system

Abstract

We provide the system. [Solution] A means for collecting user input information such as travel destination, mood, leisure activities, desired food, budget, etc. A means of sending the collected user input information to the server, A means for generating an optimal travel plan using generative artificial intelligence based on user input information, A means of sending the generated travel plan to the terminal, A means of displaying the submitted travel plan to the user, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern travel planning, there are diverse options and a vast amount of information on the Internet, and travelers require a lot of time and effort to judge and select the most suitable travel plan for themselves. Therefore, there is a need for a system that can easily propose an optimal travel plan for travelers based on their travel purposes and wishes. Also, a system that can easily make selections according to budgets and preferences is necessary.

Means for Solving the Problems

[0005] The system provides a means for collecting user input information such as travel destination, mood, leisure activities, desired meals, and budget. It includes a means for transmitting the collected user input information to a server and a means for generating an optimal travel plan using generative artificial intelligence based on the user's input information. The system solves the problem by including a means for transmitting the generated travel plan to the terminal and a means for displaying the transmitted travel plan to the user. Furthermore, it builds a system that provides an optimal travel plan that meets the user's needs by generating a travel plan using an external database and selecting the best restaurants, tourist destinations, and accommodations within the budget.

[0006] A "travel destination" is a destination that the user wishes to visit.

[0007] "Mood" refers to the feelings and experiences that users want to feel during their trip.

[0008] "Leisure" refers to activities and sightseeing enjoyed during a trip.

[0009] "Desired food" refers to specific dishes or foods that a user hopes to eat while traveling.

[0010] "Budget" refers to the range of money a user plans to spend on their trip.

[0011] "User input information" refers to data that includes various conditions and preferences related to travel.

[0012] "Generative artificial intelligence" refers to systems and algorithms that create optimal travel plans based on user input.

[0013] A "travel plan" refers to a specific travel schedule and list of places to visit that are proposed based on the user's wishes and preferences.

[0014] "External database" refers to a data source that exists on the Internet or within other systems and holds information related to travel.

[0015] "Terminal" refers to an electronic device or apparatus through which a user makes inputs and receives results.

Brief Explanation of Drawings

[0016] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing apparatus and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

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

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

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

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

[0021] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. The following describes the program processing of this system and a specific example in natural language.

[0038] System Overview

[0039] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external database.

[0040] Program Processing Description

[0041] 1. Collection of input information

[0042] The user enters detailed information such as their travel destination, mood, leisure activities, desired food, and budget on the application screen.

[0043] The device collects and temporarily stores information entered by the user.

[0044] 2. Sending data

[0045] The terminal sends the collected user input information to the server.

[0046] The server analyzes the received data and interprets the user's request.

[0047] 3. Information Analysis and Plan Generation

[0048] The server searches external databases based on user input and collects relevant travel information.

[0049] Generative artificial intelligence uses collected data to generate travel plans that are optimal for the user's needs. Specifically, it selects the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired cuisine, and leisure activities.

[0050] 4. Sending and displaying plans

[0051] The server sends the generated travel plan to the device.

[0052] The device displays the received travel plan to the user.

[0053] Specific example

[0054] User input information

[0055] The user enters "Tokyo," "relax," "feel nature," "sushi," and "budget of 50,000 yen."

[0056] Example of plan generation

[0057] 1. Restaurant Search

[0058] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants that meet the criteria of being located in "Tokyo" and serving "sushi."

[0059] 2. Search for tourist destinations

[0060] The server uses the TriPad® visor API and the Google Maps API to list multiple tourist destinations rich in nature, based on the conditions of being "Tokyo" and "experiencing nature."

[0061] 3. Search for accommodations

[0062] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[0063] 4. Creating a travel plan

[0064] The generative artificial intelligence will create a specific schedule for days 1 through 3 based on the above conditions. For example, on day 1, it might have dinner at a sushi restaurant in Ginza; on day 2, it might visit Ueno Zoo and have a sushi lunch; and on day 3, it might visit Senso-ji Temple and select accommodation.

[0065] Suggestions for users

[0066] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[0067] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0068] The following describes the processing flow.

[0069] Step 1:

[0070] The user enters detailed travel information. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, and budget from text boxes or dropdown menus on the application screen.

[0071] Step 2:

[0072] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user in variables or data storage.

[0073] Step 3:

[0074] The device converts the collected information into JSON or XML format and sends it to the server. Specifically, it sends the data to the server using HTTP requests.

[0075] Step 4:

[0076] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables.

[0077] Step 5:

[0078] The server searches an external database to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist attraction information, and accommodation information from the external database.

