System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting information relating to transportation timetables, availability status, tourist spots, food and drink information, and experiences; means for integrating and filtering the information; means for receiving a request from a user; means for generating an optimal travel plan from the integrated and filtered information based on the request; and means for providing the optimal travel plan to the user.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] The problem that this invention aims to solve is to provide a fulfilling and satisfying travel experience by reducing the burden of prior research that users face when planning trips and sightseeing, and by reducing unexpected problems during the trip. Traditionally, travel planning requires manually searching and organizing each piece of information, which requires a great deal of time and effort. In addition, the quality and reliability of the information obtained varies, often resulting in a dissatisfied travel experience. [Means for solving the problem]

[0005] The present invention automatically collects data on transportation timetables, operation status, tourist attractions, food and drink information, and travel experiences, and provides a means for integrating and filtering this data to enable easy access for users. It also provides a generation means for receiving user requests and generating optimal travel plans using a generation AI, which it then provides to the user. Furthermore, the system provides a means for generating individually customized plans based on the user's past behavioral history and preferences, and a means for reflecting user feedback information in the next plan generation, thereby improving user satisfaction.

[0006] "Transportation timetables" are information that lists the dates and times of arrival and departure of transportation such as trains, buses, and airplanes.

[0007] "Operation status" refers to information such as whether transportation is operating normally, whether there are delays or cancellations, etc.

[0008] "Tourist attractions" refer to major tourist destinations, historical sites, natural landscapes, theme parks, etc.

[0009] "Food and beverage information" refers to information about food-providing establishments such as restaurants, cafes, and bars, including recommended menus and reviews.

[0010] "Experience stories" refer to writings and reviews that describe the experiences other users have had while traveling or sightseeing.

[0011] "User Request" refers to the requests and wishes that a User enters into the System to plan their travel or sightseeing trips.

[0012] "Generative AI" refers to artificial intelligence technology that analyzes large amounts of data and generates optimal outputs (in this case, travel plans).

[0013] A "Travel Plan" is a plan created based on a User's requested destination and time period, including tourist attractions to visit, transportation options, dining options, etc.

[0014] "Feedback information" refers to the ratings and impressions provided by users based on their actual travel and sightseeing experiences. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The present invention is a system that allows users to save a lot of time and effort when planning trips and sightseeing, and provides a fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user, each of which plays a specific role.

[0037] Server Roles and Operations

[0038] Data collection and integration

[0039] The server first crawls data sources on the Internet, collecting information such as transportation timetables, service status, tourist attractions, food and drink information, and travel experiences. After collecting this data, it stores it in a database. Next, it integrates the collected data and converts it into a consistent format. In the process, it filters out duplicates and noise data to create a high-quality dataset.

[0040] Accepting and parsing requests

[0041] The server receives user requests from the device, including destination, travel duration, activities of interest, etc. The server analyzes these requests and retrieves the necessary data based on them.

[0042] Plan generation by generative AI

[0043] The server is equipped with a generation AI that generates the optimal travel plan for the user based on the analyzed request, including transportation, tourist spots to visit, places to eat, dates, etc. It also reflects the user's past behavioral history and preferences to provide an individually customized plan.

[0044] Providing plans to users and receiving feedback

[0045] The generated plan is provided to the user via the device. After the user has completed their trip, they can provide feedback, which will be reflected in the next plan generation.

[0046] Device role and operation

[0047] Providing an interface

[0048] The terminal provides a user-friendly interface for easily entering requests, including a form for inputting destination, duration, and activities of interest.

[0049] Sending a request and receiving a plan

[0050] The user's request is sent from the device to the server, and the server generates a travel plan that is displayed to the user through the device. The plan includes the route on a map, photos of the places to visit, and detailed information.

[0051] User Roles and Actions

[0052] Entering a request

[0053] Users use the device's interface to input their travel and sightseeing preferences, such as "I want to visit cultural spots in Tokyo in three days."

[0054] Review and execute the plan

[0055] Users can review the plan sent from the server and customize it as needed, allowing them to have a travel experience that suits their preferences.

[0056] Providing Feedback

[0057] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries, further improving the accuracy of the system.

[0058] Specific examples

[0059] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0060] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0061] 2. The server receives the request and searches for data on Kyoto's tourist attractions and transportation options. The generative AI then creates the optimal travel plan.

[0062] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0063] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0064] 5. The user reviews the plan and customizes it as needed.

[0065] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[0066] In this way, the present invention improves the efficiency of users' travel planning and provides a fulfilling sightseeing experience.

[0067] The processing flow will be explained below.

[0068] Step 1: Data collection

[0069] The server crawls multiple data sources on the Internet, collecting information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports. This collected data is then stored in a database.

[0070] Step 2: Data integration and filtering

[0071] The server converts the collected data into a consistent format and filters out duplicates and noise data, resulting in a high-quality dataset.

[0072] Step 3: Providing a User Interface

[0073] The terminal provides an interface where users can enter their requests, including a form to enter their destination, travel duration, and activities of interest.

[0074] Step 4: Submitting the request

[0075] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[0076] Step 5: Accepting and parsing the request

[0077] The server receives and analyzes the request sent from the terminal, reading the request content (destination, period, interests) and searching for the necessary data.

[0078] Step 6: Generative AI generates a travel plan

[0079] The server's generation AI creates an optimal travel plan based on the analysis results, including transportation, sightseeing spots, dining options, and itinerary.

[0080] Step 7: Customize your plan

[0081] The server then customizes the generated travel plan based on the user's past behavior and preferences, providing the optimal plan for each user.

[0082] Step 8: Submit your plan

[0083] The server then sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format.

[0084] Step 9: Review and change your plan

[0085] The user can review the travel plan displayed on the device and customize it as needed. Any changes made by the user are sent back to the server, and a replanning request may be required.

[0086] Step 10: Trip execution and evaluation

[0087] The user then carries out the trip based on the provided plan. After completing the trip, the user provides feedback on their experience. This feedback is reflected in the generation of future plans.

[0088] The above is the specific program processing flow of the "Chat Travel" system.

[0089] Example 1

[0090] 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."

[0091] In today's world, users require a wide variety of information when planning trips and sightseeing. Individually researching information such as transportation timetables and service status, tourist spot information, restaurant information, and travel experiences in each location is extremely time-consuming and laborious. This makes it difficult for users to easily create optimal travel plans, and there are few systems that provide plans that reflect individual preferences and past travel history. Furthermore, there is a lack of systems that can utilize post-trip feedback to improve future plans. Given this background, there is a growing need for travel planning systems that can efficiently collect, integrate, and customize information, and incorporate feedback.

[0092] 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.

[0093] In this invention, the server includes: means for collecting information on transportation timetables, operation status, tourist attractions, dining information, and travel experiences; means for integrating and filtering the information; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered information based on the request; means for generating an optimal travel plan based on the user's request using a generative AI model; means for providing the generated optimal travel plan to the user; means for collecting feedback information from users and incorporating it into the generation of the next plan; and means for individually customizing the travel plan generated by the generation means based on the user's past behavioral history and preferences. This makes it possible to efficiently collect and integrate a wide range of information and provide an optimal travel plan tailored to individual preferences. Furthermore, by incorporating user feedback into the next travel plan, an even more accurate and personalized travel experience can be provided.

[0094] "Transportation timetables" are information about detailed schedules of public transportation, such as operating times, stops, and route information.

[0095] "Operation status" refers to real-time operation information such as whether transportation is currently operating, delays, or cancellations.

[0096] "Tourist attractions" are places of interest, famous landmarks, natural landscapes, facilities, etc. within an area that are expected to interest and attract tourists and visitors.

[0097] "Dining information" refers to information about dining facilities in the area, the types of food they offer, business information, ratings, and so on.

[0098] "Experiences" are records of impressions, reviews, and specific experiences of people who have visited a region or experienced a tourist spot in the past.

[0099] "Means of collecting information" refers to the methods and techniques used to obtain the necessary data from the Internet and other data sources and incorporate it into the system.

[0100] "Information integration and filtering measures" are techniques and processes used to organize collected information, remove duplicates and irrelevant data, and put it into an appropriate format.

[0101] "Means for receiving requests from users" refers to the interface through which users input their desired travel plans and the method for importing that data into the system.

[0102] "Means for generating optimal travel plans" refers to the process or technology that automatically assembles travel schedules, places to visit, transportation methods, etc. based on collected and integrated data and user requests.

[0103] A "generative AI model" is an algorithm or system that uses artificial intelligence to automatically generate optimal travel plans based on user requests.

[0104] The "means provided to users" refers to interfaces and technologies that allow users to easily view and use the generated travel plans.

[0105] "Means for collecting and reflecting feedback information" refers to the processes and techniques for collecting opinions and impressions from users and using them to generate the next travel plan.

[0106] "Means for customization based on the user's past behavioral history and preferences" refers to the process or technology that analyzes the user's past travel data and preferences and generates the optimal travel plan based on them.

[0107] The present invention is a system that significantly reduces the effort required for users to plan trips and sightseeing, and provides a customized and fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user.

[0108] Server configuration and operation

[0109] Data collection and integration

[0110] The server first uses Python libraries such as BeautifulSoup and Scrapy to collect information such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews from various data sources on the Internet. The crawled data is temporarily stored in a database such as MySQL or PostgreSQL. The Pandas library is then used to filter out duplicates and noise from the data and format it into a consistent format.

[0111] Accepting and parsing requests

[0112] The server receives requests from the device and analyzes the user's desired travel and sightseeing details. Natural language processing libraries such as NLTK and spaCy are used for request analysis. Based on the analyzed request, relevant information is searched for in the database using SQL queries.

[0113] Plan generation by generative AI

[0114] Based on the analyzed request information, the server uses a generative AI (e.g., GPT-4) to generate an optimal travel plan. The generated plan includes transportation, tourist spots to visit, places to eat, and dates. Past behavioral history and preference information are also reflected, resulting in a personalized plan.

[0115] Providing plans to users and receiving feedback

[0116] The generated travel plan is sent to the device and presented in a visually easy-to-understand format. The plan includes a map showing the route, photos of the places visited, and detailed information. After the trip is over, feedback from the user is collected and reflected in future plan generation.

[0117] Terminal configuration and operation

[0118] Providing an interface

[0119] The device provides users with an easy-to-use interface, including a form for inputting destination, duration, and activities they are interested in. For example, it could be offered as a smartphone app or a web browser app, developed using React.js or Flutter.

[0120] Sending a request and receiving a plan

[0121] The request entered by the user is sent from the terminal to the server using an HTTP request, and the travel plan generated by the server is sent to the terminal and displayed on the user interface.

[0122] User Actions

[0123] Entering a request

[0124] Users use the device's interface to input their travel and sightseeing preferences, for example, a specific request such as "I want to visit cultural spots in Tokyo in three days."

[0125] Review and execute the plan

[0126] Users can review the travel plans sent from the server and customize them as needed, allowing them to have a travel experience that suits their preferences.

[0127] Providing Feedback

[0128] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[0129] Specific examples

[0130] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0131] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0132] 2. The server receives the request, searches for information about Kyoto's tourist attractions and transportation options, and the generation AI creates the optimal travel plan.

[0133] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0134] 4. The generated plan is sent to the device and displayed to the user in a visually easy-to-understand format.

[0135] 5. The user reviews the plan and customizes it as needed.

[0136] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[0137] Prompt Sentence Examples

[0138] "I'd like to visit cultural spots in Tokyo in three days. I'd like you to create a recommended itinerary. Places I've visited in the past include Sensoji Temple and Ueno Park."

[0139] In this way, the travel plans provided to users through the system can provide an efficient, customized, and fulfilling experience.

[0140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0141] Step 1: Data collection and integration

[0142] Input: URLs of various data sources on the Internet

[0143] Specific behavior:

[0144] The server uses the Python libraries BeautifulSoup and Scrapy to crawl the Internet for information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[0145] Data processing:

[0146] The crawled data is temporarily stored in storage and then stored in a database (e.g., MySQL, PostgreSQL).

[0147] Output: Information stored in a consistent format in a database

[0148] Step 2: Filtering data and ensuring consistency

[0149] Input: Raw data stored in a database

[0150] Specific behavior:

[0151] The server uses the Pandas library to filter out duplicates and noise from the data and format it into a consistent format.

[0152] Data processing:

[0153] Remove duplicate data, remove noise data, and format it appropriately

[0154] Output: A filtered, formatted, high-quality dataset

[0155] Step 3: Accepting the user request

[0156] Input: Requests entered by the user into the device interface (destination, travel duration, activities of interest, etc.)

[0157] Specific behavior:

[0158] The terminal sends the request entered by the user to the server via an HTTP request.

[0159] Data processing:

[0160] The request content is passed to the server in a format that can be parsed.

[0161] Output: User request data sent to the server

[0162] Step 4: Parsing the request

[0163] Input: User request data sent to the server

[0164] Specific behavior:

[0165] The server uses a natural language processing library such as NLTK or spaCy to analyze the request content.

[0166] Data processing:

[0167] Morphological analysis of request data and extraction of key information

[0168] Output: Parsed user request information

[0169] Step 5: Retrieving information from the database

[0170] Input: Parsed user request information

[0171] Specific behavior:

[0172] The server constructs an SQL query and searches the database for relevant tourist attractions and transportation information.

[0173] Data processing:

[0174] Extracting relevant information from a database and assembling it into sets based on user requests

[0175] Output: Relevant information data corresponding to the user request

[0176] Step 6: Generative AI generates a plan

[0177] Input: Relevant information data corresponding to the user request

[0178] Specific behavior:

[0179] The server uses generative AI (e.g., GPT-4) to generate an optimal travel plan based on the input request and related information data.

[0180] Data processing:

[0181] Enter a prompt into the generative AI and format the response into a travel plan

[0182] Output: Generated optimal travel plan

[0183] Step 7: Serving the generated plan

[0184] Input: Generated optimal itinerary

[0185] Specific behavior:

[0186] The server sends the generated travel plan to the terminal, which displays the plan to the user in a visually easy-to-understand format.

[0187] Data processing:

[0188] Send plan data in JSON format and display it in the user interface

[0189] Output: The itinerary displayed to the user

[0190] Step 8: Accept and implement feedback

[0191] Input: User feedback after the trip is completed

[0192] Specific behavior:

[0193] The device sends user feedback to the server, which then reflects this feedback in the next plan generation.

[0194] Data processing:

[0195] Organize feedback data and save it as input data for the next plan generation

[0196] Output: A dataset incorporating feedback information

[0197] The above are the specific processing steps of the program of this system.

[0198] (Application example 1)

[0199] 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."

[0200] In conventional travel planning systems, users had to individually research transportation timetables, service status, tourist attractions, dining information, and travel experiences, and then create their own plans, which was a significant hassle. Furthermore, when it came to food delivery, users had to consider their past ordering history and preferences when selecting restaurants and dishes, making delivery selection difficult. This resulted in a cumbersome user experience, making efficient travel planning and food delivery difficult.

[0201] 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.

[0202] In this invention, the server includes means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for providing the optimal travel plan to the user, means for suggesting optimal restaurants and dishes based on the user's preferences, past behavioral history, and order history, means for the user to confirm and select the suggested restaurants and dishes, and means for delivering the selected restaurants and dishes, thereby enabling the user to have a fulfilling travel experience and an efficient food delivery experience.

[0203] "Transportation" is a general term for public or private transportation services used as a means of moving people or goods.

[0204] A "timetable" is information that shows the operating times and schedules of transportation facilities.

[0205] "Operation status" refers to information that indicates the current operation status of transportation facilities, delay information, suspension of operations, and other conditions.

[0206] "Tourist attractions" are scenic, cultural or historical places that tourists visit.

[0207] "Dining information" includes information such as restaurant menus, opening hours, locations, and reviews.

[0208] An "experience memoir" is an article or piece of writing that describes a person's experiences and impressions about a certain event or place.

[0209] "Data collection means" refers to the methods and devices that obtain the required information from the Internet and other data sources.

[0210] "Means for integrating and filtering data" refers to methods and devices that organize collected data, remove redundancies and noise, and convert it into a consistent format.

[0211] A "means for receiving a request from a user" is a method or device that provides an input interface for requesting data or information from a user.

[0212] "Generation means" refers to a method or device that combines necessary data based on a user's request to create optimal travel plans and proposals.

[0213] "Means for providing to the user" refers to a method or device for displaying or communicating the generated travel plans or suggestions to the user.

[0214] "User Preferences" are individual interests and preferences based on a user's previously expressed interests and choices.

[0215] "Past behavior history" is a record of the actions and choices a user has made in the past.

[0216] "Order History" is a record of orders placed by a user in the past.

[0217] A "means for making suggestions" is a method or device that makes new suggestions based on collected data and the user's past records.

[0218] A "verification and selection means" is a method or device that provides an interface for a user to verify and select the proposed information.

[0219] "Delivery means" refers to the method or device for delivering the selected product or service to the user.

[0220] The present invention is a system for enabling users to have an efficient and fulfilling travel experience and food delivery experience. This system is composed of three entities: a server, a terminal, and a user, each of which fulfills a specific role.

[0221] Server Roles and Operations

[0222] The server operates using the following methods:

[0223] Data collection and integration

[0224] The server collects data from data sources on the Internet, such as transportation timetables, operation status, tourist attractions, food and drink information, experiences, restaurant information, menus, reviews, etc. The collected data is stored in a database to create a high-quality dataset.

[0225] Accepting and parsing requests

[0226] The server receives and analyzes user requests sent from the device, including destination, travel duration, activities of interest, food preferences, and past ordering history.

[0227] Plan generation and restaurant suggestions using generative AI

[0228] The server is equipped with a generation AI that generates optimal travel plans and restaurant and food suggestions based on user requests. The generated plans include transportation methods, the order in which tourist spots are visited, dining locations, dates, etc., and also reflect the user's preferences and past behavioral history.

[0229] Providing plans to users and receiving feedback

[0230] The server sends the generated travel plan and restaurant recommendations to the terminal and provides them to the user. After the user has completed the trip and received food delivery, they can provide feedback information, which will be reflected in future plan generation and restaurant recommendations.

[0231] The hardware used is a typical server machine for web servers, and the software includes the Django framework and generative AI models such as GPT-3.

[0232] Device role and operation

[0233] Providing an interface

[0234] The device provides users with an easy-to-use interface for inputting their travel plans and on-demand food delivery requests, including forms for inputting destination, travel duration, activity interests, and dietary preferences.

[0235] Sending a request and receiving a plan

[0236] The user's input request is sent from the device to the server, and the generated travel plan and restaurant suggestions are displayed to the user through the device, including the route on a map, restaurant locations, and detailed information.

[0237] The hardware used is a mobile device such as a smartphone or tablet, and a mobile application is installed as related software.

[0238] User Roles and Actions

[0239] Entering a request

[0240] Users use the device interface to input their travel and sightseeing wishes and food preferences, such as "I'd like to visit Tokyo's cultural attractions over three days" or "I'd like to have Japanese food for dinner tonight."

[0241] Review and implement plans and proposals

[0242] Users can review the travel plans and restaurant suggestions sent by the server and customize them as needed, allowing them to tailor their travel experience and dining to their preferences.

[0243] Providing Feedback

[0244] After completing a trip or delivery, users can provide feedback on their experience within the app, which will be reflected in future plan generation and restaurant suggestions, further improving the accuracy of the system.

[0245] Examples and prompts

[0246] Example 1:

[0247] If a user inputs a request such as "I want to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the server receives the request, searches data on tourist spots and transportation options, and the generation AI creates an optimal travel plan. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day. The generated plan is sent to the device and displayed in a visually easy-to-understand format to the user.

[0248] Example 2:

[0249] When a user types "I want Japanese food for dinner tonight" into a food delivery app, the server analyzes the user's order history and current mood, and the AI ​​generator suggests the most suitable Japanese restaurant. After the user confirms the suggestions and makes a selection, the restaurant delivers the food. After the delivery is complete, the user's feedback is reflected in future suggestions.

[0250] Example prompt sentence:

[0251] 1. The user has previously enjoyed ordering Japanese food. Please suggest three recommended Japanese restaurants in Tokyo.

[0252] 2. A user ordered sushi from "Sushi Place" last week and wants to eat sushi again today. Suggest two new sushi restaurants.

[0253] This provides users with a fulfilling travel experience and an efficient food delivery experience.

[0254] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0255] Step 1:

[0256] The server collects, consolidates, and filters the data.

[0257] Input: Online transportation timetables, operation status, tourist attraction data, food and drink information, experiences, restaurant information, menus, and reviews.

[0258] Processing: The server collects the required data using crawling techniques (e.g., scraping tools or APIs), stores the collected data in a database, and performs a data cleaning step to remove duplicates and noise data.

[0259] Output: A consolidated, filtered, high-quality dataset.

[0260] Step 2:

[0261] The device receives a request from the user.

[0262] Input: User inputs such as travel preferences, food preferences, past behavior, and order history.

[0263] Processing: The user enters their wishes and preferences through the device interface, and the request is sent from the device to the server.

