System

Abstract

A system is provided.SOLUTION: A system comprising: means for obtaining candidate information based on a traveler's destination information, travel duration, and preferences; means for obtaining flight information corresponding to the candidate information; means for obtaining accommodation information corresponding to the candidate information; means for using a generative model to generate local guide information based on the destination information; and means for integrating the obtained or generated information and displaying it on a user terminal.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] Travelers often face the problem of requiring a lot of time and effort when planning a trip. In particular, performing multiple steps individually, such as booking flights, arranging accommodation, and gathering local tourist information, is inefficient and causes stress. Furthermore, these procedures become even more difficult when different languages ​​and cultural barriers are encountered. The present invention aims to provide a system that reduces the complexity of travel planning and provides an efficient and enjoyable travel experience. [Means for solving the problem]

[0005] The present invention provides a system for assisting travelers in planning their trips based on their destination information, travel period, and preferences. Specifically, the system includes a means for acquiring candidate information, a means for acquiring flight information, a means for acquiring accommodation information, a means for using a generative model to generate local guide information based on the destination information, and a means for integrating this information and displaying it on a user terminal. This allows travelers to efficiently plan and process their trips based on centralized information.

[0006] "Traveller" refers to an individual or group planning a trip and needing information and arrangements at a destination.

[0007] "Destination Information" is specific information about the place a traveler is planning to visit, including city names, tourist attractions, local features, etc.

[0008] "Travel Period" means the time range including the start and end dates for which a traveler plans to travel.

[0009] "Preferences" refer to personal tastes and wishes such as the activities a traveler wants to experience during their trip, the places they want to visit, and the type of accommodation they want to stay at.

[0010] "Candidate information" is information that shows suitable options for flights, accommodations, local activities, etc. based on the traveler's destination information, travel period, and preferences.

[0011] "Flight information" refers to detailed information about the flight that a traveler will take to their destination, including flight number, departure and arrival times, airline, etc.

[0012] "Accommodation Information" means detailed information about hotels and other accommodations for travelers, including location, price, amenities, reviews, etc.

[0013] "Local Guide Information" means information that provides travelers with recommendations for activities and experiences at a destination, including tourist attractions, restaurants, events, cultural notices, etc.

[0014] A "generative model" is an algorithm or system that uses natural language processing techniques to generate specific information.

[0015] "User Terminal" refers to the electronic device (e.g., smartphone, tablet, or PC) used by a traveler to enter information or view results.

[0016] "Integration" refers to combining acquired flight information, accommodation information, and local guide information into a single entity. [Brief explanation of the drawings]

[0017] [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

[0018] 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.

[0019] First, the terms used in the following description will be explained.

[0020] 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).

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 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.

[0028] 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).

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 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.

[0035] 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.

[0036] 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.

[0037] 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."

[0038] The present invention provides a system that consistently supports travelers in planning their trips. A specific embodiment of the system will be described below.

[0039] System configuration

[0040] The system mainly consists of the following components:

[0041] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which a traveler enters travel destination information, duration, and preferences.

[0042] 2. Server: Receives data sent from user terminals, acquires and generates various information, and finally integrates it.

[0043] 3. External APIs: Various external services that provide flight and accommodation information.

[0044] 4. Generative model: An algorithm that generates local guide information using natural language processing technology.

[0045] Program processing

[0046] 1. Enter your travel information

[0047] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[0048] 2. Data transmission

[0049] The device sends the entered travel information to the server, where it is converted into JSON format and sent to the server via an HTTP request.

[0050] 3. Obtaining flight information

[0051] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" and receives flight information.

[0052] 4. Acquisition of accommodation information

[0053] The server accesses an external hotel API and retrieves hotel information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" and receives hotel information.

[0054] 5. Generating local guide information

[0055] The server uses a generative model that uses natural language processing technology to generate local guide information based on the destination information. For example, the server sends a request such as "Provide local guide information for Paris in English" to the generative model and receives information such as recommended local spots and places to eat.

[0056] 6. Providing integrated information

[0057] The server integrates the acquired flight information, hotel information, and local guide information into one package and transmits it to the user terminal, which then displays the integrated information to the user.

[0058] Specific examples

[0059] For example, a user enters the following travel itinerary:

[0060] Destination: Paris

[0061] Travel period: December 1, 2023 to December 7, 2023

[0062] Preferences: Good restaurants, cultural tourist spots

[0063] The user terminal sends this information to the server, which processes it as follows:

[0064] Get flight information to Paris from the Flights API.

[0065] Get accommodation information in Paris from the Hotel API.

[0066] Using a generative model, we generate tourist information and restaurant recommendations for Paris.

[0067] Finally, the server integrates these data and displays them on the user's device as a single itinerary, allowing the user to easily book flights and hotels.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[0071] Step 2:

[0072] The device converts the input information into JSON format and sends it to the server. Specifically, it creates an HTTP POST request and sends data including the trip information to the server.

[0073] Step 3:

[0074] The server receives the data sent from the terminal, which includes destination information, travel duration, and preferences.

[0075] Step 4:

[0076] The server accesses the Flight API and retrieves flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0077] Step 5:

[0078] The server parses the response received from the Flights API and extracts the required flight information (e.g. flight number, departure and arrival times, airline, etc.).

[0079] Step 6:

[0080] The server accesses the hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0081] Step 7:

[0082] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[0083] Step 8:

[0084] The server uses the generative model to generate local guide information based on the destination information. For example, it sends a request to the generative model saying, "Provide local guide information for Paris in English."

[0085] Step 9:

[0086] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[0087] Step 10:

[0088] The server integrates the flight information, accommodation information, and local guide information generated from the generative model into a single package.

[0089] Step 11:

[0090] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[0091] Step 12:

[0092] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[0093] Step 13:

[0094] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses local guide information to plan the details of their trip.

[0095] Example 1

[0096] 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."

[0097] Conventional travel planning support systems require travelers to collect flight information, accommodation information, and local tourist information individually, which is extremely time-consuming. Furthermore, because each source of information is different, it is difficult to manage them in an integrated manner. This makes it difficult for travelers to plan their trips quickly and efficiently.

[0098] 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.

[0099] In this invention, the server includes: means for acquiring candidate information based on a traveler's destination information, travel period, and preferences; a user terminal for converting the candidate information into JSON format and sending it to the server; means for acquiring flight information from an external API based on the destination information and travel period; means for acquiring accommodation information from the external API based on the destination and length of stay; means for using a generative AI model to generate local guide information based on the destination information; a server for integrating the acquired or generated information and sending the integrated information to the user terminal; and means for displaying the integrated information to the user. This allows travelers to consistently acquire flight information, accommodation information, and local guide information through a single system, enabling efficient travel planning.

[0100] "Traveller" refers to a person who plans and undertakes a trip.

[0101] "Destination Information" refers to information about places that a traveler plans to visit.

[0102] "Travel Period" refers to the period from the date a traveler begins to the date the travel ends.

[0103] "Preferences" refers to information about what a traveler wants to experience and their preferred activities during their trip.

[0104] "Candidate Information" refers to travel options to be considered that are obtained based on the traveler's destination information, travel duration, and preferences.

[0105] "User terminal" refers to an electronic device used by a traveler to enter data such as travel destination information, duration, preferences, etc.

[0106] "Server" refers to a computer system that receives and processes data sent from a user terminal.

[0107] "External API" refers to a program interface for obtaining data from a service provided by a third party.

[0108] "Flight Information" means data containing detailed information about the flight you are taking.

[0109] "Accommodation Information" refers to data containing detailed information about the accommodation where a traveler is staying.

[0110] A "generative AI model" refers to an algorithm that generates data using natural language processing techniques.

[0111] "Local guide information" refers to information about tourist attractions and recommended spots at your travel destination.

[0112] "Integrated information" refers to data that brings together flight information, accommodation information, and local guide information.

[0113] This invention is a system that efficiently supports travelers' travel planning by collecting and integrating necessary information based on specific destination information, travel period, and preferences, and providing it to users. This system is mainly realized using a user terminal, a server, an external API, and a generative AI model. Specific implementation methods for this system are described below.

[0114] System configuration

[0115] This system is broadly composed of the following components:

[0116] 1. User terminal: An electronic device that allows travelers to input information about their travel destinations, duration, and preferences. Specifically, a smartphone or PC is used.

[0117] 2. Server: Receives data sent from user terminals and acquires, generates, and integrates various information. The server is a high-performance computer that can quickly process large amounts of data.

[0118] 3. External APIs: These are APIs used to provide flight information or accommodation information, such as Flight APIs and Hotel APIs.

[0119] 4. Generative AI model: An algorithm that uses natural language processing technology to generate local guide information. For example, OpenAI's GPT-3 is used.

[0120] System action

[0121] 1. Enter your travel information

[0122] The user inputs travel destination information (e.g., "Paris"), travel period (December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants" and "cultural tourist spots") into the user terminal.

[0123] 2. Data transmission

[0124] The device converts the entered travel information into JSON format and sends it to the server via an HTTP request, generating the following JSON data, for example: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[0125] 3. Obtaining flight information

[0126] The server sends a request to an external flight API to retrieve flight information based on the itinerary and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" to retrieve flight information.

[0127] 4. Acquisition of accommodation information

[0128] The server sends a request to an external hotel API to retrieve accommodation information based on the travel period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" to retrieve hotel information.

[0129] 5. Generating local guide information

[0130] The server generates a prompt based on the destination information and sends it to the generative AI model. An example prompt is "Provide local guide information for Paris in English." The server receives the local guide information generated by the generative AI model.

[0131] 6. Integration and provision of information

[0132] The server aggregates the flight, accommodation, and local guide information, resulting in a JSON data stream like this: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}.

[0133] The server sends the integrated information to the user terminal, which then displays the received information to the user, who can then easily make flight and hotel reservations based on this information.

[0134] Specific examples

[0135] For example, if a user enters a travel plan such as "Paris," "December 1, 2023 to December 7, 2023," and "good restaurants and cultural tourist spots," the server will process it as follows:

[0136] 1. The server accesses the Flight API and retrieves flight information for Paris.

[0137] 2. The server accesses the hotel API and retrieves information about accommodations in Paris.

[0138] 3. The server uses the generative AI model to generate tourist information and restaurant recommendations for Paris.

[0139] Finally, the server integrates this information and sends it to the user's terminal as a single travel plan, allowing the user to efficiently make flight and hotel reservations based on this information.

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

[0141] Step 1: Enter your travel information

[0142] The user inputs information about the travel destination, travel period, and preferences into the user terminal. Specifically, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "good restaurants," and "cultural tourist spots."

[0143] Input: Destination information (Paris), travel period (December 1, 2023 to December 7, 2023), preferences (good restaurants, cultural attractions).

[0144] Output: Trip information stored on the user's device.

[0145] Step 2: Sending data

[0146] The device converts the entered travel information into JSON format and sends it to the server using an HTTP request. For example, the following JSON data is generated: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[0147] Input: Trip information entered by the user.

[0148] Data processing: Convert travel information into JSON format.

[0149] Output: The generated JSON data is sent to the server.

[0150] Step 3: Get flight information

[0151] The server then sends a request to an external flight API based on the received travel information to retrieve flight information based on the travel date and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01."

[0152] Input: Trip information (JSON format).

[0153] Data Computing: Accessing and requesting Flight APIs.

[0154] Output: Flight information (JSON format) retrieved from the Flights API.

[0155] Step 4: Obtaining accommodation information

[0156] The server sends a request to an external hotel API based on the travel period and destination to retrieve accommodation information, for example, "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0157] Input: Trip information (JSON format).

[0158] Data Operations: Accessing and requesting hotel APIs.

[0159] Output: Accommodation information obtained from the Hotel API (JSON format).

[0160] Step 5: Generate local guide information

[0161] The server generates a prompt sentence based on the destination information and sends it to the generative AI model. An example prompt sentence is "Provide local guide information for Paris in English." The local guide information generated by the generative AI model is then obtained.

[0162] Input: Travel destination information.

[0163] Data calculation: Prompt sentence generation and sending to the generative AI model.

[0164] Output: Local guide information obtained from the generative AI model.

[0165] Step 6: Integrate and provide information

[0166] The server combines the flight information, accommodation information, and local guide information and converts the combined information into JSON format. An example of the generated JSON data is: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}

[0167] Input: flight information, accommodation information, local guide information.

[0168] Data processing: Integration of each piece of information and conversion to JSON format.

[0169] Output: Consolidated information (JSON format).

[0170] Step 7: View integration information

[0171] The terminal displays the integrated information sent from the server to the user, who can then make flight and hotel reservations based on this information.

[0172] Input: Consolidated information (JSON format).

[0173] Data processing: Display of integrated information on user terminals.

[0174] Output: A set of travel plan information available to the user.

[0175] (Application example 1)

[0176] 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."

[0177] Conventional travel planning support systems are limited to providing users with information on travel destinations and accommodations, and have difficulty providing customized product information or in-store guide information for physical stores. Furthermore, they are unable to provide information based on users' preferences in real time, leaving a lack of ways to further enhance the travel experience.

[0178] 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.

[0179] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using a generative model to generate local guide information based on the destination information, means for integrating the acquired or generated information and displaying it on a user terminal, and means for providing product information and in-store guide information based on the user's preferences. This allows users to receive customized information based on their preferences in real time not only at their travel destinations but also in physical stores, significantly improving their travel and shopping experiences.

[0180] A "traveler" is an individual or group that makes travel plans based on destination information, duration, and preferences.

[0181] "Destination information" is information including the specific geographical location and name of a place that a traveler wants to visit.

[0182] "Travel period" is information about the period of time including the start and end dates of the trip that the traveler is planning.

[0183] "Preferences" refers to information that indicates the elements or conditions that a traveler is particularly interested in while traveling (e.g., good restaurants, cultural tourist spots, etc.).

[0184] "Candidate information" refers to information about multiple options obtained based on the traveler's destination information, travel period, and preferences.

[0185] "Flight information" refers to information about an airline flight, which is a traveler's means of transportation, and includes the departure point, destination, boarding time, and the like.

[0186] "Accommodation Information" means information about accommodation facilities intended for travelers' stay, including the location of the facility, fees, services provided, etc.

[0187] A "generative model" is an algorithm used to generate local guide information based on destination information, often using natural language processing techniques.

[0188] "Natural language processing technology" is a computer technology that has the ability to understand and generate human language.

[0189] "Integrated information" is information that brings together data obtained from multiple different sources.

[0190] "User terminal" refers to an electronic device that allows travelers to input and receive information, including smartphones, tablets, and personal computers.

[0191] A "server" is a computer system that receives and processes data sent from user terminals, and generates and distributes integrated information.

[0192] "Product information" refers to specific information about products and services offered in physical stores.

[0193] "In-store guide information" refers to information about product placement and recommended spots within a physical store.

[0194] The present invention is a system that provides travelers with customized information based on their travel destination information, travel period, and preferences. In addition to planning travel plans, the system can also provide product information and in-store guide information tailored to the user's preferences in brick-and-mortar stores.

[0195] System configuration

[0196] The system mainly consists of the following components:

[0197] 1. User terminal: An electronic device (e.g., a smartphone or smart glasses) through which travelers input their destination information, travel duration, and preferences.

[0198] 2. Server: Receives data sent from user terminals, acquires and generates various information, and delivers the integrated information to user terminals.

[0199] 3. External APIs: Various external services that provide flight information, accommodation information, and product information from physical stores.

[0200] 4. Generative model: An algorithm that uses natural language processing technology to generate local guide information and in-store guide information.

[0201] Explanation of program processing

[0202] 1. Enter your user information

[0203] A user wears smart glasses and enters information about their travel destination, travel duration, and preferences through the glasses, such as specific preferences like "Italian cuisine" and "modern design."

[0204] 2. Data transmission

[0205] The smart glasses convert the input information into JSON format and send it to the server via Wi-Fi or Bluetooth.

[0206] 3. Information Acquisition and Generation

[0207] The server accesses external flight and accommodation APIs to retrieve flight and hotel information based on the traveler's travel dates and destinations.

[0208] In addition, to obtain product information based on the user's preferences, the app accesses the store's external API. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian" and receives product information.

[0209] Furthermore, local guide information and in-store guide information are generated using the generative model. Specifically, information is obtained by sending prompt sentences to the generative model. For example, the prompt is "Generate guide information for Italian-themed products in a modern style."

[0210] 4. Providing integrated information

[0211] The server integrates the acquired flight information, accommodation information, product information, and guide information generated by the generative model, and sends it to the user's terminal as a single information package. The user terminal then displays this integrated information to the user.

[0212] Specific examples

[0213] For example, a user inputs the following information through smart glasses:

[0214] Travel Destination Information: Paris

[0215] Travel period: December 1, 2023 to December 7, 2023

[0216] Preferences: Italian food, modern design

[0217] The server accesses external APIs to retrieve flight information to Paris, accommodation information in Paris, and product information related to Italian cuisine. It then uses the generative model to generate tourist information about Paris and recommended Italian restaurants. Finally, the server integrates this information and displays it on the user's smart glasses.

[0218] Hardware and software used

[0219] Hardware: Smart glasses (e.g. Google Glass, Vuzix)

[0220] software:

[0221] Python 3.x

[0222] HTTP library (requests)

[0223] External API (flight information API, accommodation information API, product information API)

[0224] Natural language generation models (GPT-4, etc.)

[0225] In this way, users will be able to receive real-time, customized information not only for travel planning but also in physical stores.

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

[0227] Step 1:

[0228] The user inputs information about the travel destination, travel period, and preferences through the smart glasses. For example, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "Italian cuisine, modern design." This information is collected by the smart glasses application.

[0229] Input: Destination information, travel period, preferences

[0230] Output: User's travel information (JSON format)

[0231] Step 2:

[0232] The user device (smart glasses) converts the input information into JSON format and sends it to the server via an HTTP request. Specifically, the data is sent to the server via Wi-Fi or Bluetooth.

[0233] Input: User's travel information (JSON format)

[0234] Output: Trip information sent to the server

[0235] Step 3:

[0236] The server analyzes the received travel information and retrieves flight information by sending a request to an external API. For example, to retrieve flight information for Paris, it sends a request to "https: / / api.flightinfo.com / flights?dest=Paris&date=2023-12-01".

[0237] Input: Travel information (destination, travel period)

[0238] Output: Flight information

[0239] Step 4:

[0240] The server then accesses an external hotel information API to obtain hotel information in Paris, for example, by sending a request to "https: / / api.hotelinfo.com / hotels?dest=Paris&date=2023-12-01".

