[0588] "Feedback" refers to information that a user inputs into the system, such as opinions or requests for modifications to a presented travel plan.

[0589] "Modification" refers to a function or system that modifies and regenerates a travel plan based on user feedback.

[0590] "Accommodation" refers to a place of lodging such as a hotel, inn, or guesthouse where travelers can stay.

[0591] "Transportation" refers to the means of transportation used by travelers to travel to their destinations, such as airplanes, trains, buses, etc.

[0592] "Eating and drinking establishments" refer to places such as restaurants, cafes, and izakayas where travelers can eat.

[0593] A "tourist attraction" is a place for tourists to visit and see, such as a park, temple, or museum.

[0594] "Event information" refers to information about various events that can be participated in during a trip, such as concerts, festivals, and fireworks displays.

[0595] MODE FOR CARRYING OUT THE INVENTION

[0596] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system will be described below.

[0597] Basic system configuration

[0598] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[0599] 1. User Interface

[0600] The device provides a screen and input form for users to enter their desired travel conditions. Specifically, it includes an interface for entering items such as departure point, budget, dates, events they would like to attend, and language restrictions. The device can be a personal computer, smartphone, tablet, or other device.

[0601] 2. Analysis method

[0602] The server receives the input data sent from the device and analyzes it using natural language processing technology. This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables. The software used includes a Python natural language processing library and API.

[0603] 3. Generation means

[0604] The server retrieves the necessary information from a database based on the analyzed data. This includes information on accommodations, transportation options, restaurants, tourist attractions, and event information. It then uses a generative AI model to automatically generate an optimal travel plan. The system uses high-performance servers as hardware and software such as TensorFlow and PyTorch.

[0605] 4. Presentation means

[0606] The server sends the generated travel plan to the terminal, which then displays the detailed plan to the user. The user can then check the specific schedule of the trip based on this. The display interface can be a web browser or a dedicated application.

[0607] 5. Corrective measures

[0608] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0609] Program processing overview

[0610] The system operates as follows.

[0611] 1. Enter conditions via terminal

[0612] The user inputs the desired conditions for the trip into an input form on the terminal. For example, the user might input a prompt such as, "The departure point is Tokyo, the budget is up to 100,000 yen, I would like to travel for three days, I would like to attend a fireworks festival, and I would like to go somewhere where I can speak Japanese."

[0613] 2. Data Transmission

[0614] The input data is transmitted from the terminal to the server.

[0615] 3. Data Analysis

[0616] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0617] 4. Travel plan generation

[0618] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0619] Transportation: Fly from Tokyo to New Chitose Airport

[0620] Accommodation: Budget-friendly hotels in Sapporo

[0621] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0622] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0623] Event: Fireworks display held on the second night of the trip

[0624] 5. Plan presentation

[0625] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[0626] 6. Feedback and Regeneration

[0627] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0628] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[0629] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0630] Step 1:

[0631] The user inputs desired travel conditions. Specifically, they input specific conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Place where Japanese is spoken" into the input form on the device. This input becomes the "prompt sentence." The input data is temporarily stored in the device's memory.

[0632] Step 2:

[0633] The device sends the entered travel conditions to the server. When sending the data, the input data is converted to JSON format. The input at this time is the user's desired conditions, and the output is JSON format data sent to the server.

[0634] Step 3:

[0635] The server receives JSON format data from the terminal. The received data is stored in the server's memory. The input is JSON data, and the output indicates that the data was received successfully.

[0636] Step 4:

[0637] The server analyzes the received data using natural language processing technology. Specifically, it uses a Python natural language processing library to convert JSON-formatted data into variables. This analysis extracts conditions such as "departure point," "budget," "schedule," "event," and "language." In this step, the input data is the received JSON data, and the output is the analyzed condition data.

[0638] Step 5:

[0639] The server retrieves the necessary information from a database based on the analyzed data. The database in this case includes information on accommodations, transportation, restaurants, tourist attractions, and events. The specific operation of retrieving data is performed using SQL queries. The input is the analyzed condition data, and the output is the retrieved database information.

[0640] Step 6:

[0641] The server uses a generative AI model based on the acquired information and analysis results to generate an optimal travel plan. The AI ​​model (built with TensorFlow and PyTorch) automatically generates an optimal plan that meets the user's requirements. For example, it includes accommodation, transportation, tourist spots, and event participation schedules. The input is information acquired from the database, and the output is the generated travel plan.

[0642] Step 7:

[0643] The server converts the generated travel plan into JSON format and sends it to the terminal. The input here is the generated travel plan, and the output is JSON format data sent to the terminal.

[0644] Step 8:

[0645] The terminal displays the received itinerary to the user. Specifically, it displays a detailed itinerary using a GUI, allowing the user to check each element. In this step, the input data is the JSON-formatted itinerary received from the server, and the output is a visually displayed itinerary for the user.

[0646] Step 9:

[0647] The user inputs feedback about the presented travel plan into the terminal. Specifically, the user inputs a request for modification, such as "I would like the accommodation to be more luxurious." The input is the user's feedback, and the output is the feedback data stored on the terminal.

[0648] Step 10:

[0649] The terminal sends feedback data to the server. The feedback content is converted to JSON format and sent to the server. The input of this step is feedback data, and the output is JSON-formatted feedback data sent to the server.

[0650] Step 11:

[0651] The server re-analyzes the received feedback data and re-generates the itinerary based on the modification requests, again using a generative AI model. The input for the re-analysis and re-generation is the feedback data, and the output is the re-generated itinerary.

[0652] Step 12:

[0653] The server sends the regenerated itinerary to the terminal, and the terminal displays the regenerated itinerary to the user. The input of this step is the regenerated itinerary, and the output is the itinerary that is resent and displayed to the user.

[0654] This allows users to plan their trip efficiently and stress-free.

[0655] (Application example 1)

[0656] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0657] Conventional travel planning systems require users to manually create travel plans, which takes a lot of time and effort, making the planning process itself cumbersome. Furthermore, it is difficult to automatically generate an optimal plan that meets the user's desired conditions, and it is not easy to regenerate the plan to reflect feedback. These issues also make it difficult to keep the information up-to-date and optimal.

[0658] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0659] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for extracting conditions using natural language processing technology to analyze the input data, and a generation means for generating an optimal travel plan using a generative AI model. This makes it possible to automatically and efficiently generate an optimal travel plan based on the desired conditions input by the user, and to regenerate it based on user feedback.

[0660] A "user interface" is an operating means such as a screen or input form that allows a user to input or give instructions to a system.

[0661] "Natural language processing technology" is a technology that allows a server to understand and analyze the language that people use on a daily basis.

[0662] The "analysis means for extracting conditions" is a means for analyzing input data using natural language processing technology and extracting predetermined conditions.

[0663] A "generative AI model" is an artificial intelligence model that automatically generates optimal travel plans based on given conditions.

[0664] An "optimal travel plan" is a travel schedule and proposal that takes into maximum consideration the user's desired conditions.

[0665] The "generation means" is a means for creating a travel plan based on the extracted conditions using a generative AI model.

[0666] "Feedback" refers to evaluations and requests for modifications to the generated travel plan provided by the user.

[0667] "Regeneration" refers to recreating a travel plan based on feedback.

[0668] MODE FOR CARRYING OUT THE INVENTION

[0669] Basic system configuration

[0670] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system are described below.

[0671] Hardware and software used

[0672] Hardware: Smartphones, servers

[0673] Software: smartphone apps, server-side programs (e.g., Python, Node.js), databases (e.g., MySQL, PostgreSQL), natural language processing libraries (e.g., spaCy, NLTK), generative AI models (e.g., GPT-3)

[0674] User Interface

[0675] The user interface provides a screen and input form for users to enter their desired travel conditions. Specifically, it is designed to allow users to easily enter items such as "place of departure," "budget," "date," "events they want to attend," and "language restrictions" on their smartphones.

[0676] Data transmission and analysis

[0677] When a user enters travel conditions, the data is sent from the smartphone to a server. The server then analyzes the received data using natural language processing technology to extract conditions. This analysis is performed using natural language processing libraries such as spaCy and NLTK. For example, related event information can be extracted from the condition "events I want to attend."

[0678] Generate a travel plan

[0679] Based on the analysis results, the server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from a database. Based on the retrieved data, the server automatically generates an optimal travel plan using a generative AI model (such as GPT-3). This generation method provides a travel plan that best suits the user's requirements.

[0680] Examples of prompt statements

[0681] "Departure point: Tokyo

[0682] Budget: 100,000 yen

[0683] Duration: 3 days

[0684] Events I'd like to attend: Fireworks displays

[0685] Language restrictions: Avoid places where Japanese is not available

[0686] Generate the best itinerary for you.

[0687] Plan presentation and feedback

[0688] The generated travel plan is sent from the server to a smartphone app and presented to the user, who can then review the plan, which includes a detailed schedule and suggestions.

[0689] If a user is not satisfied with the travel plan presented to them, they can modify the conditions and resubmit them from their smartphone to the server. The server then analyzes the data and generates a new plan based on the modified data received. By repeating this process, the optimal travel plan is provided to the user.

[0690] Specific examples

[0691] As an example, consider the case where a user inputs the following conditions:

[0692] "Departure point: Tokyo

[0693] Budget: 100,000 yen

[0694] Duration: 3 days

[0695] Events I'd like to attend: Fireworks displays

[0696] Language restrictions: Avoid places where Japanese is not available

[0697] The server analyzes this information and generates a travel plan that includes, for example, a flight to New Chitose Airport, a hotel in Sapporo, sightseeing at Odori Park and Asahiyama Zoo, and information about the fireworks display.

[0698] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0699] Step 1:

[0700] The user uses the device to input their travel preferences, including their departure point, budget, dates, events they want to attend, language restrictions, etc. The device then collects the input data and prepares it.

[0701] Input: Travel conditions data entered by the user (origin, budget, schedule, events, language restrictions)

[0702] Output: Collected travel condition data

[0703] Step 2:

[0704] The terminal transmits the collected travel condition data to the server, which stores the received data and prepares it for analysis.

[0705] Input: Collected travel condition data

[0706] Output: Travel conditions data sent to the server

[0707] Step 3:

[0708] The server analyzes the received data using natural language processing technology, extracting each condition and storing it in the appropriate variable.

[0709] Input: Travel conditions data sent to the server

[0710] Output: Parsed condition variable data (departure point, budget, schedule, events, language constraints)

[0711] Specific operation: Using spaCy or NLTK, natural language processing techniques are used to extract conditions such as event information from input data.

[0712] Step 4:

[0713] The server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from the database based on the analysis results, stores the retrieved data, and prepares it for use in the next step.

[0714] Input: Variable data for the parsed condition

[0715] Output: Travel-related information obtained from the database (accommodation, transportation, restaurants, tourist spots, event information)

[0716] Specific operation: The server uses MySQL or PostgreSQL to query the database to obtain the relevant information.

[0717] Step 5:

[0718] The server generates an optimal travel plan using a generative AI model (such as GPT-3) based on the acquired data, stores the generated plan, and prepares it for presentation to the user.

[0719] Input: Acquired travel-related information

[0720] Output: Optimal travel plan

[0721] Specific operation: Input conditions into the generative AI model in the form of a prompt sentence to generate the optimal plan. For example,

[0722] "Departure point: Tokyo

[0723] Budget: 100,000 yen

[0724] Duration: 3 days

[0725] Events I'd like to attend: Fireworks displays

[0726] Language restrictions: Avoid places where Japanese is not available

[0727] Generate the best itinerary for you.

[0728] Step 6:

[0729] The server sends the generated travel plan to the terminal, which then displays the received plan to the user.

[0730] Input: Generated itinerary

[0731] Output: Trip plan sent to the device

[0732] Specific operation: The server sends the generated travel plan to the terminal in JSON format, etc., and the terminal parses it and displays it on the user interface.

[0733] Step 7:

[0734] If the user is not satisfied with the presented travel plan, he / she can modify the conditions and resend them from the terminal to the server. The server will then analyze the data and generate a new plan based on the modified data received.

[0735] Input: User feedback and revised conditions

[0736] Output: Regenerated itinerary

[0737] Specific operation: The device sends the re-entered condition data to the server, which analyzes it and regenerates a new plan using the AI ​​model.

[0738] This series of steps allows users to plan their trip efficiently and optimally.

[0739] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0740] MODE FOR CARRYING OUT THE INVENTION

[0741] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. Specific embodiments of the system will be described below.

[0742] Basic system configuration

[0743] The system includes a user interface, an analysis means, a generation means, a presentation means, a modification means, and an emotion engine.

[0744] 1. User Interface

[0745] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[0746] 2. Analysis method

[0747] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[0748] 3. Generation means

[0749] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[0750] 4. Presentation means

[0751] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[0752] 5. Corrective measures

[0753] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0754] 6. Emotion Engine

[0755] The device will have sensors and software to recognize the user's emotional state, using facial recognition and voice analysis technology, as well as analyzing input data and user operation patterns.

[0756] The server analyzes the emotional data sent from the emotion engine and evaluates the user's positive or negative emotions. Based on the user's emotional state, the server adjusts the content and method of presenting the plan to the user.

[0757] Program processing overview

[0758] The system operates as follows.

[0759] 1. Enter conditions via terminal

[0760] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[0761] 2. Data Transmission

[0762] The input data is transmitted from the terminal to the server.

[0763] 3. Data Analysis

[0764] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0765] 4. Travel plan generation

[0766] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[0767] Transportation: Plane to New Chitose Airport

[0768] Accommodation: Budget-friendly hotels in Sapporo

[0769] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[0770] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[0771] Event: Fireworks display held on the second night of the trip

[0772] 5. Plan presentation

[0773] The server sends the generated plan to the terminal, and the terminal displays the detailed plan to the user, who can then check the detailed schedule and each element.

[0774] 6. Feedback and Regeneration

[0775] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[0776] 7. Emotional Recognition and Regulation

[0777] The emotion engine recognizes the user's emotional state from their face, voice, and operation patterns, extracting positive and negative emotions.

[0778] The server evaluates the user's emotional state based on data from the emotion engine and adjusts the itinerary and its presentation accordingly, for example, highlighting the itinerary if the user is expressing positive emotions, or quickly presenting alternatives if the user is expressing negative emotions.