[0264] Output: User request data.

[0265] Step 3:

[0266] The server parses the request and retrieves the required data.

[0267] Input: User request data.

[0268] Processing: Based on the received request, the server queries the relevant data in the database and creates an input dataset to feed into the generative AI model.

[0269] Output: The input dataset to feed into a generative AI model.

[0270] Step 4:

[0271] The server uses the generative AI model to generate optimal travel plans and restaurant suggestions.

[0272] Input: User request data and associated data.

[0273] Processing: Use a generative AI model (e.g., GPT-3) to generate optimal itinerary and restaurant suggestions that match the user's request. Input the prompt sentence into the generative AI model, and parse and assemble the output.

[0274] Output: Optimal itinerary and restaurant suggestions.

[0275] Step 5:

[0276] The server sends the generated plans and proposals to the terminal.

[0277] Input: Best travel plans and restaurant suggestions.

[0278] Processing: Sends the generated plans and proposals to the device for user review and customization.

[0279] Output: Itinerary and restaurant suggestions displayed on the user's device.

[0280] Step 6:

[0281] Users review and customize plans and proposals.

[0282] Input: Provided itinerary and restaurant suggestions.

[0283] Processing: The user checks the plan and proposals through their device and customizes them as needed.

[0284] Output: Customized travel plans and restaurant orders.

[0285] Step 7:

[0286] The server processes and delivers customized plans and orders.

[0287] Input: customized travel plans and restaurant orders.

[0288] Processing: The server finalizes the customized plan, places the order with the restaurant or delivery service, and arranges travel reservations and delivery services.

[0289] Output: User's travel booking confirmation and delivery order confirmation.

[0290] Step 8:

[0291] Users experience travel and delivery and provide feedback.

[0292] Input: Feedback about your travel and delivery experience.

[0293] Processing: The user provides feedback through the device, which is sent to the server.

[0294] Output: User feedback data.

[0295] Step 9:

[0296] The server will reflect the feedback in future plan generation and restaurant suggestions.

[0297] Input: User feedback data.

[0298] Processing: The server analyzes the collected feedback and updates the information to reflect it in future plan generation and restaurant suggestions. It is used as training data for the generative AI model.

[0299] Output: An updated dataset and a generative AI model.

[0300] 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.

[0301] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. This system collects and integrates information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[0302] Server Roles and Operations

[0303] Data collection and integration

[0304] The server crawls data from the internet, such as transportation timetables, operation status, tourist attractions, food and drink information, and experience reviews. This data is stored in a database and integrated into a consistent format. Filtering is performed to eliminate duplicates and noise data, generating a high-quality dataset.

[0305] Accepting and parsing requests

[0306] The server receives and analyzes the user's request sent from the device, reading the request content (destination, period, interests), and searches for and retrieves the necessary data.

[0307] Plan generation by generative AI

[0308] The server's generation AI generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The generated plan is further customized based on the user's past behavior and preferences.

[0309] Emotional engine regulation

[0310] The server is equipped with an emotion engine that recognizes the user's emotions, and analyzes their emotional state based on their requests and past feedback. Based on this analysis, the travel plan is adjusted to suit the user's needs.

[0311] Providing plans to users and receiving feedback

[0312] The generated plan is provided to the user via the device, and the feedback the user provides after the trip is reflected in the next plan generation.

[0313] Device role and operation

[0314] Providing an interface

[0315] The device provides a user-friendly interface for inputting their request, which displays a form for inputting destination, travel duration, and activities of interest.

[0316] Sending a request and receiving a plan

[0317] The user's input request is sent from the device to the server, and the travel plan generated by the server is displayed to the user in a visually easy-to-understand format on the device.

[0318] User Roles and Actions

[0319] Entering a request

[0320] Using the device's interface, users input their travel and sightseeing preferences, such as "I'd like to visit cultural spots in Tokyo in three days."

[0321] Review and execute the plan

[0322] The user can review the plan sent from the server and customize it as needed. The user adjusts the plan to suit their preferences and then carries out the trip.

[0323] Providing Feedback

[0324] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[0325] Providing emotion data

[0326] Users provide real-time emotional data during their trip, which is captured through the device interface or specific emotion recognition devices, and this emotional data is used to dynamically change information and services provided during the trip.

[0327] Specific examples

[0328] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0329] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0330] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[0331] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0332] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0333] 5. The user reviews the plan and customizes it as needed.

[0334] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[0335] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[0336] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[0337] The processing flow will be explained below.

[0338] Step 1: Data collection

[0339] The server crawls data from multiple data sources on the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports, and stores this data in a database.

[0340] Step 2: Data integration and filtering

[0341] The server converts the collected data into a consistent format and filters out duplicates and noisy data, producing a high-quality dataset.

[0342] Step 3: Providing a User Interface

[0343] The device provides an interface where users can enter their request, including a form to enter their destination, travel duration, and activities of interest.

[0344] Step 4: Submitting the request

[0345] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[0346] Step 5: Accepting and parsing the request

[0347] The server receives the request sent from the terminal and begins analyzing it. It analyzes the request content and searches the database for the corresponding data.

[0348] Step 6: User sentiment analysis

[0349] The server uses its built-in emotion engine to analyze the user's past feedback and real-time emotion data, and based on this analysis, understands the user's current emotional state.

[0350] Step 7: Generative AI generates a travel plan

[0351] The server's generation AI generates an optimal travel plan based on the results of request analysis and sentiment analysis, including transportation, sightseeing spots, dining options, and itinerary.

[0352] Step 8: Customize your plan

[0353] The server then customizes the generated travel plan based on the user's past behavior and preferences, thereby generating the optimal plan for each user.

[0354] Step 9: Offer your plan

[0355] The server sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format and provides it to the user.

[0356] Step 10: Review and change your plan

[0357] The user checks the travel plan displayed on the device and customizes it as needed. After customization, the request is sent back to the server for replanning.

[0358] Step 11: Real-time sentiment analysis during travel

[0359] When a user travels, real-time emotional data is collected from their device or emotion recognition device. The server's emotion engine analyzes this data and dynamically changes the information and services provided as needed.

[0360] Step 12: Trip execution and evaluation

[0361] The user then undertakes the trip based on the provided plan, and after completing the trip, the user provides evaluation feedback on the travel experience via the device.

[0362] Step 13: Incorporating feedback

[0363] The server receives feedback from users and reflects it in subsequent plan generation, further improving the accuracy of the system.

[0364] The above is the specific program processing flow that combines the emotion engine in the "Chat Travel" system.

[0365] Example 2

[0366] 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."

[0367] Conventional travel planning systems only provide information on transportation timetables and tourist attractions, but lack the ability to dynamically adjust plans based on the user's emotional state, which can lead to unsatisfactory travel experiences. Furthermore, they are unable to reflect user feedback and emotional data in real time during the actual trip, meaning that the travel plans provided often do not match the user's actual situation. This leads to a problem of a poor quality travel experience for users.

[0368] 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.

[0369] In this invention, the server includes: means for collecting data on transportation timetables, operation status, tourist attractions, food and drink information, and experience reports; means for integrating and filtering the data; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered data based on the request; means for providing the optimal travel plan to the user; means including an emotion engine for analyzing the user's emotional state and dynamically adjusting the travel plan; and means for providing emotion data in real time via the user's terminal. This allows the user's travel plan to be dynamically adjusted based on emotions, providing a highly satisfying travel experience that reflects the user's actual emotional state and feedback.

[0370] A "transportation timetable" is a schedule showing the departure and arrival times of public transportation such as buses, trains, and airplanes.

[0371] "Operation status" is information indicating the current operation status of transportation facilities, and includes information such as delays, suspensions, and start of operations.

[0372] "Tourist attractions" are places and attractions that travelers want to visit, including historical buildings, natural landscapes, museums, parks, etc.

[0373] "Food and beverage information" refers to information such as the location, opening hours, menu, and ratings of restaurants.

[0374] "Experience stories" are reviews and travel reports written by people who have traveled in the past, and provide information that travelers can use as reference.

[0375] "Means of collecting data" refers to the technology or devices used to obtain the required information, including crawling tools.

[0376] "Means of data integration and filtering" refers to technologies and devices that convert collected data into a consistent format and remove duplicates and noisy data.

[0377] "Means for receiving requests" refers to the technology or device that allows the server to obtain the user's wishes and requests.

[0378] "Generation means" refers to the technology and algorithms used to create optimal travel plans based on user requirements.

[0379] "Means for providing to users" refers to a method or system for displaying the generated travel plan to users.

[0380] An "emotion engine" refers to the technology and algorithms that analyze a user's emotional state and dynamically adjust travel plans.

[0381] "Terminal" means a device on which a user inputs a request and checks the results, including a smartphone or computer.

[0382] "Feedback" refers to the ratings and opinions users provide about their travel plans and experiences, and is information that will be reflected in the generation of future plans.

[0383] "Means for providing real-time emotional data" refers to technology or devices that instantly acquire a user's emotional state while traveling and transmit it to a server.

[0384] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. The system collects information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[0385] Server Roles and Operations

[0386] Data collection and integration

[0387] The server crawls the internet to collect data such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews. This data is collected using crawling tools such as Python's BeautifulSoup and Scrapy. The collected data is stored in a database such as MySQL or PostgreSQL, and is then filtered to remove duplicates and noise data and consolidate it into a consistent format.

[0388] Accepting and parsing requests

[0389] The server receives the user's request sent from the device, which includes the destination, travel duration, and activities of interest. The server uses NLP techniques (e.g., spaCy or NLTK) to parse the request and executes the appropriate query against the database.

[0390] Plan generation by generative AI

[0391] A generative AI model (e.g., GPT-4) installed on the server generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The plan is further customized based on the user's past behavior and preferences.

[0392] Emotional engine regulation

[0393] The server is equipped with an emotion engine that analyzes the user's emotional state based on their request, past feedback, and emotional data from the trip. The engine uses Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools. Based on the analysis results, the plan is dynamically adjusted.

[0394] Providing plans to users and receiving feedback

[0395] The generated plan is provided to the user in a visually easy-to-understand format via the device, and after the trip, feedback is collected from the user and reflected in future plan generation.

[0396] Device role and operation

[0397] Providing an interface

[0398] The terminal provides an interface where users can easily input their requests. This interface displays a form to input destination, travel duration, and activities of interest. A front-end framework (e.g., React or Vue.js) is used to realize the dynamic user interface.

[0399] Sending a request and receiving a plan

[0400] The user's request is sent from the device to the server, and the travel plan generated by the server is displayed visually on the device. Data is sent in JSON format, and the device displays the results using HTML and JavaScript.

[0401] User Roles and Actions

[0402] Entering a request

[0403] Users use the device interface to input their travel and sightseeing preferences, for example, "I'd like to plan a three-day, two-night trip to Kyoto, mainly to visit temples."

[0404] Review and execute the plan

[0405] The user can review the plan sent from the server, customize it as needed, and once satisfied with the plan, carry out the trip according to that plan.

[0406] Providing feedback and sentiment data

[0407] After completing the trip, users provide feedback on their travel experience within the app, and during the trip, they provide real-time emotional data using their devices or emotion recognition devices, which allows the server to dynamically change the information and services provided.

[0408] Specific examples

[0409] For example, if a user enters a specific prompt such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the process will proceed as follows:

[0410] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0411] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[0412] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0413] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0414] 5. The user reviews the plan and customizes it as needed.

[0415] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[0416] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[0417] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[0418] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0419] Step 1:

[0420] The server crawls data from the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[0421] Input: URLs of various sources on the Internet.

[0422] Data processing: The server uses Python's BeautifulSoup and Scrapy to retrieve information from each site, extracting information such as departure and arrival times and status of buses, trains, and planes, detailed information about tourist spots, restaurant locations and menus, and traveler reviews.

[0423] Output: The raw data collected.

[0424] Step 2:

[0425] The server stores the collected data in a database and performs filtering.

[0426] Input: Raw data.

[0427] Data transformation: Before inserting data into MySQL or PostgreSQL, we remove duplicates and noise, and convert data into a consistent format, such as standardizing date formats and removing unnecessary HTML tags.

[0428] Output: Clean data in a filtered database.

[0429] Step 3:

[0430] The server receives the user's request sent from the terminal.

[0431] Input: A request containing the user's preferences (destination, travel duration, and activities of interest).

[0432] Data processing: The server receives the request in JSON format and parses it using NLP techniques (e.g., spaCy or NLTK) to break it down into destinations, durations, and activities of interest, and generates database queries.

[0433] Output: The search query.

[0434] Step 4:

[0435] The server generates the optimal travel plan using a generative AI model.

[0436] Input: Information from a database based on a search query.

[0437] Data processing: A generative AI model (e.g., GPT-4) generates a travel plan based on the tourist attractions and transportation information provided as a result of the query. This plan includes transportation options, tourist attractions, dining options, and itinerary, taking into account the user's past behavior and preferences.

[0438] Output: The generated itinerary.

[0439] Step 5:

[0440] The server uses the emotion engine to dynamically adjust the travel plan.

[0441] Input: Generated itinerary and user's real-time sentiment data.

[0442] Data processing: Using Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools, the system analyzes the user's emotional state in real time. Depending on the user's emotional state, the system can change part of the plan to include a relaxing spot or adjust the schedule.

[0443] Output: Adjusted itinerary.

[0444] Step 6:

[0445] The server transmits the adjusted travel plan to the terminal.

[0446] Input: adjusted travel plans.

[0447] Data processing: Send the adjusted plan to the device in JSON format.

[0448] Output: A visually easy-to-understand itinerary displayed on the device.

[0449] Step 7:

[0450] The user uses the interface to input requests and send them from the terminal to the server.

[0451] Input: Your request for destination, travel duration, activities of interest, etc.

[0452] Data processing: The user enters the request through an intuitive interface (e.g., a web form using HTML and JavaScript) and presses the submit button.

[0453] Output: The request sent to the server in JSON format.

[0454] Step 8:

[0455] Users can check the plans offered on their device and customize them as needed.

[0456] Input: Itinerary sent from the server.

[0457] Data processing: Visually display the plan on the device and provide an interface where users can input changes, such as adding more stops or adjusting the time.

[0458] Output: A customized plan.

[0459] Step 9:

[0460] After completing the trip, the user provides feedback, which is sent from the device to the server.

[0461] Input: Feedback on your travel experience.

[0462] Data processing: Users use a dedicated feedback form to enter their ratings and opinions of their travel experience and press the submit button.

[0463] Output: Feedback information sent to the server in JSON format.

[0464] Step 10:

[0465] The server will incorporate user feedback into the next plan generation.

[0466] Input: Feedback information.

[0467] Data processing: The feedback information is stored in a database and used as reference data when planning your next trip.

[0468] Output: An improved trip plan that takes into account the user's past behavior history and ratings.

[0469] (Application example 2)

[0470] 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."

[0471] While conventional travel planning systems provide tourist spot and transportation information based on user requests, they struggle to adapt to the user's emotional state or changing circumstances during the trip. Finding the best dining options during a trip is also challenging, potentially reducing the quality of the travel experience. Furthermore, there are limited ways to incorporate user feedback into future plans. There is a need for a system that can address these issues, adapt to the user's emotional state and real-time circumstances, and optimize the dining experience during travel.

[0472] The specific processing by the specific 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 means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for adjusting the generated travel plan based on the user's emotional state, and means for generating a dining plan based on the optimal travel plan and providing it to the user. This makes it possible to provide an appropriate travel plan tailored to the user's emotional state and to optimize the dining plan in real time.

[0473] A "transportation timetable" is a table showing the operating times of public transportation (trains, buses, airplanes, etc.).

[0474] "Operation status" is information that indicates the current state of transportation operations, including delays, cancellations, and whether the transportation is running on schedule.

[0475] "Tourist spots" are places and facilities that travelers and tourists want to visit, such as temples, art museums, and natural parks.

[0476] "Dining information" refers to information about restaurants, such as menu items, opening hours, and user ratings.

[0477] "Experiences" are records of travel and sightseeing experiences that users have actually experienced. These include blog articles and social media posts.

[0478] "Data collection methods" refers to the methods and tools used to obtain the required data from the internet and other sources.

[0479] "Data consolidation and filtering measures" refers to the methods and processes used to organize and consolidate collected data and remove unnecessary information.

[0480] "Means for receiving user requests" refers to the method or interface by which users input and send desired information or plans to the system.

[0481] "Generator" refers to the algorithms and engines that create optimal travel and dining plans based on user requests.

[0482] "Means for adjusting based on emotional state" refers to methods and tools that analyze the user's current emotions and change or adapt suggestions accordingly.

[0483] A "food and beverage plan" is a plan that suggests the best places to eat and menus for the user during their trip.

[0484] "Means for providing" refers to an interface or method for presenting the generated plan to the user in an easy-to-view manner.

[0485] This system streamlines users' travel and sightseeing planning and optimizes their travel experience by recognizing their emotions. The system consists of three main components: a server, a terminal, and a user.

[0486] Server Roles and Operations

[0487] Data collection and integration

[0488] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, dining information, and travel experiences. For example, it uses a web crawler to retrieve data from various sources and stores it in a database. The retrieved data is then filtered to remove duplicate and irrelevant information and organized into a unified format.

[0489] Accepting and parsing requests

[0490] The server receives and analyzes the user's request, which includes specific details such as travel destination, duration, and activities of interest, and searches for and retrieves relevant data based on the analyzed request.

[0491] Plan generation by generative AI

[0492] The server uses a generative AI model based on information obtained from the request to generate an optimal travel plan, including transportation, tourist attractions, dining options, and dates. For example, if a user requests a three-day trip to Kyoto's cultural attractions and to dine at highly rated local restaurants, the server can provide the optimal tourist attractions and dining plan.

[0493] Emotional engine regulation

[0494] The server is equipped with an emotion engine that analyzes the user's emotional state based on past feedback and real-time emotional data. If the user's emotional state is "happy," the system will adjust the plan, recommending highly rated restaurants, and if the user's emotional state is "sad," it will recommend comfort food to lift their mood.

[0495] Device role and operation

[0496] Providing an interface

[0497] The terminal provides a user-friendly interface for inputting their request, including forms and menus for selecting destinations, travel duration, and activities of interest.

[0498] Sending a request and receiving a plan

[0499] The requests entered by the user are sent from the device to the server, and the generated travel and dining plans are displayed to the user in a visually easy-to-understand format on the device.

[0500] User Roles and Actions

[0501] Entering a request

[0502] Users use the device interface to input their travel and sightseeing preferences, such as "I'd like to plan a three-day, two-night trip to Kyoto, mainly visiting temples."

[0503] Review and execute the plan

[0504] The user can review the travel and dining plans sent by the server and customize them as needed, for example by adding or removing specific restaurants or tourist attractions.

[0505] Providing Feedback

[0506] After completing a trip, users can provide feedback about their travel experience within the app, which will be reflected in future itineraries, improving the accuracy of the entire system.

[0507] Specific examples

[0508] As a specific example, if the user is "planning a 2-night, 3-day trip to Kyoto and would like delivery from a highly rated Japanese restaurant. The emotional state is happy," the travel plan will include a visit to Kyoto's major temples as well as a delivery plan from a highly rated Japanese restaurant. An example of a prompt sentence is "Suggest delivery from a highly rated Japanese restaurant during the user's stay in Kyoto. The user's emotional state is happy."

[0509] In this way, the present invention can significantly improve the user's travel experience by providing optimal travel plans and dining plans in real time while taking into account the user's emotional state.

[0510] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0511] Step 1: Data collection and integration

[0512] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, food and drink information, and travel experiences. Specifically, it uses a web crawler to retrieve data from various sources and stores it in a database. Input includes the URLs and API endpoints of each source. The output is an integrated dataset. The data is then converted into a unified format after removing duplicates and irrelevant information.

[0513] Step 2: Accepting and parsing the request

[0514] The server receives the user's request sent from the device. The request includes travel destination, duration, and activities of interest. The input is the information the user enters into a form. The server analyzes this information and searches for and retrieves relevant data. The output is a dataset that fits the user's request.

[0515] Step 3: Generative AI generates a plan

[0516] The server uses the analyzed request data to launch a generative AI model. The generative AI model generates an optimal travel plan based on the user's request. Specifically, it creates a plan that includes transportation, tourist spots, dining options, and itinerary. The input is the request data and related information found. The output is an optimal travel plan.

[0517] Step 4: Emotional Engine Adjustment

[0518] The server uses an emotion engine to analyze the user's emotional state. The emotional state is based on past feedback and real-time emotional data. The inputs include the user's past feedback and real-time emotional data. The generated itinerary is adjusted based on the emotion analysis. For example, a "happy" state might recommend highly rated restaurants, and a "sad" state might recommend comfort food. The output is an adjusted itinerary.

[0519] Step 5: Providing an interface and sending requests

[0520] The terminal provides an interface for the user to enter their request. This interface may include forms and menus for entering destination, travel duration, and activities of interest. Once the user enters the information, the terminal sends it to the server. The input is the user-entered data. The output is the request sent by the user to the server.