[0241] Input: Travel information (destination, travel period)

[0242] Output: Accommodation information

[0243] Step 5:

[0244] The server sends a request to an external product information API to retrieve product information from physical stores based on the user's preferences. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian".

[0245] Input: User Preferences

[0246] Output: Product information

[0247] Step 6:

[0248] The server generates local guide information and in-store guide information using the generative model. Specifically, it generates a prompt sentence, "Generate guide information for Italian-themed products in a modern style," and sends it to the generative model, which uses natural language processing technology.

[0249] Input: Destination information, user preferences

[0250] Output: Local guide information, in-store guide information

[0251] Step 7:

[0252] The server integrates the acquired flight information, accommodation information, product information, and generated guide information, and sends the integrated information as a single package to the user's terminal.The server converts the integrated information into JSON format and sends it to the user's terminal via an HTTP response.

[0253] Input: Flight information, accommodation information, product information, guide information

[0254] Output: Consolidated information (JSON format)

[0255] Step 8:

[0256] The user terminal (smart glasses) analyzes the integrated information received from the server and visually displays it to the user, allowing the user to view customized travel and shopping information in real time.

[0257] Input: Integrated information (JSON format)

[0258] Output: Customized information displayed to the user visually

[0259] 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.

[0260] The present invention provides a more personalized travel experience by combining a system that consistently supports travelers' travel planning with an emotion engine that recognizes user emotions. Specific examples of the system are described below.

[0261] System configuration

[0262] The system mainly consists of the following components:

[0263] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which travelers input their travel destination information, duration, and preferences, and which also has a built-in emotion engine that recognizes the user's emotions.

[0264] 2. Server: Receives data sent from the user device, acquires and generates various information, and finally integrates it. It also receives the output of the emotion engine and reflects it in the generation of information.

[0265] 3. External APIs: Various external services that provide flight and accommodation information.

[0266] 4. Generative model: An algorithm that generates local guide information using natural language processing technology. The output of the emotion engine is used to dynamically adjust the local guide information.

[0267] Program processing

[0268] 1. Enter your travel information

[0269] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[0270] At the same time, the emotion engine built into the user terminal analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions.

[0271] 2. Data transmission

[0272] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server via an HTTP POST request.

[0273] 3. Obtaining flight information

[0274] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0275] 4. Acquisition of accommodation information

[0276] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0277] 5. Generating local guide information

[0278] The server uses a generative model based on natural language processing technology to generate local guide information based on destination information and the user's recognized emotion data. For example, if the user is feeling stressed, it will suggest relaxing places and activities, and if the user is excited, it will suggest new experiences and challenging activities.

[0279] 6. Providing integrated information

[0280] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model, and transmits the integrated information as a single package to the user terminal, which then displays the integrated information to the user.

[0281] Specific examples

[0282] For example, a user enters the following travel itinerary:

[0283] Destination: Paris

[0284] Travel period: December 1, 2023 to December 7, 2023

[0285] Preferences: Good restaurants, cultural tourist spots

[0286] At the same time, the emotion engine of the user terminal recognizes the user's emotion as “feeling stressed.” The user terminal transmits this information to the server, which processes it as follows:

[0287] Get flight information to Paris from the Flights API.

[0288] Get accommodation information in Paris from the Hotel API.

[0289] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[0290] Finally, the server aggregates these data and displays it as a single itinerary on the user's device, allowing the user to easily book flights and hotels and enjoy a trip that includes stress-reducing activities.

[0291] The processing flow will be explained below.

[0292] Step 1:

[0293] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[0294] Step 2:

[0295] The emotion engine built into the user device analyzes the user's facial expressions, voice tone, or input text information to recognize the user's emotions. For example, if the user is smiling, it will recognize that they are "having fun," and if they are frowning, it will recognize that they are "feeling stressed."

[0296] Step 3:

[0297] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[0298] Step 4:

[0299] The server receives the data sent from the terminal, which includes the user's destination information, travel period, preferences, and emotion data.

[0300] Step 5:

[0301] The server accesses an external flight API to retrieve flight information based on the user's travel dates and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0302] Step 6:

[0303] The server parses the response received from the Flights API and extracts the required flight information (e.g., flight number, departure and arrival times, airline, etc.).

[0304] Step 7:

[0305] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0306] Step 8:

[0307] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[0308] Step 9:

[0309] The server uses the generative model to generate local guide information based on the destination information and the user's recognized emotion data. For example, if the user's emotion is recognized as "stressed," the server suggests relaxing places and activities. The server sends a request to the generative model saying, "Generate local guide information for Paris that includes relaxing activities."

[0310] Step 10:

[0311] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[0312] Step 11:

[0313] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model into a single package.

[0314] Step 12:

[0315] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[0316] Step 13:

[0317] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[0318] Step 14:

[0319] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses the local guide information to plan the details of their trip, for example booking a massage or spa treatment to relieve stress.

[0320] Example 2

[0321] 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."

[0322] Conventional travel planning support systems were able to provide information based on a traveler's destination and preferences, but they were unable to take into account the traveler's emotions, making it difficult to make optimal suggestions for each individual traveler. Furthermore, they lacked a means to integrate the acquired information and provide it to travelers in an easy-to-understand manner, resulting in a lack of convenience for travelers.

[0323] 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.

[0324] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using an emotion engine to analyze the traveler's emotions, means for using a generative model to generate local guide information based on the destination information and emotion data, and means for integrating the acquired or generated information and transmitting it to a user terminal in JSON format for display. This makes it possible to propose more personalized travel plans that take the traveler's emotions into consideration, and to provide the traveler with more appropriate and easy-to-understand information.

[0325] A "traveler" is someone who plans a travel destination and travel period and acts accordingly.

[0326] "Destination Information" refers to information about a location that a traveler intends to visit.

[0327] "Travel Period" means the period between the start and end dates for which a Traveler plans to travel.

[0328] "Preferences" refer to the specific experiences and interests that travelers seek while traveling.

[0329] "Candidate information" refers to information on various options obtained based on the traveler's destination information, travel period, and preferences.

[0330] "Flight Information" means detailed information about a flight taken by a traveler.

[0331] "Accommodation Information" means detailed information about accommodations for travelers to stay at.

[0332] An "emotion engine" refers to software or hardware functions that analyze and recognize a user's emotions.

[0333] A "generative model" refers to an algorithm that uses natural language processing techniques to generate specific information based on input data.

[0334] "Integration" refers to bringing together different types or multiple pieces of information into one.

[0335] "User terminal" refers to the electronic device used by a traveler to enter information and view results.

[0336] The present invention is a system that provides individual support for travellers' travel plans, and provides a more personalized travel experience by combining it with an emotion engine that recognises the traveller's emotions. Specific embodiments of the system are described below.

[0337] Hardware and Software Configuration

[0338] 1. User Device:

[0339] Hardware used: Smartphone or PC

[0340] Software used: Emotion engine (e.g., a general emotion recognition API)

[0341] 2. Server:

[0342] Hardware used: Cloud server (e.g., general cloud service)

[0343] Software used: External APIs (e.g., general flight information APIs, accommodation information APIs) and natural language processing technologies (e.g., general natural language processing algorithms)

[0344] Program processing

[0345] 1. The user enters information about their travel destination using a smartphone or computer. For example, they enter Paris as their destination, the travel period from December 1, 2023 to December 7, 2023, and their preferences for "good restaurants" and "cultural tourist spots."

[0346] 2. The device activates its built-in emotion engine, which analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions. For example, it determines that the user is feeling stressed.

[0347] 3. The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[0348] 4. The server analyzes the received data and sends a request to an external flight information API based on the travel date and destination to retrieve the required flight information. For example, to retrieve flight information for Paris.

[0349] 5. The server then sends a request to an external accommodation information API to retrieve the required accommodation information. For example, to retrieve accommodation information for Paris.

[0350] 6. The server uses the generative AI model to generate local guide information based on the destination information and emotion data. For example, if the user is feeling stressed, the server uses the following prompt to generate guide information including information on relaxation spots and spas:

[0351] Travel Planning Information:

[0352] Destination: Paris

[0353] Travel period: December 1, 2023 to December 7, 2023

[0354] Preferences: Good restaurants, cultural attractions

[0355] User Emotions: Stressed

[0356] Based on the above information, please generate local guide information that will help users relax.

[0357] 7. The server integrates the acquired flight information, accommodation information, and generated local guide information, and sends it as a package to the user's device. The user's device displays the integrated information to the user.

[0358] In this way, the system of the present invention can recognize the emotions of travelers and provide personalized travel information based on those emotions, thereby enabling travelers to plan trips with greater satisfaction.

[0359] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0360] Step 1:

[0361] Users input their travel information, such as destination, travel duration, and preferences, using their smartphone or computer. This input information includes data such as:

[0362] Destination: Paris

[0363] Travel period: December 1, 2023 to December 7, 2023

[0364] Preferences: Good restaurants, cultural tourist spots

[0365] Based on the input, the device activates its built-in emotion engine to analyze the user's facial expression, voice tone, and text information. For example, if the user's facial expression is tense, the emotion engine will recognize it as "feeling stressed" and output it as emotion data.

[0366] Step 2:

[0367] The device converts the travel information and recognized emotion data into JSON format. The specific input for this data conversion is as follows:

[0368] Travel information

[0369] Emotional data (e.g., "I feel stressed")

[0370] Example output in JSON format:

[0371] json

[0372] {

[0373] "destination": "Paris",

[0374] "travel_period": {

[0375] "start_date": "2023-12-01",

[0376] "end_date": "2023-12-07"

[0377] },

[0378] "preferences": ["good restaurants", "cultural tourist spots"],

[0379] "user_emotion": "stress"

[0380] }

[0381] The device sends this JSON formatted data to the server using an HTTP POST request.

[0382] Step 3:

[0383] The server analyzes the received data, specifically extracting travel itinerary and destination information.

[0384] input:

[0385] Travel information (JSON format)

[0386] The server then accesses an external flight information API and sends a request to retrieve the flight information.

[0387] Example API request:

[0388] http

[0389] GET https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01

[0390] output:

[0391] Flight information (flight number, departure time, arrival time, airline name, etc.)

[0392] Step 4:

[0393] The server similarly analyzes the received data and accesses external accommodation information APIs based on the travel destination and length of stay.

[0394] input:

[0395] Travel information (JSON format)

[0396] The server sends a request to the following URL to obtain accommodation information:

[0397] Example API request:

[0398] http

[0399] GET https: / / api.hotelapi.com / hotels?dest=Paris&checkin=2023-12-01&checkout=2023-12-07

[0400] output:

[0401] Accommodation information (hotel name, location, price, availability, etc.)

[0402] Step 5:

[0403] The server uses the generative AI model to generate local guide information.

[0404] input:

[0405] Destination information

[0406] Emotional Data

[0407] Preferences

[0408] The server inputs the following prompt sentence into the generative AI model to generate local guide information.

[0409] text

[0410] Travel Planning Information:

[0411] Destination: Paris

[0412] Travel period: December 1, 2023 to December 7, 2023

[0413] Preferences: Good restaurants, cultural attractions

[0414] User Emotions: Stressed

[0415] Based on the above information, please generate local guide information that will help users relax.

[0416] output:

[0417] Local guide information (relaxing places, spas, etc.)

[0418] Step 6:

[0419] The server integrates the acquired flight information, accommodation information, and generated local guide information.

[0420] input:

[0421] Flight information

[0422] Accommodation information

[0423] Local guide information

[0424] The integrated data is converted into JSON format and sent to the user's terminal.

[0425] Example output:

[0426] json

[0427] {

[0428] "flights": [

[0429] {

[0430] "flight_number": "AF123",

[0431] "departure_time": "2023-12-01T10:00:00",

[0432] "arrival_time": "2023-12-01T12:00:00",

[0433] "airline": "Air France"

[0434] }

[0435] ],

[0436] "hotels": [

[0437] {

[0438] "name": "Hotel du Louvre",

[0439] "location": "Centre of Paris",

[0440] "price": "200€ / night",

[0441] "availability": "Available"

[0442] }

[0443] ],

[0444] "guide": [

[0445] {

[0446] "activity": "Spa in Paris",

[0447] "description": "A great relaxing spa"

[0448] }

[0449] ]

[0450] }

[0451] The device analyzes the received data and displays it to the user, for example, by providing an app interface with flight information, accommodation information, and local guide information in an easy-to-read layout, allowing users to easily make reservations and plans.

[0452] (Application example 2)

[0453] 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."

[0454] Personalizing travel plans has become increasingly important for travelers to enhance their local experiences. However, conventional travel planning support systems have difficulty providing personalized travel suggestions that reflect the user's emotional state, limiting their ability to alleviate stress and inconvenience during travel. Furthermore, they have not offered suggestions for stores or services based on real-time emotions, and therefore have not been able to fully meet travelers' needs.

[0455] 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 recognizing the traveler's emotions and generating local guide information based on the emotions, means for dynamically adjusting store information based on the emotions in real time, and means for displaying the integrated information on the user terminal. This makes it possible to make personalized travel suggestions according to the traveler's emotional state, allowing the traveler to have a comfortable and satisfying experience in the local area.

[0456] "Tourist destination information" is information about the place that the traveler intends to visit.

[0457] "Travel period" is information about the period from the start date to the end date of a traveler's planned trip.

[0458] "Preferences" are information about the activities a traveler wants to experience at their destination and the categories of interest they have.

[0459] The "means for obtaining candidate information" refers to a means for collecting relevant travel destination and activity candidates based on the destination information, travel period, and preferences input by the traveler.

[0460] The "means for obtaining flight information" is a means for obtaining information on available flights based on the traveler's destination and travel period.

[0461] The "means for obtaining accommodation information" refers to a means for obtaining information on available accommodations based on the traveler's destination and travel period.

[0462] The "means for using a generative model" is a model used to generate local guide information based on the traveler's destination information and other related information.

[0463] The "means for integrating and displaying on the user terminal" is a means for integrating the acquired flight information, accommodation information, and generated local guide information and displaying them on the user's terminal.

[0464] The "means for recognizing user emotions" is a means for analyzing the facial expressions, voice, and input text of the traveler to recognize the emotional state of the traveler at that time.

[0465] The "means for dynamically adjusting local guide information based on emotions" refers to a means for appropriately changing local guide information based on the recognized emotional state of the traveler, and providing more appropriate information.

[0466] The "means for displaying emotion-based recommended store information in real time" is a means for providing appropriate store and service information in real time, taking into account the emotional state of the traveler, and displaying it on the user's terminal.

[0467] To implement this invention, a system including a user terminal, a server, an emotion recognition engine, a generative model, and a display interface is required.

[0468] System configuration

[0469] User terminal

[0470] The user terminal consists of a device such as a smartphone or smart glasses, and is equipped with an emotion engine that recognizes the traveler's emotions. Users can input their travel destination, duration, and preferences.

[0471] The emotion engine analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions in real time, making it possible to grasp various emotions such as stress and excitement during the trip.

[0472] server

[0473] The server receives the data sent by the user, retrieves the necessary flight and accommodation information through an external API, receives the output of the emotion recognition engine, and dynamically generates local guide information using a generative model.

[0474] The server uses the following methods:

[0475] 1. How to receive travel information

[0476] 2. Means of receiving emotion recognition data

[0477] 3. How to access external APIs

[0478] 4. Guide Information Generation Method Using Generative Model

[0479] 5. Means of transmitting integrated data to user terminals

[0480] Emotion Recognition Engine

[0481] The emotion recognition engine analyzes the user's emotional state in real time. This includes camera input (facial expression recognition) and microphone input (voice analysis). Specifically, it identifies the user's emotions using a facial expression analysis algorithm and a voice tone analysis engine, and sends the results in JSON format to the server.

[0482] Generative Model

[0483] The generative model uses natural language processing technology to generate personalized local guide information based on the user's emotional data and destination information. For example, if the user is feeling stressed, it will suggest places to relax, and if the user is excited, it will suggest places that offer new experiences. This generative model dynamically generates information based on data obtained from external APIs and data from an emotion recognition engine.

[0484] Display Interface

[0485] The user terminal is equipped with an interface for displaying the integrated information, which can provide links to booking procedures and additional information, helping users to smoothly plan their trip.

[0486] Specific examples

[0487] For example, a user enters the following travel itinerary through smart glasses:

[0488] Destination: Paris

[0489] Travel period: December 1, 2023 to December 7, 2023

[0490] Preferences: Good restaurants, cultural tourist spots

[0491] At the same time, the emotion recognition engine identifies the user's emotion as "stressed." The server receives this information and processes it as follows:

[0492] Get flight information to Paris from the Flights API.

[0493] Get accommodation information in Paris from the Hotel API.

[0494] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[0495] This information is integrated and displayed on the user's device, allowing travelers to receive the optimal travel plan based on their emotions and enjoy a comfortable and stress-free travel experience.

[0496] Prompt Sentence Examples

[0497] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[0498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0499] Step 1:

[0500] A user inputs travel destination information, travel duration, and preferences into a device (such as smart glasses or a smartphone). The input data includes the destination (e.g., Paris), travel duration (date range), and activities and interests they would like to experience at the destination. This obtains basic information about the trip.

[0501] Step 2:

[0502] The emotion engine built into the device uses the camera and microphone to analyze the user's facial expressions and voice in real time. The input data is the video from the camera and the audio from the microphone. Based on this data, the emotion engine recognizes the user's emotions (e.g., stress, excitement, relief) and generates emotion data.

[0503] Step 3:

[0504] The device converts the travel information entered in step 1 and the emotion data generated in step 2 into JSON format and sends it to the server via an HTTP POST request, which causes the server to receive the user's travel information and emotion information.

[0505] Step 4:

[0506] The server sends a request to an external API (e.g., a service that provides flight and accommodation information) based on the received travel information and emotion data. The server retrieves appropriate flight and accommodation information based on the travel destination and duration. This collects basic information necessary for the user's trip.

[0507] Step 5:

[0508] The server integrates flight and accommodation information obtained from external APIs with emotion data and generates local guide information using a generative model. The generative model uses natural language processing technology to generate guide information tailored to the traveler based on the user's destination information and emotion data. For example, if the user is feeling stressed, it generates guide information suggesting places and services where they can relax.

[0509] Step 6:

[0510] The server then combines the generated local guide information, flight information, and accommodation information and sends it to the user's device as a single package, allowing the user to view all travel information in an integrated manner.

[0511] Step 7:

[0512] The terminal receives the integrated information sent from the server and displays it on the interface. The user can view the displayed travel information and access links to make reservations or get additional information as needed, making it easier for the user to plan their trip.

[0513] Prompt Sentence Examples

[0514] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[0515] 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.

[0516] 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.

[0517] 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.