[0079] Step 6:

[0080] Based on data acquired by the server, generative artificial intelligence is used to generate the optimal travel plan. Specifically, the user's input information and acquired data are passed to an algorithm, which selects restaurants, tourist destinations, and accommodations that meet the criteria, and then creates a travel schedule.

[0081] Step 7:

[0082] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to send the data back to the device.

[0083] Step 8:

[0084] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format.

[0085] Step 9:

[0086] Users review the proposed plan and, if necessary, view further details or proceed with the booking process. Specifically, links are set up in each plan section, so that clicking them opens the booking site or detailed information page.

[0087] (Example 1)

[0088] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0089] Traditional travel planning systems require users to individually gather information and create their own plans, which is very time-consuming. Furthermore, if the collected information is insufficient, it becomes difficult to create an optimal travel plan. Thus, there is a challenge in that it is difficult for users to easily obtain high-quality travel plans.

[0090] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0091] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure, meals, and budget; means for transmitting the collected user input information to an information processing device; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan to a display device; and means for displaying the transmitted travel plan to the user. This makes it possible for users to easily and quickly obtain a high-quality, optimal travel plan.

[0092] A "travel destination" refers to a geographical location that the user wishes to visit.

[0093] "Mood" refers to the user's hopes and desires regarding their mental state and atmosphere during their trip.

[0094] "Leisure" refers to the activities and recreation that users want to enjoy while traveling.

[0095] "Meals" refers to the dishes and foods that the user wants to eat during their trip.

[0096] "Budget" refers to the amount of money a user plans to spend on a trip.

[0097] A "user" is someone who intends to use a travel plan.

[0098] "Input information" refers to the detailed travel information that the user provides to the system.

[0099] An "information processing device" is a device used to process data collected from users.

[0100] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate results based on specific input data.

[0101] A "travel plan" refers to suggestions and schedules related to a user's trip.

[0102] A "display device" is a device used to display the generated travel plan to the user.

[0103] A "data repository" is a database or API used to retrieve information from external sources in order to generate travel plans.

[0104] A "food and beverage establishment" refers to a shop or restaurant where users eat.

[0105] A "tourist attraction" refers to a tourist destination or landmark that users should visit.

[0106] "Accommodation facilities" refer to hotels, guesthouses, and other accommodations where users can stay.

[0107] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. This system includes several main components. Specific embodiments are described below.

[0108] System Overview

[0109] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external data repository.

[0110] Collect input information

[0111] The user enters detailed information such as travel destination, mood, leisure activities, meals, and budget through the application screen. For example, consider a case where the user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," and "Budget of 50,000 yen."

[0112] The device collects and temporarily stores information entered by the user. This typically involves using the local storage of a mobile device or PC. The device then converts the stored information into JSON format to facilitate subsequent data transmission and analysis.

[0113] Data transmission and analysis

[0114] The terminal sends the collected user input information to the server. Here, the data is transmitted securely using the HTTPS protocol. The server analyzes the received data and interprets the user's requests. Specifically, the data is temporarily stored in a database (e.g., MySQL®) and then analyzed.

[0115] Use of external data repositories

[0116] Based on the user's requests, the server searches external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and collects relevant travel information. For example, using the conditions "Tokyo" and "sushi," it retrieves data on highly-rated sushi restaurants using the Tabelog API. Similarly, using the conditions "Tokyo" and "experience nature," it retrieves data on tourist destinations rich in nature using the TripAdvisor API.

[0117] Travel plan generation

[0118] The server passes the collected data to the generative artificial intelligence (AI). Specifically, it inputs JSON data as prompts into the AI. The AI ​​then generates the optimal travel plan based on the input data. For example, the prompts can be set as follows:

[0119] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[0120] Proposed plan:

[0121] Day 1: Dinner at a sushi restaurant in Ginza

[0122] Day 2: Ueno Zoo and sushi lunch

[0123] Day 3: Visit to Senso-ji Temple and accommodation

[0124] Generative artificial intelligence generates and proposes travel plans that are best suited to the user's needs.

[0125] Sending and displaying plans

[0126] The server sends the generated travel plan to the device. Typically, an HTTP POST request is used for this transmission. The device then displays the received travel plan on the application screen. A user interface (e.g., an application using React or Flutter®) is often used here.

[0127] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[0128] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0129] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0130] Step 1: Collecting input information

[0131] Users enter detailed information such as their travel destination, mood, leisure activities, meals, and budget through the application screen.

[0132] Input: Detailed travel information entered by the user (e.g., "Tokyo", "Relax", "Experience nature", "Sushi", "Budget 50,000 yen")

[0133] Output: Collected user input information

[0134] The device temporarily stores the information entered by the user.

[0135] Operation: Saves data to the local storage of mobile devices or PCs.

[0136] The device converts the saved information into JSON format.