[0521] Step 6: Review and customize your plan

[0522] The user reviews the travel plan and dining plan provided through the terminal. The plan can be customized as needed. For example, it is possible to add or remove specific tourist spots or restaurants. The input is the provided travel plan and the user's customizations. The output is the final customized travel plan.

[0523] Step 7: Provide feedback

[0524] After completing the trip, the user provides feedback about their travel experience through their device. Input includes evaluations of the experience during the trip and comments. The server collects this feedback information and reflects it in generating future plans. The feedback is also used for analysis by the emotion engine. The output is the accumulated feedback data.

[0525] 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.

[0526] 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.

[0527] 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.

[0528] [Second embodiment]

[0529] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0530] 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.

[0531] 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).

[0532] 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.

[0533] 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.

[0534] 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).

[0535] 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.

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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."

[0541] The present invention is a system that allows users to save a lot of time and effort when planning trips and sightseeing, and provides a fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user, each of which plays a specific role.

[0542] Server Roles and Operations

[0543] Data collection and integration

[0544] The server first crawls data sources on the Internet, collecting information such as transportation timetables, service status, tourist attractions, food and drink information, and travel experiences. After collecting this data, it stores it in a database. Next, it integrates the collected data and converts it into a consistent format. In the process, it filters out duplicates and noise data to create a high-quality dataset.

[0545] Accepting and parsing requests

[0546] The server receives user requests from the device, including destination, travel duration, activities of interest, etc. The server analyzes these requests and retrieves the necessary data based on them.

[0547] Plan generation by generative AI

[0548] The server is equipped with a generation AI that generates the optimal travel plan for the user based on the analyzed request, including transportation, tourist spots to visit, places to eat, dates, etc. It also reflects the user's past behavioral history and preferences to provide an individually customized plan.

[0549] Providing plans to users and receiving feedback

[0550] The generated plan is provided to the user via the device. After the user has completed their trip, they can provide feedback, which will be reflected in the next plan generation.

[0551] Device role and operation

[0552] Providing an interface

[0553] The terminal provides a user-friendly interface for easily entering requests, including a form for inputting destination, duration, and activities of interest.

[0554] Sending a request and receiving a plan

[0555] The user's request is sent from the device to the server, and the server generates a travel plan that is displayed to the user through the device. The plan includes the route on a map, photos of the places to visit, and detailed information.

[0556] User Roles and Actions

[0557] Entering a request

[0558] Users use the device's interface to input their travel and sightseeing preferences, such as "I want to visit cultural spots in Tokyo in three days."

[0559] Review and execute the plan

[0560] Users can review the plan sent from the server and customize it as needed, allowing them to have a travel experience that suits their preferences.

[0561] Providing Feedback

[0562] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries, further improving the accuracy of the system.

[0563] Specific examples

[0564] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0565] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0566] 2. The server receives the request and searches for data on Kyoto's tourist attractions and transportation options. The generative AI then creates the optimal travel plan.

[0567] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0568] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0569] 5. The user reviews the plan and customizes it as needed.

[0570] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[0571] In this way, the present invention improves the efficiency of users' travel planning and provides a fulfilling sightseeing experience.

[0572] The processing flow will be explained below.

[0573] Step 1: Data collection

[0574] The server crawls multiple data sources on the Internet, collecting information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports. This collected data is then stored in a database.

[0575] Step 2: Data integration and filtering

[0576] The server converts the collected data into a consistent format and filters out duplicates and noise data, resulting in a high-quality dataset.

[0577] Step 3: Providing a User Interface

[0578] The terminal provides an interface where users can enter their requests, including a form to enter their destination, travel duration, and activities of interest.

[0579] Step 4: Submitting the request

[0580] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[0581] Step 5: Accepting and parsing the request

[0582] The server receives and analyzes the request sent from the terminal, reading the request content (destination, period, interests) and searching for the necessary data.

[0583] Step 6: Generative AI generates a travel plan

[0584] The server's generation AI creates an optimal travel plan based on the analysis results, including transportation, sightseeing spots, dining options, and itinerary.

[0585] Step 7: Customize your plan

[0586] The server then customizes the generated travel plan based on the user's past behavior and preferences, providing the optimal plan for each user.

[0587] Step 8: Submit your plan

[0588] The server then sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format.

[0589] Step 9: Review and change your plan

[0590] The user can review the travel plan displayed on the device and customize it as needed. Any changes made by the user are sent back to the server, and a replanning request may be required.

[0591] Step 10: Trip execution and evaluation

[0592] The user then carries out the trip based on the provided plan. After completing the trip, the user provides feedback on their experience. This feedback is reflected in the generation of future plans.

[0593] The above is the specific program processing flow of the "Chat Travel" system.

[0594] Example 1

[0595] 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."

[0596] In today's world, users require a wide variety of information when planning trips and sightseeing. Individually researching information such as transportation timetables and service status, tourist spot information, restaurant information, and travel experiences in each location is extremely time-consuming and laborious. This makes it difficult for users to easily create optimal travel plans, and there are few systems that provide plans that reflect individual preferences and past travel history. Furthermore, there is a lack of systems that can utilize post-trip feedback to improve future plans. Given this background, there is a growing need for travel planning systems that can efficiently collect, integrate, and customize information, and incorporate feedback.

[0597] 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.

[0598] In this invention, the server includes: means for collecting information on transportation timetables, operation status, tourist attractions, dining information, and travel experiences; means for integrating and filtering the information; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered information based on the request; means for generating an optimal travel plan based on the user's request using a generative AI model; means for providing the generated optimal travel plan to the user; means for collecting feedback information from users and incorporating it into the generation of the next plan; and means for individually customizing the travel plan generated by the generation means based on the user's past behavioral history and preferences. This makes it possible to efficiently collect and integrate a wide range of information and provide an optimal travel plan tailored to individual preferences. Furthermore, by incorporating user feedback into the next travel plan, an even more accurate and personalized travel experience can be provided.

[0599] "Transportation timetables" are information about detailed schedules of public transportation, such as operating times, stops, and route information.

[0600] "Operation status" refers to real-time operation information such as whether transportation is currently operating, delays, or cancellations.

[0601] "Tourist attractions" are places of interest, famous landmarks, natural landscapes, facilities, etc. within an area that are expected to interest and attract tourists and visitors.

[0602] "Dining information" refers to information about dining facilities in the area, the types of food they offer, business information, ratings, and so on.

[0603] "Experiences" are records of impressions, reviews, and specific experiences of people who have visited a region or experienced a tourist spot in the past.

[0604] "Means of collecting information" refers to the methods and techniques used to obtain the necessary data from the Internet and other data sources and incorporate it into the system.

[0605] "Information integration and filtering measures" are techniques and processes used to organize collected information, remove duplicates and irrelevant data, and put it into an appropriate format.

[0606] "Means for receiving requests from users" refers to the interface through which users input their desired travel plans and the method for importing that data into the system.

[0607] "Means for generating optimal travel plans" refers to the process or technology that automatically assembles travel schedules, places to visit, transportation methods, etc. based on collected and integrated data and user requests.

[0608] A "generative AI model" is an algorithm or system that uses artificial intelligence to automatically generate optimal travel plans based on user requests.

[0609] The "means provided to users" refers to interfaces and technologies that allow users to easily view and use the generated travel plans.

[0610] "Means for collecting and reflecting feedback information" refers to the processes and techniques for collecting opinions and impressions from users and using them to generate the next travel plan.

[0611] "Means for customization based on the user's past behavioral history and preferences" refers to the process or technology that analyzes the user's past travel data and preferences and generates the optimal travel plan based on them.

[0612] The present invention is a system that significantly reduces the effort required for users to plan trips and sightseeing, and provides a customized and fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user.

[0613] Server configuration and operation

[0614] Data collection and integration

[0615] The server first uses Python libraries such as BeautifulSoup and Scrapy to collect information such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews from various data sources on the Internet. The crawled data is temporarily stored in a database such as MySQL or PostgreSQL. The Pandas library is then used to filter out duplicates and noise from the data and format it into a consistent format.

[0616] Accepting and parsing requests

[0617] The server receives requests from the device and analyzes the user's desired travel and sightseeing details. Natural language processing libraries such as NLTK and spaCy are used for request analysis. Based on the analyzed request, relevant information is searched for in the database using SQL queries.

[0618] Plan generation by generative AI

[0619] Based on the analyzed request information, the server uses a generative AI (e.g., GPT-4) to generate an optimal travel plan. The generated plan includes transportation, tourist spots to visit, places to eat, and dates. Past behavioral history and preference information are also reflected, resulting in a personalized plan.

[0620] Providing plans to users and receiving feedback

[0621] The generated travel plan is sent to the device and presented in a visually easy-to-understand format. The plan includes a map showing the route, photos of the places visited, and detailed information. After the trip is over, feedback from the user is collected and reflected in future plan generation.

[0622] Terminal configuration and operation

[0623] Providing an interface

[0624] The device provides users with an easy-to-use interface, including a form for inputting destination, duration, and activities they are interested in. For example, it could be offered as a smartphone app or a web browser app, developed using React.js or Flutter.

[0625] Sending a request and receiving a plan

[0626] The request entered by the user is sent from the terminal to the server using an HTTP request, and the travel plan generated by the server is sent to the terminal and displayed on the user interface.

[0627] User Actions

[0628] Entering a request

[0629] Users use the device's interface to input their travel and sightseeing preferences, for example, a specific request such as "I want to visit cultural spots in Tokyo in three days."

[0630] Review and execute the plan

[0631] Users can review the travel plans sent from the server and customize them as needed, allowing them to have a travel experience that suits their preferences.

[0632] Providing Feedback

[0633] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[0634] Specific examples

[0635] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0636] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0637] 2. The server receives the request, searches for information about Kyoto's tourist attractions and transportation options, and the generation AI creates the optimal travel plan.

[0638] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0639] 4. The generated plan is sent to the device and displayed to the user in a visually easy-to-understand format.

[0640] 5. The user reviews the plan and customizes it as needed.

[0641] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[0642] Prompt Sentence Examples

[0643] "I'd like to visit cultural spots in Tokyo in three days. I'd like you to create a recommended itinerary. Places I've visited in the past include Sensoji Temple and Ueno Park."

[0644] In this way, the travel plans provided to users through the system can provide an efficient, customized, and fulfilling experience.

[0645] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0646] Step 1: Data collection and integration

[0647] Input: URLs of various data sources on the Internet

[0648] Specific behavior:

[0649] The server uses the Python libraries BeautifulSoup and Scrapy to crawl the Internet for information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[0650] Data processing:

[0651] The crawled data is temporarily stored in storage and then stored in a database (e.g., MySQL, PostgreSQL).

[0652] Output: Information stored in a consistent format in a database

[0653] Step 2: Filtering data and ensuring consistency

[0654] Input: Raw data stored in a database

[0655] Specific behavior:

[0656] The server uses the Pandas library to filter out duplicates and noise from the data and format it into a consistent format.

[0657] Data processing:

[0658] Remove duplicate data, remove noise data, and format it appropriately

[0659] Output: A filtered, formatted, high-quality dataset

[0660] Step 3: Accepting the user request

[0661] Input: Requests entered by the user into the device interface (destination, travel duration, activities of interest, etc.)

[0662] Specific behavior:

[0663] The terminal sends the request entered by the user to the server via an HTTP request.

[0664] Data processing:

[0665] The request content is passed to the server in a format that can be parsed.

[0666] Output: User request data sent to the server

[0667] Step 4: Parsing the request

[0668] Input: User request data sent to the server

[0669] Specific behavior:

[0670] The server uses a natural language processing library such as NLTK or spaCy to analyze the request content.

[0671] Data processing:

[0672] Morphological analysis of request data and extraction of key information

[0673] Output: Parsed user request information

[0674] Step 5: Retrieving information from the database

[0675] Input: Parsed user request information

[0676] Specific behavior:

[0677] The server constructs an SQL query and searches the database for relevant tourist attractions and transportation information.

[0678] Data processing:

[0679] Extracting relevant information from a database and assembling it into sets based on user requests

[0680] Output: Relevant information data corresponding to the user request

[0681] Step 6: Generative AI generates a plan

[0682] Input: Relevant information data corresponding to the user request

[0683] Specific behavior:

[0684] The server uses generative AI (e.g., GPT-4) to generate an optimal travel plan based on the input request and related information data.

[0685] Data processing:

[0686] Enter a prompt into the generative AI and format the response into a travel plan

[0687] Output: Generated optimal travel plan

[0688] Step 7: Serving the generated plan

[0689] Input: Generated optimal itinerary

[0690] Specific behavior:

[0691] The server sends the generated travel plan to the terminal, which displays the plan to the user in a visually easy-to-understand format.

[0692] Data processing:

[0693] Send plan data in JSON format and display it in the user interface

[0694] Output: The itinerary displayed to the user

[0695] Step 8: Accept and implement feedback

[0696] Input: User feedback after the trip is completed

[0697] Specific behavior:

[0698] The device sends user feedback to the server, which then reflects this feedback in the next plan generation.

[0699] Data processing:

[0700] Organize feedback data and save it as input data for the next plan generation

[0701] Output: A dataset incorporating feedback information

[0702] The above are the specific processing steps of the program of this system.

[0703] (Application example 1)

[0704] 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."

[0705] In conventional travel planning systems, users had to individually research transportation timetables, service status, tourist attractions, dining information, and travel experiences, and then create their own plans, which was a significant hassle. Furthermore, when it came to food delivery, users had to consider their past ordering history and preferences when selecting restaurants and dishes, making delivery selection difficult. This resulted in a cumbersome user experience, making efficient travel planning and food delivery difficult.

[0706] 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.

[0707] In this invention, the server includes means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for providing the optimal travel plan to the user, means for suggesting optimal restaurants and dishes based on the user's preferences, past behavioral history, and order history, means for the user to confirm and select the suggested restaurants and dishes, and means for delivering the selected restaurants and dishes, thereby enabling the user to have a fulfilling travel experience and an efficient food delivery experience.

[0708] "Transportation" is a general term for public or private transportation services used as a means of moving people or goods.

[0709] A "timetable" is information that shows the operating times and schedules of transportation facilities.

[0710] "Operation status" refers to information that indicates the current operation status of transportation facilities, delay information, suspension of operations, and other conditions.

[0711] "Tourist attractions" are scenic, cultural or historical places that tourists visit.

[0712] "Dining information" includes information such as restaurant menus, opening hours, locations, and reviews.

[0713] An "experience memoir" is an article or piece of writing that describes a person's experiences and impressions about a certain event or place.

[0714] "Data collection means" refers to the methods and devices that obtain the required information from the Internet and other data sources.

[0715] "Means for integrating and filtering data" refers to methods and devices that organize collected data, remove redundancies and noise, and convert it into a consistent format.

[0716] A "means for receiving a request from a user" is a method or device that provides an input interface for requesting data or information from a user.

[0717] "Generation means" refers to a method or device that combines necessary data based on a user's request to create optimal travel plans and proposals.

[0718] "Means for providing to the user" refers to a method or device for displaying or communicating the generated travel plans or suggestions to the user.

[0719] "User Preferences" are individual interests and preferences based on a user's previously expressed interests and choices.

[0720] "Past behavior history" is a record of the actions and choices a user has made in the past.

[0721] "Order History" is a record of orders placed by a user in the past.

[0722] A "means for making suggestions" is a method or device that makes new suggestions based on collected data and the user's past records.

[0723] A "verification and selection means" is a method or device that provides an interface for a user to verify and select the proposed information.

[0724] "Delivery means" refers to the method or device for delivering the selected product or service to the user.

[0725] The present invention is a system for enabling users to have an efficient and fulfilling travel experience and food delivery experience. This system is composed of three entities: a server, a terminal, and a user, each of which fulfills a specific role.

[0726] Server Roles and Operations

[0727] The server operates using the following methods:

[0728] Data collection and integration

[0729] The server collects data from data sources on the Internet, such as transportation timetables, operation status, tourist attractions, food and drink information, experiences, restaurant information, menus, reviews, etc. The collected data is stored in a database to create a high-quality dataset.

[0730] Accepting and parsing requests

[0731] The server receives and analyzes user requests sent from the device, including destination, travel duration, activities of interest, food preferences, and past ordering history.

[0732] Plan generation and restaurant suggestions using generative AI

[0733] The server is equipped with a generation AI that generates optimal travel plans and restaurant and food suggestions based on user requests. The generated plans include transportation methods, the order in which tourist spots are visited, dining locations, dates, etc., and also reflect the user's preferences and past behavioral history.

[0734] Providing plans to users and receiving feedback

[0735] The server sends the generated travel plan and restaurant recommendations to the terminal and provides them to the user. After the user has completed the trip and received food delivery, they can provide feedback information, which will be reflected in future plan generation and restaurant recommendations.

[0736] The hardware used is a typical server machine for web servers, and the software includes the Django framework and generative AI models such as GPT-3.

[0737] Device role and operation

[0738] Providing an interface

[0739] The device provides users with an easy-to-use interface for inputting their travel plans and on-demand food delivery requests, including forms for inputting destination, travel duration, activity interests, and dietary preferences.

[0740] Sending a request and receiving a plan

[0741] The user's input request is sent from the device to the server, and the generated travel plan and restaurant suggestions are displayed to the user through the device, including the route on a map, restaurant locations, and detailed information.

[0742] The hardware used is a mobile device such as a smartphone or tablet, and a mobile application is installed as related software.

[0743] User Roles and Actions

[0744] Entering a request

[0745] Users use the device's interface to input their travel and sightseeing preferences, as well as their food preferences, such as "I'd like to visit Tokyo's cultural sites over three days" or "I'd like to have Japanese food for dinner tonight."

[0746] Review and implement plans and proposals

[0747] Users can review the travel plans and restaurant suggestions sent by the server and customize them as needed, allowing them to tailor their travel experience and dining to their preferences.

[0748] Providing Feedback

[0749] After completing a trip or delivery, users can provide feedback on their experience within the app, which will be reflected in future plan generation and restaurant suggestions, further improving the accuracy of the system.

[0750] Examples and prompts

[0751] Example 1:

[0752] If a user inputs a request such as "I want to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the server receives the request, searches data on tourist spots and transportation options, and the generation AI creates an optimal travel plan. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day. The generated plan is sent to the device and displayed in a visually easy-to-understand format for the user.

[0753] Example 2:

[0754] When a user types "I want Japanese food for dinner tonight" into a food delivery app, the server analyzes the user's order history and current mood, and the AI ​​generator suggests the most suitable Japanese restaurant. After the user confirms the suggestions and makes a selection, the restaurant delivers the food. After the delivery is complete, the user's feedback is reflected in future suggestions.

[0755] Example prompt sentence:

[0756] 1. The user has previously enjoyed ordering Japanese food. Please suggest three recommended Japanese restaurants in Tokyo.

[0757] 2. A user ordered sushi from "Sushi Place" last week and wants to eat sushi again today. Suggest two new sushi restaurants.

[0758] This provides users with a fulfilling travel experience and an efficient food delivery experience.

[0759] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0760] Step 1:

[0761] The server collects, consolidates, and filters the data.

[0762] Input: Online transportation timetables, operation status, tourist attraction data, food and drink information, experiences, restaurant information, menus, and reviews.

[0763] Processing: The server collects the required data using crawling techniques (e.g., scraping tools or APIs), stores the collected data in a database, and performs a data cleaning step to remove duplicates and noise data.

[0764] Output: A consolidated, filtered, high-quality dataset.

[0765] Step 2:

[0766] The device receives a request from the user.

[0767] Input: User inputs such as travel preferences, food preferences, past behavior, and order history.

[0768] Processing: The user enters their wishes and preferences through the device interface, and the request is sent from the device to the server.

[0769] Output: User request data.

[0770] Step 3:

[0771] The server parses the request and retrieves the required data.

[0772] Input: User request data.

[0773] Processing: Based on the received request, the server queries the relevant data in the database and creates an input dataset to feed into the generative AI model.

[0774] Output: The input dataset to feed into a generative AI model.

[0775] Step 4:

[0776] The server uses the generative AI model to generate optimal travel plans and restaurant suggestions.

[0777] Input: User request data and associated data.

[0778] Processing: Use a generative AI model (e.g., GPT-3) to generate optimal itinerary and restaurant suggestions that match the user's request. Input the prompt sentence into the generative AI model, and parse and assemble the output.

[0779] Output: Optimal itinerary and restaurant suggestions.

[0780] Step 5:

[0781] The server sends the generated plans and proposals to the terminal.

[0782] Input: Best travel plans and restaurant suggestions.

[0783] Processing: Sends the generated plans and proposals to the device for user review and customization.

[0784] Output: Itinerary and restaurant suggestions displayed on the user's device.

[0785] Step 6:

[0786] Users review and customize plans and proposals.

[0787] Input: Provided itinerary and restaurant suggestions.

[0788] Processing: The user checks the plan and proposals through their device and customizes them as needed.

[0789] Output: Customized travel plans and restaurant orders.