[0518] [Second embodiment]

[0519] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0520] 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.

[0521] 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).

[0522] 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.

[0523] 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.

[0524] 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).

[0525] 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.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] In the smart glasses 214, 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.

[0530] 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."

[0531] The present invention provides a system that consistently supports travelers in planning their trips. A specific embodiment of the system will be described below.

[0532] System configuration

[0533] The system mainly consists of the following components:

[0534] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which a traveler enters travel destination information, duration, and preferences.

[0535] 2. Server: Receives data sent from user terminals, acquires and generates various information, and finally integrates it.

[0536] 3. External APIs: Various external services that provide flight and accommodation information.

[0537] 4. Generative model: An algorithm that generates local guide information using natural language processing technology.

[0538] Program processing

[0539] 1. Enter your travel information

[0540] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[0541] 2. Data transmission

[0542] The device sends the entered travel information to the server, where it is converted into JSON format and sent to the server via an HTTP request.

[0543] 3. Obtaining flight information

[0544] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" and receives flight information.

[0545] 4. Acquisition of accommodation information

[0546] The server accesses an external hotel API and retrieves hotel information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" and receives hotel information.

[0547] 5. Generating local guide information

[0548] The server uses a generative model that uses natural language processing technology to generate local guide information based on the destination information. For example, the server sends a request such as "Provide local guide information for Paris in English" to the generative model and receives information such as recommended local spots and places to eat.

[0549] 6. Providing integrated information

[0550] The server integrates the acquired flight information, hotel information, and local guide information into one package and transmits it to the user terminal, which then displays the integrated information to the user.

[0551] Specific examples

[0552] For example, a user enters the following travel itinerary:

[0553] Destination: Paris

[0554] Travel period: December 1, 2023 to December 7, 2023

[0555] Preferences: Good restaurants, cultural tourist spots

[0556] The user terminal sends this information to the server, which processes it as follows:

[0557] Get flight information to Paris from the Flights API.

[0558] Get accommodation information in Paris from the Hotel API.

[0559] Using a generative model, we generate tourist information and restaurant recommendations for Paris.

[0560] Finally, the server integrates these data and displays them on the user's device as a single itinerary, allowing the user to easily book flights and hotels.

[0561] The processing flow will be explained below.

[0562] Step 1:

[0563] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[0564] Step 2:

[0565] The device converts the input information into JSON format and sends it to the server. Specifically, it creates an HTTP POST request and sends data including the trip information to the server.

[0566] Step 3:

[0567] The server receives the data sent from the terminal, which includes destination information, travel duration, and preferences.

[0568] Step 4:

[0569] The server accesses the Flight API and retrieves flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0570] Step 5:

[0571] The server parses the response received from the Flights API and extracts the required flight information (e.g. flight number, departure and arrival times, airline, etc.).

[0572] Step 6:

[0573] The server accesses the hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0574] Step 7:

[0575] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[0576] Step 8:

[0577] The server uses the generative model to generate local guide information based on the destination information. For example, it sends a request to the generative model saying, "Provide local guide information for Paris in English."

[0578] Step 9:

[0579] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[0580] Step 10:

[0581] The server integrates the flight information, accommodation information, and local guide information generated from the generative model into a single package.

[0582] Step 11:

[0583] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[0584] Step 12:

[0585] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[0586] Step 13:

[0587] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses local guide information to plan the details of their trip.

[0588] Example 1

[0589] 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."

[0590] Conventional travel planning support systems require travelers to collect flight information, accommodation information, and local tourist information individually, which is extremely time-consuming. Furthermore, because each source of information is different, it is difficult to manage them in an integrated manner. This makes it difficult for travelers to plan their trips quickly and efficiently.

[0591] 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.

[0592] In this invention, the server includes: means for acquiring candidate information based on a traveler's destination information, travel period, and preferences; a user terminal for converting the candidate information into JSON format and sending it to the server; means for acquiring flight information from an external API based on the destination information and travel period; means for acquiring accommodation information from the external API based on the destination and length of stay; means for using a generative AI model to generate local guide information based on the destination information; a server for integrating the acquired or generated information and sending the integrated information to the user terminal; and means for displaying the integrated information to the user. This allows travelers to consistently acquire flight information, accommodation information, and local guide information through a single system, enabling efficient travel planning.

[0593] "Traveller" refers to a person who plans and undertakes a trip.

[0594] "Destination Information" refers to information about places that a traveler plans to visit.

[0595] "Travel Period" refers to the period from the date a traveler begins to the date the travel ends.

[0596] "Preferences" refers to information about what a traveler wants to experience and their preferred activities during their trip.

[0597] "Candidate Information" refers to travel options to be considered that are obtained based on the traveler's destination information, travel duration, and preferences.

[0598] "User terminal" refers to an electronic device used by a traveler to enter data such as travel destination information, duration, preferences, etc.

[0599] "Server" refers to a computer system that receives and processes data sent from a user terminal.

[0600] "External API" refers to a program interface for obtaining data from a service provided by a third party.

[0601] "Flight Information" means data containing detailed information about the flight you are taking.

[0602] "Accommodation Information" refers to data containing detailed information about the accommodation where a traveler is staying.

[0603] A "generative AI model" refers to an algorithm that generates data using natural language processing techniques.

[0604] "Local guide information" refers to information about tourist attractions and recommended spots at your travel destination.

[0605] "Integrated information" refers to data that brings together flight information, accommodation information, and local guide information.

[0606] This invention is a system that efficiently supports travelers' travel planning by collecting and integrating necessary information based on specific destination information, travel period, and preferences, and providing it to users. This system is mainly realized using a user terminal, a server, an external API, and a generative AI model. Specific implementation methods for this system are described below.

[0607] System configuration

[0608] This system is broadly composed of the following components:

[0609] 1. User terminal: An electronic device that allows travelers to input information about their travel destinations, duration, and preferences. Specifically, a smartphone or PC is used.

[0610] 2. Server: Receives data sent from user terminals and acquires, generates, and integrates various information. The server is a high-performance computer that can quickly process large amounts of data.

[0611] 3. External APIs: These are APIs used to provide flight information or accommodation information, such as Flight APIs and Hotel APIs.

[0612] 4. Generative AI model: An algorithm that uses natural language processing technology to generate local guide information. For example, OpenAI's GPT-3 is used.

[0613] System action

[0614] 1. Enter your travel information

[0615] The user inputs travel destination information (e.g., "Paris"), travel period (December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants" and "cultural tourist spots") into the user terminal.

[0616] 2. Data transmission

[0617] The device converts the entered travel information into JSON format and sends it to the server via an HTTP request, generating the following JSON data, for example: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[0618] 3. Obtaining flight information

[0619] The server sends a request to an external flight API to retrieve flight information based on the itinerary and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" to retrieve flight information.

[0620] 4. Acquisition of accommodation information

[0621] The server sends a request to an external hotel API to retrieve accommodation information based on the travel period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" to retrieve hotel information.

[0622] 5. Generating local guide information

[0623] The server generates a prompt based on the destination information and sends it to the generative AI model. An example prompt is "Provide local guide information for Paris in English." The server receives the local guide information generated by the generative AI model.

[0624] 6. Integration and provision of information

[0625] The server aggregates the flight, accommodation, and local guide information, resulting in a JSON data stream like this: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}.

[0626] The server sends the integrated information to the user terminal, which then displays the received information to the user, who can then easily make flight and hotel reservations based on this information.

[0627] Specific examples

[0628] For example, if a user enters a travel plan such as "Paris," "December 1, 2023 to December 7, 2023," and "good restaurants and cultural tourist spots," the server will process it as follows:

[0629] 1. The server accesses the Flight API and retrieves flight information for Paris.

[0630] 2. The server accesses the hotel API and retrieves information about accommodations in Paris.

[0631] 3. The server uses the generative AI model to generate tourist information and restaurant recommendations for Paris.

[0632] Finally, the server integrates this information and sends it to the user's terminal as a single travel plan, allowing the user to efficiently make flight and hotel reservations based on this information.

[0633] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0634] Step 1: Enter your travel information

[0635] The user inputs information about the travel destination, travel period, and preferences into the user terminal. Specifically, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "good restaurants," and "cultural tourist spots."

[0636] Input: Destination information (Paris), travel period (December 1, 2023 to December 7, 2023), preferences (good restaurants, cultural attractions).

[0637] Output: Trip information stored on the user's device.

[0638] Step 2: Sending data

[0639] The device converts the entered travel information into JSON format and sends it to the server using an HTTP request. For example, the following JSON data is generated: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[0640] Input: Trip information entered by the user.

[0641] Data processing: Convert travel information into JSON format.

[0642] Output: The generated JSON data is sent to the server.

[0643] Step 3: Get flight information

[0644] The server then sends a request to an external flight API based on the received travel information to retrieve flight information based on the travel date and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01."

[0645] Input: Trip information (JSON format).

[0646] Data Computing: Accessing and requesting Flight APIs.

[0647] Output: Flight information (JSON format) retrieved from the Flights API.

[0648] Step 4: Obtaining accommodation information

[0649] The server sends a request to an external hotel API based on the travel period and destination to retrieve accommodation information, for example, "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0650] Input: Trip information (JSON format).

[0651] Data Operations: Accessing and requesting hotel APIs.

[0652] Output: Accommodation information obtained from the Hotel API (JSON format).

[0653] Step 5: Generate local guide information

[0654] The server generates a prompt sentence based on the destination information and sends it to the generative AI model. An example prompt sentence is "Provide local guide information for Paris in English." The local guide information generated by the generative AI model is then obtained.

[0655] Input: Travel destination information.

[0656] Data calculation: Prompt sentence generation and sending to the generative AI model.

[0657] Output: Local guide information obtained from the generative AI model.

[0658] Step 6: Integrate and provide information

[0659] The server combines the flight information, accommodation information, and local guide information and converts the combined information into JSON format. An example of the generated JSON data is: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}

[0660] Input: flight information, accommodation information, local guide information.

[0661] Data processing: Integration of each piece of information and conversion to JSON format.

[0662] Output: Consolidated information (JSON format).

[0663] Step 7: View integration information

[0664] The terminal displays the integrated information sent from the server to the user, who can then make flight and hotel reservations based on this information.

[0665] Input: Consolidated information (JSON format).

[0666] Data processing: Display of integrated information on user terminals.

[0667] Output: A set of travel plan information available to the user.

[0668] (Application example 1)

[0669] 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."

[0670] Conventional travel planning support systems are limited to providing users with information on travel destinations and accommodations, and have difficulty providing customized product information or in-store guide information for physical stores. Furthermore, they are unable to provide information based on users' preferences in real time, leaving a lack of ways to further enhance the travel experience.

[0671] 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.

[0672] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using a generative model to generate local guide information based on the destination information, means for integrating the acquired or generated information and displaying it on a user terminal, and means for providing product information and in-store guide information based on the user's preferences. This allows users to receive customized information based on their preferences in real time not only at their travel destinations but also in physical stores, significantly improving their travel and shopping experiences.

[0673] A "traveler" is an individual or group that makes travel plans based on destination information, duration, and preferences.

[0674] "Destination information" is information including the specific geographical location and name of a place that a traveler wants to visit.

[0675] "Travel period" is information about the period of time including the start and end dates of the trip that the traveler is planning.

[0676] "Preferences" refers to information that indicates the elements or conditions that a traveler is particularly interested in while traveling (e.g., good restaurants, cultural tourist spots, etc.).

[0677] "Candidate information" refers to information about multiple options obtained based on the traveler's destination information, travel period, and preferences.

[0678] "Flight information" refers to information about an airline flight, which is a traveler's means of transportation, and includes the departure point, destination, boarding time, and the like.

[0679] "Accommodation Information" means information about accommodation facilities intended for travelers' stay, including the location of the facility, fees, services provided, etc.

[0680] A "generative model" is an algorithm used to generate local guide information based on destination information, often using natural language processing techniques.

[0681] "Natural language processing technology" is a computer technology that has the ability to understand and generate human language.

[0682] "Integrated information" is information that brings together data obtained from multiple different sources.

[0683] "User terminal" refers to an electronic device that allows travelers to input and receive information, including smartphones, tablets, and personal computers.

[0684] A "server" is a computer system that receives and processes data sent from user terminals, and generates and distributes integrated information.

[0685] "Product information" refers to specific information about products and services offered in physical stores.

[0686] "In-store guide information" refers to information about product placement and recommended spots within a physical store.

[0687] The present invention is a system that provides travelers with customized information based on their travel destination information, travel period, and preferences. In addition to planning travel plans, the system can also provide product information and in-store guide information tailored to the user's preferences in brick-and-mortar stores.

[0688] System configuration

[0689] The system mainly consists of the following components:

[0690] 1. User terminal: An electronic device (e.g., a smartphone or smart glasses) through which travelers input their destination information, travel duration, and preferences.

[0691] 2. Server: Receives data sent from user terminals, acquires and generates various information, and delivers the integrated information to user terminals.

[0692] 3. External APIs: Various external services that provide flight information, accommodation information, and product information from physical stores.

[0693] 4. Generative model: An algorithm that uses natural language processing technology to generate local guide information and in-store guide information.

[0694] Explanation of program processing

[0695] 1. Enter your user information

[0696] A user wears smart glasses and enters information about their travel destination, travel duration, and preferences through the glasses, such as specific preferences like "Italian cuisine" and "modern design."

[0697] 2. Data transmission

[0698] The smart glasses convert the input information into JSON format and send it to the server via Wi-Fi or Bluetooth.

[0699] 3. Information Acquisition and Generation

[0700] The server accesses external flight and accommodation APIs to retrieve flight and hotel information based on the traveler's travel dates and destinations.

[0701] In addition, to obtain product information based on the user's preferences, the app accesses the store's external API. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian" and receives product information.

[0702] Furthermore, local guide information and in-store guide information are generated using the generative model. Specifically, information is obtained by sending prompt sentences to the generative model. For example, the prompt is "Generate guide information for Italian-themed products in a modern style."

[0703] 4. Providing integrated information

[0704] The server integrates the acquired flight information, accommodation information, product information, and guide information generated by the generative model, and sends it to the user's terminal as a single information package. The user terminal then displays this integrated information to the user.

[0705] Specific examples

[0706] For example, a user inputs the following information through smart glasses:

[0707] Travel Destination Information: Paris

[0708] Travel period: December 1, 2023 to December 7, 2023

[0709] Preferences: Italian food, modern design

[0710] The server accesses external APIs to retrieve flight information to Paris, accommodation information in Paris, and product information related to Italian cuisine. It then uses the generative model to generate tourist information about Paris and recommended Italian restaurants. Finally, the server integrates this information and displays it on the user's smart glasses.

[0711] Hardware and software used

[0712] Hardware: Smart glasses (e.g. Google Glass, Vuzix)

[0713] software:

[0714] Python 3.x

[0715] HTTP library (requests)

[0716] External API (flight information API, accommodation information API, product information API)

[0717] Natural language generation models (GPT-4, etc.)

[0718] In this way, users will be able to receive real-time, customized information not only for travel planning but also in physical stores.

[0719] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0720] Step 1:

[0721] The user inputs information about the travel destination, travel period, and preferences through the smart glasses. For example, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "Italian cuisine, modern design." This information is collected by the smart glasses application.

[0722] Input: Destination information, travel period, preferences

[0723] Output: User's travel information (JSON format)

[0724] Step 2:

[0725] The user device (smart glasses) converts the input information into JSON format and sends it to the server via an HTTP request. Specifically, the data is sent to the server via Wi-Fi or Bluetooth.

[0726] Input: User's travel information (JSON format)

[0727] Output: Trip information sent to the server

[0728] Step 3:

[0729] The server analyzes the received travel information and retrieves flight information by sending a request to an external API. For example, to retrieve flight information for Paris, it sends a request to "https: / / api.flightinfo.com / flights?dest=Paris&date=2023-12-01".

[0730] Input: Travel information (destination, travel period)

[0731] Output: Flight information

[0732] Step 4:

[0733] The server then accesses an external hotel information API to obtain hotel information in Paris, for example, by sending a request to "https: / / api.hotelinfo.com / hotels?dest=Paris&date=2023-12-01".

[0734] Input: Travel information (destination, travel period)

[0735] Output: Accommodation information

[0736] Step 5:

[0737] The server sends a request to an external product information API to retrieve product information from physical stores based on the user's preferences. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian".

[0738] Input: User Preferences

[0739] Output: Product information

[0740] Step 6:

[0741] The server generates local guide information and in-store guide information using the generative model. Specifically, it generates a prompt sentence, "Generate guide information for Italian-themed products in a modern style," and sends it to the generative model, which uses natural language processing technology.

[0742] Input: Destination information, user preferences

[0743] Output: Local guide information, in-store guide information

[0744] Step 7:

[0745] The server integrates the acquired flight information, accommodation information, product information, and generated guide information, and sends the integrated information as a single package to the user's terminal.The server converts the integrated information into JSON format and sends it to the user's terminal via an HTTP response.

[0746] Input: Flight information, accommodation information, product information, guide information

[0747] Output: Consolidated information (JSON format)

[0748] Step 8:

[0749] The user terminal (smart glasses) analyzes the integrated information received from the server and visually displays it to the user, allowing the user to view customized travel and shopping information in real time.

[0750] Input: Integrated information (JSON format)

[0751] Output: Customized information displayed to the user visually

[0752] 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.

[0753] The present invention provides a more personalized travel experience by combining a system that consistently supports travelers' travel planning with an emotion engine that recognizes user emotions. Specific examples of the system are described below.

[0754] System configuration

[0755] The system mainly consists of the following components:

[0756] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which travelers input their travel destination information, duration, and preferences, and which also has a built-in emotion engine that recognizes the user's emotions.

[0757] 2. Server: Receives data sent from the user device, acquires and generates various information, and finally integrates it. It also receives the output of the emotion engine and reflects it in the generation of information.

[0758] 3. External APIs: Various external services that provide flight and accommodation information.

[0759] 4. Generative model: An algorithm that generates local guide information using natural language processing technology. The output of the emotion engine is used to dynamically adjust the local guide information.

[0760] Program processing

[0761] 1. Enter your travel information

[0762] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[0763] At the same time, the emotion engine built into the user terminal analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions.

[0764] 2. Data transmission

[0765] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server via an HTTP POST request.

[0766] 3. Obtaining flight information

[0767] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0768] 4. Acquisition of accommodation information

[0769] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0770] 5. Generating local guide information

[0771] The server uses a generative model based on natural language processing technology to generate local guide information based on destination information and the user's recognized emotion data. For example, if the user is feeling stressed, it will suggest relaxing places and activities, and if the user is excited, it will suggest new experiences and challenging activities.