[0779] The above embodiments allow users to plan their trips efficiently and stress-free. Furthermore, by recognizing the user's emotional state and optimizing the plan, a more personalized user experience is realized. The entire system is designed to be user-friendly and can quickly and accurately respond to the user's needs and emotions.

[0780] The processing flow will be explained below.

[0781] Step 1:

[0782] The user inputs desired travel conditions (place of departure, budget, schedule, events to attend, language restrictions, etc.) on the terminal. For example, the user inputs the departure place "Tokyo," the budget "100,000 yen," the schedule "3 days," the event to attend "fireworks display," and the language restriction "avoid places where Japanese cannot be used."

[0783] Step 2:

[0784] The terminal temporarily stores the entered data and waits for the user to click the "Submit" button.

[0785] Step 3:

[0786] The user clicks the "Submit" button.

[0787] Step 4:

[0788] The terminal packages the input data in JSON format or similar and sends it to the server.

[0789] Step 5:

[0790] The server analyzes the received data, uses natural language processing technology to interpret the user's desired conditions, and stores the data in appropriate variables.

[0791] Step 6:

[0792] Based on the analysis results, the server retrieves relevant information from a database, including information on accommodation, transportation, restaurants, tourist attractions, and events.

[0793] Step 7:

[0794] The server uses a generative AI model to generate an optimal travel plan based on the acquired information, including details of flights to New Chitose Airport, hotels in Sapporo, dining options, tourist attractions, and events.

[0795] Step 8:

[0796] The server transmits the generated travel plan to the terminal.

[0797] Step 9:

[0798] The device displays the received travel plan on the user's screen, clearly showing each element in a list or timeline format.

[0799] Step 10:

[0800] The emotion engine evaluates the user's emotional state when a plan is presented, using facial recognition technology, voice analysis, and analysis of operation patterns to assess the user's emotions in real time.

[0801] Step 11:

[0802] The emotion engine sends the acquired emotion data to the server, such as whether the user is smiling or frowning when looking at the plan.

[0803] Step 12:

[0804] The server adjusts the presentation and content of the plan in real time based on the emotional data, for example, highlighting the plan if it detects positive emotions, or presenting alternatives if it detects negative emotions.

[0805] Step 13:

[0806] The user reviews the proposed itinerary and provides any necessary corrections or feedback, for example, if they want to change their accommodation.

[0807] Step 14:

[0808] The user enters the desired modifications into the terminal and resubmits.

[0809] Step 15:

[0810] The terminal transmits the modified data to the server.

[0811] Step 16:

[0812] The server then analyzes the retransmitted data again and generates a new itinerary based on the revised conditions, taking into account the evaluation results of the emotion engine.

[0813] Step 17:

[0814] The server transmits the regenerated itinerary back to the terminal.

[0815] Step 18:

[0816] The device will then present the regenerated plan to the user, who will then confirm it again.

[0817] Step 19:

[0818] The user makes a final confirmation and clicks the "Confirm" button to confirm the final plan.

[0819] Step 20:

[0820] The terminal transmits final plan confirmation information to the server.

[0821] Step 21:

[0822] The server stores the finalized travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[0823] These are the specific processing steps of the system combined with the emotion engine, which allows users to obtain efficient and individually optimized travel plans, and adjusts the plans according to their emotional state, improving the user experience.

[0824] Example 2

[0825] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0826] Current travel planning support systems can generate plans that reflect travelers' desired conditions, but they lack the ability to optimize plans based on user emotions or adjust them to meet individual needs. This can lead to lower user satisfaction and make travel planning stressful. Furthermore, the lack of a mechanism for effectively incorporating user feedback creates the problem of cumbersome, repeated plan revisions. The objective of the present invention is to solve these problems and improve the efficiency of travel planning and user satisfaction.

[0827] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0828] In this invention, the server includes means for providing a user interface through which a user inputs desired travel conditions, analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, generation means for generating an optimal travel plan based on the extracted conditions, means for presenting the generated travel plan to the user, means including an emotion engine for recognizing the user's emotions, means for adjusting the travel plan and presentation method based on emotion data transmitted from the emotion engine, and means for correcting and regenerating the travel plan based on feedback from the user. This makes it possible to optimize the travel plan based on the user's desired conditions as well as their emotional state, and provide a highly satisfying travel plan.

[0829] "User Interface" means the means by which a user interacts directly with the system and inputs travel preferences.

[0830] "Analysis means" refers to a means that has the function of analyzing input data and extracting conditions that match the traveler's preferences.

[0831] "Generation means" refers to a means having the function of generating an optimal travel plan based on the extracted conditions.

[0832] "Presentation means" refers to a means that has the function of displaying and sharing the generated travel plan to the user.

[0833] An "emotion engine" refers to a system that includes sensors and analytical software to recognize user emotions and processes that data.

[0834] "Feedback" refers to the user's evaluation or opinion on the presented travel plan, and includes information that the system uses to revise the plan.

[0835] "Regeneration means" refers to a means that has the function of revising and generating a new travel plan based on user feedback and revision conditions.

[0836] "Database" refers to a system that stores and manages information necessary to generate travel plans, such as information on accommodations, transportation, restaurants, tourist attractions, and events.

[0837] MODE FOR CARRYING OUT THE INVENTION

[0838] Basic system configuration

[0839] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. To provide a superior user experience, the system is configured as follows:

[0840] 1. User Interface

[0841] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[0842] 2. Analysis method

[0843] The server receives the input data sent from the device and analyzes it using natural language processing technology (NLTK or similar technology). This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables.

[0844] 3. Generation means

[0845] The server generates a travel plan based on the analyzed data. It retrieves information on accommodation, transportation, restaurants, tourist attractions, and events from an internal database. It uses a generative AI model (e.g., GPT-3) to generate the optimal travel plan. Examples of prompts for the generative AI model include:

[0846] "Create a travel plan for the user. The conditions are: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend fireworks festivals, avoid places where Japanese is not spoken."

[0847] 4. Presentation means

[0848] The server sends the generated travel plan to the device, which then displays the detailed plan to the user, allowing the user to check the specific itinerary, including information on flights to New Chitose Airport, accommodations in Sapporo, tourist spots such as Odori Park and Sapporo TV Tower, and fireworks displays.

[0849] 5. Corrective measures

[0850] If the user is not satisfied with the proposed itinerary, he or she can modify the conditions and resubmit them from the terminal to the server, which will then analyze the modified conditions again and generate a new itinerary.

[0851] 6. Emotion Engine

[0852] The device is equipped with sensors and software to recognize the user's emotions, specifically using facial recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text API) to determine the user's emotional state.

[0853] The server analyzes the emotion data sent from the emotion engine and evaluates the user's emotional state. Based on the evaluation results, the server adjusts the travel plan and how it is presented. For example, if the user is expressing positive emotions, the server will emphasize the plan and present it, and if the user is expressing dissatisfaction, the server will quickly present alternative plans.

[0854] Specific examples

[0855] Let's say a user enters the following information into the input form on their device: "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken."

[0856] 1. Data transmission and analysis

[0857] This data is sent from the terminal to a server, where it is analyzed using natural language processing technology.

[0858] 2. Travel plan generation

[0859] Based on the analysis results, the server retrieves information from the database and generates a travel plan using a generative AI model. For example, the following results may be generated: a flight to New Chitose Airport, accommodation in Sapporo, Odori Park, Sapporo TV Tower, and a fireworks display to be held on the night of the second day of the trip.

[0860] 3. Plan Presentation and Emotion Recognition

[0861] The generated plan is sent to the device and displayed to the user. At the same time, the device's sensors recognize the user's emotions and transmit them to the server.

[0862] The server analyzes the emotion data to assess the user's positive or negative reaction, and adjusts the way the plan is presented depending on the emotion, offering alternatives if necessary.

[0863] In this way, the system provides optimal travel plans that take into account the user's desired conditions and emotional state, enabling users to plan their trips efficiently and stress-free.

[0864] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0865] Specific explanation of processing steps

[0866] Step 1:

[0867] The user enters desired travel conditions into an input form on the terminal, such as the departure point, budget, dates, events to attend, and language restrictions.

[0868] Input: User's desired conditions (e.g., departure point: Tokyo, budget: 100,000 yen, dates: 3 days, event to attend: fireworks festival, language: avoid places where Japanese is not spoken).

[0869] Output: Sending input data from the terminal to the server.

[0870] Step 2:

[0871] The device sends the user's input data to the server, using the secure HTTPS protocol.

[0872] Input: The user's desired conditions entered into the terminal.

[0873] Output: The user's preference data sent to the server.

[0874] Step 3:

[0875] The server receives the data sent from the device and analyzes it using natural language processing technology (e.g., Python's NLTK).

[0876] Data processing: The received data is processed as text and conditions are extracted.

[0877] Input: User preference data received by the server.

[0878] Output: Parsed condition data (e.g., departure location='Tokyo', budget=100,000 yen, date=3 days, event='fireworks festival', language constraint='Japanese only').

[0879] Step 4:

[0880] The server retrieves travel-related information from an internal database based on the extracted condition data, including information on accommodations, transportation, restaurants, tourist attractions, and events.

[0881] Data processing: Performing database queries to retrieve relevant information.

[0882] Input: Parsed condition data.

[0883] Output: Travel-related information retrieved from the database.

[0884] Step 5:

[0885] The server uses a generative AI model (e.g., GPT-3) to generate an optimal travel plan, using a prompt.

[0886] Generative AI model: An example of a prompt sentence is, "Please create a travel plan for the user. The conditions are as follows: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend the fireworks festival, avoid places where Japanese is not spoken."

[0887] Data calculation: Input the prompt sentence and condition data into the generative AI model to generate a plan.

[0888] Input: Travel-related information retrieved from the database and a prompt statement.

[0889] Output: Generated itinerary (e.g., flight to New Chitose Airport, accommodation in Sapporo city, Odori Park, Sapporo TV Tower, and fireworks festival on the second night of the trip).

[0890] Step 6:

[0891] The server transmits the generated travel plan to the terminal, which displays the detailed plan to the user.

[0892] Input: The generated itinerary.

[0893] Output: The itinerary presented to the user.

[0894] Step 7:

[0895] The user inputs feedback on the presented travel plan through the terminal. If the user is not satisfied, he / she can modify the conditions and resubmit the plan.

[0896] Input: User feedback and correction criteria.

[0897] Output: Corrected data resent from the terminal.

[0898] Step 8:

[0899] The server re-analyzes the retransmitted data and presents the regenerated itinerary to the user.

[0900] Input: Resubmitted corrected data.

[0901] Data processing and calculation: Regenerate plans using data analysis and AI models.

[0902] Output: The regenerated itinerary.

[0903] Step 9:

[0904] The device uses sensors and software (e.g., facial recognition technology and voice analysis technology) to recognize the user's emotions, determines their emotional state, and sends the data to a server.

[0905] Input: User operations, facial expressions, and voice data.

[0906] Output: Parsed emotion data.

[0907] Step 10:

[0908] The server analyzes the emotional data sent by the emotion engine and adjusts the travel plan and presentation accordingly: if the emotion is positive, the plan is emphasized, and if the emotion is negative, alternatives are presented.

[0909] Input: Parsed emotion data.

[0910] Data processing: Plan adjustment based on the results of the emotional state assessment.

[0911] Output: Adjusted travel plan or alternatives.

[0912] The above is the specific processing flow of this system.

[0913] (Application example 2)

[0914] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0915] Conventional food delivery systems have difficulty providing optimal food plans based on a user's emotional state. Furthermore, generating a plan that matches a user's preferences requires considering many factors, which makes the process complicated and burdensome for users. Therefore, there is a need for the development of a food delivery system that is easy for users to use and provides optimal plans based on their emotional state.

[0916] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for providing a user interface through which the user inputs desired conditions regarding food type, budget, and delivery time; an analysis means for analyzing the input data and extracting conditions that match the user's preferences; an emotion recognition means for recognizing the user's emotional state using facial recognition technology; a generation means for generating an optimal food plan based on the extracted conditions and emotional state; a means for presenting the generated food plan to the user; and a means for modifying and regenerating the food plan based on feedback from the user. This makes it possible to provide a fast and appropriate food delivery plan that also takes into account the user's emotional state.

[0917] A "user interface" is a means of providing a screen or input form for users to perform operations.

[0918] The "analysis means" is a function that analyzes the input data and extracts conditions that match the user's preferences.

[0919] "Emotion recognition means" is a technology for recognizing the emotional state of a user using face recognition technology.

[0920] The "generator" is a function that generates an optimal food plan based on the extracted conditions and emotional state.

[0921] "Presentation means" refers to a function that presents the generated food plan to the user.

[0922] A "modification tool" is a tool that has the ability to modify and regenerate a food plan based on user feedback.

[0923] A "food plan" is a selection of food and dining options generated based on a user's preferences and emotional state.

[0924] A "database" is an information storage system that stores information such as restaurant and event information and uses it as needed.

[0925] "Emotional state" refers to the user's emotional state, and is information detected using technologies such as facial recognition and voice analysis.

[0926] "Feedback" refers to the evaluation or opinion that a user gives regarding the information or plans provided.

[0927] A novel system for implementing this invention is designed to provide food delivery services to users. The system combines a user interface, an analysis means, an emotion recognition means, a generation means, a presentation means, and a modification means.

[0928] User Interface

[0929] The terminal provides an interface for users to input their desired conditions regarding food type, budget, and delivery time. Specifically, users can input their food delivery preferences through an input form displayed on the smartphone application screen.

[0930] Analysis means

[0931] The server receives the input data sent from the device and analyzes it using natural language processing technology. This allows it to understand the desired conditions entered by the user and store each condition, such as food type and budget, in the appropriate variables. The software used is Hugging Face Transformers, a natural language processing software.

[0932] emotion recognition means

[0933] The device uses a webcam or smartphone camera to recognize the user's emotions. It uses facial recognition technology to capture the user's face in real time and analyzes their emotional state using Hugging Face's emotion analysis model. This allows it to recognize the user's emotions as states such as "happy" or "unhappy."

[0934] generation means

[0935] The server generates an optimal meal plan based on the analyzed data and emotion recognition results. To do this, it references a database of restaurant and event information and uses a generative AI model to suggest the most suitable foods and restaurants for the user. The generative AI model receives prompts based on the user's desired conditions and emotional state, and customizes the suggestions accordingly.