[0137] Operation: Converts input information into JSON format data to prepare for subsequent processing.

[0138] Step 2: Send

[0139] The terminal sends the collected user input information to the server.

[0140] Operation: Securely transmits data using the HTTPS protocol.

[0141] Input: User input information converted to JSON format

[0142] Output: User input information sent to the server

[0143] The server analyzes the received data and interprets the user's request.

[0144] Operation: Data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[0145] Input: User input information in JSON format received

[0146] Output: Information on analyzed user requests

[0147] Step 3: Using an external data repository

[0148] Based on the user's requests, the server searches external data repositories and collects relevant travel information.

[0149] Operation: Sends requests to external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and retrieves the necessary information.

[0150] Input: Information about the analyzed user requests

[0151] Output: Travel information retrieved from an external data repository

[0152] Specific example:

[0153] The server uses the Tabelog API to retrieve data on highly-rated sushi restaurants based on the conditions "Tokyo" and "sushi".

[0154] The server uses the TripAdvisor API to retrieve data on tourist destinations rich in nature, based on the conditions of "Tokyo" and "experiencing nature."

[0155] Step 4: Creating a travel plan

[0156] The server passes the collected data to a generative artificial intelligence.

[0157] Operation: Inputs JSON formatted data as a prompt into a generative artificial intelligence system.

[0158] Input: Travel information retrieved from an external data repository

[0159] Output: Travel plan generated by generative artificial intelligence

[0160] Generative artificial intelligence generates the optimal travel plan based on input data.

[0161] Specific example:

[0162] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[0163] Proposed plan:

[0164] Day 1: Dinner at a sushi restaurant in Ginza

[0165] Day 2: Ueno Zoo and sushi lunch

[0166] Day 3: Visit to Senso-ji Temple and accommodation

[0167] Step 5: Submit and view your plan

[0168] The server sends the generated travel plan to the device.

[0169] Operation: Sends travel plans using an HTTP POST request.

[0170] Input: Travel plan generated by a generative artificial intelligence system

[0171] Output: Travel plan sent to the terminal

[0172] The device displays the received travel plan to the user.

[0173] Operation: Displays travel plans through a user interface (e.g., an application using React or Flutter).

[0174] Input: Travel plan sent from the server

[0175] Output: Travel plan displayed to the user

[0176] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[0177] (Application Example 1)

[0178] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0179] When planning a trip, it is time-consuming and burdensome for users to manually gather a lot of information and create a plan. Furthermore, there is a lack of means to provide real-time information during the trip, making it difficult to obtain local navigation and recommendations.

[0180] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0181] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure activities, desired meals, and budget; means for transmitting the collected user input information to the server; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan and real-time information to the user device; and means for displaying the transmitted travel plan and real-time information to the user and providing navigation and additional information. As a result, the user can efficiently and easily plan a trip and obtain necessary information in real time while traveling.

[0182] "User device" is a general term for terminal devices used by users, and includes smartphones, tablets, smart glasses, etc.

[0183] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates the optimal travel plan based on user input.

[0184] A "travel plan" refers to a detailed plan of what a user will do during their trip, including elements such as destination, sightseeing spots, accommodations, restaurants, and budget.

[0185] "Real-time information" refers to providing users with the latest data and navigation information at any given time while they are traveling.

[0186] "Navigation" refers to a function that guides the user to the optimal route and steps to their destination based on their current location.

[0187] An "external database" is an external source of information used to generate travel plans, and includes information on tourist attractions, restaurants, accommodations, etc.

[0188] A "tourist destination" refers to a place or region in a travel destination that is worth visiting, and includes natural landscapes, historical buildings, cultural facilities, and so on.

[0189] "Eating establishments" refer to places where customers eat, and include restaurants, cafes, and diners.

[0190] "Accommodation" refers to the place where a user stays during their trip, and includes hotels, inns, guesthouses, and so on.

[0191] This invention relates to a system that uses generative artificial intelligence to propose an optimal travel plan based on the input of detailed travel information. Its specific configuration and operation are described below.

[0192] System Overview

[0193] This system aims to provide users with efficient and real-time information for planning and executing their travel plans. Its main components include user devices, servers, generative artificial intelligence, and external databases.

[0194] Program Processing Description

[0195] 1. Collection of input information

[0196] The user enters detailed information such as travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. The user device temporarily stores this entered information.

[0197] 2. Sending data

[0198] The user device sends the collected user input information to a server in the cloud. The server analyzes the received data and interprets the user's requests.

[0199] 3. Information analysis and travel plan generation

[0200] The server searches an external database based on the user's input and collects relevant travel information. Generative artificial intelligence then uses this collected data to generate a travel plan optimized for the user's needs. Specifically, it selects the best restaurants, tourist attractions, and accommodations based on the travel destination, budget, meals, and leisure activities.