[0772] 6. Providing integrated information

[0773] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model, and transmits the integrated information as a single package to the user terminal, which then displays the integrated information to the user.

[0774] Specific examples

[0775] For example, a user enters the following travel itinerary:

[0776] Destination: Paris

[0777] Travel period: December 1, 2023 to December 7, 2023

[0778] Preferences: Good restaurants, cultural tourist spots

[0779] At the same time, the emotion engine of the user terminal recognizes the user's emotion as “feeling stressed.” The user terminal transmits this information to the server, which processes it as follows:

[0780] Get flight information to Paris from the Flights API.

[0781] Get accommodation information in Paris from the Hotel API.

[0782] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[0783] Finally, the server aggregates these data and displays it as a single itinerary on the user's device, allowing the user to easily book flights and hotels and enjoy a trip that includes stress-reducing activities.

[0784] The processing flow will be explained below.

[0785] Step 1:

[0786] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[0787] Step 2:

[0788] The emotion engine built into the user device analyzes the user's facial expressions, voice tone, or input text information to recognize the user's emotions. For example, if the user is smiling, it will recognize that they are "having fun," and if they are frowning, it will recognize that they are "feeling stressed."

[0789] Step 3:

[0790] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[0791] Step 4:

[0792] The server receives the data sent from the terminal, which includes the user's destination information, travel period, preferences, and emotion data.

[0793] Step 5:

[0794] The server accesses an external flight API to retrieve flight information based on the user's travel dates and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[0795] Step 6:

[0796] The server parses the response received from the Flights API and extracts the required flight information (e.g., flight number, departure and arrival times, airline, etc.).

[0797] Step 7:

[0798] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[0799] Step 8:

[0800] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[0801] Step 9:

[0802] The server uses the generative model to generate local guide information based on the destination information and the user's recognized emotion data. For example, if the user's emotion is recognized as "stressed," the server suggests relaxing places and activities. The server sends a request to the generative model saying, "Generate local guide information for Paris that includes relaxing activities."

[0803] Step 10:

[0804] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[0805] Step 11:

[0806] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model into a single package.

[0807] Step 12:

[0808] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[0809] Step 13:

[0810] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[0811] Step 14:

[0812] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses the local guide information to plan the details of their trip, for example booking a massage or spa treatment to relieve stress.

[0813] Example 2

[0814] 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."

[0815] Conventional travel planning support systems were able to provide information based on a traveler's destination and preferences, but they were unable to take into account the traveler's emotions, making it difficult to make optimal suggestions for each individual traveler. Furthermore, they lacked a means to integrate the acquired information and provide it to travelers in an easy-to-understand manner, resulting in a lack of convenience for travelers.

[0816] 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.

[0817] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using an emotion engine to analyze the traveler's emotions, means for using a generative model to generate local guide information based on the destination information and emotion data, and means for integrating the acquired or generated information and transmitting it to a user terminal in JSON format for display. This makes it possible to propose more personalized travel plans that take the traveler's emotions into consideration, and to provide the traveler with more appropriate and easy-to-understand information.

[0818] A "traveler" is someone who plans a travel destination and travel period and acts accordingly.

[0819] "Destination Information" refers to information about a location that a traveler intends to visit.

[0820] "Travel Period" means the period between the start and end dates for which a Traveler plans to travel.

[0821] "Preferences" refer to the specific experiences and interests that travelers seek while traveling.

[0822] "Candidate information" refers to information on various options obtained based on the traveler's destination information, travel period, and preferences.

[0823] "Flight Information" means detailed information about a flight taken by a traveler.

[0824] "Accommodation Information" means detailed information about accommodations for travelers to stay at.

[0825] An "emotion engine" refers to software or hardware functions that analyze and recognize a user's emotions.

[0826] A "generative model" refers to an algorithm that uses natural language processing techniques to generate specific information based on input data.

[0827] "Integration" refers to bringing together different types or multiple pieces of information into one.

[0828] "User terminal" refers to the electronic device used by a traveler to enter information and view results.

[0829] The present invention is a system that provides individual support for travellers' travel plans, and provides a more personalized travel experience by combining it with an emotion engine that recognises the traveller's emotions. Specific embodiments of the system are described below.

[0830] Hardware and Software Configuration

[0831] 1. User Device:

[0832] Hardware used: Smartphone or PC

[0833] Software used: Emotion engine (e.g., a general emotion recognition API)

[0834] 2. Server:

[0835] Hardware used: Cloud server (e.g., general cloud service)

[0836] Software used: External APIs (e.g., general flight information APIs, accommodation information APIs) and natural language processing technologies (e.g., general natural language processing algorithms)

[0837] Program processing

[0838] 1. The user enters information about their travel destination using a smartphone or computer. For example, they enter Paris as their destination, the travel period from December 1, 2023 to December 7, 2023, and their preferences for "good restaurants" and "cultural tourist spots."

[0839] 2. The device activates its built-in emotion engine, which analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions. For example, it determines that the user is feeling stressed.

[0840] 3. The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[0841] 4. The server analyzes the received data and sends a request to an external flight information API based on the travel date and destination to retrieve the required flight information. For example, to retrieve flight information for Paris.

[0842] 5. The server then sends a request to an external accommodation information API to retrieve the required accommodation information. For example, to retrieve accommodation information for Paris.

[0843] 6. The server uses the generative AI model to generate local guide information based on the destination information and emotion data. For example, if the user is feeling stressed, the server uses the following prompt to generate guide information including information on relaxation spots and spas:

[0844] Travel Planning Information:

[0845] Destination: Paris

[0846] Travel period: December 1, 2023 to December 7, 2023

[0847] Preferences: Good restaurants, cultural attractions

[0848] User Emotions: Stressed

[0849] Based on the above information, please generate local guide information that will help users relax.

[0850] 7. The server integrates the acquired flight information, accommodation information, and generated local guide information, and sends it as a package to the user's device. The user's device displays the integrated information to the user.

[0851] In this way, the system of the present invention can recognize the emotions of travelers and provide personalized travel information based on those emotions, thereby enabling travelers to plan trips with greater satisfaction.

[0852] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0853] Step 1:

[0854] Users input their travel information, such as destination, travel duration, and preferences, using their smartphone or computer. This input information includes data such as:

[0855] Destination: Paris

[0856] Travel period: December 1, 2023 to December 7, 2023

[0857] Preferences: Good restaurants, cultural tourist spots

[0858] Based on the input, the device activates its built-in emotion engine to analyze the user's facial expression, voice tone, and text information. For example, if the user's facial expression is tense, the emotion engine will recognize it as "feeling stressed" and output it as emotion data.

[0859] Step 2:

[0860] The device converts the travel information and recognized emotion data into JSON format. The specific input for this data conversion is as follows:

[0861] Travel information

[0862] Emotional data (e.g., "I feel stressed")

[0863] Example output in JSON format:

[0864] json

[0865] {

[0866] "destination": "Paris",

[0867] "travel_period": {

[0868] "start_date": "2023-12-01",

[0869] "end_date": "2023-12-07"

[0870] },

[0871] "preferences": ["good restaurants", "cultural tourist spots"],

[0872] "user_emotion": "stress"

[0873] }

[0874] The device sends this JSON formatted data to the server using an HTTP POST request.

[0875] Step 3:

[0876] The server analyzes the received data, specifically extracting travel itinerary and destination information.

[0877] input:

[0878] Travel information (JSON format)

[0879] The server then accesses an external flight information API and sends a request to retrieve the flight information.

[0880] Example API request:

[0881] http

[0882] GET https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01

[0883] output:

[0884] Flight information (flight number, departure time, arrival time, airline name, etc.)

[0885] Step 4:

[0886] The server similarly analyzes the received data and accesses external accommodation information APIs based on the travel destination and length of stay.

[0887] input:

[0888] Travel information (JSON format)

[0889] The server sends a request to the following URL to obtain accommodation information:

[0890] Example API request:

[0891] http

[0892] GET https: / / api.hotelapi.com / hotels?dest=Paris&checkin=2023-12-01&checkout=2023-12-07

[0893] output:

[0894] Accommodation information (hotel name, location, price, availability, etc.)

[0895] Step 5:

[0896] The server uses the generative AI model to generate local guide information.

[0897] input:

[0898] Destination information

[0899] Emotional Data

[0900] Preferences

[0901] The server inputs the following prompt sentence into the generative AI model to generate local guide information.

[0902] text

[0903] Travel Planning Information:

[0904] Destination: Paris

[0905] Travel period: December 1, 2023 to December 7, 2023

[0906] Preferences: Good restaurants, cultural attractions

[0907] User Emotions: Stressed

[0908] Based on the above information, please generate local guide information that will help users relax.

[0909] output:

[0910] Local guide information (relaxing places, spas, etc.)

[0911] Step 6:

[0912] The server integrates the acquired flight information, accommodation information, and generated local guide information.

[0913] input:

[0914] Flight information

[0915] Accommodation information

[0916] Local guide information

[0917] The integrated data is converted into JSON format and sent to the user's terminal.

[0918] Example output:

[0919] json

[0920] {

[0921] "flights": [

[0922] {

[0923] "flight_number": "AF123",

[0924] "departure_time": "2023-12-01T10:00:00",

[0925] "arrival_time": "2023-12-01T12:00:00",

[0926] "airline": "Air France"

[0927] }

[0928] ],

[0929] "hotels": [

[0930] {

[0931] "name": "Hotel du Louvre",

[0932] "location": "Centre of Paris",

[0933] "price": "200€ / night",

[0934] "availability": "Available"

[0935] }

[0936] ],

[0937] "guide": [

[0938] {

[0939] "activity": "Spa in Paris",

[0940] "description": "A great relaxing spa"

[0941] }

[0942] ]

[0943] }

[0944] The device analyzes the received data and displays it to the user, for example, by providing an app interface with flight information, accommodation information, and local guide information in an easy-to-read layout, allowing users to easily make reservations and plans.

[0945] (Application example 2)

[0946] 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."

[0947] Personalizing travel plans has become increasingly important for travelers to enhance their local experiences. However, conventional travel planning support systems have difficulty providing personalized travel suggestions that reflect the user's emotional state, limiting their ability to alleviate stress and inconvenience during travel. Furthermore, they have not offered suggestions for stores or services based on real-time emotions, and therefore have not been able to fully meet travelers' needs.

[0948] 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 recognizing the traveler's emotions and generating local guide information based on the emotions, means for dynamically adjusting store information based on the emotions in real time, and means for displaying the integrated information on the user terminal. This makes it possible to make personalized travel suggestions according to the traveler's emotional state, allowing the traveler to have a comfortable and satisfying experience in the local area.

[0949] "Tourist destination information" is information about the place that the traveler intends to visit.

[0950] "Travel period" is information about the period from the start date to the end date of a traveler's planned trip.

[0951] "Preferences" are information about the activities a traveler wants to experience at their destination and the categories of interest they have.

[0952] The "means for obtaining candidate information" refers to a means for collecting relevant travel destination and activity candidates based on the destination information, travel period, and preferences input by the traveler.

[0953] The "means for obtaining flight information" is a means for obtaining information on available flights based on the traveler's destination and travel period.

[0954] The "means for obtaining accommodation information" refers to a means for obtaining information on available accommodations based on the traveler's destination and travel period.

[0955] The "means for using a generative model" is a model used to generate local guide information based on the traveler's destination information and other related information.

[0956] The "means for integrating and displaying on the user terminal" is a means for integrating the acquired flight information, accommodation information, and generated local guide information and displaying them on the user's terminal.

[0957] The "means for recognizing user emotions" is a means for analyzing the facial expressions, voice, and input text of the traveler to recognize the emotional state of the traveler at that time.

[0958] The "means for dynamically adjusting local guide information based on emotions" refers to a means for appropriately changing local guide information based on the recognized emotional state of the traveler, and providing more appropriate information.

[0959] The "means for displaying emotion-based recommended store information in real time" is a means for providing appropriate store and service information in real time, taking into account the emotional state of the traveler, and displaying it on the user's terminal.

[0960] To implement this invention, a system including a user terminal, a server, an emotion recognition engine, a generative model, and a display interface is required.

[0961] System configuration

[0962] User terminal

[0963] The user terminal consists of a device such as a smartphone or smart glasses, and is equipped with an emotion engine that recognizes the traveler's emotions. Users can input their travel destination, duration, and preferences.

[0964] The emotion engine analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions in real time, making it possible to grasp various emotions such as stress and excitement during the trip.

[0965] server

[0966] The server receives the data sent by the user, retrieves the necessary flight and accommodation information through an external API, receives the output of the emotion recognition engine, and dynamically generates local guide information using a generative model.

[0967] The server uses the following methods:

[0968] 1. How to receive travel information

[0969] 2. Means of receiving emotion recognition data

[0970] 3. How to access external APIs

[0971] 4. Guide Information Generation Method Using Generative Model

[0972] 5. Means of transmitting integrated data to user terminals

[0973] Emotion Recognition Engine

[0974] The emotion recognition engine analyzes the user's emotional state in real time. This includes camera input (facial expression recognition) and microphone input (voice analysis). Specifically, it identifies the user's emotions using a facial expression analysis algorithm and a voice tone analysis engine, and sends the results in JSON format to the server.

[0975] Generative Model

[0976] The generative model uses natural language processing technology to generate personalized local guide information based on the user's emotional data and destination information. For example, if the user is feeling stressed, it will suggest places to relax, and if the user is excited, it will suggest places that offer new experiences. This generative model dynamically generates information based on data obtained from external APIs and data from an emotion recognition engine.

[0977] Display Interface

[0978] The user terminal is equipped with an interface for displaying the integrated information, which can provide links to booking procedures and additional information, helping users to smoothly plan their trip.

[0979] Specific examples

[0980] For example, a user enters the following travel itinerary through smart glasses:

[0981] Destination: Paris

[0982] Travel period: December 1, 2023 to December 7, 2023

[0983] Preferences: Good restaurants, cultural tourist spots

[0984] At the same time, the emotion recognition engine identifies the user's emotion as "stressed." The server receives this information and processes it as follows:

[0985] Get flight information to Paris from the Flights API.

[0986] Get accommodation information in Paris from the Hotel API.

[0987] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[0988] This information is integrated and displayed on the user's device, allowing travelers to receive the optimal travel plan based on their emotions and enjoy a comfortable and stress-free travel experience.

[0989] Prompt Sentence Examples

[0990] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[0991] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0992] Step 1:

[0993] A user inputs travel destination information, travel duration, and preferences into a device (such as smart glasses or a smartphone). The input data includes the destination (e.g., Paris), travel duration (date range), and activities and interests they would like to experience at the destination. This obtains basic information about the trip.

[0994] Step 2:

[0995] The emotion engine built into the device uses the camera and microphone to analyze the user's facial expressions and voice in real time. The input data is the video from the camera and the audio from the microphone. Based on this data, the emotion engine recognizes the user's emotions (e.g., stress, excitement, relief) and generates emotion data.

[0996] Step 3:

[0997] The device converts the travel information entered in step 1 and the emotion data generated in step 2 into JSON format and sends it to the server via an HTTP POST request, which causes the server to receive the user's travel information and emotion information.

[0998] Step 4:

[0999] The server sends a request to an external API (e.g., a service that provides flight and accommodation information) based on the received travel information and emotion data. The server retrieves appropriate flight and accommodation information based on the travel destination and duration. This collects basic information necessary for the user's trip.

[1000] Step 5:

[1001] The server integrates flight and accommodation information obtained from external APIs with emotion data and generates local guide information using a generative model. The generative model uses natural language processing technology to generate guide information tailored to the traveler based on the user's destination information and emotion data. For example, if the user is feeling stressed, it generates guide information suggesting places and services where they can relax.

[1002] Step 6:

[1003] The server then combines the generated local guide information, flight information, and accommodation information and sends it to the user's device as a single package, allowing the user to view all travel information in an integrated manner.

[1004] Step 7:

[1005] The terminal receives the integrated information sent from the server and displays it on the interface. The user can view the displayed travel information and access links to make reservations or get additional information as needed, making it easier for the user to plan their trip.

[1006] Prompt Sentence Examples

[1007] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[1008] 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.

[1009] 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.

[1010] 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.

[1011] [Third embodiment]

[1012] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1013] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1014] 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).

[1015] 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.

[1016] 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.

[1017] 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).

[1018] 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.

[1019] 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.

[1020] 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.

[1021] 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.

[1022] 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.

[1023] 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."

[1024] The present invention provides a system that consistently supports travelers in planning their trips. A specific embodiment of the system will be described below.

[1025] System configuration

[1026] The system mainly consists of the following components:

[1027] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which a traveler enters travel destination information, duration, and preferences.

[1028] 2. Server: Receives data sent from user terminals, acquires and generates various information, and finally integrates it.

[1029] 3. External APIs: Various external services that provide flight and accommodation information.

[1030] 4. Generative model: An algorithm that generates local guide information using natural language processing technology.

[1031] Program processing

[1032] 1. Enter your travel information

[1033] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[1034] 2. Data transmission

[1035] The device sends the entered travel information to the server, where it is converted into JSON format and sent to the server via an HTTP request.

[1036] 3. Obtaining flight information

[1037] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" and receives flight information.

[1038] 4. Acquisition of accommodation information

[1039] The server accesses an external hotel API and retrieves hotel information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" and receives hotel information.

[1040] 5. Generating local guide information

[1041] The server uses a generative model that uses natural language processing technology to generate local guide information based on the destination information. For example, the server sends a request such as "Provide local guide information for Paris in English" to the generative model and receives information such as recommended local spots and places to eat.

[1042] 6. Providing integrated information

[1043] The server integrates the acquired flight information, hotel information, and local guide information into one package and transmits it to the user terminal, which then displays the integrated information to the user.

[1044] Specific examples

[1045] For example, a user enters the following travel itinerary:

[1046] Destination: Paris

[1047] Travel period: December 1, 2023 to December 7, 2023

[1048] Preferences: Good restaurants, cultural tourist spots

[1049] The user terminal sends this information to the server, which processes it as follows:

[1050] Get flight information to Paris from the Flights API.

[1051] Get accommodation information in Paris from the Hotel API.

[1052] Using a generative model, we generate tourist information and restaurant recommendations for Paris.

[1053] Finally, the server integrates these data and displays them on the user's device as a single itinerary, allowing the user to easily book flights and hotels.

[1054] The processing flow will be explained below.

[1055] Step 1:

[1056] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[1057] Step 2:

[1058] The device converts the input information into JSON format and sends it to the server. Specifically, it creates an HTTP POST request and sends data including the trip information to the server.