[0936] Presentation means

[0937] The server sends the generated meal plan to the device, which displays it to the user, who can then check the proposed meal plan and detailed information about the selected restaurant through a smartphone application.

[0938] Correction means

[0939] The user can provide feedback on the presented meal plan. For example, they can input their opinion such as, "This restaurant doesn't suit my mood." Based on that feedback, the server analyzes the data again and regenerates a new meal plan that matches their conditions and emotional state.

[0940] Specific examples

[0941] For example, if a user inputs "My budget is under 2,000 yen and I want to eat pizza," and the facial image captured by the webcam is recognized as "happy," the server will consider the user's positive emotional state and suggest restaurants that offer the best pizza within their budget. Examples of prompt sentences are as follows:

[0942] Prompt statement:

[0943] A user enters "I want to eat pizza within 2,000 yen." Emotion analysis is performed on the facial image captured by the webcam, and the result is recognized as "happy." Based on this, what is the best food and restaurant for the user?

[0944] This system allows users to easily receive the optimal food delivery plan that takes their emotional state into consideration.

[0945] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0946] Step 1:

[0947] The terminal provides an interface for the user to input desired conditions regarding food type, budget, and delivery time. When the user inputs these conditions, the data is sent from the terminal to the server. The input here includes food type (e.g., pizza), budget (e.g., 2,000 yen), and delivery time (e.g., within 30 minutes). This input data is passed to the next processing step.

[0948] Step 2:

[0949] The server receives the input data sent from the terminal and analyzes the data using analytical means. Through this analysis, the user's desired conditions are understood and stored in the appropriate variables. For example, natural language processing is used to extract "food_type: pizza" from the input "pizza," and to obtain "budget: 2000" from "budget: 2,000 yen." The analysis results are passed to the next processing step.

[0950] Step 3:

[0951] To recognize the user's emotions, the device activates the webcam and captures a facial image. The captured facial image is analyzed by an emotion recognition means, and the user's emotional state is recognized as "happy" or "unhappy." For example, the facial image is analyzed using the Hugging Face emotion analysis model, and the result is "Emotional state: happy." This emotional state data is passed to the next processing step.

[0952] Step 4:

[0953] The server uses a generative means to generate an optimal meal plan based on the analysis results and the user's emotional state. The server sends the input desired conditions and emotional state as prompts to the generative AI model, which retrieves relevant restaurant and menu information from the database and proposes a meal plan that suits the user. For example, based on "food_type: pizza," "budget: 2000," and "emotional state: happy," the generative AI model recommends the optimal pizza restaurant and specific menu (e.g., Margherita pizza). This generated result is passed to the next processing step.

[0954] Step 5:

[0955] The server sends the generated food plan to the terminal through the presentation means, and the terminal displays the detailed plan to the user on the screen. The user can check the presented food plan (e.g., Margherita pizza, XX pizza restaurant), select and rate it. This displayed information is passed to the next processing step.

[0956] Step 6:

[0957] The user provides feedback on the presented food plan, and that feedback is sent from the device to the server. For example, if the user enters an opinion such as "I don't feel like going to this restaurant," that data is passed to the server. This feedback data is then passed to the next processing step.

[0958] Step 7:

[0959] The server analyzes the user's feedback data and uses the corrective measures to regenerate a new meal plan, taking into account the user's original preferences and emotional state. It then incorporates the previous feedback and uses the database and generative AI model again to generate new suggestions, e.g., re-recommend the next best pizza place and menu item based on the user's new feedback. This new meal plan then returns to step 5 and is displayed again for presentation to the user.

[0960] This specific process allows users to conveniently receive food delivery plans that reflect their emotional state in real time.

[0961] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0962] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0963] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0964] [Third embodiment]

[0965] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0966] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0967] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0968] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0969] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0970] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0971] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0972] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0973] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[0974] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0975] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0976] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0977] MODE FOR CARRYING OUT THE INVENTION

[0978] The system of the present invention provides comprehensive support for efficient travel planning, and specific embodiments thereof will be described below.

[0979] Basic system configuration

[0980] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[0981] 1. User Interface

[0982] The device provides a screen and input form for users to enter their travel preferences, including interfaces for inputting items such as departure point, budget, dates, events they would like to attend, and language restrictions.

[0983] 2. Analysis method

[0984] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[0985] 3. Generation means

[0986] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[0987] 4. Presentation means

[0988] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[0989] 5. Corrective measures

[0990] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[0991] Program processing overview

[0992] The system operates as follows.

[0993] 1. Enter conditions via terminal

[0994] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[0995] 2. Data Transmission

[0996] The input data is transmitted from the terminal to the server.

[0997] 3. Data Analysis

[0998] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[0999] 4. Travel plan generation

[1000] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1001] Transportation: Plane to New Chitose Airport

[1002] Accommodation: Budget-friendly hotels in Sapporo

[1003] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1004] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1005] Event: Fireworks display held on the second night of the trip

[1006] 5. Plan presentation

[1007] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[1008] 6. Feedback and Regeneration

[1009] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1010] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[1011] The processing flow will be explained below.

[1012] Step 1:

[1013] The user inputs the desired travel conditions (place of departure, budget, dates, events to attend, language restrictions, etc.) on the terminal.

[1014] Step 2:

[1015] The terminal temporarily stores the travel conditions entered by the user and waits for the user to click the "Submit" button.

[1016] Step 3:

[1017] The user clicks the "Submit" button.

[1018] Step 4:

[1019] The terminal packages the entered travel condition data in a format such as JSON and sends it to the server.

[1020] Step 5:

[1021] The server begins analyzing the received data. Specifically, it uses natural language processing technology to interpret the data entered by the user and stores the data in variables.

[1022] Step 6:

[1023] The server extracts the user's desired conditions based on the analysis results and retrieves related information from the database based on these, including data on accommodation, transportation, restaurants, tourist spots, and event information necessary for generating a travel plan.

[1024] Step 7:

[1025] The server then uses the generative AI model to automatically generate an optimal travel plan based on the extracted preferences, including details such as transportation, accommodation, dining options, tourist spots, and event participation.

[1026] Step 8:

[1027] The server transmits the generated travel plan to the terminal.

[1028] Step 9:

[1029] The device displays the received itinerary on the user's screen, including the ability to clearly display each element of the itinerary (transportation, accommodation, meals, sightseeing spots, and events) in list and timeline format.

[1030] Step 10:

[1031] The user can review the proposed itinerary and make any necessary modifications or final approval, for example, if they want to change certain elements.

[1032] Step 11:

[1033] When the user modifies the plan, the modified conditions are retransmitted from the terminal to the server.

[1034] Step 12:

[1035] The server re-analyzes the modified conditions from the user and regenerates a new travel plan.

[1036] Step 13:

[1037] The server transmits the regenerated itinerary back to the terminal.

[1038] Step 14:

[1039] The terminal presents the regenerated travel plan to the user again, who then reviews it and makes a final confirmation.

[1040] Step 15:

[1041] When the user has finally decided on a plan that satisfies him, he clicks on the "Confirm" button.

[1042] Step 16:

[1043] The terminal transmits final plan confirmation information to the server.

[1044] Step 17:

[1045] The server stores the confirmed travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[1046] This is the specific flow of the process, which allows users to efficiently and stress-free obtain the optimal travel plan.

[1047] Example 1

[1048] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1049] Conventional travel planning systems require users to manually gather information on accommodations, transportation options, tourist attractions, and other topics by browsing multiple websites, which is a cumbersome process. It is also difficult to quickly and efficiently generate an optimal travel plan that reflects the user's requirements and preferences. Furthermore, when a user wants to provide feedback on a presented travel plan and change the requirements, it is difficult to instantly generate a new plan that reflects that feedback.

[1050] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1051] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, a generation means using a generative AI model to generate an optimal travel plan based on the extracted conditions, a means for presenting the generated travel plan to the user, and a means for modifying and regenerating the travel plan based on feedback from the user. This allows users to efficiently and easily create travel plans within a single system and to instantly adjust the plans based on the feedback.

[1052] "User" means any individual or entity that uses the System to plan a trip.

[1053] "Travel preferences" refer to the requirements and wishes that travelers want to include in their travel plans, such as departure point, budget, dates, events they would like to attend, and language preference.

[1054] "User interface" refers to the means by which users can interact with a system, such as a screen or input form for entering travel preferences.

[1055] "Entered Data" means travel preference information provided by a User to the System through the User Interface.

[1056] "Analysis means" refers to a function or system that analyzes input data and extracts conditions that match the traveler's preferences.

[1057] The "generation means" refers to a function or system that generates an optimal travel plan based on the extracted conditions.

[1058] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to automatically generate optimal travel plans.

[1059] "Presentation means" refers to a function or system that visually or electronically presents the generated itinerary to the user.

[1060] "Feedback" refers to information that a user inputs into the system, such as opinions or requests for modifications to a presented travel plan.

[1061] "Modification" refers to a function or system that modifies and regenerates a travel plan based on user feedback.

[1062] "Accommodation" refers to a place of lodging such as a hotel, inn, or guesthouse where travelers can stay.

[1063] "Transportation" refers to the means of transportation used by travelers to travel to their destinations, such as airplanes, trains, buses, etc.

[1064] "Eating and drinking establishments" refer to places such as restaurants, cafes, and izakayas where travelers can eat.

[1065] A "tourist attraction" is a place for tourists to visit and see, such as a park, temple, or museum.

[1066] "Event information" refers to information about various events that can be participated in during a trip, such as concerts, festivals, and fireworks displays.

[1067] MODE FOR CARRYING OUT THE INVENTION

[1068] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system will be described below.

[1069] Basic system configuration

[1070] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[1071] 1. User Interface

[1072] The device provides a screen and input form for users to enter their desired travel conditions. Specifically, it includes an interface for entering items such as departure point, budget, dates, events they would like to attend, and language restrictions. The device can be a personal computer, smartphone, tablet, or other device.

[1073] 2. Analysis method

[1074] The server receives the input data sent from the device and analyzes it using natural language processing technology. This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables. The software used includes a Python natural language processing library and API.

[1075] 3. Generation means

[1076] The server retrieves the necessary information from a database based on the analyzed data. This includes information on accommodations, transportation options, restaurants, tourist attractions, and event information. It then uses a generative AI model to automatically generate an optimal travel plan. The system uses high-performance servers as hardware and software such as TensorFlow and PyTorch.

[1077] 4. Presentation means

[1078] The server sends the generated travel plan to the terminal, which then displays the detailed plan to the user. The user can then check the specific schedule of the trip based on this. The display interface can be a web browser or a dedicated application.

[1079] 5. Corrective measures

[1080] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[1081] Program processing overview

[1082] The system operates as follows.

[1083] 1. Enter conditions via terminal

[1084] The user inputs the desired conditions for the trip into an input form on the terminal. For example, the user might input a prompt such as, "The departure point is Tokyo, the budget is up to 100,000 yen, I would like to travel for three days, I would like to attend a fireworks festival, and I would like to go somewhere where I can speak Japanese."

[1085] 2. Data Transmission

[1086] The input data is transmitted from the terminal to the server.

[1087] 3. Data Analysis

[1088] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[1089] 4. Travel plan generation

[1090] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1091] Transportation: Fly from Tokyo to New Chitose Airport

[1092] Accommodation: Budget-friendly hotels in Sapporo

[1093] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1094] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1095] Event: Fireworks display held on the second night of the trip

[1096] 5. Plan presentation

[1097] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[1098] 6. Feedback and Regeneration

[1099] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1100] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[1101] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1102] Step 1:

[1103] The user inputs desired travel conditions. Specifically, they input specific conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Place where Japanese is spoken" into the input form on the device. This input becomes the "prompt sentence." The input data is temporarily stored in the device's memory.

[1104] Step 2:

[1105] The device sends the entered travel conditions to the server. When sending the data, the input data is converted to JSON format. The input at this time is the user's desired conditions, and the output is JSON format data sent to the server.

[1106] Step 3:

[1107] The server receives JSON format data from the terminal. The received data is stored in the server's memory. The input is JSON data, and the output indicates that the data was received successfully.

[1108] Step 4:

[1109] The server analyzes the received data using natural language processing technology. Specifically, it uses a Python natural language processing library to convert JSON-formatted data into variables. This analysis extracts conditions such as "departure point," "budget," "schedule," "event," and "language." In this step, the input data is the received JSON data, and the output is the analyzed condition data.

[1110] Step 5:

[1111] The server retrieves the necessary information from a database based on the analyzed data. The database in this case includes information on accommodations, transportation, restaurants, tourist attractions, and events. The specific operation of retrieving data is performed using SQL queries. The input is the analyzed condition data, and the output is the retrieved database information.

[1112] Step 6:

[1113] The server uses a generative AI model based on the acquired information and analysis results to generate an optimal travel plan. The AI ​​model (built with TensorFlow and PyTorch) automatically generates an optimal plan that meets the user's requirements. For example, it includes accommodation, transportation, tourist spots, and event participation schedules. The input is information acquired from the database, and the output is the generated travel plan.

[1114] Step 7:

[1115] The server converts the generated travel plan into JSON format and sends it to the terminal. The input here is the generated travel plan, and the output is JSON format data sent to the terminal.

[1116] Step 8:

[1117] The terminal displays the received itinerary to the user. Specifically, it displays a detailed itinerary using a GUI, allowing the user to check each element. In this step, the input data is the JSON-formatted itinerary received from the server, and the output is a visually displayed itinerary for the user.

[1118] Step 9:

[1119] The user inputs feedback about the presented travel plan into the terminal. Specifically, the user inputs a request for modification, such as "I would like the accommodation to be more luxurious." The input is the user's feedback, and the output is the feedback data stored on the terminal.

[1120] Step 10:

[1121] The terminal sends feedback data to the server. The feedback content is converted to JSON format and sent to the server. The input of this step is feedback data, and the output is JSON-formatted feedback data sent to the server.

[1122] Step 11:

[1123] The server re-analyzes the received feedback data and re-generates the itinerary based on the modification requests, again using a generative AI model. The input for the re-analysis and re-generation is the feedback data, and the output is the re-generated itinerary.

[1124] Step 12:

[1125] The server sends the regenerated itinerary to the terminal, and the terminal displays the regenerated itinerary to the user. The input of this step is the regenerated itinerary, and the output is the itinerary that is resent and displayed to the user.

[1126] This allows users to plan their trip efficiently and stress-free.