[0790] Step 7:

[0791] The server processes and delivers customized plans and orders.

[0792] Input: customized travel plans and restaurant orders.

[0793] Processing: The server finalizes the customized plan, places the order with the restaurant or delivery service, and arranges travel reservations and delivery services.

[0794] Output: User's travel booking confirmation and delivery order confirmation.

[0795] Step 8:

[0796] Users experience travel and delivery and provide feedback.

[0797] Input: Feedback about your travel and delivery experience.

[0798] Processing: The user provides feedback through the device, which is sent to the server.

[0799] Output: User feedback data.

[0800] Step 9:

[0801] The server will reflect the feedback in future plan generation and restaurant suggestions.

[0802] Input: User feedback data.

[0803] Processing: The server analyzes the collected feedback and updates the information to reflect it in future plan generation and restaurant suggestions. It is used as training data for the generative AI model.

[0804] Output: An updated dataset and a generative AI model.

[0805] 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.

[0806] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. This system collects and integrates information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[0807] Server Roles and Operations

[0808] Data collection and integration

[0809] The server crawls data from the internet, such as transportation timetables, operation status, tourist attractions, food and drink information, and experience reviews. This data is stored in a database and integrated into a consistent format. Filtering is performed to eliminate duplicates and noise data, generating a high-quality dataset.

[0810] Accepting and parsing requests

[0811] The server receives and analyzes the user's request sent from the device, reading the request content (destination, period, interests), and searches for and retrieves the necessary data.

[0812] Plan generation by generative AI

[0813] The server's generation AI generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The generated plan is further customized based on the user's past behavior and preferences.

[0814] Emotional engine regulation

[0815] The server is equipped with an emotion engine that recognizes the user's emotions, and analyzes their emotional state based on their requests and past feedback. Based on this analysis, the travel plan is adjusted to suit the user's needs.

[0816] Providing plans to users and receiving feedback

[0817] The generated plan is provided to the user via the device, and the feedback the user provides after the trip is reflected in the next plan generation.

[0818] Device role and operation

[0819] Providing an interface

[0820] The device provides a user-friendly interface for inputting their request, which displays a form for inputting destination, travel duration, and activities of interest.

[0821] Sending a request and receiving a plan

[0822] The user's input request is sent from the device to the server, and the travel plan generated by the server is displayed to the user in a visually easy-to-understand format on the device.

[0823] User Roles and Actions

[0824] Entering a request

[0825] Using the device's interface, users input their travel and sightseeing preferences, such as "I'd like to visit cultural spots in Tokyo in three days."

[0826] Review and execute the plan

[0827] The user can review the plan sent from the server and customize it as needed. The user adjusts the plan to suit their preferences and then carries out the trip.

[0828] Providing Feedback

[0829] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[0830] Providing emotion data

[0831] Users provide real-time emotional data during their trip, which is captured through the device interface or specific emotion recognition devices, and this emotional data is used to dynamically change information and services provided during the trip.

[0832] Specific examples

[0833] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[0834] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0835] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[0836] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0837] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0838] 5. The user reviews the plan and customizes it as needed.

[0839] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[0840] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[0841] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[0842] The processing flow will be explained below.

[0843] Step 1: Data collection

[0844] The server crawls data from multiple data sources on the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports, and stores this data in a database.

[0845] Step 2: Data integration and filtering

[0846] The server converts the collected data into a consistent format and filters out duplicates and noisy data, producing a high-quality dataset.

[0847] Step 3: Providing a User Interface

[0848] The device provides an interface where users can enter their request, including a form to enter their destination, travel duration, and activities of interest.

[0849] Step 4: Submitting the request

[0850] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[0851] Step 5: Accepting and parsing the request

[0852] The server receives the request sent from the terminal and begins analyzing it. It analyzes the request content and searches the database for the corresponding data.

[0853] Step 6: User sentiment analysis

[0854] The server uses its built-in emotion engine to analyze the user's past feedback and real-time emotion data, and based on this analysis, understands the user's current emotional state.

[0855] Step 7: Generative AI generates a travel plan

[0856] The server's generation AI generates an optimal travel plan based on the results of request analysis and sentiment analysis, including transportation, sightseeing spots, dining options, and itinerary.

[0857] Step 8: Customize your plan

[0858] The server then customizes the generated travel plan based on the user's past behavior and preferences, thereby generating the optimal plan for each user.

[0859] Step 9: Offer your plan

[0860] The server sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format and provides it to the user.

[0861] Step 10: Review and change your plan

[0862] The user checks the travel plan displayed on the device and customizes it as needed. After customization, the request is sent back to the server for replanning.

[0863] Step 11: Real-time sentiment analysis during travel

[0864] When a user travels, real-time emotional data is collected from their device or emotion recognition device. The server's emotion engine analyzes this data and dynamically changes the information and services provided as needed.

[0865] Step 12: Trip execution and evaluation

[0866] The user then undertakes the trip based on the provided plan, and after completing the trip, the user provides evaluation feedback on the travel experience via the device.

[0867] Step 13: Incorporating feedback

[0868] The server receives feedback from users and reflects it in subsequent plan generation, further improving the accuracy of the system.

[0869] The above is the specific program processing flow that combines the emotion engine in the "Chat Travel" system.

[0870] Example 2

[0871] 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."

[0872] Conventional travel planning systems only provide information on transportation timetables and tourist attractions, but lack the ability to dynamically adjust plans based on the user's emotional state, which can lead to unsatisfactory travel experiences. Furthermore, they are unable to reflect user feedback and emotional data in real time during the actual trip, meaning that the travel plans provided often do not match the user's actual situation. This leads to a problem of a poor quality travel experience for users.

[0873] 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.

[0874] In this invention, the server includes: means for collecting data on transportation timetables, operation status, tourist attractions, food and drink information, and experience reports; means for integrating and filtering the data; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered data based on the request; means for providing the optimal travel plan to the user; means including an emotion engine for analyzing the user's emotional state and dynamically adjusting the travel plan; and means for providing emotion data in real time via the user's terminal. This allows the user's travel plan to be dynamically adjusted based on emotions, providing a highly satisfying travel experience that reflects the user's actual emotional state and feedback.

[0875] A "transportation timetable" is a schedule showing the departure and arrival times of public transportation such as buses, trains, and airplanes.

[0876] "Operation status" is information indicating the current operation status of transportation facilities, and includes information such as delays, suspensions, and start of operations.

[0877] "Tourist attractions" are places and attractions that travelers want to visit, including historical buildings, natural landscapes, museums, parks, etc.

[0878] "Food and beverage information" refers to information such as the location, opening hours, menu, and ratings of restaurants.

[0879] "Experience stories" are reviews and travel reports written by people who have traveled in the past, and provide information that travelers can use as reference.

[0880] "Means of collecting data" refers to the technology or devices used to obtain the required information, including crawling tools.

[0881] "Means of data integration and filtering" refers to technologies and devices that convert collected data into a consistent format and remove duplicates and noisy data.

[0882] "Means for receiving requests" refers to the technology or device that allows the server to obtain the user's wishes and requests.

[0883] "Generation means" refers to the technology and algorithms used to create optimal travel plans based on user requirements.

[0884] "Means for providing to users" refers to a method or system for displaying the generated travel plan to users.

[0885] An "emotion engine" refers to the technology and algorithms that analyze a user's emotional state and dynamically adjust travel plans.

[0886] "Terminal" means a device on which a user inputs a request and checks the results, including a smartphone or computer.

[0887] "Feedback" refers to the ratings and opinions users provide about their travel plans and experiences, and is information that will be reflected in the generation of future plans.

[0888] "Means for providing real-time emotional data" refers to technology or devices that instantly acquire a user's emotional state while traveling and transmit it to a server.

[0889] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. The system collects information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[0890] Server Roles and Operations

[0891] Data collection and integration

[0892] The server crawls the internet to collect data such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews. This data is collected using crawling tools such as Python's BeautifulSoup and Scrapy. The collected data is stored in a database such as MySQL or PostgreSQL, and is then filtered to remove duplicates and noise data and consolidate it into a consistent format.

[0893] Accepting and parsing requests

[0894] The server receives the user's request sent from the device, which includes the destination, travel duration, and activities of interest. The server uses NLP techniques (e.g., spaCy or NLTK) to parse the request and executes the appropriate query against the database.

[0895] Plan generation by generative AI

[0896] A generative AI model (e.g., GPT-4) installed on the server generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The plan is further customized based on the user's past behavior and preferences.

[0897] Emotional engine regulation

[0898] The server is equipped with an emotion engine that analyzes the user's emotional state based on their request, past feedback, and emotional data from the trip. The engine uses Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools. Based on the analysis results, the plan is dynamically adjusted.

[0899] Providing plans to users and receiving feedback

[0900] The generated plan is provided to the user in a visually easy-to-understand format via the device, and after the trip, feedback is collected from the user and reflected in future plan generation.

[0901] Device role and operation

[0902] Providing an interface

[0903] The terminal provides an interface where users can easily input their requests. This interface displays a form to input destination, travel duration, and activities of interest. A front-end framework (e.g., React or Vue.js) is used to realize the dynamic user interface.

[0904] Sending a request and receiving a plan

[0905] The user's request is sent from the device to the server, and the travel plan generated by the server is displayed visually on the device. Data is sent in JSON format, and the device displays the results using HTML and JavaScript.

[0906] User Roles and Actions

[0907] Entering a request

[0908] Users use the device interface to input their travel and sightseeing preferences, for example, "I'd like to plan a three-day, two-night trip to Kyoto, mainly to visit temples."

[0909] Review and execute the plan

[0910] The user can review the plan sent from the server, customize it as needed, and once satisfied with the plan, carry out the trip according to that plan.

[0911] Providing feedback and sentiment data

[0912] After completing the trip, users provide feedback on their travel experience within the app, and during the trip, they provide real-time emotional data using their devices or emotion recognition devices, which allows the server to dynamically change the information and services provided.

[0913] Specific examples

[0914] For example, if a user enters a specific prompt such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the process will proceed as follows:

[0915] 1. The user enters a request into the interface and sends it from the terminal to the server.

[0916] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[0917] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[0918] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[0919] 5. The user reviews the plan and customizes it as needed.

[0920] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[0921] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[0922] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[0923] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0924] Step 1:

[0925] The server crawls data from the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[0926] Input: URLs of various sources on the Internet.

[0927] Data processing: The server uses Python's BeautifulSoup and Scrapy to retrieve information from each site, extracting information such as departure and arrival times and status of buses, trains, and planes, detailed information about tourist spots, restaurant locations and menus, and traveler reviews.

[0928] Output: The raw data collected.

[0929] Step 2:

[0930] The server stores the collected data in a database and performs filtering.

[0931] Input: Raw data.

[0932] Data transformation: Before inserting data into MySQL or PostgreSQL, we remove duplicates and noise, and convert data into a consistent format, such as standardizing date formats and removing unnecessary HTML tags.

[0933] Output: Clean data in a filtered database.

[0934] Step 3:

[0935] The server receives the user's request sent from the terminal.

[0936] Input: A request containing the user's preferences (destination, travel duration, and activities of interest).

[0937] Data processing: The server receives the request in JSON format and parses it using NLP techniques (e.g., spaCy or NLTK) to break it down into destinations, durations, and activities of interest, and generates database queries.

[0938] Output: The search query.

[0939] Step 4:

[0940] The server generates the optimal travel plan using a generative AI model.

[0941] Input: Information from a database based on a search query.

[0942] Data processing: A generative AI model (e.g., GPT-4) generates a travel plan based on the tourist attractions and transportation information provided as a result of the query. This plan includes transportation options, tourist attractions, dining options, and itinerary, taking into account the user's past behavior and preferences.

[0943] Output: The generated itinerary.

[0944] Step 5:

[0945] The server uses the emotion engine to dynamically adjust the travel plan.

[0946] Input: Generated itinerary and user's real-time sentiment data.

[0947] Data processing: Using Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools, the system analyzes the user's emotional state in real time. Depending on the user's emotional state, the system can change part of the plan to include a relaxing spot or adjust the schedule.

[0948] Output: Adjusted itinerary.

[0949] Step 6:

[0950] The server transmits the adjusted travel plan to the terminal.

[0951] Input: adjusted travel plans.

[0952] Data processing: Send the adjusted plan to the device in JSON format.

[0953] Output: A visually easy-to-understand itinerary displayed on the device.

[0954] Step 7:

[0955] The user uses the interface to input requests and send them from the terminal to the server.

[0956] Input: Your request for destination, travel duration, activities of interest, etc.

[0957] Data processing: The user enters the request through an intuitive interface (e.g., a web form using HTML and JavaScript) and presses the submit button.

[0958] Output: The request sent to the server in JSON format.

[0959] Step 8:

[0960] Users can check the plans offered on their device and customize them as needed.

[0961] Input: Itinerary sent from the server.

[0962] Data processing: Visually display the plan on the device and provide an interface where users can input changes, such as adding more stops or adjusting the time.

[0963] Output: A customized plan.

[0964] Step 9:

[0965] After completing the trip, the user provides feedback, which is sent from the device to the server.

[0966] Input: Feedback on your travel experience.

[0967] Data processing: Users use a dedicated feedback form to enter their ratings and opinions of their travel experience and press the submit button.

[0968] Output: Feedback information sent to the server in JSON format.

[0969] Step 10:

[0970] The server will incorporate user feedback into the next plan generation.

[0971] Input: Feedback information.

[0972] Data processing: The feedback information is stored in a database and used as reference data when planning your next trip.

[0973] Output: An improved trip plan that takes into account the user's past behavior history and ratings.

[0974] (Application example 2)

[0975] 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."

[0976] While conventional travel planning systems provide tourist spot and transportation information based on user requests, they struggle to adapt to the user's emotional state or changing circumstances during the trip. Finding the best dining options during a trip is also challenging, potentially reducing the quality of the travel experience. Furthermore, there are limited ways to incorporate user feedback into future plans. There is a need for a system that can address these issues, adapt to the user's emotional state and real-time circumstances, and optimize the dining experience during travel.

[0977] The specific processing by the specific 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 means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for adjusting the generated travel plan based on the user's emotional state, and means for generating a dining plan based on the optimal travel plan and providing it to the user. This makes it possible to provide an appropriate travel plan tailored to the user's emotional state and to optimize the dining plan in real time.

[0978] A "transportation timetable" is a table showing the operating times of public transportation (trains, buses, airplanes, etc.).

[0979] "Operation status" is information that indicates the current status of transportation operations, including delays, cancellations, and whether the transportation is running on schedule.

[0980] "Tourist spots" are places and facilities that travelers and tourists want to visit, such as temples, art museums, and natural parks.

[0981] "Dining information" refers to information about restaurants, such as menu items, opening hours, and user ratings.

[0982] "Experiences" are records of travel and sightseeing experiences that users have actually experienced. These include blog articles and social media posts.

[0983] "Data collection methods" refers to the methods and tools used to obtain the required data from the internet and other sources.

[0984] "Data consolidation and filtering measures" refers to the methods and processes used to consolidate and organize collected data and remove unnecessary information.

[0985] "Means for receiving user requests" refers to the method or interface by which users input and send desired information or plans to the system.

[0986] "Generator" refers to the algorithms and engines that create optimal travel and dining plans based on user requests.

[0987] "Means for adjusting based on emotional state" refers to methods and tools that analyze the user's current emotions and change or adapt suggestions accordingly.

[0988] A "food and beverage plan" is a plan that suggests the best places to eat and menus for the user during their trip.

[0989] "Means for providing" refers to an interface or method for presenting the generated plan to the user in an easy-to-view manner.

[0990] This system streamlines users' travel and sightseeing planning and optimizes their travel experience by recognizing their emotions. The system consists of three main components: a server, a terminal, and a user.

[0991] Server Roles and Operations

[0992] Data collection and integration

[0993] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, dining information, and travel experiences. For example, it uses a web crawler to retrieve data from various sources and stores it in a database. The retrieved data is then filtered to remove duplicate and irrelevant information and organized into a unified format.

[0994] Accepting and parsing requests

[0995] The server receives and analyzes the user's request, which includes specific details such as travel destination, duration, and activities of interest, and searches for and retrieves relevant data based on the analyzed request.

[0996] Plan generation by generative AI

[0997] The server uses a generative AI model based on information obtained from the request to generate an optimal travel plan, including transportation, tourist attractions, dining options, and dates. For example, if a user requests a three-day trip to Kyoto's cultural attractions and to dine at highly rated local restaurants, the server can provide the optimal tourist attractions and dining plan.

[0998] Emotional engine regulation

[0999] The server is equipped with an emotion engine that analyzes the user's emotional state based on past feedback and real-time emotional data. If the user's emotional state is "happy," the system will adjust the plan, recommending highly rated restaurants, and if the user's emotional state is "sad," it will recommend comfort food to lift their mood.

[1000] Device role and operation

[1001] Providing an interface

[1002] The terminal provides a user-friendly interface for inputting their request, including forms and menus for selecting destinations, travel duration, and activities of interest.

[1003] Sending a request and receiving a plan

[1004] The requests entered by the user are sent from the device to the server, and the generated travel and dining plans are displayed to the user in a visually easy-to-understand format on the device.

[1005] User Roles and Actions

[1006] Entering a request

[1007] Users use the device interface to input their travel and sightseeing preferences, such as "I'd like to plan a three-day, two-night trip to Kyoto, mainly visiting temples."

[1008] Review and execute the plan

[1009] The user can review the travel and dining plans sent by the server and customize them as needed, for example by adding or removing specific restaurants or tourist attractions.

[1010] Providing Feedback

[1011] After completing a trip, users can provide feedback about their travel experience within the app, which will be reflected in future itineraries, improving the accuracy of the entire system.

[1012] Specific examples

[1013] As a specific example, if the user is "planning a 2-night, 3-day trip to Kyoto and would like delivery from a highly rated Japanese restaurant. The emotional state is happy," the travel plan will include a visit to Kyoto's major temples as well as a delivery plan from a highly rated Japanese restaurant. An example of a prompt sentence is "Suggest delivery from a highly rated Japanese restaurant during the user's stay in Kyoto. The user's emotional state is happy."

[1014] In this way, the present invention can significantly improve the user's travel experience by providing optimal travel plans and dining plans in real time while taking into account the user's emotional state.

[1015] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1016] Step 1: Data collection and integration

[1017] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, food and drink information, and travel experiences. Specifically, it uses a web crawler to retrieve data from various sources and stores it in a database. Input includes the URLs and API endpoints of each source. The output is an integrated dataset. The data is then converted into a unified format after removing duplicates and irrelevant information.

[1018] Step 2: Accepting and parsing the request

[1019] The server receives the user's request sent from the device. The request includes travel destination, duration, and activities of interest. The input is the information the user enters into a form. The server analyzes this information and searches for and retrieves relevant data. The output is a dataset that fits the user's request.

[1020] Step 3: Generative AI generates a plan

[1021] The server uses the analyzed request data to launch a generative AI model. The generative AI model generates an optimal travel plan based on the user's request. Specifically, it creates a plan that includes transportation, tourist spots, dining options, and itinerary. The input is the request data and related information found. The output is an optimal travel plan.

[1022] Step 4: Emotional Engine Adjustment

[1023] The server uses an emotion engine to analyze the user's emotional state. The emotional state is based on past feedback and real-time emotional data. The inputs include the user's past feedback and real-time emotional data. The generated itinerary is adjusted based on the emotion analysis. For example, a "happy" state might recommend highly rated restaurants, and a "sad" state might recommend comfort food. The output is an adjusted itinerary.

[1024] Step 5: Providing an interface and sending requests

[1025] The terminal provides an interface for the user to enter their request. This interface may include forms and menus for entering destination, travel duration, and activities of interest. Once the user enters the information, the terminal sends it to the server. The input is the user-entered data. The output is the request sent by the user to the server.

[1026] Step 6: Review and customize your plan

[1027] The user reviews the travel plan and dining plan provided through the terminal. The plan can be customized as needed. For example, it is possible to add or remove specific tourist spots or restaurants. The input is the provided travel plan and the user's customizations. The output is the final customized travel plan.

[1028] Step 7: Provide feedback

[1029] After completing the trip, the user provides feedback about their travel experience through their device. Input includes evaluations of the experience during the trip and comments. The server collects this feedback information and reflects it in generating future plans. The feedback is also used for analysis by the emotion engine. The output is the accumulated feedback data.

[1030] 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.

[1031] 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.

[1032] 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.

[1033] [Third embodiment]

[1034] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1035] 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.

[1036] 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).

[1037] 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.

[1038] 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.

[1039] 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).

[1040] 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.

[1041] 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.

[1042] 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.

[1043] 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.

[1044] 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.

[1045] 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."

[1046] The present invention is a system that allows users to save a lot of time and effort when planning trips and sightseeing, and provides a fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user, each of which plays a specific role.

[1047] Server Roles and Operations

[1048] Data collection and integration

[1049] The server first crawls data sources on the Internet, collecting information such as transportation timetables, service status, tourist attractions, food and drink information, and travel experiences. After collecting this data, it stores it in a database. Next, it integrates the collected data and converts it into a consistent format. In the process, it filters out duplicates and noise data to create a high-quality dataset.