[0201] 4. Provision of real-time information

[0202] The server sends real-time information to the user's device along with the generated travel plan. For example, it can use AR functionality to provide local information and navigation to the user's smart glasses.

[0203] 5. Presentation of travel plan and navigation

[0204] The user device displays the generated travel plan and real-time information to the user. Furthermore, it uses navigation functions to support the user's actions at the destination and presents additional information and recommendations.

[0205] Specific example

[0206] The user enters their travel preferences into their smartphone, such as "Destination: Tokyo, I want to relax, I want to go somewhere with nature, I want to eat sushi, budget: 50,000 yen." Based on this information, the server generates a travel plan, selecting information such as highly-rated sushi restaurants in Ginza, Ueno Zoo, and Senso-ji Temple. It also lists and presents multiple accommodation options within the budget. Furthermore, upon arrival at the destination, smart glasses use augmented reality (AR) to display the optimal route and timely recommendations in real time.

[0207] Example of a prompt

[0208] "Please suggest a travel plan for Tokyo, where I want to relax, experience nature, eat sushi, and have a budget of 50,000 yen."

[0209] With this configuration, the system allows users to simply input travel information, and the generative artificial intelligence utilizes advanced technology to provide an optimal travel plan. Furthermore, it can enhance the user's travel experience by providing on-site navigation and real-time information.

[0210] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0211] Step 1:

[0212] Users input detailed information such as their travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. This input information is temporarily stored in a database within the user device. Specifically, text data is collected through the user device's interface.

[0213] Input: Detailed information entered by the user, such as travel destination, mood, leisure activities, desired meals, and budget.

[0214] Output: Detailed information data stored on the user's device

[0215] Step 2:

[0216] The user device sends the collected user input information to a server in the cloud. During transmission, the information stored in the database within the user device is sent to the server via an API request.

[0217] Input: Detailed information data stored on the user's device

[0218] Output: Detailed information data sent to a server in the cloud.

[0219] Step 3:

[0220] The server analyzes the received data and interprets the user's requests. Based on the received information, it understands the travel experience the user desires and sets search criteria accordingly.

[0221] Input: Detailed information data sent to a server in the cloud.

[0222] Output: Search criteria interpreted from user requests

[0223] Step 4:

[0224] The server searches external databases based on user input and collects relevant travel information. Specifically, it retrieves information on restaurants, tourist attractions, accommodations, etc., via APIs.

[0225] Input: Search criteria interpreted from user requests

[0226] Output: Travel information retrieved from an external database.

[0227] Step 5:

[0228] Generative artificial intelligence generates optimal travel plans tailored to the user's needs based on collected travel information. Specifically, it combines collected information on restaurants, tourist attractions, and accommodations to create a travel schedule that matches the user's preferences and budget.

[0229] Input: Travel information obtained from an external database

[0230] Output: Generated travel plan

[0231] Step 6:

[0232] The server sends real-time information to the user's device along with the generated travel plan. This real-time information includes local weather information, traffic conditions, and the latest event information.

[0233] Input: Generated travel plan

[0234] Output: Travel plans and real-time information sent to the user's device.

[0235] Step 7:

[0236] The user device displays the received travel plan and real-time information to the user. Furthermore, it uses navigation functionality to provide route guidance and additional recommendations based on the user's current location. When using smart glasses, augmented reality (AR) functionality is used to display local information and navigation information.

[0237] Input: Travel plans and real-time information sent to the user's device.

[0238] Output: Travel plan and real-time information displayed to the user.

[0239] Through the above processing steps, users can efficiently plan their trips and always have access to the latest information while traveling. As an example of a specific prompt to the generating AI model, the following is used: "Please suggest a travel plan for Tokyo, where I want to relax, where I can experience nature, where I want to eat sushi, and with a budget of 50,000 yen."

[0240] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0241] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest the optimal travel plan based on the user's input of detailed travel information and emotional information. The following describes the program processing of this system and a specific example in natural language.

[0242] System Overview

[0243] This system collects user input and emotional information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include a terminal, a server, generative artificial intelligence, an emotional engine, and an external database.

[0244] Program Processing Description

[0245] 1. Collection of input information

[0246] Users input detailed information such as their travel destination, mood, leisure activities, desired food, budget, and emotional information on the application screen.

[0247] The device collects and temporarily stores information entered by the user.

[0248] 2. Sending data

[0249] The terminal converts the collected user input information and sentiment information into JSON or XML format and sends it to the server.

[0250] The server analyzes the received data and interprets the user's requests and emotions.