[1127] (Application example 1)

[1128] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1129] Conventional travel planning systems require users to manually create travel plans, which takes a lot of time and effort, making the planning process itself cumbersome. Furthermore, it is difficult to automatically generate an optimal plan that meets the user's desired conditions, and it is not easy to regenerate the plan to reflect feedback. These issues also make it difficult to keep the information up-to-date and optimal.

[1130] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1131] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for extracting conditions using natural language processing technology to analyze the input data, and a generation means for generating an optimal travel plan using a generative AI model. This makes it possible to automatically and efficiently generate an optimal travel plan based on the desired conditions input by the user, and to regenerate it based on user feedback.

[1132] A "user interface" is an operating means such as a screen or input form that allows a user to input or give instructions to a system.

[1133] "Natural language processing technology" is a technology that allows a server to understand and analyze the language that people use on a daily basis.

[1134] The "analysis means for extracting conditions" is a means for analyzing input data using natural language processing technology and extracting predetermined conditions.

[1135] A "generative AI model" is an artificial intelligence model that automatically generates optimal travel plans based on given conditions.

[1136] An "optimal travel plan" is a travel schedule and proposal that takes into maximum consideration the user's desired conditions.

[1137] The "generation means" is a means for creating a travel plan based on the extracted conditions using a generative AI model.

[1138] "Feedback" refers to evaluations and requests for modifications to the generated travel plan provided by the user.

[1139] "Regeneration" refers to recreating a travel plan based on feedback.

[1140] MODE FOR CARRYING OUT THE INVENTION

[1141] Basic system configuration

[1142] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system are described below.

[1143] Hardware and software used

[1144] Hardware: Smartphones, servers

[1145] Software: smartphone apps, server-side programs (e.g., Python, Node.js), databases (e.g., MySQL, PostgreSQL), natural language processing libraries (e.g., spaCy, NLTK), generative AI models (e.g., GPT-3)

[1146] User Interface

[1147] The user interface provides a screen and input form for users to enter their desired travel conditions. Specifically, it is designed to allow users to easily enter items such as "place of departure," "budget," "date," "events they want to attend," and "language restrictions" on their smartphones.

[1148] Data transmission and analysis

[1149] When a user enters travel conditions, the data is sent from the smartphone to a server. The server then analyzes the received data using natural language processing technology to extract conditions. This analysis is performed using natural language processing libraries such as spaCy and NLTK. For example, related event information can be extracted from the condition "events I want to attend."

[1150] Generate a travel plan

[1151] Based on the analysis results, the server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from a database. Based on the retrieved data, the server automatically generates an optimal travel plan using a generative AI model (such as GPT-3). This generation method provides a travel plan that best suits the user's requirements.

[1152] Examples of prompt statements

[1153] "Departure point: Tokyo

[1154] Budget: 100,000 yen

[1155] Duration: 3 days

[1156] Events I'd like to attend: Fireworks displays

[1157] Language restrictions: Avoid places where Japanese is not available

[1158] Generate the best itinerary for you.

[1159] Plan presentation and feedback

[1160] The generated travel plan is sent from the server to a smartphone app and presented to the user, who can then review the plan, which includes a detailed schedule and suggestions.

[1161] If a user is not satisfied with the travel plan presented to them, they can modify the conditions and resubmit them from their smartphone to the server. The server then analyzes the data and generates a new plan based on the modified data received. By repeating this process, the optimal travel plan is provided to the user.

[1162] Specific examples

[1163] As an example, consider the case where a user inputs the following conditions:

[1164] "Departure point: Tokyo

[1165] Budget: 100,000 yen

[1166] Duration: 3 days

[1167] Events I'd like to attend: Fireworks displays

[1168] Language restrictions: Avoid places where Japanese is not available

[1169] The server analyzes this information and generates a travel plan that includes, for example, a flight to New Chitose Airport, a hotel in Sapporo, sightseeing at Odori Park and Asahiyama Zoo, and information about the fireworks display.

[1170] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1171] Step 1:

[1172] The user uses the device to input their travel preferences, including their departure point, budget, dates, events they want to attend, language restrictions, etc. The device then collects the input data and prepares it.

[1173] Input: Travel conditions data entered by the user (origin, budget, schedule, events, language restrictions)

[1174] Output: Collected travel condition data

[1175] Step 2:

[1176] The terminal transmits the collected travel condition data to the server, which stores the received data and prepares it for analysis.

[1177] Input: Collected travel condition data

[1178] Output: Travel conditions data sent to the server

[1179] Step 3:

[1180] The server analyzes the received data using natural language processing technology, extracting each condition and storing it in the appropriate variable.

[1181] Input: Travel conditions data sent to the server

[1182] Output: Parsed condition variable data (departure point, budget, schedule, events, language constraints)

[1183] Specific operation: Using spaCy or NLTK, natural language processing techniques are used to extract conditions such as event information from input data.

[1184] Step 4:

[1185] The server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from the database based on the analysis results, stores the retrieved data, and prepares it for use in the next step.

[1186] Input: Variable data for the parsed condition

[1187] Output: Travel-related information obtained from the database (accommodation, transportation, restaurants, tourist spots, event information)

[1188] Specific operation: The server uses MySQL or PostgreSQL to query the database to obtain the relevant information.

[1189] Step 5:

[1190] The server generates an optimal travel plan using a generative AI model (such as GPT-3) based on the acquired data, stores the generated plan, and prepares it for presentation to the user.

[1191] Input: Acquired travel-related information

[1192] Output: Optimal travel plan

[1193] Specific operation: Input conditions into the generative AI model in the form of a prompt sentence to generate the optimal plan. For example,

[1194] "Departure point: Tokyo

[1195] Budget: 100,000 yen

[1196] Duration: 3 days

[1197] Events I'd like to attend: Fireworks displays

[1198] Language restrictions: Avoid places where Japanese is not available

[1199] Generate the best itinerary for you.

[1200] Step 6:

[1201] The server sends the generated travel plan to the terminal, which then displays the received plan to the user.

[1202] Input: Generated itinerary

[1203] Output: Trip plan sent to the device

[1204] Specific operation: The server sends the generated travel plan to the terminal in JSON format, etc., and the terminal parses it and displays it on the user interface.

[1205] Step 7:

[1206] If the user is not satisfied with the presented travel plan, he / she can modify the conditions and resend them from the terminal to the server. The server will then analyze the data and generate a new plan based on the modified data received.

[1207] Input: User feedback and revised conditions

[1208] Output: Regenerated itinerary

[1209] Specific operation: The device sends the re-entered condition data to the server, which analyzes it and regenerates a new plan using the AI ​​model.

[1210] This series of steps allows users to plan their trip efficiently and optimally.

[1211] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1212] MODE FOR CARRYING OUT THE INVENTION

[1213] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. Specific embodiments of the system will be described below.

[1214] Basic system configuration

[1215] The system includes a user interface, an analysis means, a generation means, a presentation means, a modification means, and an emotion engine.

[1216] 1. User Interface

[1217] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[1218] 2. Analysis method

[1219] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[1220] 3. Generation means

[1221] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[1222] 4. Presentation means

[1223] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[1224] 5. Corrective measures

[1225] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[1226] 6. Emotion Engine

[1227] The device will have sensors and software to recognize the user's emotional state, using facial recognition and voice analysis technology, as well as analyzing input data and user operation patterns.

[1228] The server analyzes the emotional data sent from the emotion engine and evaluates the user's positive or negative emotions. Based on the user's emotional state, the server adjusts the content and method of presenting the plan to the user.

[1229] Program processing overview

[1230] The system operates as follows.

[1231] 1. Enter conditions via terminal

[1232] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[1233] 2. Data Transmission

[1234] The input data is transmitted from the terminal to the server.

[1235] 3. Data Analysis

[1236] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[1237] 4. Travel plan generation

[1238] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1239] Transportation: Plane to New Chitose Airport

[1240] Accommodation: Budget-friendly hotels in Sapporo

[1241] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1242] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1243] Event: Fireworks display held on the second night of the trip

[1244] 5. Plan presentation

[1245] The server sends the generated plan to the terminal, and the terminal displays the detailed plan to the user, who can then check the detailed schedule and each element.

[1246] 6. Feedback and Regeneration

[1247] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1248] 7. Emotional Recognition and Regulation

[1249] The emotion engine recognizes the user's emotional state from their face, voice, and operation patterns, extracting positive and negative emotions.

[1250] The server evaluates the user's emotional state based on data from the emotion engine and adjusts the itinerary and its presentation accordingly, for example, highlighting the itinerary if the user is expressing positive emotions, or quickly presenting alternatives if the user is expressing negative emotions.

[1251] The above embodiments allow users to plan their trips efficiently and stress-free. Furthermore, by recognizing the user's emotional state and optimizing the plan, a more personalized user experience is realized. The entire system is designed to be user-friendly and can quickly and accurately respond to the user's needs and emotions.

[1252] The processing flow will be explained below.

[1253] Step 1:

[1254] The user inputs desired travel conditions (place of departure, budget, schedule, events to attend, language restrictions, etc.) on the terminal. For example, the user inputs the departure place "Tokyo," the budget "100,000 yen," the schedule "3 days," the event to attend "fireworks display," and the language restriction "avoid places where Japanese cannot be used."

[1255] Step 2:

[1256] The terminal temporarily stores the entered data and waits for the user to click the "Submit" button.

[1257] Step 3:

[1258] The user clicks the "Submit" button.

[1259] Step 4:

[1260] The terminal packages the input data in JSON format or similar and sends it to the server.

[1261] Step 5:

[1262] The server analyzes the received data, uses natural language processing technology to interpret the user's desired conditions, and stores the data in appropriate variables.

[1263] Step 6:

[1264] Based on the analysis results, the server retrieves relevant information from a database, including information on accommodation, transportation, restaurants, tourist attractions, and events.

[1265] Step 7:

[1266] The server uses a generative AI model to generate an optimal travel plan based on the acquired information, including details of flights to New Chitose Airport, hotels in Sapporo, dining options, tourist attractions, and events.

[1267] Step 8:

[1268] The server transmits the generated travel plan to the terminal.

[1269] Step 9:

[1270] The device displays the received travel plan on the user's screen, clearly showing each element in a list or timeline format.

[1271] Step 10:

[1272] The emotion engine evaluates the user's emotional state when a plan is presented, using facial recognition technology, voice analysis, and analysis of operation patterns to assess the user's emotions in real time.

[1273] Step 11:

[1274] The emotion engine sends the acquired emotion data to the server, such as whether the user is smiling or frowning when looking at the plan.

[1275] Step 12:

[1276] The server adjusts the presentation and content of the plan in real time based on the emotional data, for example, highlighting the plan if it detects positive emotions, or presenting alternatives if it detects negative emotions.

[1277] Step 13:

[1278] The user reviews the proposed itinerary and provides any necessary corrections or feedback, for example, if they want to change their accommodation.

[1279] Step 14:

[1280] The user enters the desired modifications into the terminal and resubmits.

[1281] Step 15:

[1282] The terminal transmits the modified data to the server.

[1283] Step 16:

[1284] The server then analyzes the retransmitted data again and generates a new itinerary based on the revised conditions, taking into account the evaluation results of the emotion engine.

[1285] Step 17:

[1286] The server transmits the regenerated itinerary back to the terminal.

[1287] Step 18:

[1288] The device will then present the regenerated plan to the user, who will then confirm it again.

[1289] Step 19:

[1290] The user makes a final confirmation and clicks the "Confirm" button to confirm the final plan.

[1291] Step 20:

[1292] The terminal transmits final plan confirmation information to the server.

[1293] Step 21:

[1294] The server stores the finalized travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[1295] These are the specific processing steps of the system combined with the emotion engine, which allows users to obtain efficient and individually optimized travel plans, and adjusts the plans according to their emotional state, improving the user experience.

[1296] Example 2

[1297] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1298] Current travel planning support systems can generate plans that reflect travelers' desired conditions, but they lack the ability to optimize plans based on user emotions or adjust them to meet individual needs. This can lead to lower user satisfaction and make travel planning stressful. Furthermore, the lack of a mechanism for effectively incorporating user feedback creates the problem of cumbersome, repeated plan revisions. The objective of the present invention is to solve these problems and improve the efficiency of travel planning and user satisfaction.

[1299] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1300] In this invention, the server includes means for providing a user interface through which a user inputs desired travel conditions, analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, generation means for generating an optimal travel plan based on the extracted conditions, means for presenting the generated travel plan to the user, means including an emotion engine for recognizing the user's emotions, means for adjusting the travel plan and presentation method based on emotion data transmitted from the emotion engine, and means for correcting and regenerating the travel plan based on feedback from the user. This makes it possible to optimize the travel plan based on the user's desired conditions as well as their emotional state, and provide a highly satisfying travel plan.

[1301] "User Interface" means the means by which a user interacts directly with the system and inputs travel preferences.

[1302] "Analysis means" refers to a means that has the function of analyzing input data and extracting conditions that match the traveler's preferences.

[1303] "Generation means" refers to a means having the function of generating an optimal travel plan based on the extracted conditions.

[1304] "Presentation means" refers to a means that has the function of displaying and sharing the generated travel plan to the user.

[1305] An "emotion engine" refers to a system that includes sensors and analytical software to recognize user emotions and processes that data.

[1306] "Feedback" refers to the user's evaluation or opinion on the presented travel plan, and includes information that the system uses to revise the plan.

[1307] "Regeneration means" refers to a means that has the function of revising and generating a new travel plan based on user feedback and revision conditions.

[1308] "Database" refers to a system that stores and manages information necessary to generate travel plans, such as information on accommodations, transportation, restaurants, tourist attractions, and events.

[1309] MODE FOR CARRYING OUT THE INVENTION

[1310] Basic system configuration

[1311] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. To provide a superior user experience, the system is configured as follows:

[1312] 1. User Interface

[1313] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[1314] 2. Analysis method

[1315] The server receives the input data sent from the device and analyzes it using natural language processing technology (NLTK or similar technology). This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables.

[1316] 3. Generation means

[1317] The server generates a travel plan based on the analyzed data. It retrieves information on accommodation, transportation, restaurants, tourist attractions, and events from an internal database. It uses a generative AI model (e.g., GPT-3) to generate the optimal travel plan. Examples of prompts for the generative AI model include:

[1318] "Create a travel plan for the user. The conditions are: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend fireworks festivals, avoid places where Japanese is not spoken."