[1059] Step 3:

[1060] The server receives the data sent from the terminal, which includes destination information, travel duration, and preferences.

[1061] Step 4:

[1062] The server accesses the Flight API and retrieves flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1063] Step 5:

[1064] The server parses the response received from the Flights API and extracts the required flight information (e.g. flight number, departure and arrival times, airline, etc.).

[1065] Step 6:

[1066] The server accesses the hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1067] Step 7:

[1068] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[1069] Step 8:

[1070] The server uses the generative model to generate local guide information based on the destination information. For example, it sends a request to the generative model saying, "Provide local guide information for Paris in English."

[1071] Step 9:

[1072] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[1073] Step 10:

[1074] The server integrates the flight information, accommodation information, and local guide information generated from the generative model into a single package.

[1075] Step 11:

[1076] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[1077] Step 12:

[1078] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[1079] Step 13:

[1080] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses local guide information to plan the details of their trip.

[1081] Example 1

[1082] 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."

[1083] Conventional travel planning support systems require travelers to collect flight information, accommodation information, and local tourist information individually, which is extremely time-consuming. Furthermore, because each source of information is different, it is difficult to manage them in an integrated manner. This makes it difficult for travelers to plan their trips quickly and efficiently.

[1084] 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.

[1085] In this invention, the server includes: means for acquiring candidate information based on a traveler's destination information, travel period, and preferences; a user terminal for converting the candidate information into JSON format and sending it to the server; means for acquiring flight information from an external API based on the destination information and travel period; means for acquiring accommodation information from the external API based on the destination and length of stay; means for using a generative AI model to generate local guide information based on the destination information; a server for integrating the acquired or generated information and sending the integrated information to the user terminal; and means for displaying the integrated information to the user. This allows travelers to consistently acquire flight information, accommodation information, and local guide information through a single system, enabling efficient travel planning.

[1086] "Traveller" refers to a person who plans and undertakes a trip.

[1087] "Destination Information" refers to information about places that a traveler plans to visit.

[1088] "Travel Period" refers to the period from the date a traveler begins to the date the travel ends.

[1089] "Preferences" refers to information about what a traveler wants to experience and their preferred activities during their trip.

[1090] "Candidate Information" refers to travel options to be considered that are obtained based on the traveler's destination information, travel duration, and preferences.

[1091] "User terminal" refers to an electronic device used by a traveler to enter data such as travel destination information, duration, preferences, etc.

[1092] "Server" refers to a computer system that receives and processes data sent from a user terminal.

[1093] "External API" refers to a program interface for obtaining data from a service provided by a third party.

[1094] "Flight Information" means data containing detailed information about the flight you are taking.

[1095] "Accommodation Information" refers to data containing detailed information about the accommodation where a traveler is staying.

[1096] A "generative AI model" refers to an algorithm that generates data using natural language processing techniques.

[1097] "Local guide information" refers to information about tourist attractions and recommended spots at your travel destination.

[1098] "Integrated information" refers to data that brings together flight information, accommodation information, and local guide information.

[1099] This invention is a system that efficiently supports travelers' travel planning by collecting and integrating necessary information based on specific destination information, travel period, and preferences, and providing it to users. This system is mainly realized using a user terminal, a server, an external API, and a generative AI model. Specific implementation methods for this system are described below.

[1100] System configuration

[1101] This system is broadly composed of the following components:

[1102] 1. User terminal: An electronic device that allows travelers to input information about their travel destinations, duration, and preferences. Specifically, a smartphone or PC is used.

[1103] 2. Server: Receives data sent from user terminals and acquires, generates, and integrates various information. The server is a high-performance computer that can quickly process large amounts of data.

[1104] 3. External APIs: These are APIs used to provide flight information or accommodation information, such as Flight APIs and Hotel APIs.

[1105] 4. Generative AI model: An algorithm that uses natural language processing technology to generate local guide information. For example, OpenAI's GPT-3 is used.

[1106] System action

[1107] 1. Enter your travel information

[1108] The user inputs travel destination information (e.g., "Paris"), travel period (December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants" and "cultural tourist spots") into the user terminal.

[1109] 2. Data transmission

[1110] The device converts the entered travel information into JSON format and sends it to the server via an HTTP request, generating the following JSON data, for example: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[1111] 3. Obtaining flight information

[1112] The server sends a request to an external flight API to retrieve flight information based on the itinerary and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" to retrieve flight information.

[1113] 4. Acquisition of accommodation information

[1114] The server sends a request to an external hotel API to retrieve accommodation information based on the travel period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" to retrieve hotel information.

[1115] 5. Generating local guide information

[1116] The server generates a prompt based on the destination information and sends it to the generative AI model. An example prompt is "Provide local guide information for Paris in English." The server receives the local guide information generated by the generative AI model.

[1117] 6. Integration and provision of information

[1118] The server aggregates the flight, accommodation, and local guide information, resulting in a JSON data stream like this: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}.

[1119] The server sends the integrated information to the user terminal, which then displays the received information to the user, who can then easily make flight and hotel reservations based on this information.

[1120] Specific examples

[1121] For example, if a user enters a travel plan such as "Paris," "December 1, 2023 to December 7, 2023," and "good restaurants and cultural tourist spots," the server will process it as follows:

[1122] 1. The server accesses the Flight API and retrieves flight information for Paris.

[1123] 2. The server accesses the hotel API and retrieves information about accommodations in Paris.

[1124] 3. The server uses the generative AI model to generate tourist information and restaurant recommendations for Paris.

[1125] Finally, the server integrates this information and sends it to the user's terminal as a single travel plan, allowing the user to efficiently make flight and hotel reservations based on this information.

[1126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1127] Step 1: Enter your travel information

[1128] The user inputs information about the travel destination, travel period, and preferences into the user terminal. Specifically, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "good restaurants," and "cultural tourist spots."

[1129] Input: Destination information (Paris), travel period (December 1, 2023 to December 7, 2023), preferences (good restaurants, cultural attractions).

[1130] Output: Trip information stored on the user's device.

[1131] Step 2: Sending data

[1132] The device converts the entered travel information into JSON format and sends it to the server using an HTTP request. For example, the following JSON data is generated: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[1133] Input: Trip information entered by the user.

[1134] Data processing: Convert travel information into JSON format.

[1135] Output: The generated JSON data is sent to the server.

[1136] Step 3: Get flight information

[1137] The server then sends a request to an external flight API based on the received travel information to retrieve flight information based on the travel date and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01."

[1138] Input: Trip information (JSON format).

[1139] Data Computing: Accessing and requesting Flight APIs.

[1140] Output: Flight information (JSON format) retrieved from the Flights API.

[1141] Step 4: Obtaining accommodation information

[1142] The server sends a request to an external hotel API based on the travel period and destination to retrieve accommodation information, for example, "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1143] Input: Trip information (JSON format).

[1144] Data Operations: Accessing and requesting hotel APIs.

[1145] Output: Accommodation information obtained from the Hotel API (JSON format).

[1146] Step 5: Generate local guide information

[1147] The server generates a prompt sentence based on the destination information and sends it to the generative AI model. An example prompt sentence is "Provide local guide information for Paris in English." The local guide information generated by the generative AI model is then obtained.

[1148] Input: Travel destination information.

[1149] Data calculation: Prompt sentence generation and sending to the generative AI model.

[1150] Output: Local guide information obtained from the generative AI model.

[1151] Step 6: Integrate and provide information

[1152] The server combines the flight information, accommodation information, and local guide information and converts the combined information into JSON format. An example of the generated JSON data is: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}

[1153] Input: flight information, accommodation information, local guide information.

[1154] Data processing: Integration of each piece of information and conversion to JSON format.

[1155] Output: Consolidated information (JSON format).

[1156] Step 7: View integration information

[1157] The terminal displays the integrated information sent from the server to the user, who can then make flight and hotel reservations based on this information.

[1158] Input: Consolidated information (JSON format).

[1159] Data processing: Display of integrated information on user terminals.

[1160] Output: A set of travel plan information available to the user.

[1161] (Application example 1)

[1162] 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."

[1163] Conventional travel planning support systems are limited to providing users with information on travel destinations and accommodations, and have difficulty providing customized product information or in-store guide information for physical stores. Furthermore, they are unable to provide information based on users' preferences in real time, leaving a lack of ways to further enhance the travel experience.

[1164] 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.

[1165] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using a generative model to generate local guide information based on the destination information, means for integrating the acquired or generated information and displaying it on a user terminal, and means for providing product information and in-store guide information based on the user's preferences. This allows users to receive customized information based on their preferences in real time not only at their travel destinations but also in physical stores, significantly improving their travel and shopping experiences.

[1166] A "traveler" is an individual or group that makes travel plans based on destination information, duration, and preferences.

[1167] "Destination information" is information including the specific geographical location and name of a place that a traveler wants to visit.

[1168] "Travel period" is information about the period of time including the start and end dates of the trip that the traveler is planning.

[1169] "Preferences" refers to information that indicates the elements or conditions that a traveler is particularly interested in while traveling (e.g., good restaurants, cultural tourist spots, etc.).

[1170] "Candidate information" refers to information about multiple options obtained based on the traveler's destination information, travel period, and preferences.

[1171] "Flight information" refers to information about an airline flight, which is a traveler's means of transportation, and includes the departure point, destination, boarding time, and the like.

[1172] "Accommodation Information" means information about accommodation facilities intended for travelers' stay, including the location of the facility, fees, services provided, etc.

[1173] A "generative model" is an algorithm used to generate local guide information based on destination information, often using natural language processing techniques.

[1174] "Natural language processing technology" is a computer technology that has the ability to understand and generate human language.

[1175] "Integrated information" is information that brings together data obtained from multiple different sources.

[1176] "User terminal" refers to an electronic device that allows travelers to input and receive information, including smartphones, tablets, and personal computers.

[1177] A "server" is a computer system that receives and processes data sent from user terminals, and generates and distributes integrated information.

[1178] "Product information" refers to specific information about products and services offered in physical stores.

[1179] "In-store guide information" refers to information about product placement and recommended spots within a physical store.

[1180] The present invention is a system that provides travelers with customized information based on their travel destination information, travel period, and preferences. In addition to planning travel plans, the system can also provide product information and in-store guide information tailored to the user's preferences in brick-and-mortar stores.

[1181] System configuration

[1182] The system mainly consists of the following components:

[1183] 1. User terminal: An electronic device (e.g., a smartphone or smart glasses) through which travelers input their destination information, travel duration, and preferences.

[1184] 2. Server: Receives data sent from user terminals, acquires and generates various information, and delivers the integrated information to user terminals.

[1185] 3. External APIs: Various external services that provide flight information, accommodation information, and product information from physical stores.

[1186] 4. Generative model: An algorithm that uses natural language processing technology to generate local guide information and in-store guide information.

[1187] Explanation of program processing

[1188] 1. Enter your user information

[1189] A user wears smart glasses and enters information about their travel destination, travel duration, and preferences through the glasses, such as specific preferences like "Italian cuisine" and "modern design."

[1190] 2. Data transmission

[1191] The smart glasses convert the input information into JSON format and send it to the server via Wi-Fi or Bluetooth.

[1192] 3. Information Acquisition and Generation

[1193] The server accesses external flight and accommodation APIs to retrieve flight and hotel information based on the traveler's travel dates and destinations.

[1194] In addition, to obtain product information based on the user's preferences, the app accesses the store's external API. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian" and receives product information.

[1195] Furthermore, local guide information and in-store guide information are generated using the generative model. Specifically, information is obtained by sending prompt sentences to the generative model. For example, the prompt is "Generate guide information for Italian-themed products in a modern style."

[1196] 4. Providing integrated information

[1197] The server integrates the acquired flight information, accommodation information, product information, and guide information generated by the generative model, and sends it to the user's terminal as a single information package. The user terminal then displays this integrated information to the user.

[1198] Specific examples

[1199] For example, a user inputs the following information through smart glasses:

[1200] Travel Destination Information: Paris

[1201] Travel period: December 1, 2023 to December 7, 2023

[1202] Preferences: Italian food, modern design

[1203] The server accesses external APIs to retrieve flight information to Paris, accommodation information in Paris, and product information related to Italian cuisine. It then uses the generative model to generate tourist information about Paris and recommended Italian restaurants. Finally, the server integrates this information and displays it on the user's smart glasses.

[1204] Hardware and software used

[1205] Hardware: Smart glasses (e.g. Google Glass, Vuzix)

[1206] software:

[1207] Python 3.x

[1208] HTTP library (requests)

[1209] External API (flight information API, accommodation information API, product information API)

[1210] Natural language generation models (GPT-4, etc.)

[1211] In this way, users will be able to receive real-time, customized information not only for travel planning but also in physical stores.

[1212] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1213] Step 1:

[1214] The user inputs information about the travel destination, travel period, and preferences through the smart glasses. For example, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "Italian cuisine, modern design." This information is collected by the smart glasses application.

[1215] Input: Destination information, travel period, preferences

[1216] Output: User's travel information (JSON format)

[1217] Step 2:

[1218] The user device (smart glasses) converts the input information into JSON format and sends it to the server via an HTTP request. Specifically, the data is sent to the server via Wi-Fi or Bluetooth.

[1219] Input: User's travel information (JSON format)

[1220] Output: Trip information sent to the server

[1221] Step 3:

[1222] The server analyzes the received travel information and retrieves flight information by sending a request to an external API. For example, to retrieve flight information for Paris, it sends a request to "https: / / api.flightinfo.com / flights?dest=Paris&date=2023-12-01".

[1223] Input: Travel information (destination, travel period)

[1224] Output: Flight information

[1225] Step 4:

[1226] The server then accesses an external hotel information API to obtain hotel information in Paris, for example, by sending a request to "https: / / api.hotelinfo.com / hotels?dest=Paris&date=2023-12-01".

[1227] Input: Travel information (destination, travel period)

[1228] Output: Accommodation information

[1229] Step 5:

[1230] The server sends a request to an external product information API to retrieve product information from physical stores based on the user's preferences. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian".

[1231] Input: User Preferences

[1232] Output: Product information

[1233] Step 6:

[1234] The server generates local guide information and in-store guide information using the generative model. Specifically, it generates a prompt sentence, "Generate guide information for Italian-themed products in a modern style," and sends it to the generative model, which uses natural language processing technology.

[1235] Input: Destination information, user preferences

[1236] Output: Local guide information, in-store guide information

[1237] Step 7:

[1238] The server integrates the acquired flight information, accommodation information, product information, and generated guide information, and sends the integrated information as a single package to the user's terminal.The server converts the integrated information into JSON format and sends it to the user's terminal via an HTTP response.

[1239] Input: Flight information, accommodation information, product information, guide information

[1240] Output: Consolidated information (JSON format)

[1241] Step 8:

[1242] The user terminal (smart glasses) analyzes the integrated information received from the server and visually displays it to the user, allowing the user to view customized travel and shopping information in real time.

[1243] Input: Integrated information (JSON format)

[1244] Output: Customized information displayed to the user visually

[1245] 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.

[1246] The present invention provides a more personalized travel experience by combining a system that consistently supports travelers' travel planning with an emotion engine that recognizes user emotions. Specific examples of the system are described below.

[1247] System configuration

[1248] The system mainly consists of the following components:

[1249] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which travelers input their travel destination information, duration, and preferences, and which also has a built-in emotion engine that recognizes the user's emotions.

[1250] 2. Server: Receives data sent from the user device, acquires and generates various information, and finally integrates it. It also receives the output of the emotion engine and reflects it in the generation of information.

[1251] 3. External APIs: Various external services that provide flight and accommodation information.

[1252] 4. Generative model: An algorithm that generates local guide information using natural language processing technology. The output of the emotion engine is used to dynamically adjust the local guide information.

[1253] Program processing

[1254] 1. Enter your travel information

[1255] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[1256] At the same time, the emotion engine built into the user terminal analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions.

[1257] 2. Data transmission

[1258] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server via an HTTP POST request.

[1259] 3. Obtaining flight information

[1260] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1261] 4. Acquisition of accommodation information

[1262] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1263] 5. Generating local guide information

[1264] The server uses a generative model based on natural language processing technology to generate local guide information based on destination information and the user's recognized emotion data. For example, if the user is feeling stressed, it will suggest relaxing places and activities, and if the user is excited, it will suggest new experiences and challenging activities.

[1265] 6. Providing integrated information

[1266] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model, and transmits the integrated information as a single package to the user terminal, which then displays the integrated information to the user.

[1267] Specific examples

[1268] For example, a user enters the following travel itinerary:

[1269] Destination: Paris

[1270] Travel period: December 1, 2023 to December 7, 2023

[1271] Preferences: Good restaurants, cultural tourist spots

[1272] At the same time, the emotion engine of the user terminal recognizes the user's emotion as “feeling stressed.” The user terminal transmits this information to the server, which processes it as follows:

[1273] Get flight information to Paris from the Flights API.

[1274] Get accommodation information in Paris from the Hotel API.

[1275] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[1276] Finally, the server aggregates these data and displays it as a single itinerary on the user's device, allowing the user to easily book flights and hotels and enjoy a trip that includes stress-reducing activities.

[1277] The processing flow will be explained below.

[1278] Step 1:

[1279] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[1280] Step 2:

[1281] The emotion engine built into the user device analyzes the user's facial expressions, voice tone, or input text information to recognize the user's emotions. For example, if the user is smiling, it will recognize that they are "having fun," and if they are frowning, it will recognize that they are "feeling stressed."

[1282] Step 3:

[1283] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[1284] Step 4:

[1285] The server receives the data sent from the terminal, which includes the user's destination information, travel period, preferences, and emotion data.

[1286] Step 5:

[1287] The server accesses an external flight API to retrieve flight information based on the user's travel dates and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1288] Step 6:

[1289] The server parses the response received from the Flights API and extracts the required flight information (e.g., flight number, departure and arrival times, airline, etc.).

[1290] Step 7:

[1291] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1292] Step 8:

[1293] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[1294] Step 9:

[1295] The server uses the generative model to generate local guide information based on the destination information and the user's recognized emotion data. For example, if the user's emotion is recognized as "stressed," the server suggests relaxing places and activities. The server sends a request to the generative model saying, "Generate local guide information for Paris that includes relaxing activities."

[1296] Step 10:

[1297] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[1298] Step 11:

[1299] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model into a single package.

[1300] Step 12:

[1301] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[1302] Step 13:

[1303] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[1304] Step 14:

[1305] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses the local guide information to plan the details of their trip, for example booking a massage or spa treatment to relieve stress.

[1306] Example 2

[1307] 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."