[0251] 3. Information Analysis and Plan Generation

[0252] The server searches external databases and collects relevant travel information based on user input and sentiment information.

[0253] Generative artificial intelligence and an emotion engine use collected data to generate travel plans that are optimally suited to the user's requests and emotions. Specifically, they select the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired food, leisure activities, and emotions.

[0254] 4. Sending and displaying plans

[0255] The server converts the generated travel plan into JSON or XML format and sends it to the terminal.

[0256] The device analyzes the received travel plan and displays it on the application screen.

[0257] Specific example

[0258] User input information

[0259] The user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[0260] Example of plan generation

[0261] 1. Restaurant Search

[0262] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[0263] The emotional engine further filters out shops with a quiet and relaxing atmosphere that are considered good for stress relief.

[0264] 2. Search for tourist destinations

[0265] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[0266] The emotional engine selects quiet, natural spots where you can relax.

[0267] 3. Search for accommodations

[0268] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[0269] The emotional engine selects accommodations in quiet environments suitable for stress relief.

[0270] 4. Creating a travel plan

[0271] The generative artificial intelligence and emotion engine will create a specific schedule for days 1 through 3 based on the above conditions. For example, day 1 might include dinner at a quiet sushi restaurant in Ginza, day 2 might involve a visit to Ueno Zoo and a stroll through relaxing nature spots, and day 3 might include a visit to Senso-ji Temple and the selection of accommodation suitable for stress relief.

[0272] Suggestions for users

[0273] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[0274] In this way, by simply having the user input detailed travel information and emotional information, the generative artificial intelligence and emotion engine analyze all the information and provide an optimal travel plan that also takes the user's emotions into consideration, significantly reducing the effort required from the user and enabling a more satisfying travel experience. With this system, users can easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0275] The following describes the processing flow.

[0276] Step 1:

[0277] The user enters travel details and emotional information on the application screen. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, budget, and emotional information (e.g., want to relax, relieve stress) from text boxes or dropdown menus.

[0278] Step 2:

[0279] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user. For example, it collects data such as "Tokyo" for travel destination, "Relaxed" for mood, and "Stress Relief" for emotional information.

[0280] Step 3:

[0281] The device collects information, converts it into JSON or XML format, and sends it to the server. Specifically, it sends data to the server using HTTP requests. An example of the format sent is {"destination": "Tokyo", "mood": "relax", "activity": "nature", "food": "sushi", "budget": "50000", "emotion": "stress relief"}.

[0282] Step 4:

[0283] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables. For example, information such as travel destination "Tokyo", mood "relaxed", and emotional information "stress relief" is stored in variables.

[0284] Step 5:

[0285] The server searches an external database to collect relevant information. Specifically, it uses API calls to obtain restaurant information, tourist attraction information, and accommodation facility information from the external database. For example, it searches with "Tokyo Sushi" using the Tabelog API and with "Tokyo Natural Tourist Attraction" using the TripAdvisor API.

[0286] Step 6:

[0287] The server uses an emotion engine to analyze the user's emotional information. Specifically, based on emotions such as "stress relief", the emotion engine filters restaurants, tourist attractions, and accommodation facilities in a relaxing environment.

[0288] Step 7:

[0289] The generative artificial intelligence generates an optimal travel plan based on the user's input information and emotional information. Specifically, it selects restaurants, tourist attractions, and accommodation facilities that meet the conditions and creates a specific schedule for each day. For example, on the first day, dinner at a quiet sushi restaurant in Ginza, on the second day, a stroll in Ueno Zoo and a natural spot for relaxation, and on the third day, a visit to Asakusa Temple and selection of a quiet accommodation facility.

[0290] Step 8:

[0291] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to return the data to the device. An example format is: {"day1": {"arrival_time": "13:00", "dinner": "Sushi restaurant in Ginza", "cost": 15000}, "day2": {"morning": "Ueno Zoo", "lunch": "Quiet sushi lunch", "afternoon": "Relaxing nature spot", "cost": 5000}, "day3": {"morning": "Senso-ji Temple", "afternoon": "Quiet accommodation", "cost": 10000}}

[0292] Step 9:

[0293] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format. For example, it might display "Sushi restaurant in Ginza" for dinner on day 1, and "Ueno Zoo" for the morning of day 2.

[0294] Step 10:

[0295] The user reviews the suggested plan and, if necessary, checks further details or proceeds with the booking process. Specifically, links are set up for each plan item, so that clicking them opens the booking site or detailed information page. For example, clicking the "Sushi restaurant in Ginza" link will open the restaurant's booking page.

[0296] (Example 2)

[0297] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0298] Conventional travel plan generation systems require users to manually create detailed travel plans, which is time-consuming and laborious. Furthermore, it is often difficult to create plans that take into account the user's emotional state and specific requests, resulting in unsatisfactory plans. This invention aims to increase user satisfaction by automatically generating optimal travel plans based on user input and emotional information.