[1319] 4. Presentation means

[1320] The server sends the generated travel plan to the device, which then displays the detailed plan to the user, allowing the user to check the specific itinerary, including information on flights to New Chitose Airport, accommodations in Sapporo, tourist spots such as Odori Park and Sapporo TV Tower, and fireworks displays.

[1321] 5. Corrective measures

[1322] If the user is not satisfied with the proposed itinerary, he or she can modify the conditions and resubmit them from the terminal to the server, which will then analyze the modified conditions again and generate a new itinerary.

[1323] 6. Emotion Engine

[1324] The device is equipped with sensors and software to recognize the user's emotions, specifically using facial recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text API) to determine the user's emotional state.

[1325] The server analyzes the emotion data sent from the emotion engine and evaluates the user's emotional state. Based on the evaluation results, the server adjusts the travel plan and how it is presented. For example, if the user is expressing positive emotions, the server will emphasize the plan and present it, and if the user is expressing dissatisfaction, the server will quickly present alternative plans.

[1326] Specific examples

[1327] Let's say a user enters the following information into the input form on their device: "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken."

[1328] 1. Data transmission and analysis

[1329] This data is sent from the terminal to a server, where it is analyzed using natural language processing technology.

[1330] 2. Travel plan generation

[1331] Based on the analysis results, the server retrieves information from the database and generates a travel plan using a generative AI model. For example, the following results may be generated: a flight to New Chitose Airport, accommodation in Sapporo, Odori Park, Sapporo TV Tower, and a fireworks display to be held on the night of the second day of the trip.

[1332] 3. Plan Presentation and Emotion Recognition

[1333] The generated plan is sent to the device and displayed to the user. At the same time, the device's sensors recognize the user's emotions and transmit them to the server.

[1334] The server analyzes the emotion data to assess the user's positive or negative reaction, and adjusts the way the plan is presented depending on the emotion, offering alternatives if necessary.

[1335] In this way, the system provides optimal travel plans that take into account the user's desired conditions and emotional state, enabling users to plan their trips efficiently and stress-free.

[1336] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1337] Specific explanation of processing steps

[1338] Step 1:

[1339] The user enters desired travel conditions into an input form on the terminal, such as the departure point, budget, dates, events to attend, and language restrictions.

[1340] Input: User's desired conditions (e.g., departure point: Tokyo, budget: 100,000 yen, dates: 3 days, event to attend: fireworks festival, language: avoid places where Japanese is not spoken).

[1341] Output: Sending input data from the terminal to the server.

[1342] Step 2:

[1343] The device sends the user's input data to the server, using the secure HTTPS protocol.

[1344] Input: The user's desired conditions entered into the terminal.

[1345] Output: The user's preference data sent to the server.

[1346] Step 3:

[1347] The server receives the data sent from the device and analyzes it using natural language processing technology (e.g., Python's NLTK).

[1348] Data processing: The received data is processed as text and conditions are extracted.

[1349] Input: User preference data received by the server.

[1350] Output: Parsed condition data (e.g., departure location='Tokyo', budget=100,000 yen, date=3 days, event='fireworks festival', language constraint='Japanese only').

[1351] Step 4:

[1352] The server retrieves travel-related information from an internal database based on the extracted condition data, including information on accommodations, transportation, restaurants, tourist attractions, and events.

[1353] Data processing: Performing database queries to retrieve relevant information.

[1354] Input: Parsed condition data.

[1355] Output: Travel-related information retrieved from the database.

[1356] Step 5:

[1357] The server uses a generative AI model (e.g., GPT-3) to generate an optimal travel plan, using a prompt.

[1358] Generative AI model: An example of a prompt sentence is, "Please create a travel plan for the user. The conditions are as follows: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend the fireworks festival, avoid places where Japanese is not spoken."

[1359] Data calculation: Input the prompt sentence and condition data into the generative AI model to generate a plan.

[1360] Input: Travel-related information retrieved from the database and a prompt statement.

[1361] Output: Generated itinerary (e.g., flight to New Chitose Airport, accommodation in Sapporo city, Odori Park, Sapporo TV Tower, and fireworks festival on the second night of the trip).

[1362] Step 6:

[1363] The server transmits the generated travel plan to the terminal, which displays the detailed plan to the user.

[1364] Input: The generated itinerary.

[1365] Output: The itinerary presented to the user.

[1366] Step 7:

[1367] The user inputs feedback on the presented travel plan through the terminal. If the user is not satisfied, he / she can modify the conditions and resubmit the plan.

[1368] Input: User feedback and correction criteria.

[1369] Output: Corrected data resent from the terminal.

[1370] Step 8:

[1371] The server re-analyzes the retransmitted data and presents the regenerated itinerary to the user.

[1372] Input: Resubmitted corrected data.

[1373] Data processing and calculation: Regenerate plans using data analysis and AI models.

[1374] Output: The regenerated itinerary.

[1375] Step 9:

[1376] The device uses sensors and software (e.g., facial recognition technology and voice analysis technology) to recognize the user's emotions, determines their emotional state, and sends the data to a server.

[1377] Input: User operations, facial expressions, and voice data.

[1378] Output: Parsed emotion data.

[1379] Step 10:

[1380] The server analyzes the emotional data sent by the emotion engine and adjusts the travel plan and presentation accordingly: if the emotion is positive, the plan is emphasized, and if the emotion is negative, alternatives are presented.

[1381] Input: Parsed emotion data.

[1382] Data processing: Plan adjustment based on the results of the emotional state assessment.

[1383] Output: Adjusted travel plan or alternatives.

[1384] The above is the specific processing flow of this system.

[1385] (Application example 2)

[1386] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1387] Conventional food delivery systems have difficulty providing optimal food plans based on a user's emotional state. Furthermore, generating a plan that matches a user's preferences requires considering many factors, which makes the process complicated and burdensome for users. Therefore, there is a need for the development of a food delivery system that is easy for users to use and provides optimal plans based on their emotional state.

[1388] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for providing a user interface through which the user inputs desired conditions regarding food type, budget, and delivery time; an analysis means for analyzing the input data and extracting conditions that match the user's preferences; an emotion recognition means for recognizing the user's emotional state using facial recognition technology; a generation means for generating an optimal food plan based on the extracted conditions and emotional state; a means for presenting the generated food plan to the user; and a means for modifying and regenerating the food plan based on feedback from the user. This makes it possible to provide a fast and appropriate food delivery plan that also takes into account the user's emotional state.

[1389] A "user interface" is a means of providing a screen or input form for users to perform operations.

[1390] The "analysis means" is a function that analyzes the input data and extracts conditions that match the user's preferences.

[1391] "Emotion recognition means" is a technology for recognizing the emotional state of a user using face recognition technology.

[1392] The "generator" is a function that generates an optimal food plan based on the extracted conditions and emotional state.

[1393] "Presentation means" refers to a function that presents the generated food plan to the user.

[1394] A "modification tool" is a tool that has the ability to modify and regenerate a food plan based on user feedback.

[1395] A "food plan" is a selection of food and dining options generated based on a user's preferences and emotional state.

[1396] A "database" is an information storage system that stores information such as restaurant and event information and uses it as needed.

[1397] "Emotional state" refers to the user's emotional state, and is information detected using technologies such as facial recognition and voice analysis.

[1398] "Feedback" refers to the evaluation or opinion that a user gives regarding the information or plans provided.

[1399] A novel system for implementing this invention is designed to provide food delivery services to users. The system combines a user interface, an analysis means, an emotion recognition means, a generation means, a presentation means, and a modification means.

[1400] User Interface

[1401] The terminal provides an interface for users to input their desired conditions regarding food type, budget, and delivery time. Specifically, users can input their food delivery preferences through an input form displayed on the smartphone application screen.

[1402] Analysis means

[1403] The server receives the input data sent from the device and analyzes it using natural language processing technology. This allows it to understand the desired conditions entered by the user and store each condition, such as food type and budget, in the appropriate variables. The software used is Hugging Face Transformers, a natural language processing software.

[1404] emotion recognition means

[1405] The device uses a webcam or smartphone camera to recognize the user's emotions. It uses facial recognition technology to capture the user's face in real time and analyzes their emotional state using Hugging Face's emotion analysis model. This allows it to recognize the user's emotions as states such as "happy" or "unhappy."

[1406] generation means

[1407] The server generates an optimal meal plan based on the analyzed data and emotion recognition results. To do this, it references a database of restaurant and event information and uses a generative AI model to suggest the most suitable foods and restaurants for the user. The generative AI model receives prompts based on the user's desired conditions and emotional state, and customizes the suggestions accordingly.

[1408] Presentation means

[1409] The server sends the generated meal plan to the device, which displays it to the user, who can then check the proposed meal plan and detailed information about the selected restaurant through a smartphone application.

[1410] Correction means

[1411] The user can provide feedback on the presented meal plan. For example, they can input their opinion such as, "This restaurant doesn't suit my mood." Based on that feedback, the server analyzes the data again and regenerates a new meal plan that matches their conditions and emotional state.

[1412] Specific examples

[1413] For example, if a user inputs "My budget is under 2,000 yen and I want to eat pizza," and the facial image captured by the webcam is recognized as "happy," the server will consider the user's positive emotional state and suggest restaurants that offer the best pizza within their budget. Examples of prompt sentences are as follows:

[1414] Prompt statement:

[1415] A user enters "I want to eat pizza within 2,000 yen." Emotion analysis is performed on the facial image captured by the webcam, and the result is recognized as "happy." Based on this, what is the best food and restaurant for the user?

[1416] This system allows users to easily receive the optimal food delivery plan that takes their emotional state into consideration.

[1417] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1418] Step 1:

[1419] The terminal provides an interface for the user to input desired conditions regarding food type, budget, and delivery time. When the user inputs these conditions, the data is sent from the terminal to the server. The input here includes food type (e.g., pizza), budget (e.g., 2,000 yen), and delivery time (e.g., within 30 minutes). This input data is passed to the next processing step.

[1420] Step 2:

[1421] The server receives the input data sent from the terminal and analyzes the data using analytical means. Through this analysis, the user's desired conditions are understood and stored in the appropriate variables. For example, natural language processing is used to extract "food_type: pizza" from the input "pizza," and to obtain "budget: 2000" from "budget: 2,000 yen." The analysis results are passed to the next processing step.

[1422] Step 3:

[1423] To recognize the user's emotions, the device activates the webcam and captures a facial image. The captured facial image is analyzed by an emotion recognition means, and the user's emotional state is recognized as "happy" or "unhappy." For example, the facial image is analyzed using the Hugging Face emotion analysis model, and the result is "Emotional state: happy." This emotional state data is passed to the next processing step.

[1424] Step 4:

[1425] The server uses a generative means to generate an optimal meal plan based on the analysis results and the user's emotional state. The server sends the input desired conditions and emotional state as prompts to the generative AI model, which retrieves relevant restaurant and menu information from the database and proposes a meal plan that suits the user. For example, based on "food_type: pizza," "budget: 2000," and "emotional state: happy," the generative AI model recommends the optimal pizza restaurant and specific menu (e.g., Margherita pizza). This generated result is passed to the next processing step.

[1426] Step 5:

[1427] The server sends the generated food plan to the terminal through the presentation means, and the terminal displays the detailed plan to the user on the screen. The user can check the presented food plan (e.g., Margherita pizza, XX pizza restaurant), select and rate it. This displayed information is passed to the next processing step.

[1428] Step 6:

[1429] The user provides feedback on the presented food plan, and that feedback is sent from the device to the server. For example, if the user enters an opinion such as "I don't feel like going to this restaurant," that data is passed to the server. This feedback data is then passed to the next processing step.

[1430] Step 7:

[1431] The server analyzes the user's feedback data and uses the corrective measures to regenerate a new meal plan, taking into account the user's original preferences and emotional state. It then incorporates the previous feedback and uses the database and generative AI model again to generate new suggestions, e.g., re-recommend the next best pizza place and menu item based on the user's new feedback. This new meal plan then returns to step 5 and is displayed again for presentation to the user.

[1432] This specific process allows users to conveniently receive food delivery plans that reflect their emotional state in real time.

[1433] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1434] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1435] 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 the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1436] [Fourth embodiment]

[1437] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1438] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1439] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1440] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1441] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1442] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1443] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1444] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1445] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1446] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific 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.

[1447] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1448] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1449] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1450] MODE FOR CARRYING OUT THE INVENTION

[1451] The system of the present invention provides comprehensive support for efficient travel planning, and specific embodiments thereof will be described below.

[1452] Basic system configuration

[1453] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[1454] 1. User Interface

[1455] The device provides a screen and input form for users to enter their travel preferences, including interfaces for inputting items such as departure point, budget, dates, events they would like to attend, and language restrictions.

[1456] 2. Analysis method

[1457] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[1458] 3. Generation means

[1459] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[1460] 4. Presentation means

[1461] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[1462] 5. Corrective measures

[1463] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[1464] Program processing overview

[1465] The system operates as follows.

[1466] 1. Enter conditions via terminal

[1467] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[1468] 2. Data Transmission

[1469] The input data is transmitted from the terminal to the server.

[1470] 3. Data Analysis

[1471] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[1472] 4. Travel plan generation

[1473] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1474] Transportation: Plane to New Chitose Airport

[1475] Accommodation: Budget-friendly hotels in Sapporo

[1476] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1477] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1478] Event: Fireworks display held on the second night of the trip

[1479] 5. Plan presentation

[1480] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[1481] 6. Feedback and Regeneration

[1482] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1483] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[1484] The processing flow will be explained below.

[1485] Step 1:

[1486] The user inputs the desired travel conditions (place of departure, budget, dates, events to attend, language restrictions, etc.) on the terminal.

[1487] Step 2:

[1488] The terminal temporarily stores the travel conditions entered by the user and waits for the user to click the "Submit" button.

[1489] Step 3:

[1490] The user clicks the "Submit" button.

[1491] Step 4:

[1492] The terminal packages the entered travel condition data in a format such as JSON and sends it to the server.

[1493] Step 5:

[1494] The server begins analyzing the received data. Specifically, it uses natural language processing technology to interpret the data entered by the user and stores the data in variables.