[1050] Accepting and parsing requests

[1051] The server receives user requests from the device, including destination, travel duration, activities of interest, etc. The server analyzes these requests and retrieves the necessary data based on them.

[1052] Plan generation by generative AI

[1053] The server is equipped with a generation AI that generates the optimal travel plan for the user based on the analyzed request, including transportation, tourist spots to visit, places to eat, dates, etc. It also reflects the user's past behavioral history and preferences to provide an individually customized plan.

[1054] Providing plans to users and receiving feedback

[1055] The generated plan is provided to the user via the device. After the user has completed their trip, they can provide feedback, which will be reflected in the next plan generation.

[1056] Device role and operation

[1057] Providing an interface

[1058] The terminal provides a user-friendly interface for easily entering requests, including a form for inputting destination, duration, and activities of interest.

[1059] Sending a request and receiving a plan

[1060] The user's request is sent from the device to the server, and the server generates a travel plan that is displayed to the user through the device. The plan includes the route on a map, photos of the places to visit, and detailed information.

[1061] User Roles and Actions

[1062] Entering a request

[1063] Users use the device's interface to input their travel and sightseeing preferences, such as "I want to visit cultural spots in Tokyo in three days."

[1064] Review and execute the plan

[1065] Users can review the plan sent from the server and customize it as needed, allowing them to have a travel experience that suits their preferences.

[1066] Providing Feedback

[1067] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries, further improving the accuracy of the system.

[1068] Specific examples

[1069] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1070] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1071] 2. The server receives the request and searches for data on Kyoto's tourist attractions and transportation options. The generative AI then creates the optimal travel plan.

[1072] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1073] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1074] 5. The user reviews the plan and customizes it as needed.

[1075] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[1076] In this way, the present invention improves the efficiency of users' travel planning and provides a fulfilling sightseeing experience.

[1077] The processing flow will be explained below.

[1078] Step 1: Data collection

[1079] The server crawls multiple data sources on the Internet, collecting information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports. This collected data is then stored in a database.

[1080] Step 2: Data integration and filtering

[1081] The server converts the collected data into a consistent format and filters out duplicates and noise data, resulting in a high-quality dataset.

[1082] Step 3: Providing a User Interface

[1083] The terminal provides an interface where users can enter their requests, including a form to enter their destination, travel duration, and activities of interest.

[1084] Step 4: Submitting the request

[1085] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[1086] Step 5: Accepting and parsing the request

[1087] The server receives and analyzes the request sent from the terminal, reading the request content (destination, period, interests) and searching for the necessary data.

[1088] Step 6: Generative AI generates a travel plan

[1089] The server's generation AI creates an optimal travel plan based on the analysis results, including transportation, sightseeing spots, dining options, and itinerary.

[1090] Step 7: Customize your plan

[1091] The server then customizes the generated travel plan based on the user's past behavior and preferences, providing the optimal plan for each user.

[1092] Step 8: Submit your plan

[1093] The server then sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format.

[1094] Step 9: Review and change your plan

[1095] The user can review the travel plan displayed on the device and customize it as needed. Any changes made by the user are sent back to the server, and a replanning request may be required.

[1096] Step 10: Trip execution and evaluation

[1097] The user then carries out the trip based on the provided plan. After completing the trip, the user provides feedback on their experience. This feedback is reflected in the generation of future plans.

[1098] The above is the specific program processing flow of the "Chat Travel" system.

[1099] Example 1

[1100] 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."

[1101] In today's world, users require a wide variety of information when planning trips and sightseeing. Individually researching information such as transportation timetables and service status, tourist spot information, restaurant information, and travel experiences in each location is extremely time-consuming and laborious. This makes it difficult for users to easily create optimal travel plans, and there are few systems that provide plans that reflect individual preferences and past travel history. Furthermore, there is a lack of systems that can utilize post-trip feedback to improve future plans. Given this background, there is a growing need for travel planning systems that can efficiently collect, integrate, and customize information, and incorporate feedback.

[1102] 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.

[1103] In this invention, the server includes: means for collecting information on transportation timetables, operation status, tourist attractions, dining information, and travel experiences; means for integrating and filtering the information; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered information based on the request; means for generating an optimal travel plan based on the user's request using a generative AI model; means for providing the generated optimal travel plan to the user; means for collecting feedback information from users and incorporating it into the generation of the next plan; and means for individually customizing the travel plan generated by the generation means based on the user's past behavioral history and preferences. This makes it possible to efficiently collect and integrate a wide range of information and provide an optimal travel plan tailored to individual preferences. Furthermore, by incorporating user feedback into the next travel plan, an even more accurate and personalized travel experience can be provided.

[1104] "Transportation timetables" are information about detailed schedules of public transportation, such as operating times, stops, and route information.

[1105] "Operation status" refers to real-time operation information such as whether transportation is currently operating, delays, or cancellations.

[1106] "Tourist attractions" are places of interest, famous landmarks, natural landscapes, facilities, etc. within an area that are expected to interest and attract tourists and visitors.

[1107] "Dining information" refers to information about dining facilities in the area, the types of food they offer, business information, ratings, and so on.

[1108] "Experiences" are records of impressions, reviews, and specific experiences of people who have visited a region or experienced a tourist spot in the past.

[1109] "Means of collecting information" refers to the methods and techniques used to obtain the necessary data from the Internet and other data sources and incorporate it into the system.

[1110] "Information integration and filtering measures" are techniques and processes used to organize collected information, remove duplicate data, remove irrelevant data, and prepare it in an appropriate format.

[1111] "Means for receiving requests from users" refers to the interface through which users input their desired travel plans and the method for importing that data into the system.

[1112] "Means for generating optimal travel plans" refers to the process or technology that automatically assembles travel schedules, places to visit, transportation methods, etc. based on collected and integrated data and user requests.

[1113] A "generative AI model" is an algorithm or system that uses artificial intelligence to automatically generate optimal travel plans based on user requests.

[1114] The "means provided to users" refers to interfaces and technologies that allow users to easily view and use the generated travel plans.

[1115] "Means for collecting and reflecting feedback information" refers to the processes and techniques for collecting opinions and impressions from users and using them to generate the next travel plan.

[1116] "Means for customization based on the user's past behavioral history and preferences" refers to the process or technology that analyzes the user's past travel data and preferences and generates the optimal travel plan based on them.

[1117] The present invention is a system that significantly reduces the effort required for users to plan trips and sightseeing, and provides a customized and fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user.

[1118] Server configuration and operation

[1119] Data collection and integration

[1120] The server first uses Python libraries such as BeautifulSoup and Scrapy to collect information such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews from various data sources on the Internet. The crawled data is temporarily stored in a database such as MySQL or PostgreSQL. The Pandas library is then used to filter out duplicates and noise from the data and format it into a consistent format.

[1121] Accepting and parsing requests

[1122] The server receives requests from the device and analyzes the user's desired travel and sightseeing details. Natural language processing libraries such as NLTK and spaCy are used for request analysis. Based on the analyzed request, relevant information is searched for in the database using SQL queries.

[1123] Plan generation by generative AI

[1124] Based on the analyzed request information, the server uses a generative AI (e.g., GPT-4) to generate an optimal travel plan. The generated plan includes transportation, tourist spots to visit, places to eat, and dates. Past behavioral history and preference information are also reflected, resulting in a personalized plan.

[1125] Providing plans to users and receiving feedback

[1126] The generated travel plan is sent to the device and presented in a visually easy-to-understand format. The plan includes a map showing the route, photos of the places visited, and detailed information. After the trip is over, feedback from the user is collected and reflected in future plan generation.

[1127] Terminal configuration and operation

[1128] Providing an interface

[1129] The device provides users with an easy-to-use interface, including a form for inputting destination, duration, and activities they are interested in. For example, it could be offered as a smartphone app or a web browser app, developed using React.js or Flutter.

[1130] Sending a request and receiving a plan

[1131] The request entered by the user is sent from the terminal to the server using an HTTP request, and the travel plan generated by the server is sent to the terminal and displayed on the user interface.

[1132] User Actions

[1133] Entering a request

[1134] Users use the device's interface to input their travel and sightseeing preferences, for example, a specific request such as "I want to visit cultural spots in Tokyo in three days."

[1135] Review and execute the plan

[1136] Users can review the travel plans sent from the server and customize them as needed, allowing them to have a travel experience that suits their preferences.

[1137] Providing Feedback

[1138] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[1139] Specific examples

[1140] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1141] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1142] 2. The server receives the request, searches for information about Kyoto's tourist attractions and transportation options, and the generation AI creates the optimal travel plan.

[1143] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1144] 4. The generated plan is sent to the device and displayed to the user in a visually easy-to-understand format.

[1145] 5. The user reviews the plan and customizes it as needed.

[1146] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[1147] Prompt Sentence Examples

[1148] "I'd like to visit cultural spots in Tokyo in three days. I'd like you to create a recommended itinerary. Places I've visited in the past include Sensoji Temple and Ueno Park."

[1149] In this way, the travel plans provided to users through the system can provide an efficient, customized, and fulfilling experience.

[1150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1151] Step 1: Data collection and integration

[1152] Input: URLs of various data sources on the Internet

[1153] Specific behavior:

[1154] The server uses the Python libraries BeautifulSoup and Scrapy to crawl the Internet for information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[1155] Data processing:

[1156] The crawled data is temporarily stored in storage and then stored in a database (e.g., MySQL, PostgreSQL).

[1157] Output: Information stored in a consistent format in a database

[1158] Step 2: Filtering data and ensuring consistency

[1159] Input: Raw data stored in a database

[1160] Specific behavior:

[1161] The server uses the Pandas library to filter out duplicates and noise from the data and format it into a consistent format.

[1162] Data processing:

[1163] Remove duplicate data, remove noise data, and format it appropriately

[1164] Output: A filtered, formatted, high-quality dataset

[1165] Step 3: Accepting the user request

[1166] Input: Requests entered by the user into the device interface (destination, travel duration, activities of interest, etc.)

[1167] Specific behavior:

[1168] The terminal sends the request entered by the user to the server via an HTTP request.

[1169] Data processing:

[1170] The request content is passed to the server in a format that can be parsed.

[1171] Output: User request data sent to the server

[1172] Step 4: Parsing the request

[1173] Input: User request data sent to the server

[1174] Specific behavior:

[1175] The server uses a natural language processing library such as NLTK or spaCy to analyze the request content.

[1176] Data processing:

[1177] Morphological analysis of request data and extraction of key information

[1178] Output: Parsed user request information

[1179] Step 5: Retrieving information from the database

[1180] Input: Parsed user request information

[1181] Specific behavior:

[1182] The server constructs an SQL query and searches the database for relevant tourist attractions and transportation information.

[1183] Data processing:

[1184] Extracting relevant information from a database and assembling it into sets based on user requests

[1185] Output: Relevant information data corresponding to the user request

[1186] Step 6: Generative AI generates a plan

[1187] Input: Relevant information data corresponding to the user request

[1188] Specific behavior:

[1189] The server uses generative AI (e.g., GPT-4) to generate an optimal travel plan based on the input request and related information data.

[1190] Data processing:

[1191] Enter a prompt into the generative AI and format the response into a travel plan

[1192] Output: Generated optimal travel plan

[1193] Step 7: Serving the generated plan

[1194] Input: Generated optimal itinerary

[1195] Specific behavior:

[1196] The server sends the generated travel plan to the terminal, which displays the plan to the user in a visually easy-to-understand format.

[1197] Data processing:

[1198] Send plan data in JSON format and display it in the user interface

[1199] Output: The itinerary displayed to the user

[1200] Step 8: Accept and implement feedback

[1201] Input: User feedback after the trip is completed

[1202] Specific behavior:

[1203] The device sends user feedback to the server, which then reflects this feedback in the next plan generation.

[1204] Data processing:

[1205] Organize feedback data and save it as input data for the next plan generation

[1206] Output: A dataset incorporating feedback information

[1207] The above are the specific processing steps of the program of this system.

[1208] (Application example 1)

[1209] 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."

[1210] In conventional travel planning systems, users had to individually research transportation timetables, service status, tourist attractions, dining information, and travel experiences, and then create their own plans, which was a significant hassle. Furthermore, when it came to food delivery, users had to consider their past ordering history and preferences when selecting restaurants and dishes, making delivery selection difficult. This resulted in a cumbersome user experience, making efficient travel planning and food delivery difficult.

[1211] 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.

[1212] In this invention, the server includes means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for providing the optimal travel plan to the user, means for suggesting optimal restaurants and dishes based on the user's preferences, past behavioral history, and order history, means for the user to confirm and select the suggested restaurants and dishes, and means for delivering the selected restaurants and dishes, thereby enabling the user to have a fulfilling travel experience and an efficient food delivery experience.

[1213] "Transportation" is a general term for public or private transportation services used as a means of moving people or goods.

[1214] A "timetable" is information that shows the operating times and schedules of transportation facilities.

[1215] "Operation status" refers to information that indicates the current operation status of transportation facilities, delay information, suspension of operations, and other conditions.

[1216] "Tourist attractions" are scenic, cultural or historical places that tourists visit.

[1217] "Dining information" includes information such as restaurant menus, opening hours, locations, and reviews.

[1218] An "experience memoir" is an article or piece of writing that describes a person's experiences and impressions about a certain event or place.

[1219] "Data collection means" refers to the methods and devices that obtain the required information from the Internet and other data sources.

[1220] "Means for integrating and filtering data" refers to methods and devices that organize collected data, remove redundancies and noise, and convert it into a consistent format.

[1221] A "means for receiving a request from a user" is a method or device that provides an input interface for requesting data or information from a user.

[1222] "Generation means" refers to a method or device that combines necessary data based on a user's request to create optimal travel plans and proposals.

[1223] "Means for providing to the user" refers to a method or device for displaying or communicating the generated travel plans or suggestions to the user.

[1224] "User Preferences" are individual interests and preferences based on a user's previously expressed interests and choices.

[1225] "Past behavior history" is a record of the actions and choices a user has made in the past.

[1226] "Order History" is a record of orders placed by a user in the past.

[1227] A "means for making suggestions" is a method or device that makes new suggestions based on collected data and the user's past records.

[1228] A "verification and selection means" is a method or device that provides an interface for a user to verify and select the proposed information.

[1229] "Delivery means" refers to the method or device for delivering the selected product or service to the user.

[1230] The present invention is a system for enabling users to have an efficient and fulfilling travel experience and food delivery experience. This system is composed of three entities: a server, a terminal, and a user, each of which fulfills a specific role.

[1231] Server Roles and Operations

[1232] The server operates using the following methods:

[1233] Data collection and integration

[1234] The server collects data from data sources on the Internet, such as transportation timetables, operation status, tourist attractions, food and drink information, experiences, restaurant information, menus, reviews, etc. The collected data is stored in a database to create a high-quality dataset.

[1235] Accepting and parsing requests

[1236] The server receives and analyzes user requests sent from the device, including destination, travel duration, activities of interest, food preferences, and past ordering history.

[1237] Plan generation and restaurant suggestions using generative AI

[1238] The server is equipped with a generation AI that generates optimal travel plans and restaurant and food suggestions based on user requests. The generated plans include transportation methods, the order in which tourist spots are visited, dining locations, dates, etc., and also reflect the user's preferences and past behavioral history.

[1239] Providing plans to users and receiving feedback

[1240] The server sends the generated travel plan and restaurant recommendations to the terminal and provides them to the user. After the user has completed the trip and received food delivery, they can provide feedback information, which will be reflected in future plan generation and restaurant recommendations.

[1241] The hardware used is a typical server machine for web servers, and the software includes the Django framework and generative AI models such as GPT-3.

[1242] Device role and operation

[1243] Providing an interface

[1244] The device provides users with an easy-to-use interface for inputting their travel plans and on-demand food delivery requests, including forms for inputting destination, travel duration, activity interests, and dietary preferences.

[1245] Sending a request and receiving a plan

[1246] The user's input request is sent from the device to the server, and the generated travel plan and restaurant suggestions are displayed to the user through the device, including the route on a map, restaurant locations, and detailed information.

[1247] The hardware used is a mobile device such as a smartphone or tablet, and a mobile application is installed as related software.

[1248] User Roles and Actions

[1249] Entering a request

[1250] Users use the device's interface to input their travel and sightseeing preferences, as well as their food preferences, such as "I'd like to visit Tokyo's cultural sites over three days" or "I'd like to have Japanese food for dinner tonight."

[1251] Review and implement plans and proposals

[1252] Users can review the travel plans and restaurant suggestions sent by the server and customize them as needed, allowing them to tailor their travel experience and dining to their preferences.

[1253] Providing Feedback

[1254] After completing a trip or delivery, users can provide feedback on their experience within the app, which will be reflected in future plan generation and restaurant suggestions, further improving the accuracy of the system.

[1255] Examples and prompts

[1256] Example 1:

[1257] If a user inputs a request such as "I want to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the server receives the request, searches data on tourist spots and transportation options, and the generation AI creates an optimal travel plan. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day. The generated plan is sent to the device and displayed in a visually easy-to-understand format for the user.

[1258] Example 2:

[1259] When a user types "I want Japanese food for dinner tonight" into a food delivery app, the server analyzes the user's order history and current mood, and the AI ​​generator suggests the most suitable Japanese restaurant. After the user confirms the suggestions and makes a selection, the restaurant delivers the food. After the delivery is complete, the user's feedback is reflected in future suggestions.

[1260] Example prompt sentence:

[1261] 1. The user has previously enjoyed ordering Japanese food. Please suggest three recommended Japanese restaurants in Tokyo.

[1262] 2. A user ordered sushi from "Sushi Place" last week and wants to eat sushi again today. Suggest two new sushi restaurants.

[1263] This provides users with a fulfilling travel experience and an efficient food delivery experience.

[1264] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1265] Step 1:

[1266] The server collects, consolidates, and filters the data.

[1267] Input: Online transportation timetables, operation status, tourist attraction data, food and drink information, experiences, restaurant information, menus, and reviews.

[1268] Processing: The server collects the required data using crawling techniques (e.g., scraping tools or APIs), stores the collected data in a database, and performs a data cleaning step to remove duplicates and noise data.

[1269] Output: A consolidated, filtered, high-quality dataset.

[1270] Step 2:

[1271] The device receives a request from the user.

[1272] Input: User inputs such as travel preferences, food preferences, past behavior, and order history.

[1273] Processing: The user enters their wishes and preferences through the device interface, and the request is sent from the device to the server.

[1274] Output: User request data.

[1275] Step 3:

[1276] The server parses the request and retrieves the required data.

[1277] Input: User request data.

[1278] Processing: Based on the received request, the server queries the relevant data in the database and creates an input dataset to feed into the generative AI model.

[1279] Output: The input dataset to feed into a generative AI model.

[1280] Step 4:

[1281] The server uses the generative AI model to generate optimal travel plans and restaurant suggestions.

[1282] Input: User request data and associated data.

[1283] Processing: Use a generative AI model (e.g., GPT-3) to generate optimal itinerary and restaurant suggestions that match the user's request. Input the prompt sentence into the generative AI model, and parse and assemble the output.

[1284] Output: Optimal itinerary and restaurant suggestions.

[1285] Step 5:

[1286] The server sends the generated plans and proposals to the terminal.

[1287] Input: Best travel plans and restaurant suggestions.

[1288] Processing: Sends the generated plans and proposals to the device for user review and customization.

[1289] Output: Itinerary and restaurant suggestions displayed on the user's device.

[1290] Step 6:

[1291] Users review and customize plans and proposals.

[1292] Input: Provided itinerary and restaurant suggestions.

[1293] Processing: The user checks the plan and proposals through their device and customizes them as needed.

[1294] Output: Customized travel plans and restaurant orders.

[1295] Step 7:

[1296] The server processes and delivers customized plans and orders.

[1297] Input: customized travel plans and restaurant orders.

[1298] Processing: The server finalizes the customized plan, places the order with the restaurant or delivery service, and arranges travel reservations and delivery services.

[1299] Output: User's travel booking confirmation and delivery order confirmation.

[1300] Step 8:

[1301] Users experience travel and delivery and provide feedback.

[1302] Input: Feedback about your travel and delivery experience.

[1303] Processing: The user provides feedback through the device, which is sent to the server.

[1304] Output: User feedback data.

[1305] Step 9:

[1306] The server will reflect the feedback in future plan generation and restaurant suggestions.

[1307] Input: User feedback data.

[1308] Processing: The server analyzes the collected feedback and updates the information to reflect it in future plan generation and restaurant suggestions. It is used as training data for the generative AI model.

[1309] Output: An updated dataset and a generative AI model.

[1310] 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.

[1311] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. This system collects and integrates information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[1312] Server Roles and Operations

[1313] Data collection and integration

[1314] The server crawls data from the internet, such as transportation timetables, operation status, tourist attractions, food and drink information, and experience reviews. This data is stored in a database and integrated into a consistent format. Filtering is performed to eliminate duplicates and noise data, generating a high-quality dataset.