[0299] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's travel destination, mood, leisure, meals, budget, and emotional information; means for temporarily storing the input information on the terminal; means for converting the stored information into JSON or XML format and sending it to the server; means for analyzing the information received by the server and collecting relevant travel information using an external database; means for generating an optimal travel plan based on the collected information and the user's emotional state using generative artificial intelligence and an emotional engine; means for converting the generated travel plan into JSON or XML format and sending it to the terminal; and means for displaying the transmitted travel plan on the terminal's application screen. This makes it possible to automatically generate an optimal travel plan based on the user's input information and emotional information, saving the user time and providing a higher level of satisfaction.

[0300] "User input information" refers to all information that the user enters into the application screen, including travel destination, mood, leisure activities, meals, budget, and emotional information.

[0301] A "terminal" refers to a device used by a user to input information and send it to a server, and includes smartphones, tablets, and personal computers.

[0302] A "server" is a computer system that receives user input information, analyzes it, and performs all the necessary backend processing to generate a travel plan.

[0303] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, which is a format for expressing data in a text format that is easy for humans and machines to read.

[0304] "XML format" is an abbreviation for eXtensible Markup Language, which is a markup language for expressing data structurally.

[0305] "Generative artificial intelligence" is an artificial intelligence model that analyzes users' input information and emotional information and is used to generate an optimal travel plan.

[0306] "Emotion engine" is a software component that interprets the emotional state of users and selects the optimal elements of a travel plan based on that information.

[0307] "External database" is an external data source that provides travel information, restaurant information, accommodation facility information, etc., and can be accessed by the server via an API.

[0308] "Travel plan" is a travel schedule and activity plan generated based on users' input information and emotional information, and includes information such as specific restaurants, tourist attractions, accommodation facilities, etc.

[0309] "Application screen" is a software interface used by users to input travel details and emotional information and view the generated travel plan.

[0310] This invention relates to a system that proposes an optimal travel plan using generative artificial intelligence and an emotion engine by a user inputting travel details and emotional information. The system of this invention includes a terminal, a server, generative artificial intelligence, an emotion engine, and an external database. Hereinafter, how to implement this system will be described in detail.

[0311] 1. Collection of users' input information

[0312] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The input method involves filling in each field on a form displayed on the screen. For example, information such as "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief" might be entered.

[0313] 2. Information storage and transmission

[0314] The terminal collects user input in real time and temporarily stores it in memory. The collected data is then converted to JSON or XML format. The converted data is sent to the server via an HTTP POST request.

[0315] 3. Information analysis on the server

[0316] The server deserializes the data received from the terminal and converts it into an internal data structure. Next, it searches external databases and collects relevant travel information based on the user's input. Specifically, it uses the Tabelog API and Google Maps API to obtain restaurant information and the TripAdvisor API and Google Maps API to collect tourist destination information.

[0317] 4. Creating a travel plan

[0318] The server uses generative artificial intelligence and an emotion engine to generate the optimal travel plan based on collected travel information and user sentiment data. The generative AI creates a travel schedule tailored to the user's specific requests, while the emotion engine selects restaurants, tourist destinations, and accommodations that are best suited to the user's emotional state.

[0319] Examples of specific prompt messages include the following:

[0320] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[0321] 5. Sending and displaying plans

[0322] The generated travel plan is converted back into JSON or XML format and sent to the terminal as an HTTP response. The terminal parses the received data and displays the travel plan to the user on the application screen. This display uses a graphical interface that includes detailed information and links.

[0323] For example, the following travel plan might be generated:

[0324] Day 1: Dinner at a quiet sushi restaurant in Ginza

[0325] Day 2: A relaxing stroll through nature in Ueno Park.

[0326] Day 3: Visit Senso-ji Temple and stay at accommodation suitable for stress relief.

[0327] This system allows generative artificial intelligence and an emotion engine to automatically generate the optimal travel plan based on the information entered by the user, saving the user time and providing a higher level of satisfaction.

[0328] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0329] Step 1:

[0330] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The information entered by the user is entered into a form and sent to the device when the submit button is clicked. This input information includes things like "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[0331] Input: User input of travel destination, mood, leisure, food, budget, and emotional information.

[0332] Output: Sending the input information to the terminal.

[0333] Specific actions:

[0334] The user enters information into each field and clicks the submit button.

[0335] The terminal verifies the input content and checks for any input errors.

[0336] Step 2:

[0337] The terminal collects user input in real time and temporarily stores it in memory. The collected information is converted to either JSON or XML format. For example, in the case of JSON format, the "JSON.stringify" function is used.