[1495] Step 6:

[1496] The server extracts the user's desired conditions based on the analysis results and retrieves related information from the database based on these, including data on accommodation, transportation, restaurants, tourist spots, and event information necessary for generating a travel plan.

[1497] Step 7:

[1498] The server then uses the generative AI model to automatically generate an optimal travel plan based on the extracted preferences, including details such as transportation, accommodation, dining options, tourist spots, and event participation.

[1499] Step 8:

[1500] The server transmits the generated travel plan to the terminal.

[1501] Step 9:

[1502] The device displays the received itinerary on the user's screen, including the ability to clearly display each element of the itinerary (transportation, accommodation, meals, sightseeing spots, and events) in list and timeline format.

[1503] Step 10:

[1504] The user can review the proposed itinerary and make any necessary modifications or final approval, for example, if they want to change certain elements.

[1505] Step 11:

[1506] When the user modifies the plan, the modified conditions are retransmitted from the terminal to the server.

[1507] Step 12:

[1508] The server re-analyzes the modified conditions from the user and regenerates a new travel plan.

[1509] Step 13:

[1510] The server transmits the regenerated itinerary back to the terminal.

[1511] Step 14:

[1512] The terminal presents the regenerated travel plan to the user again, who then reviews it and makes a final confirmation.

[1513] Step 15:

[1514] When the user has finally decided on a plan that satisfies him, he clicks on the "Confirm" button.

[1515] Step 16:

[1516] The terminal transmits final plan confirmation information to the server.

[1517] Step 17:

[1518] The server stores the confirmed travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[1519] This is the specific flow of the process, which allows users to efficiently and stress-free obtain the optimal travel plan.

[1520] Example 1

[1521] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1522] Conventional travel planning systems require users to manually gather information on accommodations, transportation options, tourist attractions, and other topics by browsing multiple websites, which is a cumbersome process. It is also difficult to quickly and efficiently generate an optimal travel plan that reflects the user's requirements and preferences. Furthermore, when a user wants to provide feedback on a presented travel plan and change the requirements, it is difficult to instantly generate a new plan that reflects that feedback.

[1523] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1524] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, a generation means using a generative AI model to generate an optimal travel plan based on the extracted conditions, a means for presenting the generated travel plan to the user, and a means for modifying and regenerating the travel plan based on feedback from the user. This allows users to efficiently and easily create travel plans within a single system and to instantly adjust the plans based on the feedback.

[1525] "User" means any individual or entity that uses the System to plan a trip.

[1526] "Travel preferences" refer to the requirements and wishes that travelers want to include in their travel plans, such as departure point, budget, dates, events they would like to attend, and language preference.

[1527] "User interface" refers to the means by which users can interact with a system, such as a screen or input form for entering travel preferences.

[1528] "Entered Data" means travel preference information provided by a User to the System through the User Interface.

[1529] "Analysis means" refers to a function or system that analyzes input data and extracts conditions that match the traveler's preferences.

[1530] The "generation means" refers to a function or system that generates an optimal travel plan based on the extracted conditions.

[1531] A "generative AI model" is an algorithm or model that uses artificial intelligence technology to automatically generate optimal travel plans.

[1532] "Presentation means" refers to a function or system that visually or electronically presents the generated itinerary to the user.

[1533] "Feedback" refers to information that a user inputs into the system, such as opinions or requests for modifications to a presented travel plan.

[1534] "Modification" refers to a function or system that modifies and regenerates a travel plan based on user feedback.

[1535] "Accommodation" refers to a place of lodging such as a hotel, inn, or guesthouse where travelers can stay.

[1536] "Transportation" refers to the means of transportation used by travelers to travel to their destinations, such as airplanes, trains, buses, etc.

[1537] "Eating and drinking establishments" refer to places such as restaurants, cafes, and izakayas where travelers can eat.

[1538] A "tourist attraction" is a place for tourists to visit and see, such as a park, temple, or museum.

[1539] "Event information" refers to information about various events that can be participated in during a trip, such as concerts, festivals, and fireworks displays.

[1540] MODE FOR CARRYING OUT THE INVENTION

[1541] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system will be described below.

[1542] Basic system configuration

[1543] The system includes a user interface, an analyzing means, a generating means, a presenting means, and a modifying means.

[1544] 1. User Interface

[1545] The device provides a screen and input form for users to enter their desired travel conditions. Specifically, it includes an interface for entering items such as departure point, budget, dates, events they would like to attend, and language restrictions. The device can be a personal computer, smartphone, tablet, or other device.

[1546] 2. Analysis method

[1547] The server receives the input data sent from the device and analyzes it using natural language processing technology. This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables. The software used includes a Python natural language processing library and API.

[1548] 3. Generation means

[1549] The server retrieves the necessary information from a database based on the analyzed data. This includes information on accommodations, transportation options, restaurants, tourist attractions, and event information. It then uses a generative AI model to automatically generate an optimal travel plan. The system uses high-performance servers as hardware and software such as TensorFlow and PyTorch.

[1550] 4. Presentation means

[1551] The server sends the generated travel plan to the terminal, which then displays the detailed plan to the user. The user can then check the specific schedule of the trip based on this. The display interface can be a web browser or a dedicated application.

[1552] 5. Corrective measures

[1553] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[1554] Program processing overview

[1555] The system operates as follows.

[1556] 1. Enter conditions via terminal

[1557] The user inputs the desired conditions for the trip into an input form on the terminal. For example, the user might input a prompt such as, "The departure point is Tokyo, the budget is up to 100,000 yen, I would like to travel for three days, I would like to attend a fireworks festival, and I would like to go somewhere where I can speak Japanese."

[1558] 2. Data Transmission

[1559] The input data is transmitted from the terminal to the server.

[1560] 3. Data Analysis

[1561] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[1562] 4. Travel plan generation

[1563] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1564] Transportation: Fly from Tokyo to New Chitose Airport

[1565] Accommodation: Budget-friendly hotels in Sapporo

[1566] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1567] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1568] Event: Fireworks display held on the second night of the trip

[1569] 5. Plan presentation

[1570] The server sends the generated plan to the terminal, which displays it to the user, who can then check the detailed schedule and each element.

[1571] 6. Feedback and Regeneration

[1572] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1573] The above embodiment allows users to plan their trips efficiently and stress-free. The entire system is designed to be user-friendly and to respond quickly to user needs.

[1574] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1575] Step 1:

[1576] The user inputs desired travel conditions. Specifically, they input specific conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Place where Japanese is spoken" into the input form on the device. This input becomes the "prompt sentence." The input data is temporarily stored in the device's memory.

[1577] Step 2:

[1578] The device sends the entered travel conditions to the server. When sending the data, the input data is converted to JSON format. The input at this time is the user's desired conditions, and the output is JSON format data sent to the server.

[1579] Step 3:

[1580] The server receives JSON format data from the terminal. The received data is stored in the server's memory. The input is JSON data, and the output indicates that the data was received successfully.

[1581] Step 4:

[1582] The server analyzes the received data using natural language processing technology. Specifically, it uses a Python natural language processing library to convert JSON-formatted data into variables. This analysis extracts conditions such as "departure point," "budget," "schedule," "event," and "language." In this step, the input data is the received JSON data, and the output is the analyzed condition data.

[1583] Step 5:

[1584] The server retrieves the necessary information from a database based on the analyzed data. The database in this case includes information on accommodations, transportation, restaurants, tourist attractions, and events. The specific operation of retrieving data is performed using SQL queries. The input is the analyzed condition data, and the output is the retrieved database information.

[1585] Step 6:

[1586] The server uses a generative AI model based on the acquired information and analysis results to generate an optimal travel plan. The AI ​​model (built with TensorFlow and PyTorch) automatically generates an optimal plan that meets the user's requirements. For example, it includes accommodation, transportation, tourist spots, and event participation schedules. The input is information acquired from the database, and the output is the generated travel plan.

[1587] Step 7:

[1588] The server converts the generated travel plan into JSON format and sends it to the terminal. The input here is the generated travel plan, and the output is JSON format data sent to the terminal.

[1589] Step 8:

[1590] The terminal displays the received itinerary to the user. Specifically, it displays a detailed itinerary using a GUI, allowing the user to check each element. In this step, the input data is the JSON-formatted itinerary received from the server, and the output is a visually displayed itinerary for the user.

[1591] Step 9:

[1592] The user inputs feedback about the presented travel plan into the terminal. Specifically, the user inputs a request for modification, such as "I would like the accommodation to be more luxurious." The input is the user's feedback, and the output is the feedback data stored on the terminal.

[1593] Step 10:

[1594] The terminal sends feedback data to the server. The feedback content is converted to JSON format and sent to the server. The input of this step is feedback data, and the output is JSON-formatted feedback data sent to the server.

[1595] Step 11:

[1596] The server re-analyzes the received feedback data and re-generates the itinerary based on the modification requests, again using a generative AI model. The input for the re-analysis and re-generation is the feedback data, and the output is the re-generated itinerary.

[1597] Step 12:

[1598] The server sends the regenerated itinerary to the terminal, and the terminal displays the regenerated itinerary to the user. The input of this step is the regenerated itinerary, and the output is the itinerary that is resent and displayed to the user.

[1599] This allows users to plan their trip efficiently and stress-free.

[1600] (Application example 1)

[1601] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1602] Conventional travel planning systems require users to manually create travel plans, which takes a lot of time and effort, making the planning process itself cumbersome. Furthermore, it is difficult to automatically generate an optimal plan that meets the user's desired conditions, and it is not easy to regenerate the plan to reflect feedback. These issues also make it difficult to keep the information up-to-date and optimal.

[1603] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1604] In this invention, the server includes a means for providing a user interface through which a user inputs desired travel conditions, an analysis means for extracting conditions using natural language processing technology to analyze the input data, and a generation means for generating an optimal travel plan using a generative AI model. This makes it possible to automatically and efficiently generate an optimal travel plan based on the desired conditions input by the user, and to regenerate it based on user feedback.

[1605] A "user interface" is an operating means such as a screen or input form that allows a user to input or give instructions to a system.

[1606] "Natural language processing technology" is a technology that allows a server to understand and analyze the language that people use on a daily basis.

[1607] The "analysis means for extracting conditions" is a means for analyzing input data using natural language processing technology and extracting predetermined conditions.

[1608] A "generative AI model" is an artificial intelligence model that automatically generates optimal travel plans based on given conditions.

[1609] An "optimal travel plan" is a travel schedule and proposal that takes into maximum consideration the user's desired conditions.

[1610] The "generation means" is a means for creating a travel plan based on the extracted conditions using a generative AI model.

[1611] "Feedback" refers to evaluations and requests for modifications to the generated travel plan provided by the user.

[1612] "Regeneration" refers to recreating a travel plan based on feedback.

[1613] MODE FOR CARRYING OUT THE INVENTION

[1614] Basic system configuration

[1615] The system of the present invention provides comprehensive support for users to efficiently plan their travels. Specific embodiments of the system are described below.

[1616] Hardware and software used

[1617] Hardware: Smartphones, servers

[1618] Software: smartphone apps, server-side programs (e.g., Python, Node.js), databases (e.g., MySQL, PostgreSQL), natural language processing libraries (e.g., spaCy, NLTK), generative AI models (e.g., GPT-3)

[1619] User Interface

[1620] The user interface provides a screen and input form for users to enter their desired travel conditions. Specifically, it is designed to allow users to easily enter items such as "place of departure," "budget," "date," "events they want to attend," and "language restrictions" on their smartphones.

[1621] Data transmission and analysis

[1622] When a user enters travel conditions, the data is sent from the smartphone to a server. The server then analyzes the received data using natural language processing technology to extract conditions. This analysis is performed using natural language processing libraries such as spaCy and NLTK. For example, related event information can be extracted from the condition "events I want to attend."

[1623] Generate a travel plan

[1624] Based on the analysis results, the server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from a database. Based on the retrieved data, the server automatically generates an optimal travel plan using a generative AI model (such as GPT-3). This generation method provides a travel plan that best suits the user's requirements.

[1625] Examples of prompt statements

[1626] "Departure point: Tokyo

[1627] Budget: 100,000 yen

[1628] Duration: 3 days

[1629] Events I'd like to attend: Fireworks displays

[1630] Language restrictions: Avoid places where Japanese is not available

[1631] Generate the best itinerary for you.

[1632] Plan presentation and feedback

[1633] The generated travel plan is sent from the server to a smartphone app and presented to the user, who can then review the plan, which includes a detailed schedule and suggestions.

[1634] If a user is not satisfied with the travel plan presented to them, they can modify the conditions and resubmit them from their smartphone to the server. The server then analyzes the data and generates a new plan based on the modified data received. By repeating this process, the optimal travel plan is provided to the user.

[1635] Specific examples

[1636] As an example, consider the case where a user inputs the following conditions:

[1637] "Departure point: Tokyo

[1638] Budget: 100,000 yen

[1639] Duration: 3 days

[1640] Events I'd like to attend: Fireworks displays

[1641] Language restrictions: Avoid places where Japanese is not available

[1642] The server analyzes this information and generates a travel plan that includes, for example, a flight to New Chitose Airport, a hotel in Sapporo, sightseeing at Odori Park and Asahiyama Zoo, and information about the fireworks display.

[1643] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1644] Step 1:

[1645] The user uses the device to input their travel preferences, including their departure point, budget, dates, events they want to attend, language restrictions, etc. The device then collects the input data and prepares it.

[1646] Input: Travel conditions data entered by the user (origin, budget, schedule, events, language restrictions)

[1647] Output: Collected travel condition data

[1648] Step 2:

[1649] The terminal transmits the collected travel condition data to the server, which stores the received data and prepares it for analysis.

[1650] Input: Collected travel condition data

[1651] Output: Travel conditions data sent to the server

[1652] Step 3:

[1653] The server analyzes the received data using natural language processing technology, extracting each condition and storing it in the appropriate variable.

[1654] Input: Travel conditions data sent to the server

[1655] Output: Parsed condition variable data (departure point, budget, schedule, events, language constraints)

[1656] Specific operation: Using spaCy or NLTK, natural language processing techniques are used to extract conditions such as event information from input data.

[1657] Step 4:

[1658] The server retrieves information on accommodations, transportation, restaurants, tourist spots, and events from the database based on the analysis results, stores the retrieved data, and prepares it for use in the next step.