[1308] Conventional travel planning support systems were able to provide information based on a traveler's destination and preferences, but they were unable to take into account the traveler's emotions, making it difficult to make optimal suggestions for each individual traveler. Furthermore, they lacked a means to integrate the acquired information and provide it to travelers in an easy-to-understand manner, resulting in a lack of convenience for travelers.

[1309] 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.

[1310] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using an emotion engine to analyze the traveler's emotions, means for using a generative model to generate local guide information based on the destination information and emotion data, and means for integrating the acquired or generated information and transmitting it to a user terminal in JSON format for display. This makes it possible to propose more personalized travel plans that take the traveler's emotions into consideration, and to provide the traveler with more appropriate and easy-to-understand information.

[1311] A "traveler" is someone who plans a travel destination and travel period and acts accordingly.

[1312] "Destination Information" refers to information about a location that a traveler intends to visit.

[1313] "Travel Period" means the period between the start and end dates for which a Traveler plans to travel.

[1314] "Preferences" refer to the specific experiences and interests that travelers seek while traveling.

[1315] "Candidate information" refers to information on various options obtained based on the traveler's destination information, travel period, and preferences.

[1316] "Flight Information" means detailed information about a flight taken by a traveler.

[1317] "Accommodation Information" means detailed information about accommodations for travelers to stay at.

[1318] An "emotion engine" refers to software or hardware functions that analyze and recognize a user's emotions.

[1319] A "generative model" refers to an algorithm that uses natural language processing techniques to generate specific information based on input data.

[1320] "Integration" refers to bringing together different types or multiple pieces of information into one.

[1321] "User terminal" refers to the electronic device used by a traveler to enter information and view results.

[1322] The present invention is a system that provides individual support for travellers' travel plans, and provides a more personalized travel experience by combining it with an emotion engine that recognises the traveller's emotions. Specific embodiments of the system are described below.

[1323] Hardware and Software Configuration

[1324] 1. User Device:

[1325] Hardware used: Smartphone or PC

[1326] Software used: Emotion engine (e.g., a general emotion recognition API)

[1327] 2. Server:

[1328] Hardware used: Cloud server (e.g., general cloud service)

[1329] Software used: External APIs (e.g., general flight information APIs, accommodation information APIs) and natural language processing technologies (e.g., general natural language processing algorithms)

[1330] Program processing

[1331] 1. The user enters information about their travel destination using a smartphone or computer. For example, they enter Paris as their destination, the travel period from December 1, 2023 to December 7, 2023, and their preferences for "good restaurants" and "cultural tourist spots."

[1332] 2. The device activates its built-in emotion engine, which analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions. For example, it determines that the user is feeling stressed.

[1333] 3. The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[1334] 4. The server analyzes the received data and sends a request to an external flight information API based on the travel date and destination to retrieve the required flight information. For example, to retrieve flight information for Paris.

[1335] 5. The server then sends a request to an external accommodation information API to retrieve the required accommodation information. For example, to retrieve accommodation information for Paris.

[1336] 6. The server uses the generative AI model to generate local guide information based on the destination information and emotion data. For example, if the user is feeling stressed, the server uses the following prompt to generate guide information including information on relaxation spots and spas:

[1337] Travel Planning Information:

[1338] Destination: Paris

[1339] Travel period: December 1, 2023 to December 7, 2023

[1340] Preferences: Good restaurants, cultural attractions

[1341] User Emotions: Stressed

[1342] Based on the above information, please generate local guide information that will help users relax.

[1343] 7. The server integrates the acquired flight information, accommodation information, and generated local guide information, and sends it as a package to the user's device. The user's device displays the integrated information to the user.

[1344] In this way, the system of the present invention can recognize the emotions of travelers and provide personalized travel information based on those emotions, thereby enabling travelers to plan trips with greater satisfaction.

[1345] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1346] Step 1:

[1347] Users input their travel information, such as destination, travel duration, and preferences, using their smartphone or computer. This input information includes data such as:

[1348] Destination: Paris

[1349] Travel period: December 1, 2023 to December 7, 2023

[1350] Preferences: Good restaurants, cultural tourist spots

[1351] Based on the input, the device activates its built-in emotion engine to analyze the user's facial expression, voice tone, and text information. For example, if the user's facial expression is tense, the emotion engine will recognize it as "feeling stressed" and output it as emotion data.

[1352] Step 2:

[1353] The device converts the travel information and recognized emotion data into JSON format. The specific input for this data conversion is as follows:

[1354] Travel information

[1355] Emotional data (e.g., "I feel stressed")

[1356] Example output in JSON format:

[1357] json

[1358] {

[1359] "destination": "Paris",

[1360] "travel_period": {

[1361] "start_date": "2023-12-01",

[1362] "end_date": "2023-12-07"

[1363] },

[1364] "preferences": ["good restaurants", "cultural tourist spots"],

[1365] "user_emotion": "stress"

[1366] }

[1367] The device sends this JSON formatted data to the server using an HTTP POST request.

[1368] Step 3:

[1369] The server analyzes the received data, specifically extracting travel itinerary and destination information.

[1370] input:

[1371] Travel information (JSON format)

[1372] The server then accesses an external flight information API and sends a request to retrieve the flight information.

[1373] Example API request:

[1374] http

[1375] GET https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01

[1376] output:

[1377] Flight information (flight number, departure time, arrival time, airline name, etc.)

[1378] Step 4:

[1379] The server similarly analyzes the received data and accesses external accommodation information APIs based on the travel destination and length of stay.

[1380] input:

[1381] Travel information (JSON format)

[1382] The server sends a request to the following URL to obtain accommodation information:

[1383] Example API request:

[1384] http

[1385] GET https: / / api.hotelapi.com / hotels?dest=Paris&checkin=2023-12-01&checkout=2023-12-07

[1386] output:

[1387] Accommodation information (hotel name, location, price, availability, etc.)

[1388] Step 5:

[1389] The server uses the generative AI model to generate local guide information.

[1390] input:

[1391] Destination information

[1392] Emotional Data

[1393] Preferences

[1394] The server inputs the following prompt sentence into the generative AI model to generate local guide information.

[1395] text

[1396] Travel Planning Information:

[1397] Destination: Paris

[1398] Travel period: December 1, 2023 to December 7, 2023

[1399] Preferences: Good restaurants, cultural attractions

[1400] User Emotions: Stressed

[1401] Based on the above information, please generate local guide information that will help users relax.

[1402] output:

[1403] Local guide information (relaxing places, spas, etc.)

[1404] Step 6:

[1405] The server integrates the acquired flight information, accommodation information, and generated local guide information.

[1406] input:

[1407] Flight information

[1408] Accommodation information

[1409] Local guide information

[1410] The integrated data is converted into JSON format and sent to the user's terminal.

[1411] Example output:

[1412] json

[1413] {

[1414] "flights": [

[1415] {

[1416] "flight_number": "AF123",

[1417] "departure_time": "2023-12-01T10:00:00",

[1418] "arrival_time": "2023-12-01T12:00:00",

[1419] "airline": "Air France"

[1420] }

[1421] ],

[1422] "hotels": [

[1423] {

[1424] "name": "Hotel du Louvre",

[1425] "location": "Centre of Paris",

[1426] "price": "200€ / night",

[1427] "availability": "Available"

[1428] }

[1429] ],

[1430] "guide": [

[1431] {

[1432] "activity": "Spa in Paris",

[1433] "description": "A great relaxing spa"

[1434] }

[1435] ]

[1436] }

[1437] The device analyzes the received data and displays it to the user, for example, by providing an app interface with flight information, accommodation information, and local guide information in an easy-to-read layout, allowing users to easily make reservations and plans.

[1438] (Application example 2)

[1439] 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."

[1440] Personalizing travel plans has become increasingly important for travelers to enhance their local experiences. However, conventional travel planning support systems have difficulty providing personalized travel suggestions that reflect the user's emotional state, limiting their ability to alleviate stress and inconvenience during travel. Furthermore, they have not offered suggestions for stores or services based on real-time emotions, and therefore have not been able to fully meet travelers' needs.

[1441] 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 recognizing the traveler's emotions and generating local guide information based on the emotions, means for dynamically adjusting store information based on the emotions in real time, and means for displaying the integrated information on the user terminal. This makes it possible to make personalized travel suggestions according to the traveler's emotional state, allowing the traveler to have a comfortable and satisfying experience in the local area.

[1442] "Tourist destination information" is information about the place that the traveler intends to visit.

[1443] "Travel period" is information about the period from the start date to the end date of a traveler's planned trip.

[1444] "Preferences" are information about the activities a traveler wants to experience at their destination and the categories of interest they have.

[1445] The "means for obtaining candidate information" refers to a means for collecting relevant travel destination and activity candidates based on the destination information, travel period, and preferences input by the traveler.

[1446] The "means for obtaining flight information" is a means for obtaining information on available flights based on the traveler's destination and travel period.

[1447] The "means for obtaining accommodation information" refers to a means for obtaining information on available accommodations based on the traveler's destination and travel period.

[1448] The "means for using a generative model" is a model used to generate local guide information based on the traveler's destination information and other related information.

[1449] The "means for integrating and displaying on the user terminal" is a means for integrating the acquired flight information, accommodation information, and generated local guide information and displaying them on the user's terminal.

[1450] The "means for recognizing user emotions" is a means for analyzing the facial expressions, voice, and input text of the traveler to recognize the emotional state of the traveler at that time.

[1451] The "means for dynamically adjusting local guide information based on emotions" refers to a means for appropriately changing local guide information based on the recognized emotional state of the traveler, and providing more appropriate information.

[1452] The "means for displaying emotion-based recommended store information in real time" is a means for providing appropriate store and service information in real time, taking into account the emotional state of the traveler, and displaying it on the user's terminal.

[1453] To implement this invention, a system including a user terminal, a server, an emotion recognition engine, a generative model, and a display interface is required.

[1454] System configuration

[1455] User terminal

[1456] The user terminal consists of a device such as a smartphone or smart glasses, and is equipped with an emotion engine that recognizes the traveler's emotions. Users can input their travel destination, duration, and preferences.

[1457] The emotion engine analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions in real time, making it possible to grasp various emotions such as stress and excitement during the trip.

[1458] server

[1459] The server receives the data sent by the user, retrieves the necessary flight and accommodation information through an external API, receives the output of the emotion recognition engine, and dynamically generates local guide information using a generative model.

[1460] The server uses the following methods:

[1461] 1. How to receive travel information

[1462] 2. Means of receiving emotion recognition data

[1463] 3. How to access external APIs

[1464] 4. Guide Information Generation Method Using Generative Model

[1465] 5. Means of transmitting integrated data to user terminals

[1466] Emotion Recognition Engine

[1467] The emotion recognition engine analyzes the user's emotional state in real time. This includes camera input (facial expression recognition) and microphone input (voice analysis). Specifically, it identifies the user's emotions using a facial expression analysis algorithm and a voice tone analysis engine, and sends the results in JSON format to the server.

[1468] Generative Model

[1469] The generative model uses natural language processing technology to generate personalized local guide information based on the user's emotional data and destination information. For example, if the user is feeling stressed, it will suggest places to relax, and if the user is excited, it will suggest places that offer new experiences. This generative model dynamically generates information based on data obtained from external APIs and data from an emotion recognition engine.

[1470] Display Interface

[1471] The user terminal is equipped with an interface for displaying the integrated information, which can provide links to booking procedures and additional information, helping users to smoothly plan their trip.

[1472] Specific examples

[1473] For example, a user enters the following travel itinerary through smart glasses:

[1474] Destination: Paris

[1475] Travel period: December 1, 2023 to December 7, 2023

[1476] Preferences: Good restaurants, cultural tourist spots

[1477] At the same time, the emotion recognition engine identifies the user's emotion as "stressed." The server receives this information and processes it as follows:

[1478] Get flight information to Paris from the Flights API.

[1479] Get accommodation information in Paris from the Hotel API.

[1480] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[1481] This information is integrated and displayed on the user's device, allowing travelers to receive the optimal travel plan based on their emotions and enjoy a comfortable and stress-free travel experience.

[1482] Prompt Sentence Examples

[1483] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[1484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1485] Step 1:

[1486] A user inputs travel destination information, travel duration, and preferences into a device (such as smart glasses or a smartphone). The input data includes the destination (e.g., Paris), travel duration (date range), and activities and interests they would like to experience at the destination. This obtains basic information about the trip.

[1487] Step 2:

[1488] The emotion engine built into the device uses the camera and microphone to analyze the user's facial expressions and voice in real time. The input data is the video from the camera and the audio from the microphone. Based on this data, the emotion engine recognizes the user's emotions (e.g., stress, excitement, relief) and generates emotion data.

[1489] Step 3:

[1490] The device converts the travel information entered in step 1 and the emotion data generated in step 2 into JSON format and sends it to the server via an HTTP POST request, which causes the server to receive the user's travel information and emotion information.

[1491] Step 4:

[1492] The server sends a request to an external API (e.g., a service that provides flight and accommodation information) based on the received travel information and emotion data. The server retrieves appropriate flight and accommodation information based on the travel destination and duration. This collects basic information necessary for the user's trip.

[1493] Step 5:

[1494] The server integrates flight and accommodation information obtained from external APIs with emotion data and generates local guide information using a generative model. The generative model uses natural language processing technology to generate guide information tailored to the traveler based on the user's destination information and emotion data. For example, if the user is feeling stressed, it generates guide information suggesting places and services where they can relax.

[1495] Step 6:

[1496] The server then combines the generated local guide information, flight information, and accommodation information and sends it to the user's device as a single package, allowing the user to view all travel information in an integrated manner.

[1497] Step 7:

[1498] The terminal receives the integrated information sent from the server and displays it on the interface. The user can view the displayed travel information and access links to make reservations or get additional information as needed, making it easier for the user to plan their trip.

[1499] Prompt Sentence Examples

[1500] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[1501] 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.

[1502] 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.

[1503] 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.

[1504] [Fourth embodiment]

[1505] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1506] 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.

[1507] 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).

[1508] 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.

[1509] 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.

[1510] 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).

[1511] 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.

[1512] 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.

[1513] 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.

[1514] 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.

[1515] 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.

[1516] 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.

[1517] 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."

[1518] The present invention provides a system that consistently supports travelers in planning their trips. A specific embodiment of the system will be described below.

[1519] System configuration

[1520] The system mainly consists of the following components:

[1521] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which a traveler enters travel destination information, duration, and preferences.

[1522] 2. Server: Receives data sent from user terminals, acquires and generates various information, and finally integrates it.

[1523] 3. External APIs: Various external services that provide flight and accommodation information.

[1524] 4. Generative model: An algorithm that generates local guide information using natural language processing technology.

[1525] Program processing

[1526] 1. Enter your travel information

[1527] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[1528] 2. Data transmission

[1529] The device sends the entered travel information to the server, where it is converted into JSON format and sent to the server via an HTTP request.

[1530] 3. Obtaining flight information

[1531] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" and receives flight information.

[1532] 4. Acquisition of accommodation information

[1533] The server accesses an external hotel API and retrieves hotel information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" and receives hotel information.

[1534] 5. Generating local guide information

[1535] The server uses a generative model that uses natural language processing technology to generate local guide information based on the destination information. For example, the server sends a request such as "Provide local guide information for Paris in English" to the generative model and receives information such as recommended local spots and places to eat.

[1536] 6. Providing integrated information

[1537] The server integrates the acquired flight information, hotel information, and local guide information into one package and transmits it to the user terminal, which then displays the integrated information to the user.

[1538] Specific examples

[1539] For example, a user enters the following travel itinerary:

[1540] Destination: Paris

[1541] Travel period: December 1, 2023 to December 7, 2023

[1542] Preferences: Good restaurants, cultural tourist spots

[1543] The user terminal sends this information to the server, which processes it as follows:

[1544] Get flight information to Paris from the Flights API.

[1545] Get accommodation information in Paris from the Hotel API.

[1546] Using a generative model, we generate tourist information and restaurant recommendations for Paris.

[1547] Finally, the server integrates these data and displays them on the user's device as a single itinerary, allowing the user to easily book flights and hotels.

[1548] The processing flow will be explained below.

[1549] Step 1:

[1550] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[1551] Step 2:

[1552] The device converts the input information into JSON format and sends it to the server. Specifically, it creates an HTTP POST request and sends data including the trip information to the server.

[1553] Step 3:

[1554] The server receives the data sent from the terminal, which includes destination information, travel duration, and preferences.

[1555] Step 4:

[1556] The server accesses the Flight API and retrieves flight information based on the user's travel date and destination. For example, it sends a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1557] Step 5:

[1558] The server parses the response received from the Flights API and extracts the required flight information (e.g. flight number, departure and arrival times, airline, etc.).

[1559] Step 6:

[1560] The server accesses the hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1561] Step 7:

[1562] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[1563] Step 8:

[1564] The server uses the generative model to generate local guide information based on the destination information. For example, it sends a request to the generative model saying, "Provide local guide information for Paris in English."

[1565] Step 9:

[1566] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[1567] Step 10:

[1568] The server integrates the flight information, accommodation information, and local guide information generated from the generative model into a single package.

[1569] Step 11:

[1570] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[1571] Step 12:

[1572] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[1573] Step 13:

[1574] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses local guide information to plan the details of their trip.

[1575] Example 1

[1576] 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."

[1577] Conventional travel planning support systems require travelers to collect flight information, accommodation information, and local tourist information individually, which is extremely time-consuming. Furthermore, because each source of information is different, it is difficult to manage them in an integrated manner. This makes it difficult for travelers to plan their trips quickly and efficiently.

[1578] 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.

[1579] In this invention, the server includes: means for acquiring candidate information based on a traveler's destination information, travel period, and preferences; a user terminal for converting the candidate information into JSON format and sending it to the server; means for acquiring flight information from an external API based on the destination information and travel period; means for acquiring accommodation information from the external API based on the destination and length of stay; means for using a generative AI model to generate local guide information based on the destination information; a server for integrating the acquired or generated information and sending the integrated information to the user terminal; and means for displaying the integrated information to the user. This allows travelers to consistently acquire flight information, accommodation information, and local guide information through a single system, enabling efficient travel planning.

[1580] "Traveller" refers to a person who plans and undertakes a trip.

[1581] "Destination Information" refers to information about places that a traveler plans to visit.

[1582] "Travel Period" refers to the period from the date a traveler begins to the date the travel ends.

[1583] "Preferences" refers to information about what a traveler wants to experience and their preferred activities during their trip.

[1584] "Candidate Information" refers to travel options to be considered that are obtained based on the traveler's destination information, travel duration, and preferences.