[0338] Input: Collected user input information

[0339] Output: Data converted to JSON or XML format.

[0340] Specific actions:

[0341] The terminal uses the "JSON.stringify" function to convert the input information into JSON format.

[0342] Step 3:

[0343] The terminal sends the converted data to the server. Specifically, the data is sent using an HTTP POST request.

[0344] Input: User input data converted to JSON or XML format.

[0345] Output: Data to send to the server

[0346] Specific actions:

[0347] The terminal sends data to the server using the "fetch" function.

[0348] Step 4:

[0349] The server deserializes the data received from the terminal and converts it into an internal data structure. Specifically, it analyzes the data structure and separates user input information from sentiment information.

[0350] Input: Data in JSON or XML format sent from the device.

[0351] Output: User input information converted to an internal data structure

[0352] Specific actions:

[0353] The server uses the "JSON.parse" function to deserialize the received data.

[0354] Step 5:

[0355] Based on the analyzed data, the server uses external database APIs (e.g., Tabelog API, Google Maps API, TripAdvisor API) to collect travel information related to the user's input.

[0356] Input: User input information converted to an internal data structure

[0357] Output: Related travel information retrieved from an external database

[0358] Specific actions:

[0359] The server retrieves restaurant information via the Tabelog API and collects tourist information using the Google Maps API.

[0360] Step 6:

[0361] The server's generative AI and emotion engine generate the optimal travel plan based on collected travel information and user emotion information. The generative AI creates a specific travel schedule, while the emotion engine selects elements that best suit the user's emotions.

[0362] Input: Relevant travel information obtained from an external database, user sentiment information

[0363] Output: Optimal travel plan

[0364] Specific actions:

[0365] The server sends the following prompt to the generative artificial intelligence to generate the schedule:

[0366] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[0367] Step 7:

[0368] The server converts the generated travel plan back into JSON or XML format and sends it to the terminal as an HTTP response.

[0369] Input: Generated travel plan

[0370] Output: Plan data converted to JSON or XML format.

[0371] Specific actions:

[0372] The server uses the "JSON.stringify" function to convert the travel plan into JSON format and sends it to the terminal in the HTTP response.

[0373] Step 8:

[0374] The device analyzes the received travel plan and displays it to the user on the application screen. The display method includes a graphical interface with detailed information and links.

[0375] Input: Travel plan data in JSON format sent from the server.

[0376] Output: Display of travel plan for the user

[0377] Specific actions:

[0378] The device parses the received JSON data and displays the travel plan graphically to the user.

[0379] (Application Example 2)

[0380] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0381] Traditional content delivery services have struggled to provide personalized content tailored to users' interests and emotions. In particular, they lack mechanisms to suggest optimal content based on the specific emotional state a user is currently experiencing. As a result, users have to expend considerable effort to find content that matches their interests and mood, leading to decreased satisfaction.

[0382] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0383] In this invention, the server includes means for collecting user interest topics and current sentiment information, means for transmitting the collected user input information to the server, means for generating optimal content using generative artificial intelligence based on the user input information, means for transmitting the generated content to a terminal, and means for displaying the transmitted content to the user. This makes it possible to automatically suggest optimal content that matches the user's interests and sentiments.

[0384] "Topics of interest" refer to specific fields or themes that a user is interested in.

[0385] "Emotional information" refers to data that indicates the user's current mood and emotional state.

[0386] "Means of collection" refers to the methods and systems used to acquire and store information entered by users.

[0387] A "server" is a computer system that receives user input information and performs processing and analysis on it.

[0388] "Means of transmission" refers to methods or functions for transferring acquired information to other systems or terminals.

[0389] "Generative artificial intelligence" refers to algorithms and models that generate information tailored to user needs based on large amounts of data.

[0390] "Optimal content" refers to information and media that best match the user's interests and emotions.

[0391] A "terminal" is a device that a user uses to input information or view suggested information.

[0392] "Means of display" refers to methods or systems for providing generated information to users visually.

[0393] An "external database" is an external information resource used for searching and referencing information entered by the user.

[0394] "Music, video, or text" refers to various media content provided according to the user's interests and emotions.

[0395] This invention is a system that collects user interest topics and current sentiment information, and proposes optimal content using generative artificial intelligence and an external database. The program processing and details of this system are described below.

[0396] Program Processing Description

[0397] Hardware and software configuration

[0398] 1. Hardware

[0399] Device: Smartphone (iOS / ANDROID® compatible)

[0400] Server: A computer server (one with processing speed and storage capacity)

[0401] 2. Software

[0402] Smartphone application: Developed using React Native

[0403] Server-side applications: Server applications using Node.js

[0404] Generative artificial intelligence models: For example, GPT-3 (registered trademark) from OpenAI (registered trademark).