[1659] Input: Variable data for the parsed condition

[1660] Output: Travel-related information obtained from the database (accommodation, transportation, restaurants, tourist spots, event information)

[1661] Specific operation: The server uses MySQL or PostgreSQL to query the database to obtain the relevant information.

[1662] Step 5:

[1663] The server generates an optimal travel plan using a generative AI model (such as GPT-3) based on the acquired data, stores the generated plan, and prepares it for presentation to the user.

[1664] Input: Acquired travel-related information

[1665] Output: Optimal travel plan

[1666] Specific operation: Input conditions into the generative AI model in the form of a prompt sentence to generate the optimal plan. For example,

[1667] "Departure point: Tokyo

[1668] Budget: 100,000 yen

[1669] Duration: 3 days

[1670] Events I'd like to attend: Fireworks displays

[1671] Language restrictions: Avoid places where Japanese is not available

[1672] Generate the best itinerary for you.

[1673] Step 6:

[1674] The server sends the generated travel plan to the terminal, which then displays the received plan to the user.

[1675] Input: Generated itinerary

[1676] Output: Trip plan sent to the device

[1677] Specific operation: The server sends the generated travel plan to the terminal in JSON format, etc., and the terminal parses it and displays it on the user interface.

[1678] Step 7:

[1679] If the user is not satisfied with the presented travel plan, he / she can modify the conditions and resend them from the terminal to the server. The server will then analyze the data and generate a new plan based on the modified data received.

[1680] Input: User feedback and revised conditions

[1681] Output: Regenerated itinerary

[1682] Specific operation: The device sends the re-entered condition data to the server, which analyzes it and regenerates a new plan using the AI ​​model.

[1683] This series of steps allows users to plan their trip efficiently and optimally.

[1684] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1685] MODE FOR CARRYING OUT THE INVENTION

[1686] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. Specific embodiments of the system will be described below.

[1687] Basic system configuration

[1688] The system includes a user interface, an analysis means, a generation means, a presentation means, a modification means, and an emotion engine.

[1689] 1. User Interface

[1690] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[1691] 2. Analysis method

[1692] The server receives the input data sent from the device and analyzes it using natural language processing technology. Through this analysis, it understands the travel conditions entered by the user and stores the data in appropriate variables.

[1693] 3. Generation means

[1694] Based on the analyzed data, the server retrieves necessary information from a database, including information on accommodations, transportation options, restaurants, tourist attractions, and events, and then uses a generative AI model to automatically generate an optimal travel plan.

[1695] 4. Presentation means

[1696] The server sends the generated travel plan to the terminal, and the terminal displays the detailed plan to the user, allowing the user to check the specific schedule of the trip.

[1697] 5. Corrective measures

[1698] If the user is not satisfied with the proposed travel plan, he or she can modify the conditions and resubmit the plan. In this case, the modified data is sent via the terminal to the server, which then analyzes and regenerates the plan.

[1699] 6. Emotion Engine

[1700] The device will have sensors and software to recognize the user's emotional state, using facial recognition and voice analysis technology, as well as analyzing input data and user operation patterns.

[1701] The server analyzes the emotional data sent from the emotion engine and evaluates the user's positive or negative emotions. Based on the user's emotional state, the server adjusts the content and method of presenting the plan to the user.

[1702] Program processing overview

[1703] The system operates as follows.

[1704] 1. Enter conditions via terminal

[1705] The user enters conditions such as "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken" into the input form on the device.

[1706] 2. Data Transmission

[1707] The input data is transmitted from the terminal to the server.

[1708] 3. Data Analysis

[1709] The server analyzes the received data, extracts the user's desired conditions, and uses natural language processing technology to convert the conditions into appropriate variables and obtain the analysis results.

[1710] 4. Travel plan generation

[1711] The server retrieves relevant information from the database based on the analysis results and generates an optimal travel plan using a generative AI model. For example, the following plan may be generated:

[1712] Transportation: Plane to New Chitose Airport

[1713] Accommodation: Budget-friendly hotels in Sapporo

[1714] Dining options: Ramen restaurants and seafood izakayas in Sapporo

[1715] Tourist attractions: Odori Park, Sapporo TV Tower, Asahiyama Zoo

[1716] Event: Fireworks display held on the second night of the trip

[1717] 5. Plan presentation

[1718] The server sends the generated plan to the terminal, and the terminal displays the detailed plan to the user, who can then check the detailed schedule and each element.

[1719] 6. Feedback and Regeneration

[1720] If the user is not satisfied with the plan, they can resubmit the revised conditions from their device, and the server will analyze and generate the plan again, providing the user with the optimal travel plan.

[1721] 7. Emotional Recognition and Regulation

[1722] The emotion engine recognizes the user's emotional state from their face, voice, and operation patterns, extracting positive and negative emotions.

[1723] The server evaluates the user's emotional state based on data from the emotion engine and adjusts the itinerary and its presentation accordingly, for example, highlighting the itinerary if the user is expressing positive emotions, or quickly presenting alternatives if the user is expressing negative emotions.

[1724] The above embodiments allow users to plan their trips efficiently and stress-free. Furthermore, by recognizing the user's emotional state and optimizing the plan, a more personalized user experience is realized. The entire system is designed to be user-friendly and can quickly and accurately respond to the user's needs and emotions.

[1725] The processing flow will be explained below.

[1726] Step 1:

[1727] The user inputs desired travel conditions (place of departure, budget, schedule, events to attend, language restrictions, etc.) on the terminal. For example, the user inputs the departure place "Tokyo," the budget "100,000 yen," the schedule "3 days," the event to attend "fireworks display," and the language restriction "avoid places where Japanese cannot be used."

[1728] Step 2:

[1729] The terminal temporarily stores the entered data and waits for the user to click the "Submit" button.

[1730] Step 3:

[1731] The user clicks the "Submit" button.

[1732] Step 4:

[1733] The terminal packages the input data in JSON format or similar and sends it to the server.

[1734] Step 5:

[1735] The server analyzes the received data, uses natural language processing technology to interpret the user's desired conditions, and stores the data in appropriate variables.

[1736] Step 6:

[1737] Based on the analysis results, the server retrieves relevant information from a database, including information on accommodation, transportation, restaurants, tourist attractions, and events.

[1738] Step 7:

[1739] The server uses a generative AI model to generate an optimal travel plan based on the acquired information, including details of flights to New Chitose Airport, hotels in Sapporo, dining options, tourist attractions, and events.

[1740] Step 8:

[1741] The server transmits the generated travel plan to the terminal.

[1742] Step 9:

[1743] The device displays the received travel plan on the user's screen, clearly showing each element in a list or timeline format.

[1744] Step 10:

[1745] The emotion engine evaluates the user's emotional state when a plan is presented, using facial recognition technology, voice analysis, and analysis of operation patterns to assess the user's emotions in real time.

[1746] Step 11:

[1747] The emotion engine sends the acquired emotion data to the server, such as whether the user is smiling or frowning when looking at the plan.

[1748] Step 12:

[1749] The server adjusts the presentation and content of the plan in real time based on the emotional data, for example, highlighting the plan if it detects positive emotions, or presenting alternatives if it detects negative emotions.

[1750] Step 13:

[1751] The user reviews the proposed itinerary and provides any necessary corrections or feedback, for example, if they want to change their accommodation.

[1752] Step 14:

[1753] The user enters the desired modifications into the terminal and resubmits.

[1754] Step 15:

[1755] The terminal transmits the modified data to the server.

[1756] Step 16:

[1757] The server then analyzes the retransmitted data again and generates a new itinerary based on the revised conditions, taking into account the evaluation results of the emotion engine.

[1758] Step 17:

[1759] The server transmits the regenerated itinerary back to the terminal.

[1760] Step 18:

[1761] The device will then present the regenerated plan to the user, who will then confirm it again.

[1762] Step 19:

[1763] The user makes a final confirmation and clicks the "Confirm" button to confirm the final plan.

[1764] Step 20:

[1765] The terminal transmits final plan confirmation information to the server.

[1766] Step 21:

[1767] The server stores the finalized travel plans and shares the information with relevant third parties (such as accommodation providers, transportation providers, and event organizers) as necessary.

[1768] These are the specific processing steps of the system combined with the emotion engine, which allows users to obtain efficient and individually optimized travel plans, and adjusts the plans according to their emotional state, improving the user experience.

[1769] Example 2

[1770] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1771] Current travel planning support systems can generate plans that reflect travelers' desired conditions, but they lack the ability to optimize plans based on user emotions or adjust them to meet individual needs. This can lead to lower user satisfaction and make travel planning stressful. Furthermore, the lack of a mechanism for effectively incorporating user feedback creates the problem of cumbersome, repeated plan revisions. The objective of the present invention is to solve these problems and improve the efficiency of travel planning and user satisfaction.

[1772] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1773] In this invention, the server includes means for providing a user interface through which a user inputs desired travel conditions, analysis means for analyzing the input data and extracting conditions that match the traveler's preferences, generation means for generating an optimal travel plan based on the extracted conditions, means for presenting the generated travel plan to the user, means including an emotion engine for recognizing the user's emotions, means for adjusting the travel plan and presentation method based on emotion data transmitted from the emotion engine, and means for correcting and regenerating the travel plan based on feedback from the user. This makes it possible to optimize the travel plan based on the user's desired conditions as well as their emotional state, and provide a highly satisfying travel plan.

[1774] "User Interface" means the means by which a user interacts directly with the system and inputs travel preferences.

[1775] "Analysis means" refers to a means that has the function of analyzing input data and extracting conditions that match the traveler's preferences.

[1776] "Generation means" refers to a means having the function of generating an optimal travel plan based on the extracted conditions.

[1777] "Presentation means" refers to a means that has the function of displaying and sharing the generated travel plan to the user.

[1778] An "emotion engine" refers to a system that includes sensors and analytical software to recognize user emotions and processes that data.

[1779] "Feedback" refers to the user's evaluation or opinion on the presented travel plan, and includes information that the system uses to revise the plan.

[1780] "Regeneration means" refers to a means that has the function of revising and generating a new travel plan based on user feedback and revision conditions.

[1781] "Database" refers to a system that stores and manages information necessary to generate travel plans, such as information on accommodations, transportation, restaurants, tourist attractions, and events.

[1782] MODE FOR CARRYING OUT THE INVENTION

[1783] Basic system configuration

[1784] The system of the present invention provides comprehensive support for efficient travel planning and further optimizes the plan by recognizing the user's emotions. To provide a superior user experience, the system is configured as follows:

[1785] 1. User Interface

[1786] The device provides a screen and input form for users to input their travel preferences, including an interface for inputting items such as departure point, budget, dates, events they wish to attend, and language restrictions.

[1787] 2. Analysis method

[1788] The server receives the input data sent from the device and analyzes it using natural language processing technology (NLTK or similar technology). This analysis allows it to understand the travel conditions entered by the user and store the data in appropriate variables.

[1789] 3. Generation means

[1790] The server generates a travel plan based on the analyzed data. It retrieves information on accommodation, transportation, restaurants, tourist attractions, and events from an internal database. It uses a generative AI model (e.g., GPT-3) to generate the optimal travel plan. Examples of prompts for the generative AI model include:

[1791] "Create a travel plan for the user. The conditions are: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend fireworks festivals, avoid places where Japanese is not spoken."

[1792] 4. Presentation means

[1793] The server sends the generated travel plan to the device, which then displays the detailed plan to the user, allowing the user to check the specific itinerary, including information on flights to New Chitose Airport, accommodations in Sapporo, tourist spots such as Odori Park and Sapporo TV Tower, and fireworks displays.

[1794] 5. Corrective measures

[1795] If the user is not satisfied with the proposed itinerary, he or she can modify the conditions and resubmit them from the terminal to the server, which will then analyze the modified conditions again and generate a new itinerary.

[1796] 6. Emotion Engine

[1797] The device is equipped with sensors and software to recognize the user's emotions, specifically using facial recognition technology (e.g., OpenCV) and voice analysis technology (e.g., Google Cloud Speech-to-Text API) to determine the user's emotional state.

[1798] The server analyzes the emotion data sent from the emotion engine and evaluates the user's emotional state. Based on the evaluation results, the server adjusts the travel plan and how it is presented. For example, if the user is expressing positive emotions, the server will emphasize the plan and present it, and if the user is expressing dissatisfaction, the server will quickly present alternative plans.

[1799] Specific examples

[1800] Let's say a user enters the following information into the input form on their device: "Departure point: Tokyo," "Budget: 100,000 yen," "Date: 3 days," "Event to attend: Fireworks festival," and "Language: Avoid places where Japanese is not spoken."

[1801] 1. Data transmission and analysis

[1802] This data is sent from the terminal to a server, where it is analyzed using natural language processing technology.

[1803] 2. Travel plan generation

[1804] Based on the analysis results, the server retrieves information from the database and generates a travel plan using a generative AI model. For example, the following results may be generated: a flight to New Chitose Airport, accommodation in Sapporo, Odori Park, Sapporo TV Tower, and a fireworks display to be held on the night of the second day of the trip.

[1805] 3. Plan Presentation and Emotion Recognition

[1806] The generated plan is sent to the device and displayed to the user. At the same time, the device's sensors recognize the user's emotions and transmit them to the server.

[1807] The server analyzes the emotion data to assess the user's positive or negative reaction, and adjusts the way the plan is presented depending on the emotion, offering alternatives if necessary.

[1808] In this way, the system provides optimal travel plans that take into account the user's desired conditions and emotional state, enabling users to plan their trips efficiently and stress-free.

[1809] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1810] Specific explanation of processing steps

[1811] Step 1:

[1812] The user enters desired travel conditions into an input form on the terminal, such as the departure point, budget, dates, events to attend, and language restrictions.

[1813] Input: User's desired conditions (e.g., departure point: Tokyo, budget: 100,000 yen, dates: 3 days, event to attend: fireworks festival, language: avoid places where Japanese is not spoken).

[1814] Output: Sending input data from the terminal to the server.

[1815] Step 2:

[1816] The device sends the user's input data to the server, using the secure HTTPS protocol.

[1817] Input: The user's desired conditions entered into the terminal.

[1818] Output: The user's preference data sent to the server.

[1819] Step 3:

[1820] The server receives the data sent from the device and analyzes it using natural language processing technology (e.g., Python's NLTK).

[1821] Data processing: The received data is processed as text and conditions are extracted.

[1822] Input: User preference data received by the server.