[1315] Accepting and parsing requests

[1316] The server receives and analyzes the user's request sent from the device, reading the request content (destination, period, interests), and searches for and retrieves the necessary data.

[1317] Plan generation by generative AI

[1318] The server's generation AI generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The generated plan is further customized based on the user's past behavior and preferences.

[1319] Emotional engine regulation

[1320] The server is equipped with an emotion engine that recognizes the user's emotions, and analyzes their emotional state based on their requests and past feedback. Based on this analysis, the travel plan is adjusted to suit the user's needs.

[1321] Providing plans to users and receiving feedback

[1322] The generated plan is provided to the user via the device, and the feedback the user provides after the trip is reflected in the next plan generation.

[1323] Device role and operation

[1324] Providing an interface

[1325] The device provides a user-friendly interface for inputting their request, which displays a form for inputting destination, travel duration, and activities of interest.

[1326] Sending a request and receiving a plan

[1327] The user's input request is sent from the device to the server, and the travel plan generated by the server is displayed to the user in a visually easy-to-understand format on the device.

[1328] User Roles and Actions

[1329] Entering a request

[1330] Using the device's interface, users input their travel and sightseeing preferences, such as "I'd like to visit cultural spots in Tokyo in three days."

[1331] Review and execute the plan

[1332] The user can review the plan sent from the server and customize it as needed. The user adjusts the plan to suit their preferences and then carries out the trip.

[1333] Providing Feedback

[1334] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[1335] Providing emotion data

[1336] Users provide real-time emotional data during their trip, which is captured through the device interface or specific emotion recognition devices, and this emotional data is used to dynamically change information and services provided during the trip.

[1337] Specific examples

[1338] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1339] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1340] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[1341] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1342] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1343] 5. The user reviews the plan and customizes it as needed.

[1344] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[1345] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[1346] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[1347] The processing flow will be explained below.

[1348] Step 1: Data collection

[1349] The server crawls data from multiple data sources on the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports, and stores this data in a database.

[1350] Step 2: Data integration and filtering

[1351] The server converts the collected data into a consistent format and filters out duplicates and noisy data, producing a high-quality dataset.

[1352] Step 3: Providing a User Interface

[1353] The device provides an interface where users can enter their request, including a form to enter their destination, travel duration, and activities of interest.

[1354] Step 4: Submitting the request

[1355] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[1356] Step 5: Accepting and parsing the request

[1357] The server receives the request sent from the terminal and begins analyzing it. It analyzes the request content and searches the database for the corresponding data.

[1358] Step 6: User sentiment analysis

[1359] The server uses its built-in emotion engine to analyze the user's past feedback and real-time emotion data, and based on this analysis, understands the user's current emotional state.

[1360] Step 7: Generative AI generates a travel plan

[1361] The server's generation AI generates an optimal travel plan based on the results of request analysis and sentiment analysis, including transportation, sightseeing spots, dining options, and itinerary.

[1362] Step 8: Customize your plan

[1363] The server then customizes the generated travel plan based on the user's past behavior and preferences, thereby generating the optimal plan for each user.

[1364] Step 9: Offer your plan

[1365] The server sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format and provides it to the user.

[1366] Step 10: Review and change your plan

[1367] The user checks the travel plan displayed on the device and customizes it as needed. After customization, the request is sent back to the server for replanning.

[1368] Step 11: Real-time sentiment analysis during travel

[1369] When a user travels, real-time emotional data is collected from their device or emotion recognition device. The server's emotion engine analyzes this data and dynamically changes the information and services provided as needed.

[1370] Step 12: Trip execution and evaluation

[1371] The user then undertakes the trip based on the provided plan, and after completing the trip, the user provides evaluation feedback on the travel experience via the device.

[1372] Step 13: Incorporating feedback

[1373] The server receives feedback from users and reflects it in subsequent plan generation, further improving the accuracy of the system.

[1374] The above is the specific program processing flow that combines the emotion engine in the "Chat Travel" system.

[1375] Example 2

[1376] 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."

[1377] Conventional travel planning systems only provide information on transportation timetables and tourist attractions, but lack the ability to dynamically adjust plans based on the user's emotional state, which can lead to unsatisfactory travel experiences. Furthermore, they are unable to reflect user feedback and emotional data in real time during the actual trip, meaning that the travel plans provided often do not match the user's actual situation. This leads to a problem of a poor quality travel experience for users.

[1378] 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.

[1379] In this invention, the server includes: means for collecting data on transportation timetables, operation status, tourist attractions, food and drink information, and experience reports; means for integrating and filtering the data; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered data based on the request; means for providing the optimal travel plan to the user; means including an emotion engine for analyzing the user's emotional state and dynamically adjusting the travel plan; and means for providing emotion data in real time via the user's terminal. This allows the user's travel plan to be dynamically adjusted based on emotions, providing a highly satisfying travel experience that reflects the user's actual emotional state and feedback.

[1380] A "transportation timetable" is a schedule showing the departure and arrival times of public transportation such as buses, trains, and airplanes.

[1381] "Operation status" is information indicating the current operation status of transportation facilities, and includes information such as delays, suspensions, and start of operations.

[1382] "Tourist attractions" are places and attractions that travelers want to visit, including historical buildings, natural landscapes, museums, parks, etc.

[1383] "Food and beverage information" refers to information such as the location, opening hours, menu, and ratings of restaurants.

[1384] "Experience stories" are reviews and travel reports written by people who have traveled in the past, and provide information that travelers can use as reference.

[1385] "Means of collecting data" refers to the technology or devices used to obtain the required information, including crawling tools.

[1386] "Means of data integration and filtering" refers to technologies and devices that convert collected data into a consistent format and remove duplicates and noisy data.

[1387] "Means for receiving requests" refers to the technology or device that allows the server to obtain the user's wishes and requests.

[1388] "Generation means" refers to the technology and algorithms used to create optimal travel plans based on user requirements.

[1389] "Means for providing to users" refers to a method or system for displaying the generated travel plan to users.

[1390] An "emotion engine" refers to the technology and algorithms that analyze a user's emotional state and dynamically adjust travel plans.

[1391] "Terminal" means a device on which a user inputs a request and checks the results, including a smartphone or computer.

[1392] "Feedback" refers to the ratings and opinions users provide about their travel plans and experiences, and is information that will be reflected in the generation of future plans.

[1393] "Means for providing real-time emotional data" refers to technology or devices that instantly acquire a user's emotional state while traveling and transmit it to a server.

[1394] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. The system collects information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[1395] Server Roles and Operations

[1396] Data collection and integration

[1397] The server crawls the internet to collect data such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews. This data is collected using crawling tools such as Python's BeautifulSoup and Scrapy. The collected data is stored in a database such as MySQL or PostgreSQL, and is then filtered to remove duplicates and noise data and consolidate it into a consistent format.

[1398] Accepting and parsing requests

[1399] The server receives the user's request sent from the device, which includes the destination, travel duration, and activities of interest. The server uses NLP techniques (e.g., spaCy or NLTK) to parse the request and executes the appropriate query against the database.

[1400] Plan generation by generative AI

[1401] A generative AI model (e.g., GPT-4) installed on the server generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The plan is further customized based on the user's past behavior and preferences.

[1402] Emotional engine regulation

[1403] The server is equipped with an emotion engine that analyzes the user's emotional state based on their request, past feedback, and emotional data from the trip. The engine uses Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools. Based on the analysis results, the plan is dynamically adjusted.

[1404] Providing plans to users and receiving feedback

[1405] The generated plan is provided to the user in a visually easy-to-understand format via the device, and after the trip, feedback is collected from the user and reflected in future plan generation.

[1406] Device role and operation

[1407] Providing an interface

[1408] The terminal provides an interface where users can easily input their requests. This interface displays a form to input destination, travel duration, and activities of interest. A front-end framework (e.g., React or Vue.js) is used to realize the dynamic user interface.

[1409] Sending a request and receiving a plan

[1410] The user's request is sent from the device to the server, and the travel plan generated by the server is displayed visually on the device. Data is sent in JSON format, and the device displays the results using HTML and JavaScript.

[1411] User Roles and Actions

[1412] Entering a request

[1413] Users use the device interface to input their travel and sightseeing preferences, for example, "I'd like to plan a three-day, two-night trip to Kyoto, mainly to visit temples."

[1414] Review and execute the plan

[1415] The user can review the plan sent from the server, customize it as needed, and once satisfied with the plan, carry out the trip according to that plan.

[1416] Providing feedback and sentiment data

[1417] After completing the trip, users provide feedback on their travel experience within the app, and during the trip, they provide real-time emotional data using their devices or emotion recognition devices, which allows the server to dynamically change the information and services provided.

[1418] Specific examples

[1419] For example, if a user enters a specific prompt such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the process will proceed as follows:

[1420] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1421] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[1422] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1423] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1424] 5. The user reviews the plan and customizes it as needed.

[1425] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[1426] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[1427] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[1428] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1429] Step 1:

[1430] The server crawls data from the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[1431] Input: URLs of various sources on the Internet.

[1432] Data processing: The server uses Python's BeautifulSoup and Scrapy to retrieve information from each site, extracting information such as departure and arrival times and status of buses, trains, and planes, detailed information about tourist spots, restaurant locations and menus, and traveler reviews.

[1433] Output: The raw data collected.

[1434] Step 2:

[1435] The server stores the collected data in a database and performs filtering.

[1436] Input: Raw data.

[1437] Data transformation: Before inserting data into MySQL or PostgreSQL, we remove duplicates and noise, and convert data into a consistent format, such as standardizing date formats and removing unnecessary HTML tags.

[1438] Output: Clean data in a filtered database.

[1439] Step 3:

[1440] The server receives the user's request sent from the terminal.

[1441] Input: A request containing the user's preferences (destination, travel duration, and activities of interest).

[1442] Data processing: The server receives the request in JSON format and parses it using NLP techniques (e.g., spaCy or NLTK) to break it down into destinations, durations, and activities of interest, and generates database queries.

[1443] Output: The search query.

[1444] Step 4:

[1445] The server generates the optimal travel plan using a generative AI model.

[1446] Input: Information from a database based on a search query.

[1447] Data processing: A generative AI model (e.g., GPT-4) generates a travel plan based on the tourist attractions and transportation information provided as a result of the query. This plan includes transportation options, tourist attractions, dining options, and itinerary, taking into account the user's past behavior and preferences.

[1448] Output: The generated itinerary.

[1449] Step 5:

[1450] The server uses the emotion engine to dynamically adjust the travel plan.

[1451] Input: Generated itinerary and user's real-time sentiment data.

[1452] Data processing: Using Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools, the system analyzes the user's emotional state in real time. Depending on the user's emotional state, the system can change part of the plan to include a relaxing spot or adjust the schedule.

[1453] Output: Adjusted itinerary.

[1454] Step 6:

[1455] The server transmits the adjusted travel plan to the terminal.

[1456] Input: adjusted travel plans.

[1457] Data processing: Send the adjusted plan to the device in JSON format.

[1458] Output: A visually easy-to-understand itinerary displayed on the device.

[1459] Step 7:

[1460] The user uses the interface to input requests and send them from the terminal to the server.

[1461] Input: Your request for destination, travel duration, activities of interest, etc.

[1462] Data processing: The user enters the request through an intuitive interface (e.g., a web form using HTML and JavaScript) and presses the submit button.

[1463] Output: The request sent to the server in JSON format.

[1464] Step 8:

[1465] Users can check the plans offered on their device and customize them as needed.

[1466] Input: Itinerary sent from the server.

[1467] Data processing: Visually display the plan on the device and provide an interface where users can input changes, such as adding more stops or adjusting the time.

[1468] Output: A customized plan.

[1469] Step 9:

[1470] After completing the trip, the user provides feedback, which is sent from the device to the server.

[1471] Input: Feedback on your travel experience.

[1472] Data processing: Users use a dedicated feedback form to enter their ratings and opinions of their travel experience and press the submit button.

[1473] Output: Feedback information sent to the server in JSON format.

[1474] Step 10:

[1475] The server will incorporate user feedback into the next plan generation.

[1476] Input: Feedback information.

[1477] Data processing: The feedback information is stored in a database and used as reference data when planning your next trip.

[1478] Output: An improved trip plan that takes into account the user's past behavior history and ratings.

[1479] (Application example 2)

[1480] 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."

[1481] While conventional travel planning systems provide tourist spot and transportation information based on user requests, they struggle to adapt to the user's emotional state or changing circumstances during the trip. Finding the best dining options during a trip is also challenging, potentially reducing the quality of the travel experience. Furthermore, there are limited ways to incorporate user feedback into future plans. There is a need for a system that can address these issues, adapt to the user's emotional state and real-time circumstances, and optimize the dining experience during travel.

[1482] The specific processing by the specific 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 means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for adjusting the generated travel plan based on the user's emotional state, and means for generating a dining plan based on the optimal travel plan and providing it to the user. This makes it possible to provide an appropriate travel plan tailored to the user's emotional state and to optimize the dining plan in real time.

[1483] A "transportation timetable" is a table showing the operating times of public transportation (trains, buses, airplanes, etc.).

[1484] "Operation status" is information that indicates the current state of transportation operations, including delays, cancellations, and whether the transportation is running on schedule.

[1485] "Tourist spots" are places and facilities that travelers and tourists want to visit, such as temples, art museums, and natural parks.

[1486] "Dining information" refers to information about restaurants, such as menu items, opening hours, and user ratings.

[1487] "Experiences" are records of travel and sightseeing experiences that users have actually experienced. These include blog articles and social media posts.

[1488] "Data collection methods" refers to the methods and tools used to obtain the required data from the internet and other sources.

[1489] "Data consolidation and filtering measures" refers to the methods and processes used to organize and consolidate collected data and remove unnecessary information.

[1490] "Means for receiving user requests" refers to the method or interface by which users input and send desired information or plans to the system.

[1491] "Generator" refers to the algorithms and engines that create optimal travel and dining plans based on user requests.

[1492] "Means for adjusting based on emotional state" refers to methods and tools that analyze the user's current emotions and change or adapt suggestions accordingly.

[1493] A "food and beverage plan" is a plan that suggests the best places to eat and menus for the user during their trip.

[1494] "Means for providing" refers to an interface or method for presenting the generated plan to the user in an easy-to-view manner.

[1495] This system streamlines users' travel and sightseeing planning and optimizes their travel experience by recognizing their emotions. The system consists of three main components: a server, a terminal, and a user.

[1496] Server Roles and Operations

[1497] Data collection and integration

[1498] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, dining information, and travel experiences. For example, it uses a web crawler to retrieve data from various sources and stores it in a database. The retrieved data is then filtered to remove duplicate and irrelevant information and organized into a unified format.

[1499] Accepting and parsing requests

[1500] The server receives and analyzes the user's request, which includes specific details such as travel destination, duration, and activities of interest, and searches for and retrieves relevant data based on the analyzed request.

[1501] Plan generation by generative AI

[1502] The server uses a generative AI model based on information obtained from the request to generate an optimal travel plan, including transportation, tourist attractions, dining options, and dates. For example, if a user requests a three-day trip to Kyoto's cultural attractions and to dine at highly rated local restaurants, the server can provide the optimal tourist attractions and dining plan.

[1503] Emotional engine regulation

[1504] The server is equipped with an emotion engine that analyzes the user's emotional state based on past feedback and real-time emotional data. If the user's emotional state is "happy," the system will adjust the plan, recommending highly rated restaurants, and if the user's emotional state is "sad," it will recommend comfort food to lift their mood.

[1505] Device role and operation

[1506] Providing an interface

[1507] The terminal provides a user-friendly interface for inputting their request, including forms and menus for selecting destinations, travel duration, and activities of interest.

[1508] Sending a request and receiving a plan

[1509] The requests entered by the user are sent from the device to the server, and the generated travel and dining plans are displayed to the user in a visually easy-to-understand format on the device.

[1510] User Roles and Actions

[1511] Entering a request

[1512] Users use the device interface to input their travel and sightseeing preferences, such as "I'd like to plan a three-day, two-night trip to Kyoto, mainly visiting temples."

[1513] Review and execute the plan

[1514] The user can review the travel and dining plans sent by the server and customize them as needed, for example by adding or removing specific restaurants or tourist attractions.

[1515] Providing Feedback

[1516] After completing a trip, users can provide feedback about their travel experience within the app, which will be reflected in future itineraries, improving the accuracy of the entire system.

[1517] Specific examples

[1518] As a specific example, if the user is "planning a 2-night, 3-day trip to Kyoto and would like delivery from a highly rated Japanese restaurant. The emotional state is happy," the travel plan will include a visit to Kyoto's major temples as well as a delivery plan from a highly rated Japanese restaurant. An example of a prompt sentence is "Suggest delivery from a highly rated Japanese restaurant during the user's stay in Kyoto. The user's emotional state is happy."

[1519] In this way, the present invention can significantly improve the user's travel experience by providing optimal travel plans and dining plans in real time while taking into account the user's emotional state.

[1520] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1521] Step 1: Data collection and integration

[1522] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, food and drink information, and travel experiences. Specifically, it uses a web crawler to retrieve data from various sources and stores it in a database. Input includes the URLs and API endpoints of each source. The output is an integrated dataset. The data is then converted into a unified format after removing duplicates and irrelevant information.

[1523] Step 2: Accepting and parsing the request

[1524] The server receives the user's request sent from the device. The request includes travel destination, duration, and activities of interest. The input is the information the user enters into a form. The server analyzes this information and searches for and retrieves relevant data. The output is a dataset that fits the user's request.

[1525] Step 3: Generative AI generates a plan

[1526] The server uses the analyzed request data to launch a generative AI model. The generative AI model generates an optimal travel plan based on the user's request. Specifically, it creates a plan that includes transportation, tourist spots, dining options, and itinerary. The input is the request data and related information found. The output is an optimal travel plan.

[1527] Step 4: Emotional Engine Adjustment

[1528] The server uses an emotion engine to analyze the user's emotional state. The emotional state is based on past feedback and real-time emotional data. The inputs include the user's past feedback and real-time emotional data. The generated itinerary is adjusted based on the emotion analysis. For example, a "happy" state might recommend highly rated restaurants, and a "sad" state might recommend comfort food. The output is an adjusted itinerary.

[1529] Step 5: Providing an interface and sending requests

[1530] The terminal provides an interface for the user to enter their request. This interface may include forms and menus for entering destination, travel duration, and activities of interest. Once the user enters the information, the terminal sends it to the server. The input is the user-entered data. The output is the request sent by the user to the server.

[1531] Step 6: Review and customize your plan

[1532] The user reviews the travel plan and dining plan provided through the terminal. The plan can be customized as needed. For example, it is possible to add or remove specific tourist spots or restaurants. The input is the provided travel plan and the user's customizations. The output is the final customized travel plan.

[1533] Step 7: Provide feedback

[1534] After completing the trip, the user provides feedback about their travel experience through their device. Input includes evaluations of the experience during the trip and comments. The server collects this feedback information and reflects it in generating future plans. The feedback is also used for analysis by the emotion engine. The output is the accumulated feedback data.

[1535] 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.

[1536] 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.

[1537] 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.

[1538] [Fourth embodiment]

[1539] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1540] 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.

[1541] 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).

[1542] 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.

[1543] 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.

[1544] 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).

[1545] 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.

[1546] 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.

[1547] 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.

[1548] 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.

[1549] 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.

[1550] 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.

[1551] 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."

[1552] The present invention is a system that allows users to save a lot of time and effort when planning trips and sightseeing, and provides a fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user, each of which plays a specific role.

[1553] Server Roles and Operations

[1554] Data collection and integration

[1555] The server first crawls data sources on the Internet, collecting information such as transportation timetables, service status, tourist attractions, food and drink information, and travel experiences. After collecting this data, it stores it in a database. Next, it integrates the collected data and converts it into a consistent format. In the process, it filters out duplicates and noise data to create a high-quality dataset.

[1556] Accepting and parsing requests

[1557] The server receives user requests from the device, including destination, travel duration, activities of interest, etc. The server analyzes these requests and retrieves the necessary data based on them.

[1558] Plan generation by generative AI

[1559] The server is equipped with a generation AI that generates the optimal travel plan for the user based on the analyzed request, including transportation, tourist spots to visit, places to eat, dates, etc. It also reflects the user's past behavioral history and preferences to provide an individually customized plan.

[1560] Providing plans to users and receiving feedback

[1561] The generated plan is provided to the user via the device. After the user has completed their trip, they can provide feedback, which will be reflected in the next plan generation.

[1562] Device role and operation

[1563] Providing an interface

[1564] The terminal provides a user-friendly interface for easily entering requests, including a form for inputting destination, duration, and activities of interest.

[1565] Sending a request and receiving a plan

[1566] The user's request is sent from the device to the server, and the server generates a travel plan that is displayed to the user through the device. The plan includes the route on a map, photos of the places to visit, and detailed information.