[1585] "User terminal" refers to an electronic device used by a traveler to enter data such as travel destination information, duration, preferences, etc.

[1586] "Server" refers to a computer system that receives and processes data sent from a user terminal.

[1587] "External API" refers to a program interface for obtaining data from a service provided by a third party.

[1588] "Flight Information" means data containing detailed information about the flight you are taking.

[1589] "Accommodation Information" refers to data containing detailed information about the accommodation where a traveler is staying.

[1590] A "generative AI model" refers to an algorithm that generates data using natural language processing techniques.

[1591] "Local guide information" refers to information about tourist attractions and recommended spots at your travel destination.

[1592] "Integrated information" refers to data that brings together flight information, accommodation information, and local guide information.

[1593] This invention is a system that efficiently supports travelers' travel planning by collecting and integrating necessary information based on specific destination information, travel period, and preferences, and providing it to users. This system is mainly realized using a user terminal, a server, an external API, and a generative AI model. Specific implementation methods for this system are described below.

[1594] System configuration

[1595] This system is broadly composed of the following components:

[1596] 1. User terminal: An electronic device that allows travelers to input information about their travel destinations, duration, and preferences. Specifically, a smartphone or PC is used.

[1597] 2. Server: Receives data sent from user terminals and acquires, generates, and integrates various information. The server is a high-performance computer that can quickly process large amounts of data.

[1598] 3. External APIs: These are APIs used to provide flight information or accommodation information, such as Flight APIs and Hotel APIs.

[1599] 4. Generative AI model: An algorithm that uses natural language processing technology to generate local guide information. For example, OpenAI's GPT-3 is used.

[1600] System action

[1601] 1. Enter your travel information

[1602] The user inputs travel destination information (e.g., "Paris"), travel period (December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants" and "cultural tourist spots") into the user terminal.

[1603] 2. Data transmission

[1604] The device converts the entered travel information into JSON format and sends it to the server via an HTTP request, generating the following JSON data, for example: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[1605] 3. Obtaining flight information

[1606] The server sends a request to an external flight API to retrieve flight information based on the itinerary and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01" to retrieve flight information.

[1607] 4. Acquisition of accommodation information

[1608] The server sends a request to an external hotel API to retrieve accommodation information based on the travel period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01" to retrieve hotel information.

[1609] 5. Generating local guide information

[1610] The server generates a prompt based on the destination information and sends it to the generative AI model. An example prompt is "Provide local guide information for Paris in English." The server receives the local guide information generated by the generative AI model.

[1611] 6. Integration and provision of information

[1612] The server aggregates the flight, accommodation, and local guide information, resulting in a JSON data stream like this: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}.

[1613] The server sends the integrated information to the user terminal, which then displays the received information to the user, who can then easily make flight and hotel reservations based on this information.

[1614] Specific examples

[1615] For example, if a user enters a travel plan such as "Paris," "December 1, 2023 to December 7, 2023," and "good restaurants and cultural tourist spots," the server will process it as follows:

[1616] 1. The server accesses the Flight API and retrieves flight information for Paris.

[1617] 2. The server accesses the hotel API and retrieves information about accommodations in Paris.

[1618] 3. The server uses the generative AI model to generate tourist information and restaurant recommendations for Paris.

[1619] Finally, the server integrates this information and sends it to the user's terminal as a single travel plan, allowing the user to efficiently make flight and hotel reservations based on this information.

[1620] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1621] Step 1: Enter your travel information

[1622] The user inputs information about the travel destination, travel period, and preferences into the user terminal. Specifically, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "good restaurants," and "cultural tourist spots."

[1623] Input: Destination information (Paris), travel period (December 1, 2023 to December 7, 2023), preferences (good restaurants, cultural attractions).

[1624] Output: Trip information stored on the user's device.

[1625] Step 2: Sending data

[1626] The device converts the entered travel information into JSON format and sends it to the server using an HTTP request. For example, the following JSON data is generated: {"destination":"Paris", "startDate":"2023-12-01", "endDate":"2023-12-07", "preferences":["good restaurants", "cultural tourist spots"]}.

[1627] Input: Trip information entered by the user.

[1628] Data processing: Convert travel information into JSON format.

[1629] Output: The generated JSON data is sent to the server.

[1630] Step 3: Get flight information

[1631] The server then sends a request to an external flight API based on the received travel information to retrieve flight information based on the travel date and destination, for example, "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01."

[1632] Input: Trip information (JSON format).

[1633] Data Computing: Accessing and requesting Flight APIs.

[1634] Output: Flight information (JSON format) retrieved from the Flights API.

[1635] Step 4: Obtaining accommodation information

[1636] The server sends a request to an external hotel API based on the travel period and destination to retrieve accommodation information, for example, "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1637] Input: Trip information (JSON format).

[1638] Data Operations: Accessing and requesting hotel APIs.

[1639] Output: Accommodation information obtained from the Hotel API (JSON format).

[1640] Step 5: Generate local guide information

[1641] The server generates a prompt sentence based on the destination information and sends it to the generative AI model. An example prompt sentence is "Provide local guide information for Paris in English." The local guide information generated by the generative AI model is then obtained.

[1642] Input: Travel destination information.

[1643] Data calculation: Prompt sentence generation and sending to the generative AI model.

[1644] Output: Local guide information obtained from the generative AI model.

[1645] Step 6: Integrate and provide information

[1646] The server combines the flight information, accommodation information, and local guide information and converts the combined information into JSON format. An example of the generated JSON data is: {"flights":[...], "hotels":[...], "guide":"You should visit the Louvre and try the local dish, coq au vin."}

[1647] Input: flight information, accommodation information, local guide information.

[1648] Data processing: Integration of each piece of information and conversion to JSON format.

[1649] Output: Consolidated information (JSON format).

[1650] Step 7: View integration information

[1651] The terminal displays the integrated information sent from the server to the user, who can then make flight and hotel reservations based on this information.

[1652] Input: Consolidated information (JSON format).

[1653] Data processing: Display of integrated information on user terminals.

[1654] Output: A set of travel plan information available to the user.

[1655] (Application example 1)

[1656] 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."

[1657] Conventional travel planning support systems are limited to providing users with information on travel destinations and accommodations, and have difficulty providing customized product information or in-store guide information for physical stores. Furthermore, they are unable to provide information based on users' preferences in real time, leaving a lack of ways to further enhance the travel experience.

[1658] 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.

[1659] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using a generative model to generate local guide information based on the destination information, means for integrating the acquired or generated information and displaying it on a user terminal, and means for providing product information and in-store guide information based on the user's preferences. This allows users to receive customized information based on their preferences in real time not only at their travel destinations but also in physical stores, significantly improving their travel and shopping experiences.

[1660] A "traveler" is an individual or group that makes travel plans based on destination information, duration, and preferences.

[1661] "Destination information" is information including the specific geographical location and name of a place that a traveler wants to visit.

[1662] "Travel period" is information about the period of time including the start and end dates of the trip that the traveler is planning.

[1663] "Preferences" refers to information that indicates the elements or conditions that a traveler is particularly interested in while traveling (e.g., good restaurants, cultural tourist spots, etc.).

[1664] "Candidate information" refers to information about multiple options obtained based on the traveler's destination information, travel period, and preferences.

[1665] "Flight information" refers to information about an airline flight, which is a traveler's means of transportation, and includes the departure point, destination, boarding time, and the like.

[1666] "Accommodation Information" means information about accommodation facilities intended for travelers' stay, including the location of the facility, fees, services provided, etc.

[1667] A "generative model" is an algorithm used to generate local guide information based on destination information, often using natural language processing techniques.

[1668] "Natural language processing technology" is a computer technology that has the ability to understand and generate human language.

[1669] "Integrated information" is information that brings together data obtained from multiple different sources.

[1670] "User terminal" refers to an electronic device that allows travelers to input and receive information, including smartphones, tablets, and personal computers.

[1671] A "server" is a computer system that receives and processes data sent from user terminals, and generates and distributes integrated information.

[1672] "Product information" refers to specific information about products and services offered in physical stores.

[1673] "In-store guide information" refers to information about product placement and recommended spots within a physical store.

[1674] The present invention is a system that provides travelers with customized information based on their travel destination information, travel period, and preferences. In addition to planning travel plans, the system can also provide product information and in-store guide information tailored to the user's preferences in brick-and-mortar stores.

[1675] System configuration

[1676] The system mainly consists of the following components:

[1677] 1. User terminal: An electronic device (e.g., a smartphone or smart glasses) through which travelers input their destination information, travel duration, and preferences.

[1678] 2. Server: Receives data sent from user terminals, acquires and generates various information, and delivers the integrated information to user terminals.

[1679] 3. External APIs: Various external services that provide flight information, accommodation information, and product information from physical stores.

[1680] 4. Generative model: An algorithm that uses natural language processing technology to generate local guide information and in-store guide information.

[1681] Explanation of program processing

[1682] 1. Enter your user information

[1683] A user wears smart glasses and enters information about their travel destination, travel duration, and preferences through the glasses, such as specific preferences like "Italian cuisine" and "modern design."

[1684] 2. Data transmission

[1685] The smart glasses convert the input information into JSON format and send it to the server via Wi-Fi or Bluetooth.

[1686] 3. Information Acquisition and Generation

[1687] The server accesses external flight and accommodation APIs to retrieve flight and hotel information based on the traveler's travel dates and destinations.

[1688] In addition, to obtain product information based on the user's preferences, the app accesses the store's external API. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian" and receives product information.

[1689] Furthermore, local guide information and in-store guide information are generated using the generative model. Specifically, information is obtained by sending prompt sentences to the generative model. For example, the prompt is "Generate guide information for Italian-themed products in a modern style."

[1690] 4. Providing integrated information

[1691] The server integrates the acquired flight information, accommodation information, product information, and guide information generated by the generative model, and sends it to the user's terminal as a single information package. The user terminal then displays this integrated information to the user.

[1692] Specific examples

[1693] For example, a user inputs the following information through smart glasses:

[1694] Travel Destination Information: Paris

[1695] Travel period: December 1, 2023 to December 7, 2023

[1696] Preferences: Italian food, modern design

[1697] The server accesses external APIs to retrieve flight information to Paris, accommodation information in Paris, and product information related to Italian cuisine. It then uses the generative model to generate tourist information about Paris and recommended Italian restaurants. Finally, the server integrates this information and displays it on the user's smart glasses.

[1698] Hardware and software used

[1699] Hardware: Smart glasses (e.g. Google Glass, Vuzix)

[1700] software:

[1701] Python 3.x

[1702] HTTP library (requests)

[1703] External API (flight information API, accommodation information API, product information API)

[1704] Natural language generation models (GPT-4, etc.)

[1705] In this way, users will be able to receive real-time, customized information not only for travel planning but also in physical stores.

[1706] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1707] Step 1:

[1708] The user inputs information about the travel destination, travel period, and preferences through the smart glasses. For example, the user inputs information such as "Paris," "December 1, 2023 to December 7, 2023," "Italian cuisine, modern design." This information is collected by the smart glasses application.

[1709] Input: Destination information, travel period, preferences

[1710] Output: User's travel information (JSON format)

[1711] Step 2:

[1712] The user device (smart glasses) converts the input information into JSON format and sends it to the server via an HTTP request. Specifically, the data is sent to the server via Wi-Fi or Bluetooth.

[1713] Input: User's travel information (JSON format)

[1714] Output: Trip information sent to the server

[1715] Step 3:

[1716] The server analyzes the received travel information and retrieves flight information by sending a request to an external API. For example, to retrieve flight information for Paris, it sends a request to "https: / / api.flightinfo.com / flights?dest=Paris&date=2023-12-01".

[1717] Input: Travel information (destination, travel period)

[1718] Output: Flight information

[1719] Step 4:

[1720] The server then accesses an external hotel information API to obtain hotel information in Paris, for example, by sending a request to "https: / / api.hotelinfo.com / hotels?dest=Paris&date=2023-12-01".

[1721] Input: Travel information (destination, travel period)

[1722] Output: Accommodation information

[1723] Step 5:

[1724] The server sends a request to an external product information API to retrieve product information from physical stores based on the user's preferences. For example, it sends a request to "https: / / api.storeproducts.com / products?type=italian".

[1725] Input: User Preferences

[1726] Output: Product information

[1727] Step 6:

[1728] The server generates local guide information and in-store guide information using the generative model. Specifically, it generates a prompt sentence, "Generate guide information for Italian-themed products in a modern style," and sends it to the generative model, which uses natural language processing technology.

[1729] Input: Destination information, user preferences

[1730] Output: Local guide information, in-store guide information

[1731] Step 7:

[1732] The server integrates the acquired flight information, accommodation information, product information, and generated guide information, and sends the integrated information as a single package to the user's terminal.The server converts the integrated information into JSON format and sends it to the user's terminal via an HTTP response.

[1733] Input: Flight information, accommodation information, product information, guide information

[1734] Output: Consolidated information (JSON format)

[1735] Step 8:

[1736] The user terminal (smart glasses) analyzes the integrated information received from the server and visually displays it to the user, allowing the user to view customized travel and shopping information in real time.

[1737] Input: Integrated information (JSON format)

[1738] Output: Customized information displayed to the user visually

[1739] 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.

[1740] The present invention provides a more personalized travel experience by combining a system that consistently supports travelers' travel planning with an emotion engine that recognizes user emotions. Specific examples of the system are described below.

[1741] System configuration

[1742] The system mainly consists of the following components:

[1743] 1. User terminal: An electronic device (e.g., a smartphone or PC) through which travelers input their travel destination information, duration, and preferences, and which also has a built-in emotion engine that recognizes the user's emotions.

[1744] 2. Server: Receives data sent from the user device, acquires and generates various information, and finally integrates it. It also receives the output of the emotion engine and reflects it in the generation of information.

[1745] 3. External APIs: Various external services that provide flight and accommodation information.

[1746] 4. Generative model: An algorithm that generates local guide information using natural language processing technology. The output of the emotion engine is used to dynamically adjust the local guide information.

[1747] Program processing

[1748] 1. Enter your travel information

[1749] The user inputs travel destination information (e.g., "Paris"), travel period (e.g., December 1, 2023 to December 7, 2023), and preferences (e.g., "good restaurants," "cultural tourist spots") into the user terminal.

[1750] At the same time, the emotion engine built into the user terminal analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions.

[1751] 2. Data transmission

[1752] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server via an HTTP POST request.

[1753] 3. Obtaining flight information

[1754] The server accesses an external flight API to retrieve flight information based on the user's travel date and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1755] 4. Acquisition of accommodation information

[1756] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1757] 5. Generating local guide information

[1758] The server uses a generative model based on natural language processing technology to generate local guide information based on destination information and the user's recognized emotion data. For example, if the user is feeling stressed, it will suggest relaxing places and activities, and if the user is excited, it will suggest new experiences and challenging activities.

[1759] 6. Providing integrated information

[1760] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model, and transmits the integrated information as a single package to the user terminal, which then displays the integrated information to the user.

[1761] Specific examples

[1762] For example, a user enters the following travel itinerary:

[1763] Destination: Paris

[1764] Travel period: December 1, 2023 to December 7, 2023

[1765] Preferences: Good restaurants, cultural tourist spots

[1766] At the same time, the emotion engine of the user terminal recognizes the user's emotion as “feeling stressed.” The user terminal transmits this information to the server, which processes it as follows:

[1767] Get flight information to Paris from the Flights API.

[1768] Get accommodation information in Paris from the Hotel API.

[1769] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[1770] Finally, the server aggregates these data and displays it as a single itinerary on the user's device, allowing the user to easily book flights and hotels and enjoy a trip that includes stress-reducing activities.

[1771] The processing flow will be explained below.

[1772] Step 1:

[1773] The user inputs information about the travel destination, duration, and preferences into the terminal. For example, the user inputs "Paris" as the travel destination, "December 1, 2023 to December 7, 2023" as the travel duration, and "good restaurants" and "cultural tourist spots" as preferences.

[1774] Step 2:

[1775] The emotion engine built into the user device analyzes the user's facial expressions, voice tone, or input text information to recognize the user's emotions. For example, if the user is smiling, it will recognize that they are "having fun," and if they are frowning, it will recognize that they are "feeling stressed."

[1776] Step 3:

[1777] The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[1778] Step 4:

[1779] The server receives the data sent from the terminal, which includes the user's destination information, travel period, preferences, and emotion data.

[1780] Step 5:

[1781] The server accesses an external flight API to retrieve flight information based on the user's travel dates and destination, for example, by sending a request to "https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01".

[1782] Step 6:

[1783] The server parses the response received from the Flights API and extracts the required flight information (e.g., flight number, departure and arrival times, airline, etc.).

[1784] Step 7:

[1785] The server accesses an external hotel API and retrieves accommodation information based on the user's stay period and destination. For example, it sends a request to "https: / / api.hotelapi.com / hotels?dest=Paris&date=2023-12-01".

[1786] Step 8:

[1787] The server analyzes the response received from the hotel API and extracts the necessary accommodation information (e.g., hotel name, location, price, facilities, etc.).

[1788] Step 9:

[1789] The server uses the generative model to generate local guide information based on the destination information and the user's recognized emotion data. For example, if the user's emotion is recognized as "stressed," the server suggests relaxing places and activities. The server sends a request to the generative model saying, "Generate local guide information for Paris that includes relaxing activities."

[1790] Step 10:

[1791] The generative model generates local guide information and returns it to the server, including tourist attractions, recommended restaurants, and local cultural events.

[1792] Step 11:

[1793] The server integrates the acquired flight information, accommodation information, and local guide information generated from the generative model into a single package.

[1794] Step 12:

[1795] The server converts the integrated information into JSON format and sends it to the user's device. Specifically, it creates an HTTP response and sends data including the travel plan.

[1796] Step 13:

[1797] The terminal analyzes the integrated information received from the server and displays it to the user, who can then proceed with booking flights and hotels based on this information.

[1798] Step 14:

[1799] The user reviews the displayed information and makes flight and hotel reservations as needed, and also uses the local guide information to plan the details of their trip, for example booking a massage or spa treatment to relieve stress.

[1800] Example 2

[1801] 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."

[1802] Conventional travel planning support systems were able to provide information based on a traveler's destination and preferences, but they were unable to take into account the traveler's emotions, making it difficult to make optimal suggestions for each individual traveler. Furthermore, they lacked a means to integrate the acquired information and provide it to travelers in an easy-to-understand manner, resulting in a lack of convenience for travelers.

[1803] 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.