[1823] Output: Parsed condition data (e.g., departure location='Tokyo', budget=100,000 yen, date=3 days, event='fireworks festival', language constraint='Japanese only').

[1824] Step 4:

[1825] The server retrieves travel-related information from an internal database based on the extracted condition data, including information on accommodations, transportation, restaurants, tourist attractions, and events.

[1826] Data processing: Performing database queries to retrieve relevant information.

[1827] Input: Parsed condition data.

[1828] Output: Travel-related information retrieved from the database.

[1829] Step 5:

[1830] The server uses a generative AI model (e.g., GPT-3) to generate an optimal travel plan, using a prompt.

[1831] Generative AI model: An example of a prompt sentence is, "Please create a travel plan for the user. The conditions are as follows: departure point is Tokyo, budget is 100,000 yen, duration is 3 days, want to attend the fireworks festival, avoid places where Japanese is not spoken."

[1832] Data calculation: Input the prompt sentence and condition data into the generative AI model to generate a plan.

[1833] Input: Travel-related information retrieved from the database and a prompt statement.

[1834] Output: Generated itinerary (e.g., flight to New Chitose Airport, accommodation in Sapporo city, Odori Park, Sapporo TV Tower, and fireworks festival on the second night of the trip).

[1835] Step 6:

[1836] The server transmits the generated travel plan to the terminal, which displays the detailed plan to the user.

[1837] Input: The generated itinerary.

[1838] Output: The itinerary presented to the user.

[1839] Step 7:

[1840] The user inputs feedback on the presented travel plan through the terminal. If the user is not satisfied, he / she can modify the conditions and resubmit the plan.

[1841] Input: User feedback and correction criteria.

[1842] Output: Corrected data resent from the terminal.

[1843] Step 8:

[1844] The server re-analyzes the retransmitted data and presents the regenerated itinerary to the user.

[1845] Input: Resubmitted corrected data.

[1846] Data processing and calculation: Regenerate plans using data analysis and AI models.

[1847] Output: The regenerated itinerary.

[1848] Step 9:

[1849] The device uses sensors and software (e.g., facial recognition technology and voice analysis technology) to recognize the user's emotions, determines their emotional state, and sends the data to a server.

[1850] Input: User operations, facial expressions, and voice data.

[1851] Output: Parsed emotion data.

[1852] Step 10:

[1853] The server analyzes the emotional data sent by the emotion engine and adjusts the travel plan and presentation accordingly: if the emotion is positive, the plan is emphasized, and if the emotion is negative, alternatives are presented.

[1854] Input: Parsed emotion data.

[1855] Data processing: Plan adjustment based on the results of the emotional state assessment.

[1856] Output: Adjusted travel plan or alternatives.

[1857] The above is the specific processing flow of this system.

[1858] (Application example 2)

[1859] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1860] Conventional food delivery systems have difficulty providing optimal food plans based on a user's emotional state. Furthermore, generating a plan that matches a user's preferences requires considering many factors, which makes the process complicated and burdensome for users. Therefore, there is a need for the development of a food delivery system that is easy for users to use and provides optimal plans based on their emotional state.

[1861] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for providing a user interface through which the user inputs desired conditions regarding food type, budget, and delivery time; an analysis means for analyzing the input data and extracting conditions that match the user's preferences; an emotion recognition means for recognizing the user's emotional state using facial recognition technology; a generation means for generating an optimal food plan based on the extracted conditions and emotional state; a means for presenting the generated food plan to the user; and a means for modifying and regenerating the food plan based on feedback from the user. This makes it possible to provide a fast and appropriate food delivery plan that also takes into account the user's emotional state.

[1862] A "user interface" is a means of providing a screen or input form for users to perform operations.

[1863] The "analysis means" is a function that analyzes the input data and extracts conditions that match the user's preferences.

[1864] "Emotion recognition means" is a technology for recognizing the emotional state of a user using face recognition technology.

[1865] The "generator" is a function that generates an optimal food plan based on the extracted conditions and emotional state.

[1866] "Presentation means" refers to a function that presents the generated food plan to the user.

[1867] A "modification tool" is a tool that has the ability to modify and regenerate a food plan based on user feedback.

[1868] A "food plan" is a selection of food and dining options generated based on a user's preferences and emotional state.

[1869] A "database" is an information storage system that stores information such as restaurant and event information and uses it as needed.

[1870] "Emotional state" refers to the user's emotional state, and is information detected using technologies such as facial recognition and voice analysis.

[1871] "Feedback" refers to the evaluation or opinion that a user gives regarding the information or plans provided.

[1872] A novel system for implementing this invention is designed to provide food delivery services to users. The system combines a user interface, an analysis means, an emotion recognition means, a generation means, a presentation means, and a modification means.

[1873] User Interface

[1874] The terminal provides an interface for users to input their desired conditions regarding food type, budget, and delivery time. Specifically, users can input their food delivery preferences through an input form displayed on the smartphone application screen.

[1875] Analysis means

[1876] The server receives the input data sent from the device and analyzes it using natural language processing technology. This allows it to understand the desired conditions entered by the user and store each condition, such as food type and budget, in the appropriate variables. The software used is Hugging Face Transformers, a natural language processing software.

[1877] emotion recognition means

[1878] The device uses a webcam or smartphone camera to recognize the user's emotions. It uses facial recognition technology to capture the user's face in real time and analyzes their emotional state using Hugging Face's emotion analysis model. This allows it to recognize the user's emotions as states such as "happy" or "unhappy."

[1879] generation means

[1880] The server generates an optimal meal plan based on the analyzed data and emotion recognition results. To do this, it references a database of restaurant and event information and uses a generative AI model to suggest the most suitable foods and restaurants for the user. The generative AI model receives prompts based on the user's desired conditions and emotional state, and customizes the suggestions accordingly.

[1881] Presentation means

[1882] The server sends the generated meal plan to the device, which displays it to the user, who can then check the proposed meal plan and detailed information about the selected restaurant through a smartphone application.

[1883] Correction means

[1884] The user can provide feedback on the presented meal plan. For example, they can input their opinion such as, "This restaurant doesn't suit my mood." Based on that feedback, the server analyzes the data again and regenerates a new meal plan that matches their conditions and emotional state.

[1885] Specific examples

[1886] For example, if a user inputs "My budget is under 2,000 yen and I want to eat pizza," and the facial image captured by the webcam is recognized as "happy," the server will consider the user's positive emotional state and suggest restaurants that offer the best pizza within their budget. Examples of prompt sentences are as follows:

[1887] Prompt statement:

[1888] A user enters "I want to eat pizza within 2,000 yen." Emotion analysis is performed on the facial image captured by the webcam, and the result is recognized as "happy." Based on this, what is the best food and restaurant for the user?

[1889] This system allows users to easily receive the optimal food delivery plan that takes their emotional state into consideration.

[1890] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1891] Step 1:

[1892] The terminal provides an interface for the user to input desired conditions regarding food type, budget, and delivery time. When the user inputs these conditions, the data is sent from the terminal to the server. The input here includes food type (e.g., pizza), budget (e.g., 2,000 yen), and delivery time (e.g., within 30 minutes). This input data is passed to the next processing step.

[1893] Step 2:

[1894] The server receives the input data sent from the terminal and analyzes the data using analytical means. Through this analysis, the user's desired conditions are understood and stored in the appropriate variables. For example, natural language processing is used to extract "food_type: pizza" from the input "pizza," and to obtain "budget: 2000" from "budget: 2,000 yen." The analysis results are passed to the next processing step.

[1895] Step 3:

[1896] To recognize the user's emotions, the device activates the webcam and captures a facial image. The captured facial image is analyzed by an emotion recognition means, and the user's emotional state is recognized as "happy" or "unhappy." For example, the facial image is analyzed using the Hugging Face emotion analysis model, and the result is "Emotional state: happy." This emotional state data is passed to the next processing step.

[1897] Step 4:

[1898] The server uses a generative means to generate an optimal meal plan based on the analysis results and the user's emotional state. The server sends the input desired conditions and emotional state as prompts to the generative AI model, which retrieves relevant restaurant and menu information from the database and proposes a meal plan that suits the user. For example, based on "food_type: pizza," "budget: 2000," and "emotional state: happy," the generative AI model recommends the optimal pizza restaurant and specific menu (e.g., Margherita pizza). This generated result is passed to the next processing step.

[1899] Step 5:

[1900] The server sends the generated food plan to the terminal through the presentation means, and the terminal displays the detailed plan to the user on the screen. The user can check the presented food plan (e.g., Margherita pizza, XX pizza restaurant), select and rate it. This displayed information is passed to the next processing step.

[1901] Step 6:

[1902] The user provides feedback on the presented food plan, and that feedback is sent from the device to the server. For example, if the user enters an opinion such as "I don't feel like going to this restaurant," that data is passed to the server. This feedback data is then passed to the next processing step.

[1903] Step 7:

[1904] The server analyzes the user's feedback data and uses the corrective measures to regenerate a new meal plan, taking into account the user's original preferences and emotional state. It then incorporates the previous feedback and uses the database and generative AI model again to generate new suggestions, e.g., re-recommend the next best pizza place and menu item based on the user's new feedback. This new meal plan then returns to step 5 and is displayed again for presentation to the user.

[1905] This specific process allows users to conveniently receive food delivery plans that reflect their emotional state in real time.

[1906] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1907] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1908] 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 the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1909] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1910] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1911] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1912] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1913] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1914] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1915] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1916] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1917] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1918] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1919] 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.

[1920] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1921] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1922] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1923] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1924] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1925] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1926] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1927] The following is further disclosed regarding the above embodiment.

[1928] (Claim 1)

[1929] means for providing a user interface for inputting travel requirements;

[1930] An analysis means for analyzing the input data and extracting conditions that match the traveler's preferences;

[1931] A generation means for generating an optimal travel plan based on the extracted conditions;

[1932] means for presenting the generated travel plan to a user;

[1933] a means of modifying and regenerating itineraries based on user feedback;

[1934] A system including:

[1935] (Claim 2)

[1936] 2. The system according to claim 1, wherein a database of accommodation, transportation, restaurants, tourist spots and event information is used to generate the travel plan.

[1937] (Claim 3)

[1938] 10. The system of claim 1, further comprising means for providing a user interface that allows the user to modify and resubmit the proposed itinerary if the user is not satisfied with the proposed itinerary.

[1939] "Example 1"

[1940] (Claim 1)

[1941] means for providing a user interface for inputting travel requirements;

[1942] An analysis means for analyzing the input data and extracting conditions that match the traveler's preferences;

[1943] A generation means using a generative AI model that generates an optimal travel plan based on the extracted conditions;

[1944] means for presenting the generated travel plan to a user;

[1945] a means of modifying and regenerating itineraries based on user feedback;

[1946] A system including:

[1947] (Claim 2)

[1948] 2. The system according to claim 1, wherein a database of accommodation, transportation, restaurants, tourist spots and event information is used to generate the travel plan.

[1949] (Claim 3)

[1950] 10. The system of claim 1, further comprising means for providing a user interface that allows the user to modify and resubmit the proposed itinerary if the user is not satisfied with the proposed itinerary.

[1951] "Application Example 1"

[1952] (Claim 1)

[1953] means for providing a user interface for inputting travel requirements;

[1954] an analysis means for extracting conditions using natural language processing technology that analyzes input data;

[1955] A generation means for generating an optimal travel plan using an AI model that generates a travel plan based on the extracted conditions;

[1956] means for presenting the generated travel plan to a user;

[1957] a means of modifying and regenerating itineraries based on user feedback;

[1958] A system including:

[1959] (Claim 2)

[1960] 2. The system according to claim 1, wherein a database of accommodation, transportation, restaurants, tourist spots and event information is used to generate the travel plan.

[1961] (Claim 3)

[1962] 10. The system of claim 1, further comprising means for providing a user interface that allows the user to modify and resubmit the proposed itinerary if the user is not satisfied with the proposed itinerary.

[1963] "Example 2: Combining Emotion Engines"

[1964] (Claim 1)

[1965] means for providing a user interface for inputting travel requirements;

[1966] An analysis means for analyzing the input data and extracting conditions that match the traveler's preferences;

[1967] A generation means for generating an optimal travel plan based on the extracted conditions;

[1968] means for presenting the generated travel plan to a user;

[1969] means including an emotion engine for recognizing an emotion of a user;

[1970] a means for adjusting the travel plan and presentation based on the emotion data sent from the emotion engine;

[1971] a means of modifying and regenerating itineraries based on user feedback;

[1972] A system including:

[1973] (Claim 2)

[1974] 2. The system according to claim 1, wherein a database of accommodation, transportation, restaurants, tourist spots and event information is used to generate the travel plan.

[1975] (Claim 3)

[1976] 10. The system of claim 1, further comprising means for providing a user interface that allows a user to modify and resubmit a proposed itinerary if the user is not satisfied with the proposed itinerary.

[1977] "Application example 2 when combining emotion engines"

[1978] (Claim 1)

[1979] means for providing a user interface for inputting preferences regarding food type, budget, and delivery time;

[1980] an analysis means for analyzing the input data and extracting conditions that match the user's preferences;

[1981] emotion recognition means for recognizing the emotional state of a user using facial recognition technology;

[1982] generating means for generating an optimal food plan based on the extracted conditions and emotional state;

[1983] a means for presenting the generated food plan to the user;

[1984] A means to modify and regenerate food plans based on user feedback;

[1985] A system including:

[1986] (Claim 2)

[1987] 10. The system of claim 1, wherein a database of restaurant and event information is used to generate the food plan.

[1988] (Claim 3)

[1989] 10. The system of claim 1, further comprising means for providing a user interface that allows the user to modify and resubmit the proposed food plan if the user is not satisfied with the plan. [Explanation of symbols]

[1990] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for providing a user interface for inputting travel requirements; An analysis means for analyzing the input data and extracting conditions that match the traveler's preferences; A generation means for generating an optimal travel plan based on the extracted conditions; means for presenting the generated travel plan to a user; a means of modifying and regenerating itineraries based on user feedback; A system including:

2. 2. The system according to claim 1, wherein a database of accommodations, transportation, restaurants, tourist spots, and event information is used to generate the travel plan.

3. 2. The system of claim 1, further comprising means for providing a user interface that allows the user to modify and resubmit the proposed itinerary if the user is not satisfied with the proposed itinerary.

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