[1567] User Roles and Actions

[1568] Entering a request

[1569] Users use the device's interface to input their travel and sightseeing preferences, such as "I want to visit cultural spots in Tokyo in three days."

[1570] Review and execute the plan

[1571] Users can review the plan sent from the server and customize it as needed, allowing them to have a travel experience that suits their preferences.

[1572] Providing Feedback

[1573] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries, further improving the accuracy of the system.

[1574] Specific examples

[1575] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1576] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1577] 2. The server receives the request and searches for data on Kyoto's tourist attractions and transportation options. The generative AI then creates the optimal travel plan.

[1578] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1579] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1580] 5. The user reviews the plan and customizes it as needed.

[1581] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[1582] In this way, the present invention improves the efficiency of users' travel planning and provides a fulfilling sightseeing experience.

[1583] The processing flow will be explained below.

[1584] Step 1: Data collection

[1585] The server crawls multiple data sources on the Internet, collecting information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports. This collected data is then stored in a database.

[1586] Step 2: Data integration and filtering

[1587] The server converts the collected data into a consistent format and filters out duplicates and noise data, resulting in a high-quality dataset.

[1588] Step 3: Providing a User Interface

[1589] The terminal provides an interface where users can enter their requests, including a form to enter their destination, travel duration, and activities of interest.

[1590] Step 4: Submitting the request

[1591] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[1592] Step 5: Accepting and parsing the request

[1593] The server receives and analyzes the request sent from the terminal, reading the request content (destination, period, interests) and searching for the necessary data.

[1594] Step 6: Generative AI generates a travel plan

[1595] The server's generation AI creates an optimal travel plan based on the analysis results, including transportation, sightseeing spots, dining options, and itinerary.

[1596] Step 7: Customize your plan

[1597] The server then customizes the generated travel plan based on the user's past behavior and preferences, providing the optimal plan for each user.

[1598] Step 8: Submit your plan

[1599] The server then sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format.

[1600] Step 9: Review and change your plan

[1601] The user can review the travel plan displayed on the device and customize it as needed. Any changes made by the user are sent back to the server, and a replanning request may be required.

[1602] Step 10: Trip execution and evaluation

[1603] The user then carries out the trip based on the provided plan. After completing the trip, the user provides feedback on their experience. This feedback is reflected in the generation of future plans.

[1604] The above is the specific program processing flow of the "Chat Travel" system.

[1605] Example 1

[1606] 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."

[1607] In today's world, users require a wide variety of information when planning trips and sightseeing. Individually researching information such as transportation timetables and service status, tourist spot information, restaurant information, and travel experiences in each location is extremely time-consuming and laborious. This makes it difficult for users to easily create optimal travel plans, and there are few systems that provide plans that reflect individual preferences and past travel history. Furthermore, there is a lack of systems that can utilize post-trip feedback to improve future plans. Given this background, there is a growing need for travel planning systems that can efficiently collect, integrate, and customize information, and incorporate feedback.

[1608] 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.

[1609] In this invention, the server includes: means for collecting information on transportation timetables, operation status, tourist attractions, dining information, and travel experiences; means for integrating and filtering the information; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered information based on the request; means for generating an optimal travel plan based on the user's request using a generative AI model; means for providing the generated optimal travel plan to the user; means for collecting feedback information from users and incorporating it into the generation of the next plan; and means for individually customizing the travel plan generated by the generation means based on the user's past behavioral history and preferences. This makes it possible to efficiently collect and integrate a wide range of information and provide an optimal travel plan tailored to individual preferences. Furthermore, by incorporating user feedback into the next travel plan, an even more accurate and personalized travel experience can be provided.

[1610] "Transportation timetables" are information about detailed schedules of public transportation, such as operating times, stops, and route information.

[1611] "Operation status" refers to real-time operation information such as whether transportation is currently operating, delays, or cancellations.

[1612] "Tourist attractions" are places of interest, famous landmarks, natural landscapes, facilities, etc. within an area that are expected to interest and attract tourists and visitors.

[1613] "Dining information" refers to information about dining facilities in the area, the types of food they offer, business information, ratings, and so on.

[1614] "Experiences" are records of impressions, reviews, and specific experiences of people who have visited a region or experienced a tourist spot in the past.

[1615] "Means of collecting information" refers to the methods and techniques used to obtain the necessary data from the Internet and other data sources and incorporate it into the system.

[1616] "Information integration and filtering measures" are techniques and processes used to organize collected information, remove duplicate data, remove irrelevant data, and prepare it in an appropriate format.

[1617] "Means for receiving requests from users" refers to the interface through which users input their desired travel plans and the method for importing that data into the system.

[1618] "Means for generating optimal travel plans" refers to the process or technology that automatically assembles travel schedules, places to visit, transportation methods, etc. based on collected and integrated data and user requests.

[1619] A "generative AI model" is an algorithm or system that uses artificial intelligence to automatically generate optimal travel plans based on user requests.

[1620] The "means provided to users" refers to interfaces and technologies that allow users to easily view and use the generated travel plans.

[1621] "Means for collecting and reflecting feedback information" refers to the processes and techniques for collecting opinions and impressions from users and using them to generate the next travel plan.

[1622] "Means for customization based on the user's past behavioral history and preferences" refers to the process or technology that analyzes the user's past travel data and preferences and generates the optimal travel plan based on them.

[1623] The present invention is a system that significantly reduces the effort required for users to plan trips and sightseeing, and provides a customized and fulfilling experience. This system is mainly composed of three parties: a server, a terminal, and a user.

[1624] Server configuration and operation

[1625] Data collection and integration

[1626] The server first uses Python libraries such as BeautifulSoup and Scrapy to collect information such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews from various data sources on the Internet. The crawled data is temporarily stored in a database such as MySQL or PostgreSQL. The Pandas library is then used to filter out duplicates and noise from the data and format it into a consistent format.

[1627] Accepting and parsing requests

[1628] The server receives requests from the device and analyzes the user's desired travel and sightseeing details. Natural language processing libraries such as NLTK and spaCy are used for request analysis. Based on the analyzed request, relevant information is searched for in the database using SQL queries.

[1629] Plan generation by generative AI

[1630] Based on the analyzed request information, the server uses a generative AI (e.g., GPT-4) to generate an optimal travel plan. The generated plan includes transportation, tourist spots to visit, places to eat, and dates. Past behavioral history and preference information are also reflected, resulting in a personalized plan.

[1631] Providing plans to users and receiving feedback

[1632] The generated travel plan is sent to the device and presented in a visually easy-to-understand format. The plan includes a map showing the route, photos of the places visited, and detailed information. After the trip is over, feedback from the user is collected and reflected in future plan generation.

[1633] Terminal configuration and operation

[1634] Providing an interface

[1635] The device provides users with an easy-to-use interface, including a form for inputting destination, duration, and activities they are interested in. For example, it could be offered as a smartphone app or a web browser app, developed using React.js or Flutter.

[1636] Sending a request and receiving a plan

[1637] The request entered by the user is sent from the terminal to the server using an HTTP request, and the travel plan generated by the server is sent to the terminal and displayed on the user interface.

[1638] User Actions

[1639] Entering a request

[1640] Users use the device's interface to input their travel and sightseeing preferences, for example, a specific request such as "I want to visit cultural spots in Tokyo in three days."

[1641] Review and execute the plan

[1642] Users can review the travel plans sent from the server and customize them as needed, allowing them to have a travel experience that suits their preferences.

[1643] Providing Feedback

[1644] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[1645] Specific examples

[1646] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1647] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1648] 2. The server receives the request, searches for information about Kyoto's tourist attractions and transportation options, and the generation AI creates the optimal travel plan.

[1649] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1650] 4. The generated plan is sent to the device and displayed to the user in a visually easy-to-understand format.

[1651] 5. The user reviews the plan and customizes it as needed.

[1652] 6. After the trip is over, users provide feedback, which is then reflected in the next itinerary generation.

[1653] Prompt Sentence Examples

[1654] "I'd like to visit cultural spots in Tokyo in three days. I'd like you to create a recommended itinerary. Places I've visited in the past include Sensoji Temple and Ueno Park."

[1655] In this way, the travel plans provided to users through the system can provide an efficient, customized, and fulfilling experience.

[1656] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1657] Step 1: Data collection and integration

[1658] Input: URLs of various data sources on the Internet

[1659] Specific behavior:

[1660] The server uses the Python libraries BeautifulSoup and Scrapy to crawl the Internet for information such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[1661] Data processing:

[1662] The crawled data is temporarily stored in storage and then stored in a database (e.g., MySQL, PostgreSQL).

[1663] Output: Information stored in a consistent format in a database

[1664] Step 2: Filtering data and ensuring consistency

[1665] Input: Raw data stored in a database

[1666] Specific behavior:

[1667] The server uses the Pandas library to filter out duplicates and noise from the data and format it into a consistent format.

[1668] Data processing:

[1669] Remove duplicate data, remove noise data, and format it appropriately

[1670] Output: A filtered, formatted, high-quality dataset

[1671] Step 3: Accepting the user request

[1672] Input: Requests entered by the user into the device interface (destination, travel duration, activities of interest, etc.)

[1673] Specific behavior:

[1674] The terminal sends the request entered by the user to the server via an HTTP request.

[1675] Data processing:

[1676] The request content is passed to the server in a format that can be parsed.

[1677] Output: User request data sent to the server

[1678] Step 4: Parsing the request

[1679] Input: User request data sent to the server

[1680] Specific behavior:

[1681] The server uses a natural language processing library such as NLTK or spaCy to analyze the request content.

[1682] Data processing:

[1683] Morphological analysis of request data and extraction of key information

[1684] Output: Parsed user request information

[1685] Step 5: Retrieving information from the database

[1686] Input: Parsed user request information

[1687] Specific behavior:

[1688] The server constructs an SQL query and searches the database for relevant tourist attractions and transportation information.

[1689] Data processing:

[1690] Extracting relevant information from a database and assembling it into sets based on user requests

[1691] Output: Relevant information data corresponding to the user request

[1692] Step 6: Generative AI generates a plan

[1693] Input: Relevant information data corresponding to the user request

[1694] Specific behavior:

[1695] The server uses generative AI (e.g., GPT-4) to generate an optimal travel plan based on the input request and related information data.

[1696] Data processing:

[1697] Enter a prompt into the generative AI and format the response into a travel plan

[1698] Output: Generated optimal travel plan

[1699] Step 7: Serving the generated plan

[1700] Input: Generated optimal itinerary

[1701] Specific behavior:

[1702] The server sends the generated travel plan to the terminal, which displays the plan to the user in a visually easy-to-understand format.

[1703] Data processing:

[1704] Send plan data in JSON format and display it in the user interface

[1705] Output: The itinerary displayed to the user

[1706] Step 8: Accept and implement feedback

[1707] Input: User feedback after the trip is completed

[1708] Specific behavior:

[1709] The device sends user feedback to the server, which then reflects this feedback in the next plan generation.

[1710] Data processing:

[1711] Organize feedback data and save it as input data for the next plan generation

[1712] Output: A dataset incorporating feedback information

[1713] The above are the specific processing steps of the program of this system.

[1714] (Application example 1)

[1715] 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."

[1716] In conventional travel planning systems, users had to individually research transportation timetables, service status, tourist attractions, dining information, and travel experiences, and then create their own plans, which was a significant hassle. Furthermore, when it came to food delivery, users had to consider their past ordering history and preferences when selecting restaurants and dishes, making delivery selection difficult. This resulted in a cumbersome user experience, making efficient travel planning and food delivery difficult.

[1717] 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.

[1718] In this invention, the server includes means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for providing the optimal travel plan to the user, means for suggesting optimal restaurants and dishes based on the user's preferences, past behavioral history, and order history, means for the user to confirm and select the suggested restaurants and dishes, and means for delivering the selected restaurants and dishes, thereby enabling the user to have a fulfilling travel experience and an efficient food delivery experience.

[1719] "Transportation" is a general term for public or private transportation services used as a means of moving people or goods.

[1720] A "timetable" is information that shows the operating times and schedules of transportation facilities.

[1721] "Operation status" refers to information that indicates the current operation status of transportation facilities, delay information, suspension of operations, and other conditions.

[1722] "Tourist attractions" are scenic, cultural or historical places that tourists visit.

[1723] "Dining information" includes information such as restaurant menus, opening hours, locations, and reviews.

[1724] An "experience memoir" is an article or piece of writing that describes a person's experiences and impressions about a certain event or place.

[1725] "Data collection means" refers to the methods and devices that obtain the required information from the Internet and other data sources.

[1726] "Means for integrating and filtering data" refers to methods and devices that organize collected data, remove redundancies and noise, and convert it into a consistent format.

[1727] A "means for receiving a request from a user" is a method or device that provides an input interface for requesting data or information from a user.

[1728] "Generation means" refers to a method or device that combines necessary data based on a user's request to create optimal travel plans and proposals.

[1729] "Means for providing to the user" refers to a method or device for displaying or communicating the generated travel plans or suggestions to the user.

[1730] "User Preferences" are individual interests and preferences based on a user's previously expressed interests and choices.

[1731] "Past behavior history" is a record of the actions and choices a user has made in the past.

[1732] "Order History" is a record of orders placed by a user in the past.

[1733] A "means for making suggestions" is a method or device that makes new suggestions based on collected data and the user's past records.

[1734] A "verification and selection means" is a method or device that provides an interface for a user to verify and select the proposed information.

[1735] "Delivery means" refers to the method or device for delivering the selected product or service to the user.

[1736] The present invention is a system for enabling users to have an efficient and fulfilling travel experience and food delivery experience. This system is composed of three entities: a server, a terminal, and a user, each of which fulfills a specific role.

[1737] Server Roles and Operations

[1738] The server operates using the following methods:

[1739] Data collection and integration

[1740] The server collects data from data sources on the Internet, such as transportation timetables, operation status, tourist attractions, food and drink information, experiences, restaurant information, menus, reviews, etc. The collected data is stored in a database to create a high-quality dataset.

[1741] Accepting and parsing requests

[1742] The server receives and analyzes user requests sent from the device, including destination, travel duration, activities of interest, food preferences, and past ordering history.

[1743] Plan generation and restaurant suggestions using generative AI

[1744] The server is equipped with a generation AI that generates optimal travel plans and restaurant and food suggestions based on user requests. The generated plans include transportation methods, the order in which tourist spots are visited, dining locations, dates, etc., and also reflect the user's preferences and past behavioral history.

[1745] Providing plans to users and receiving feedback

[1746] The server sends the generated travel plan and restaurant recommendations to the terminal and provides them to the user. After the user has completed the trip and received food delivery, they can provide feedback information, which will be reflected in future plan generation and restaurant recommendations.

[1747] The hardware used is a typical server machine for web servers, and the software includes the Django framework and generative AI models such as GPT-3.

[1748] Device role and operation

[1749] Providing an interface

[1750] The device provides users with an easy-to-use interface for inputting their travel plans and on-demand food delivery requests, including forms for inputting destination, travel duration, activity interests, and dietary preferences.

[1751] Sending a request and receiving a plan

[1752] The user's input request is sent from the device to the server, and the generated travel plan and restaurant suggestions are displayed to the user through the device, including the route on a map, restaurant locations, and detailed information.

[1753] The hardware used is a mobile device such as a smartphone or tablet, and a mobile application is installed as related software.

[1754] User Roles and Actions

[1755] Entering a request

[1756] Users use the device's interface to input their travel and sightseeing preferences, as well as their food preferences, such as "I'd like to visit Tokyo's cultural sites over three days" or "I'd like to have Japanese food for dinner tonight."

[1757] Review and implement plans and proposals

[1758] Users can review the travel plans and restaurant suggestions sent by the server and customize them as needed, allowing them to tailor their travel experience and dining to their preferences.

[1759] Providing Feedback

[1760] After completing a trip or delivery, users can provide feedback on their experience within the app, which will be reflected in future plan generation and restaurant suggestions, further improving the accuracy of the system.

[1761] Examples and prompts

[1762] Example 1:

[1763] If a user inputs a request such as "I want to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the server receives the request, searches data on tourist spots and transportation options, and the generation AI creates an optimal travel plan. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day. The generated plan is sent to the device and displayed in a visually easy-to-understand format for the user.

[1764] Example 2:

[1765] When a user types "I want Japanese food for dinner tonight" into a food delivery app, the server analyzes the user's order history and current mood, and the AI ​​generator suggests the most suitable Japanese restaurant. After the user confirms the suggestions and makes a selection, the restaurant delivers the food. After the delivery is complete, the user's feedback is reflected in future suggestions.

[1766] Example prompt sentence:

[1767] 1. The user has previously enjoyed ordering Japanese food. Please suggest three recommended Japanese restaurants in Tokyo.

[1768] 2. A user ordered sushi from "Sushi Place" last week and wants to eat sushi again today. Suggest two new sushi restaurants.

[1769] This provides users with a fulfilling travel experience and an efficient food delivery experience.

[1770] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1771] Step 1:

[1772] The server collects, consolidates, and filters the data.

[1773] Input: Online transportation timetables, operation status, tourist attraction data, food and drink information, experiences, restaurant information, menus, and reviews.

[1774] Processing: The server collects the required data using crawling techniques (e.g., scraping tools or APIs), stores the collected data in a database, and performs a data cleaning step to remove duplicates and noise data.

[1775] Output: A consolidated, filtered, high-quality dataset.

[1776] Step 2:

[1777] The device receives a request from the user.

[1778] Input: User inputs such as travel preferences, food preferences, past behavior, and order history.

[1779] Processing: The user enters their wishes and preferences through the device interface, and the request is sent from the device to the server.

[1780] Output: User request data.

[1781] Step 3:

[1782] The server parses the request and retrieves the required data.

[1783] Input: User request data.

[1784] Processing: Based on the received request, the server queries the relevant data in the database and creates an input dataset to feed into the generative AI model.

[1785] Output: The input dataset to feed into a generative AI model.

[1786] Step 4:

[1787] The server uses the generative AI model to generate optimal travel plans and restaurant suggestions.

[1788] Input: User request data and associated data.

[1789] Processing: Use a generative AI model (e.g., GPT-3) to generate optimal itinerary and restaurant suggestions that match the user's request. Input the prompt sentence into the generative AI model, and parse and assemble the output.

[1790] Output: Optimal itinerary and restaurant suggestions.

[1791] Step 5:

[1792] The server sends the generated plans and proposals to the terminal.

[1793] Input: Best travel plans and restaurant suggestions.

[1794] Processing: Sends the generated plans and proposals to the device for user review and customization.

[1795] Output: Itinerary and restaurant suggestions displayed on the user's device.

[1796] Step 6:

[1797] Users review and customize plans and proposals.

[1798] Input: Provided itinerary and restaurant suggestions.

[1799] Processing: The user checks the plan and proposals through their device and customizes them as needed.

[1800] Output: Customized travel plans and restaurant orders.

[1801] Step 7:

[1802] The server processes and delivers customized plans and orders.

[1803] Input: customized travel plans and restaurant orders.

[1804] Processing: The server finalizes the customized plan, places the order with the restaurant or delivery service, and arranges travel reservations and delivery services.

[1805] Output: User's travel booking confirmation and delivery order confirmation.

[1806] Step 8:

[1807] Users experience travel and delivery and provide feedback.

[1808] Input: Feedback about your travel and delivery experience.

[1809] Processing: The user provides feedback through the device, which is sent to the server.

[1810] Output: User feedback data.

[1811] Step 9:

[1812] The server will reflect the feedback in future plan generation and restaurant suggestions.

[1813] Input: User feedback data.

[1814] Processing: The server analyzes the collected feedback and updates the information to reflect it in future plan generation and restaurant suggestions. It is used as training data for the generative AI model.

[1815] Output: An updated dataset and a generative AI model.

[1816] 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.

[1817] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. This system collects and integrates information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[1818] Server Roles and Operations

[1819] Data collection and integration

[1820] The server crawls data from the internet, such as transportation timetables, operation status, tourist attractions, food and drink information, and experience reviews. This data is stored in a database and integrated into a consistent format. Filtering is performed to eliminate duplicates and noise data, generating a high-quality dataset.

[1821] Accepting and parsing requests

[1822] The server receives and analyzes the user's request sent from the device, reading the request content (destination, period, interests), and searches for and retrieves the necessary data.

[1823] Plan generation by generative AI

[1824] The server's generation AI generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The generated plan is further customized based on the user's past behavior and preferences.

[1825] Emotional engine regulation

[1826] The server is equipped with an emotion engine that recognizes the user's emotions, and analyzes their emotional state based on their requests and past feedback. Based on this analysis, the travel plan is adjusted to suit the user's needs.

[1827] Providing plans to users and receiving feedback

[1828] The generated plan is provided to the user via the device, and the feedback the user provides after the trip is reflected in the next plan generation.

[1829] Device role and operation

[1830] Providing an interface

[1831] The device provides a user-friendly interface for inputting their request, which displays a form for inputting destination, travel duration, and activities of interest.