[1804] In this invention, the server includes means for acquiring candidate information based on the traveler's destination information, travel period, and preferences, means for acquiring flight information corresponding to the candidate information, means for acquiring accommodation information corresponding to the candidate information, means for using an emotion engine to analyze the traveler's emotions, means for using a generative model to generate local guide information based on the destination information and emotion data, and means for integrating the acquired or generated information and transmitting it to a user terminal in JSON format for display. This makes it possible to propose more personalized travel plans that take the traveler's emotions into consideration, and to provide the traveler with more appropriate and easy-to-understand information.

[1805] A "traveler" is someone who plans a travel destination and travel period and acts accordingly.

[1806] "Destination Information" refers to information about a location that a traveler intends to visit.

[1807] "Travel Period" means the period between the start and end dates for which a Traveler plans to travel.

[1808] "Preferences" refer to the specific experiences and interests that travelers seek while traveling.

[1809] "Candidate information" refers to information on various options obtained based on the traveler's destination information, travel period, and preferences.

[1810] "Flight Information" means detailed information about a flight taken by a traveler.

[1811] "Accommodation Information" means detailed information about accommodations for travelers to stay at.

[1812] An "emotion engine" refers to software or hardware functions that analyze and recognize a user's emotions.

[1813] A "generative model" refers to an algorithm that uses natural language processing techniques to generate specific information based on input data.

[1814] "Integration" refers to bringing together different types or multiple pieces of information into one.

[1815] "User terminal" refers to the electronic device used by a traveler to enter information and view results.

[1816] The present invention is a system that provides individual support for travellers' travel plans, and provides a more personalized travel experience by combining it with an emotion engine that recognises the traveller's emotions. Specific embodiments of the system are described below.

[1817] Hardware and Software Configuration

[1818] 1. User Device:

[1819] Hardware used: Smartphone or PC

[1820] Software used: Emotion engine (e.g., a general emotion recognition API)

[1821] 2. Server:

[1822] Hardware used: Cloud server (e.g., general cloud service)

[1823] Software used: External APIs (e.g., general flight information APIs, accommodation information APIs) and natural language processing technologies (e.g., general natural language processing algorithms)

[1824] Program processing

[1825] 1. The user enters information about their travel destination using a smartphone or computer. For example, they enter Paris as their destination, the travel period from December 1, 2023 to December 7, 2023, and their preferences for "good restaurants" and "cultural tourist spots."

[1826] 2. The device activates its built-in emotion engine, which analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions. For example, it determines that the user is feeling stressed.

[1827] 3. The device converts the input travel information and recognized emotion data into JSON format and sends it to the server using an HTTP POST request.

[1828] 4. The server analyzes the received data and sends a request to an external flight information API based on the travel date and destination to retrieve the required flight information. For example, to retrieve flight information for Paris.

[1829] 5. The server then sends a request to an external accommodation information API to retrieve the required accommodation information. For example, to retrieve accommodation information for Paris.

[1830] 6. The server uses the generative AI model to generate local guide information based on the destination information and emotion data. For example, if the user is feeling stressed, the server uses the following prompt to generate guide information including information on relaxation spots and spas:

[1831] Travel Planning Information:

[1832] Destination: Paris

[1833] Travel period: December 1, 2023 to December 7, 2023

[1834] Preferences: Good restaurants, cultural attractions

[1835] User Emotions: Stressed

[1836] Based on the above information, please generate local guide information that will help users relax.

[1837] 7. The server integrates the acquired flight information, accommodation information, and generated local guide information, and sends it as a package to the user's device. The user's device displays the integrated information to the user.

[1838] In this way, the system of the present invention can recognize the emotions of travelers and provide personalized travel information based on those emotions, thereby enabling travelers to plan trips with greater satisfaction.

[1839] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1840] Step 1:

[1841] Users input their travel information, such as destination, travel duration, and preferences, using their smartphone or computer. This input information includes data such as:

[1842] Destination: Paris

[1843] Travel period: December 1, 2023 to December 7, 2023

[1844] Preferences: Good restaurants, cultural tourist spots

[1845] Based on the input, the device activates its built-in emotion engine to analyze the user's facial expression, voice tone, and text information. For example, if the user's facial expression is tense, the emotion engine will recognize it as "feeling stressed" and output it as emotion data.

[1846] Step 2:

[1847] The device converts the travel information and recognized emotion data into JSON format. The specific input for this data conversion is as follows:

[1848] Travel information

[1849] Emotional data (e.g., "I feel stressed")

[1850] Example output in JSON format:

[1851] json

[1852] {

[1853] "destination": "Paris",

[1854] "travel_period": {

[1855] "start_date": "2023-12-01",

[1856] "end_date": "2023-12-07"

[1857] },

[1858] "preferences": ["good restaurants", "cultural tourist spots"],

[1859] "user_emotion": "stress"

[1860] }

[1861] The device sends this JSON formatted data to the server using an HTTP POST request.

[1862] Step 3:

[1863] The server analyzes the received data, specifically extracting travel itinerary and destination information.

[1864] input:

[1865] Travel information (JSON format)

[1866] The server then accesses an external flight information API and sends a request to retrieve the flight information.

[1867] Example API request:

[1868] http

[1869] GET https: / / api.flightapi.com / flights?dest=Paris&date=2023-12-01

[1870] output:

[1871] Flight information (flight number, departure time, arrival time, airline name, etc.)

[1872] Step 4:

[1873] The server similarly analyzes the received data and accesses external accommodation information APIs based on the travel destination and length of stay.

[1874] input:

[1875] Travel information (JSON format)

[1876] The server sends a request to the following URL to obtain accommodation information:

[1877] Example API request:

[1878] http

[1879] GET https: / / api.hotelapi.com / hotels?dest=Paris&checkin=2023-12-01&checkout=2023-12-07

[1880] output:

[1881] Accommodation information (hotel name, location, price, availability, etc.)

[1882] Step 5:

[1883] The server uses the generative AI model to generate local guide information.

[1884] input:

[1885] Destination information

[1886] Emotional Data

[1887] Preferences

[1888] The server inputs the following prompt sentence into the generative AI model to generate local guide information.

[1889] text

[1890] Travel Planning Information:

[1891] Destination: Paris

[1892] Travel period: December 1, 2023 to December 7, 2023

[1893] Preferences: Good restaurants, cultural attractions

[1894] User Emotions: Stressed

[1895] Based on the above information, please generate local guide information that will help users relax.

[1896] output:

[1897] Local guide information (relaxing places, spas, etc.)

[1898] Step 6:

[1899] The server integrates the acquired flight information, accommodation information, and generated local guide information.

[1900] input:

[1901] Flight information

[1902] Accommodation information

[1903] Local guide information

[1904] The integrated data is converted into JSON format and sent to the user's terminal.

[1905] Example output:

[1906] json

[1907] {

[1908] "flights": [

[1909] {

[1910] "flight_number": "AF123",

[1911] "departure_time": "2023-12-01T10:00:00",

[1912] "arrival_time": "2023-12-01T12:00:00",

[1913] "airline": "Air France"

[1914] }

[1915] ],

[1916] "hotels": [

[1917] {

[1918] "name": "Hotel du Louvre",

[1919] "location": "Centre of Paris",

[1920] "price": "200€ / night",

[1921] "availability": "Available"

[1922] }

[1923] ],

[1924] "guide": [

[1925] {

[1926] "activity": "Spa in Paris",

[1927] "description": "A great relaxing spa"

[1928] }

[1929] ]

[1930] }

[1931] The device analyzes the received data and displays it to the user, for example, by providing an app interface with flight information, accommodation information, and local guide information in an easy-to-read layout, allowing users to easily make reservations and plans.

[1932] (Application example 2)

[1933] 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."

[1934] Personalizing travel plans has become increasingly important for travelers to enhance their local experiences. However, conventional travel planning support systems have difficulty providing personalized travel suggestions that reflect the user's emotional state, limiting their ability to alleviate stress and inconvenience during travel. Furthermore, they have not offered suggestions for stores or services based on real-time emotions, and therefore have not been able to fully meet travelers' needs.

[1935] 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 recognizing the traveler's emotions and generating local guide information based on the emotions, means for dynamically adjusting store information based on the emotions in real time, and means for displaying the integrated information on the user terminal. This makes it possible to make personalized travel suggestions according to the traveler's emotional state, allowing the traveler to have a comfortable and satisfying experience in the local area.

[1936] "Tourist destination information" is information about the place that the traveler intends to visit.

[1937] "Travel period" is information about the period from the start date to the end date of a traveler's planned trip.

[1938] "Preferences" are information about the activities a traveler wants to experience at their destination and the categories of interest they have.

[1939] The "means for obtaining candidate information" refers to a means for collecting relevant travel destination and activity candidates based on the destination information, travel period, and preferences input by the traveler.

[1940] The "means for obtaining flight information" is a means for obtaining information on available flights based on the traveler's destination and travel period.

[1941] The "means for obtaining accommodation information" refers to a means for obtaining information on available accommodations based on the traveler's destination and travel period.

[1942] The "means for using a generative model" is a model used to generate local guide information based on the traveler's destination information and other related information.

[1943] The "means for integrating and displaying on the user terminal" is a means for integrating the acquired flight information, accommodation information, and generated local guide information and displaying them on the user's terminal.

[1944] The "means for recognizing user emotions" is a means for analyzing the facial expressions, voice, and input text of the traveler to recognize the emotional state of the traveler at that time.

[1945] The "means for dynamically adjusting local guide information based on emotions" refers to a means for appropriately changing local guide information based on the recognized emotional state of the traveler, and providing more appropriate information.

[1946] The "means for displaying emotion-based recommended store information in real time" is a means for providing appropriate store and service information in real time, taking into account the emotional state of the traveler, and displaying it on the user's terminal.

[1947] To implement this invention, a system including a user terminal, a server, an emotion recognition engine, a generative model, and a display interface is required.

[1948] System configuration

[1949] User terminal

[1950] The user terminal consists of a device such as a smartphone or smart glasses, and is equipped with an emotion engine that recognizes the traveler's emotions. Users can input their travel destination, duration, and preferences.

[1951] The emotion engine analyzes the user's facial expressions, voice tone, and input text information to recognize the user's emotions in real time, making it possible to grasp various emotions such as stress and excitement during the trip.

[1952] server

[1953] The server receives the data sent by the user, retrieves the necessary flight and accommodation information through an external API, receives the output of the emotion recognition engine, and dynamically generates local guide information using a generative model.

[1954] The server uses the following methods:

[1955] 1. How to receive travel information

[1956] 2. Means of receiving emotion recognition data

[1957] 3. How to access external APIs

[1958] 4. Guide Information Generation Method Using Generative Model

[1959] 5. Means of transmitting integrated data to user terminals

[1960] Emotion Recognition Engine

[1961] The emotion recognition engine analyzes the user's emotional state in real time. This includes camera input (facial expression recognition) and microphone input (voice analysis). Specifically, it identifies the user's emotions using a facial expression analysis algorithm and a voice tone analysis engine, and sends the results in JSON format to the server.

[1962] Generative Model

[1963] The generative model uses natural language processing technology to generate personalized local guide information based on the user's emotional data and destination information. For example, if the user is feeling stressed, it will suggest places to relax, and if the user is excited, it will suggest places that offer new experiences. This generative model dynamically generates information based on data obtained from external APIs and data from an emotion recognition engine.

[1964] Display Interface

[1965] The user terminal is equipped with an interface for displaying the integrated information, which can provide links to booking procedures and additional information, helping users to smoothly plan their trip.

[1966] Specific examples

[1967] For example, a user enters the following travel itinerary through smart glasses:

[1968] Destination: Paris

[1969] Travel period: December 1, 2023 to December 7, 2023

[1970] Preferences: Good restaurants, cultural tourist spots

[1971] At the same time, the emotion recognition engine identifies the user's emotion as "stressed." The server receives this information and processes it as follows:

[1972] Get flight information to Paris from the Flights API.

[1973] Get accommodation information in Paris from the Hotel API.

[1974] Using a generative model, we generate guide information focusing on relaxation spots and spas in Paris.

[1975] This information is integrated and displayed on the user's device, allowing travelers to receive the optimal travel plan based on their emotions and enjoy a comfortable and stress-free travel experience.

[1976] Prompt Sentence Examples

[1977] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[1978] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1979] Step 1:

[1980] A user inputs travel destination information, travel duration, and preferences into a device (such as smart glasses or a smartphone). The input data includes the destination (e.g., Paris), travel duration (date range), and activities and interests they would like to experience at the destination. This obtains basic information about the trip.

[1981] Step 2:

[1982] The emotion engine built into the device uses the camera and microphone to analyze the user's facial expressions and voice in real time. The input data is the video from the camera and the audio from the microphone. Based on this data, the emotion engine recognizes the user's emotions (e.g., stress, excitement, relief) and generates emotion data.

[1983] Step 3:

[1984] The device converts the travel information entered in step 1 and the emotion data generated in step 2 into JSON format and sends it to the server via an HTTP POST request, which causes the server to receive the user's travel information and emotion information.

[1985] Step 4:

[1986] The server sends a request to an external API (e.g., a service that provides flight and accommodation information) based on the received travel information and emotion data. The server retrieves appropriate flight and accommodation information based on the travel destination and duration. This collects basic information necessary for the user's trip.

[1987] Step 5:

[1988] The server integrates flight and accommodation information obtained from external APIs with emotion data and generates local guide information using a generative model. The generative model uses natural language processing technology to generate guide information tailored to the traveler based on the user's destination information and emotion data. For example, if the user is feeling stressed, it generates guide information suggesting places and services where they can relax.

[1989] Step 6:

[1990] The server then combines the generated local guide information, flight information, and accommodation information and sends it to the user's device as a single package, allowing the user to view all travel information in an integrated manner.

[1991] Step 7:

[1992] The terminal receives the integrated information sent from the server and displays it on the interface. The user can view the displayed travel information and access links to make reservations or get additional information as needed, making it easier for the user to plan their trip.

[1993] Prompt Sentence Examples

[1994] "Generate information to recommend relaxing cafes and spas in a shopping mall near Tokyo Station where the user's emotions indicate stress."

[1995] 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.

[1996] 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.

[1997] 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.

[1998] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1999] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2000] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[2001] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[2002] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[2003] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[2004] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[2005] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[2006] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[2007] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[2008] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[2009] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[2010] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[2011] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[2012] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[2013] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[2014] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[2015] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[2016] The following is further disclosed regarding the above embodiment.

[2017] (Claim 1)

[2018] means for obtaining candidate information based on the traveler's destination information, travel period and preferences;

[2019] means for acquiring flight information corresponding to the candidate information;

[2020] a means for acquiring accommodation facility information corresponding to the candidate information;

[2021] a means for using a generative model to generate local guide information based on the destination information;

[2022] means for integrating the acquired or generated information and displaying it on a user terminal;

[2023] A system including:

[2024] (Claim 2)

[2025] The system according to claim 1, wherein the generative model for providing the local guide information uses natural language processing technology.

[2026] (Claim 3)

[2027] 2. The system according to claim 1, wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information.

[2028] "Example 1"

[2029] (Claim 1)

[2030] means for obtaining candidate information based on the traveler's destination information, travel period and preferences;

[2031] a user terminal that converts the candidate information into a JSON format and transmits the converted information to a server;

[2032] means for acquiring flight information from an external API based on the destination information and travel period;

[2033] means for obtaining accommodation information from an external API based on the destination and length of stay;

[2034] A means for using a generation AI model to generate local guide information based on the destination information;

[2035] a server that integrates the acquired or generated information and transmits the integrated information to a user terminal;

[2036] means for displaying the integrated information to a user;

[2037] A system including:

[2038] (Claim 2)

[2039] The system according to claim 1, wherein the generation AI model that generates the local guide information uses natural language processing technology.

[2040] (Claim 3)

[2041] 2. The system according to claim 1, wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information.

[2042] "Application Example 1"

[2043] (Claim 1)

[2044] means for obtaining candidate information based on the traveler's destination information, travel period and preferences;

[2045] means for acquiring flight information corresponding to the candidate information;

[2046] a means for acquiring accommodation facility information corresponding to the candidate information;

[2047] a means for using a generative model to generate local guide information based on the destination information;

[2048] means for integrating the acquired or generated information and displaying it on a user terminal;

[2049] A means for providing product information and in-store guide information based on the user's preferences;

[2050] A system including:

[2051] (Claim 2)

[2052] The system according to claim 1, wherein the generative model for providing the local guide information and in-store guide information uses natural language processing technology.

[2053] (Claim 3)

[2054] The system of claim 1, wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information, and displays customized product information based on the user's preferences in the store.

[2055] "Example 2: Combining Emotion Engines"

[2056] (Claim 1)

[2057] means for obtaining candidate information based on the traveler's destination information, travel period and preferences;

[2058] means for acquiring flight information corresponding to the candidate information;

[2059] a means for acquiring accommodation facility information corresponding to the candidate information;

[2060] a means for using an emotion engine to analyze the emotions of the traveler;

[2061] a means for using a generative model to generate local guide information based on the destination information and emotion data;

[2062] A means for integrating the acquired or generated information and transmitting and displaying it in JSON format on a user terminal;

[2063] A system including:

[2064] (Claim 2)

[2065] The system according to claim 1, wherein the generative model for providing the local guide information uses natural language processing technology.

[2066] (Claim 3)

[2067] 2. The system according to claim 1, wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information.

[2068] "Application example 2 when combining emotion engines"

[2069] (Claim 1)

[2070] means for obtaining candidate information based on the traveler's destination information, travel period and preferences;

[2071] means for acquiring flight information corresponding to the candidate information;

[2072] a means for acquiring accommodation facility information corresponding to the candidate information;

[2073] a means for using a generative model to generate local guide information based on the destination information;

[2074] means for integrating the acquired or generated information and displaying it on a user terminal;

[2075] means for recognizing a user's emotion and dynamically adjusting local guide information based on the emotion;

[2076] A means for displaying real-time emotion-based store recommendation information;

[2077] A system including:

[2078] (Claim 2)

[2079] The system according to claim 1, wherein the generation model for providing the local guide information and recommended store information uses natural language processing technology.

[2080] (Claim 3)

[2081] 2. The system according to claim 1, wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information and recommended store information. [Explanation of symbols]

[2082] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for obtaining candidate information based on the traveler's destination information, travel period and preferences; means for acquiring flight information corresponding to the candidate information; a means for acquiring accommodation facility information corresponding to the candidate information; a means for using a generative model to generate local guide information based on the destination information; means for integrating the acquired or generated information and displaying it on a user terminal; A system including:

2. The system according to claim 1 , wherein the generation model for providing the local guide information uses natural language processing technology.

3. The system according to claim 1 , wherein the user terminal displays an interface that provides links to reservation procedures and additional information based on the integrated information.

Images