[1832] Sending a request and receiving a plan

[1833] The user's input request is sent from the device to the server, and the travel plan generated by the server is displayed to the user in a visually easy-to-understand format on the device.

[1834] User Roles and Actions

[1835] Entering a request

[1836] Using the device's interface, users input their travel and sightseeing preferences, such as "I'd like to visit cultural spots in Tokyo in three days."

[1837] Review and execute the plan

[1838] The user can review the plan sent from the server and customize it as needed. The user adjusts the plan to suit their preferences and then carries out the trip.

[1839] Providing Feedback

[1840] After completing a trip, users can provide feedback on their travel experience within the app, which will be reflected in future itineraries.

[1841] Providing emotion data

[1842] Users provide real-time emotional data during their trip, which is captured through the device interface or specific emotion recognition devices, and this emotional data is used to dynamically change information and services provided during the trip.

[1843] Specific examples

[1844] For example, if a user inputs a request such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly to visit temples," the process will proceed as follows:

[1845] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1846] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[1847] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1848] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1849] 5. The user reviews the plan and customizes it as needed.

[1850] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[1851] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[1852] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[1853] The processing flow will be explained below.

[1854] Step 1: Data collection

[1855] The server crawls data from multiple data sources on the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports, and stores this data in a database.

[1856] Step 2: Data integration and filtering

[1857] The server converts the collected data into a consistent format and filters out duplicates and noisy data, producing a high-quality dataset.

[1858] Step 3: Providing a User Interface

[1859] The device provides an interface where users can enter their request, including a form to enter their destination, travel duration, and activities of interest.

[1860] Step 4: Submitting the request

[1861] Users input their desired destination, travel duration, and activities of interest into the interface and submit a request, which is then sent from the device to the server.

[1862] Step 5: Accepting and parsing the request

[1863] The server receives the request sent from the terminal and begins analyzing it. It analyzes the request content and searches the database for the corresponding data.

[1864] Step 6: User sentiment analysis

[1865] The server uses its built-in emotion engine to analyze the user's past feedback and real-time emotion data, and based on this analysis, understands the user's current emotional state.

[1866] Step 7: Generative AI generates a travel plan

[1867] The server's generation AI generates an optimal travel plan based on the results of request analysis and sentiment analysis, including transportation, sightseeing spots, dining options, and itinerary.

[1868] Step 8: Customize your plan

[1869] The server then customizes the generated travel plan based on the user's past behavior and preferences, thereby generating the optimal plan for each user.

[1870] Step 9: Offer your plan

[1871] The server sends the completed travel plan to the terminal, which displays the plan in a visually easy-to-understand format and provides it to the user.

[1872] Step 10: Review and change your plan

[1873] The user checks the travel plan displayed on the device and customizes it as needed. After customization, the request is sent back to the server for replanning.

[1874] Step 11: Real-time sentiment analysis during travel

[1875] When a user travels, real-time emotional data is collected from their device or emotion recognition device. The server's emotion engine analyzes this data and dynamically changes the information and services provided as needed.

[1876] Step 12: Trip execution and evaluation

[1877] The user then undertakes the trip based on the provided plan, and after completing the trip, the user provides evaluation feedback on the travel experience via the device.

[1878] Step 13: Incorporating feedback

[1879] The server receives feedback from users and reflects it in subsequent plan generation, further improving the accuracy of the system.

[1880] The above is the specific program processing flow that combines the emotion engine in the "Chat Travel" system.

[1881] Example 2

[1882] 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."

[1883] Conventional travel planning systems only provide information on transportation timetables and tourist attractions, but lack the ability to dynamically adjust plans based on the user's emotional state, which can lead to unsatisfactory travel experiences. Furthermore, they are unable to reflect user feedback and emotional data in real time during the actual trip, meaning that the travel plans provided often do not match the user's actual situation. This leads to a problem of a poor quality travel experience for users.

[1884] 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.

[1885] In this invention, the server includes: means for collecting data on transportation timetables, operation status, tourist attractions, food and drink information, and experience reports; means for integrating and filtering the data; means for receiving requests from users; means for generating an optimal travel plan from the integrated and filtered data based on the request; means for providing the optimal travel plan to the user; means including an emotion engine for analyzing the user's emotional state and dynamically adjusting the travel plan; and means for providing emotion data in real time via the user's terminal. This allows the user's travel plan to be dynamically adjusted based on emotions, providing a highly satisfying travel experience that reflects the user's actual emotional state and feedback.

[1886] A "transportation timetable" is a schedule showing the departure and arrival times of public transportation such as buses, trains, and airplanes.

[1887] "Operation status" is information indicating the current operation status of transportation facilities, and includes information such as delays, suspensions, and start of operations.

[1888] "Tourist attractions" are places and attractions that travelers want to visit, including historical buildings, natural landscapes, museums, parks, etc.

[1889] "Food and beverage information" refers to information such as the location, opening hours, menu, and ratings of restaurants.

[1890] "Experience stories" are reviews and travel reports written by people who have traveled in the past, and provide information that travelers can use as reference.

[1891] "Means of collecting data" refers to the technology or devices used to obtain the required information, including crawling tools.

[1892] "Means of data integration and filtering" refers to technologies and devices that convert collected data into a consistent format and remove duplicates and noisy data.

[1893] "Means for receiving requests" refers to the technology or device that allows the server to obtain the user's wishes and requests.

[1894] "Generation means" refers to the technology and algorithms used to create optimal travel plans based on user requirements.

[1895] "Means for providing to users" refers to a method or system for displaying the generated travel plan to users.

[1896] An "emotion engine" refers to the technology and algorithms that analyze a user's emotional state and dynamically adjust travel plans.

[1897] "Terminal" means a device on which a user inputs a request and checks the results, including a smartphone or computer.

[1898] "Feedback" refers to the ratings and opinions users provide about their travel plans and experiences, and is information that will be reflected in the generation of future plans.

[1899] "Means for providing real-time emotional data" refers to technology or devices that instantly acquire a user's emotional state while traveling and transmit it to a server.

[1900] This invention is a system that streamlines users' travel and sightseeing planning and optimizes the travel experience by recognizing the user's emotions. The system collects information such as transportation timetables and operation status, tourist spots, food and drink information, and travel experiences, and provides optimal travel plans based on the user's requests. In addition, by combining it with an emotion engine, it is possible to adjust travel plans and dynamically change the information provided based on the user's emotions.

[1901] Server Roles and Operations

[1902] Data collection and integration

[1903] The server crawls the internet to collect data such as transportation timetables, service status, tourist attractions, food and drink information, and experience reviews. This data is collected using crawling tools such as Python's BeautifulSoup and Scrapy. The collected data is stored in a database such as MySQL or PostgreSQL, and is then filtered to remove duplicates and noise data and consolidate it into a consistent format.

[1904] Accepting and parsing requests

[1905] The server receives the user's request sent from the device, which includes the destination, travel duration, and activities of interest. The server uses NLP techniques (e.g., spaCy or NLTK) to parse the request and executes the appropriate query against the database.

[1906] Plan generation by generative AI

[1907] A generative AI model (e.g., GPT-4) installed on the server generates an optimal travel plan based on the analyzed request, including transportation, tourist attractions, dining options, and itinerary. The plan is further customized based on the user's past behavior and preferences.

[1908] Emotional engine regulation

[1909] The server is equipped with an emotion engine that analyzes the user's emotional state based on their request, past feedback, and emotional data from the trip. The engine uses Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools. Based on the analysis results, the plan is dynamically adjusted.

[1910] Providing plans to users and receiving feedback

[1911] The generated plan is provided to the user in a visually easy-to-understand format via the device, and after the trip, feedback is collected from the user and reflected in future plan generation.

[1912] Device role and operation

[1913] Providing an interface

[1914] The terminal provides an interface where users can easily input their requests. This interface displays a form to input destination, travel duration, and activities of interest. A front-end framework (e.g., React or Vue.js) is used to realize the dynamic user interface.

[1915] Sending a request and receiving a plan

[1916] The user's request is sent from the device to the server, and the travel plan generated by the server is displayed visually on the device. Data is sent in JSON format, and the device displays the results using HTML and JavaScript.

[1917] User Roles and Actions

[1918] Entering a request

[1919] Users use the device interface to input their travel and sightseeing preferences, for example, "I'd like to plan a three-day, two-night trip to Kyoto, mainly to visit temples."

[1920] Review and execute the plan

[1921] The user can review the plan sent from the server, customize it as needed, and once satisfied with the plan, carry out the trip according to that plan.

[1922] Providing feedback and sentiment data

[1923] After completing the trip, users provide feedback on their travel experience within the app, and during the trip, they provide real-time emotional data using their devices or emotion recognition devices, which allows the server to dynamically change the information and services provided.

[1924] Specific examples

[1925] For example, if a user enters a specific prompt such as "I would like to plan a 2-night, 3-day trip to Kyoto, mainly visiting temples," the process will proceed as follows:

[1926] 1. The user enters a request into the interface and sends it from the terminal to the server.

[1927] 2. The server receives the request, searches for data on Kyoto's tourist attractions and transportation options, and the generative AI creates the optimal travel plan.

[1928] 3. The plan includes visiting Kiyomizu-dera Temple and Gion on the first day, and Kinkaku-ji Temple and Arashiyama on the second day.

[1929] 4. The generated plan is sent to the device and displayed to the user in a visually understandable format.

[1930] 5. The user reviews the plan and customizes it as needed.

[1931] 6. During the journey, real-time emotional data is acquired through terminals and emotion recognition devices, and the emotion engine on the server dynamically adjusts the information and services provided accordingly.

[1932] 7. After completing the trip, users provide feedback, which is then reflected in the generation of the next plan.

[1933] In this way, the present invention streamlines users' travel planning and provides a fulfilling sightseeing experience, while the introduction of an emotion engine realizes even more satisfying service.

[1934] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1935] Step 1:

[1936] The server crawls data from the Internet, such as transportation timetables, operation status, tourist spots, food and drink information, and experience reports.

[1937] Input: URLs of various sources on the Internet.

[1938] Data processing: The server uses Python's BeautifulSoup and Scrapy to retrieve information from each site, extracting information such as departure and arrival times and status of buses, trains, and planes, detailed information about tourist spots, restaurant locations and menus, and traveler reviews.

[1939] Output: The raw data collected.

[1940] Step 2:

[1941] The server stores the collected data in a database and performs filtering.

[1942] Input: Raw data.

[1943] Data transformation: Before inserting data into MySQL or PostgreSQL, we remove duplicates and noise, and convert data into a consistent format, such as standardizing date formats and removing unnecessary HTML tags.

[1944] Output: Clean data in a filtered database.

[1945] Step 3:

[1946] The server receives the user's request sent from the terminal.

[1947] Input: A request containing the user's preferences (destination, travel duration, and activities of interest).

[1948] Data processing: The server receives the request in JSON format and parses it using NLP techniques (e.g., spaCy or NLTK) to break it down into destinations, durations, and activities of interest, and generates database queries.

[1949] Output: The search query.

[1950] Step 4:

[1951] The server generates the optimal travel plan using a generative AI model.

[1952] Input: Information from a database based on a search query.

[1953] Data processing: A generative AI model (e.g., GPT-4) generates a travel plan based on the tourist attractions and transportation information provided as a result of the query. This plan includes transportation options, tourist attractions, dining options, and itinerary, taking into account the user's past behavior and preferences.

[1954] Output: The generated itinerary.

[1955] Step 5:

[1956] The server uses the emotion engine to dynamically adjust the travel plan.

[1957] Input: Generated itinerary and user's real-time sentiment data.

[1958] Data processing: Using Microsoft Azure's emotion recognition API and IBM Watson's emotion analysis tools, the system analyzes the user's emotional state in real time. Depending on the user's emotional state, the system can change part of the plan to include a relaxing spot or adjust the schedule.

[1959] Output: Adjusted itinerary.

[1960] Step 6:

[1961] The server transmits the adjusted travel plan to the terminal.

[1962] Input: adjusted travel plans.

[1963] Data processing: Send the adjusted plan to the device in JSON format.

[1964] Output: A visually easy-to-understand itinerary displayed on the device.

[1965] Step 7:

[1966] The user uses the interface to input requests and send them from the terminal to the server.

[1967] Input: Your request for destination, travel duration, activities of interest, etc.

[1968] Data processing: The user enters the request through an intuitive interface (e.g., a web form using HTML and JavaScript) and presses the submit button.

[1969] Output: The request sent to the server in JSON format.

[1970] Step 8:

[1971] Users can check the plans offered on their device and customize them as needed.

[1972] Input: Itinerary sent from the server.

[1973] Data processing: Visually display the plan on the device and provide an interface where users can input changes, such as adding more stops or adjusting the time.

[1974] Output: A customized plan.

[1975] Step 9:

[1976] After completing the trip, the user provides feedback, which is sent from the device to the server.

[1977] Input: Feedback on your travel experience.

[1978] Data processing: Users use a dedicated feedback form to enter their ratings and opinions of their travel experience and press the submit button.

[1979] Output: Feedback information sent to the server in JSON format.

[1980] Step 10:

[1981] The server will incorporate user feedback into the next plan generation.

[1982] Input: Feedback information.

[1983] Data processing: The feedback information is stored in a database and used as reference data when planning your next trip.

[1984] Output: An improved trip plan that takes into account the user's past behavior history and ratings.

[1985] (Application example 2)

[1986] 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."

[1987] While conventional travel planning systems provide tourist spot and transportation information based on user requests, they struggle to adapt to the user's emotional state or changing circumstances during the trip. Finding the best dining options during a trip is also challenging, potentially reducing the quality of the travel experience. Furthermore, there are limited ways to incorporate user feedback into future plans. There is a need for a system that can address these issues, adapt to the user's emotional state and real-time circumstances, and optimize the dining experience during travel.

[1988] The specific processing by the specific 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 means for collecting data on transportation timetables, operation status, tourist spots, food and drink information, and experience stories, means for integrating and filtering the data, means for receiving requests from users, means for generating an optimal travel plan from the integrated and filtered data based on the request, means for adjusting the generated travel plan based on the user's emotional state, and means for generating a dining plan based on the optimal travel plan and providing it to the user. This makes it possible to provide an appropriate travel plan tailored to the user's emotional state and to optimize the dining plan in real time.

[1989] A "transportation timetable" is a table showing the operating times of public transportation (trains, buses, airplanes, etc.).

[1990] "Operation status" is information that indicates the current state of transportation operations, including delays, cancellations, and whether the transportation is running on schedule.

[1991] "Tourist spots" are places and facilities that travelers and tourists want to visit, such as temples, art museums, and natural parks.

[1992] "Dining information" refers to information about restaurants, such as menu items, opening hours, and user ratings.

[1993] "Experiences" are records of travel and sightseeing experiences that users have actually experienced. These include blog articles and social media posts.

[1994] "Data collection methods" refers to the methods and tools used to obtain the required data from the internet and other sources.

[1995] "Data consolidation and filtering measures" refers to the methods and processes used to organize and consolidate collected data and remove unnecessary information.

[1996] "Means for receiving user requests" refers to the method or interface by which users input and send desired information or plans to the system.

[1997] "Generator" refers to the algorithms and engines that create optimal travel and dining plans based on user requests.

[1998] "Means for adjusting based on emotional state" refers to methods and tools that analyze the user's current emotions and change or adapt suggestions accordingly.

[1999] A "food and beverage plan" is a plan that suggests the best places to eat and menus for the user during their trip.

[2000] "Means for providing" refers to an interface or method for presenting the generated plan to the user in an easy-to-view manner.

[2001] This system streamlines users' travel and sightseeing planning and optimizes their travel experience by recognizing their emotions. The system consists of three main components: a server, a terminal, and a user.

[2002] Server Roles and Operations

[2003] Data collection and integration

[2004] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, dining information, and travel experiences. For example, it uses a web crawler to retrieve data from various sources and stores it in a database. The retrieved data is then filtered to remove duplicate and irrelevant information and organized into a unified format.

[2005] Accepting and parsing requests

[2006] The server receives and analyzes the user's request, which includes specific details such as travel destination, duration, and activities of interest, and searches for and retrieves relevant data based on the analyzed request.

[2007] Plan generation by generative AI

[2008] The server uses a generative AI model based on information obtained from the request to generate an optimal travel plan, including transportation, tourist attractions, dining options, and dates. For example, if a user requests a three-day trip to Kyoto's cultural attractions and to dine at highly rated local restaurants, the server can provide the optimal tourist attractions and dining plan.

[2009] Emotional engine regulation

[2010] The server is equipped with an emotion engine that analyzes the user's emotional state based on past feedback and real-time emotional data. If the user's emotional state is "happy," the system will adjust the plan, recommending highly rated restaurants, and if the user's emotional state is "sad," it will recommend comfort food to lift their mood.

[2011] Device role and operation

[2012] Providing an interface

[2013] The terminal provides a user-friendly interface for inputting their request, including forms and menus for selecting destinations, travel duration, and activities of interest.

[2014] Sending a request and receiving a plan

[2015] The requests entered by the user are sent from the device to the server, and the generated travel and dining plans are displayed to the user in a visually easy-to-understand format on the device.

[2016] User Roles and Actions

[2017] Entering a request

[2018] Users use the device interface to input their travel and sightseeing preferences, such as "I'd like to plan a three-day, two-night trip to Kyoto, mainly visiting temples."

[2019] Review and execute the plan

[2020] The user can review the travel and dining plans sent by the server and customize them as needed, for example by adding or removing specific restaurants or tourist attractions.

[2021] Providing Feedback

[2022] After completing a trip, users can provide feedback about their travel experience within the app, which will be reflected in future itineraries, improving the accuracy of the entire system.

[2023] Specific examples

[2024] As a specific example, if the user is "planning a 2-night, 3-day trip to Kyoto and would like delivery from a highly rated Japanese restaurant. The emotional state is happy," the travel plan will include a visit to Kyoto's major temples as well as a delivery plan from a highly rated Japanese restaurant. An example of a prompt sentence is "Suggest delivery from a highly rated Japanese restaurant during the user's stay in Kyoto. The user's emotional state is happy."

[2025] In this way, the present invention can significantly improve the user's travel experience by providing optimal travel plans and dining plans in real time while taking into account the user's emotional state.

[2026] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2027] Step 1: Data collection and integration

[2028] The server collects data from the internet and elsewhere, including information on transportation schedules, service status, tourist attractions, food and drink information, and travel experiences. Specifically, it uses a web crawler to retrieve data from various sources and stores it in a database. Input includes the URLs and API endpoints of each source. The output is an integrated dataset. The data is then converted into a unified format after removing duplicates and irrelevant information.

[2029] Step 2: Accepting and parsing the request

[2030] The server receives the user's request sent from the device. The request includes travel destination, duration, and activities of interest. The input is the information the user enters into a form. The server analyzes this information and searches for and retrieves relevant data. The output is a dataset that fits the user's request.

[2031] Step 3: Generative AI generates a plan

[2032] The server uses the analyzed request data to launch a generative AI model. The generative AI model generates an optimal travel plan based on the user's request. Specifically, it creates a plan that includes transportation, tourist spots, dining options, and itinerary. The input is the request data and related information found. The output is an optimal travel plan.

[2033] Step 4: Emotional Engine Adjustment

[2034] The server uses an emotion engine to analyze the user's emotional state. The emotional state is based on past feedback and real-time emotional data. The inputs include the user's past feedback and real-time emotional data. The generated itinerary is adjusted based on the emotion analysis. For example, a "happy" state might recommend highly rated restaurants, and a "sad" state might recommend comfort food. The output is an adjusted itinerary.

[2035] Step 5: Providing an interface and sending requests

[2036] The terminal provides an interface for the user to enter their request. This interface may include forms and menus for entering destination, travel duration, and activities of interest. Once the user enters the information, the terminal sends it to the server. The input is the user-entered data. The output is the request sent by the user to the server.

[2037] Step 6: Review and customize your plan

[2038] The user reviews the travel plan and dining plan provided through the terminal. The plan can be customized as needed. For example, it is possible to add or remove specific tourist spots or restaurants. The input is the provided travel plan and the user's customizations. The output is the final customized travel plan.

[2039] Step 7: Provide feedback

[2040] After completing the trip, the user provides feedback about their travel experience through their device. Input includes evaluations of the experience during the trip and comments. The server collects this feedback information and reflects it in generating future plans. The feedback is also used for analysis by the emotion engine. The output is the accumulated feedback data.

[2041] 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.

[2042] 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.

[2043] 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.

[2044] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a spec...

Claims

1. A means of collecting data on transport timetables, operation status, tourist attractions, food and drink information, and experience reports; means for aggregating and filtering said data; A means of receiving requests from users; and a generating means for generating an optimal travel plan from the integrated and filtered data based on the request; A system including a means for providing the optimal travel plan to a user.

2. 2. The system according to claim 1, further comprising means for individually customizing the travel plan generated by said generating means based on the user's past behavior history and preferences.

3. 2. The system according to claim 1, further comprising means for allowing a user to review the provided travel plan and for the user to reflect the feedback information in the generation of the next plan.

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