[0405] Sentiment analysis engine: For example, IBM Watson®'s Sentiment Analysis.

[0406] External database APIs: YouTube® API, Spotify API, Google Books API, etc.

[0407] System operation

[0408] 1. Collection of user information

[0409] Users input their areas of interest (music, movies, reading, etc.) and their current emotional state (want to relax, want to feel energized, etc.) through a smartphone app.

[0410] The terminal converts the input information into JSON format and stores it temporarily.

[0411] 2. Sending data

[0412] The terminal sends the collected user input information to the server. Real-time data communication is achieved by using the Axios library for transmission.

[0413] 3. Analysis of Information

[0414] The server analyzes the received data and, based on that analysis, uses a combination of a generative artificial intelligence model (such as GPT-3) and an emotion analysis engine.

[0415] The generative artificial intelligence searches external databases based on topics of interest, and the sentiment analysis engine selects the most suitable content based on the user's emotional information.

[0416] 4. Content generation and transmission

[0417] The server generates the most suitable content, converts the recommendation list into JSON format, and sends it to the terminal.

[0418] The device analyzes the recommendation list and displays it in a way that the user can visually confirm.

[0419] Specific example

[0420] User input information

[0421] If the user enters "movie" and "want to relax".

[0422] Example of a prompt

[0423] The user entered "movie" and "want to relax." Please recommend a movie that is perfect for relaxation.

[0424] Examples of content recommendations

[0425] 1. Movie Search

[0426] The server uses external database APIs (such as the YouTube API and Netflix API) to collect movie lists based on the criterion of "relaxing movies."

[0427] The emotion analysis engine selects the best candidates from among "relaxing" movies, and a generative artificial intelligence model organizes them.

[0428] 2. Music Search

[0429] The server uses the Spotify API to collect playlists categorized as "relaxing music."

[0430] The emotion analysis engine selects the most suitable music album or playlist for the feeling of wanting to relax.

[0431] Display to the user

[0432] The device displays a generated list of recommended content to the user, allowing them to watch movies or play music on the spot.

[0433] This makes it possible to create a system that automatically provides the most suitable content simply by the user inputting their areas of interest and emotional information.

[0434] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0435] Step 1:

[0436] Collection of user information

[0437] Users use a smartphone app to input topics of interest (e.g., movies, music, reading) and their current emotional state (e.g., want to relax, want to feel energized).

[0438] Input: User-entered topics of interest and sentiment information.

[0439] Output: User information converted to JSON format.

[0440] Specific operation: A form for entering topics of interest and sentiment information is displayed through the user interface. Once the user enters the information and presses the submit button, the data is converted into JSON format.

[0441] Step 2:

[0442] Sending data

[0443] The terminal sends the collected user input information to the server.

[0444] Input: User information in JSON format.

[0445] Output: Data sent to the server.

[0446] Specific operation: The terminal uses the Axios library to send JSON-formatted data to the server-side endpoint via asynchronous communication.

[0447] Step 3:

[0448] Information analysis

[0449] The server analyzes the received data, identifies topics of interest to the user, and evaluates sentiment information.

[0450] Input: JSON formatted data sent to the server.

[0451] Output: Analysis results based on user interest and sentiment information.

[0452] Specific operation: The server parses the received JSON data and passes it to a generative artificial intelligence model and sentiment analysis engine to analyze topics of interest and sentiment information.

[0453] Step 4:

[0454] Content generation

[0455] The server uses generative artificial intelligence and sentiment analysis engines to generate optimal content.

[0456] Input: Analyzed user interest topics and sentiment information.

[0457] Output: A list of recommended content that is best suited for your needs.

[0458] Specific operation: Interest topics and sentiment information are input into prompts of a generative artificial intelligence model (such as GPT-3), and the system uses an external database API to collect and generate optimal content.

[0459] Step 5:

[0460] Send content

[0461] The server converts the generated content recommendation list into JSON format and sends it to the terminal.

[0462] Input: A list of recommended content that is best suited for your needs.

[0463] Output: JSON formatted data sent to the terminal.

[0464] Specific operation: Serialize the recommendation list into JSON format and send it to the endpoint on the terminal side.

[0465] Step 6:

[0466] Display content

[0467] The device analyzes the received content recommendation list and displays it visually to the user.

[0468] Input: JSON formatted data sent to the terminal.

[0469] Output: A list of content recommendations displayed visually to the user.

[0470] Specific operation: The device parses the received JSON data and displays detailed content information in the user interface. The user can then watch recommended movies or play music.

[0471] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0472] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0473] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0474] [Second Embodiment]

[0475] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0476] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0477] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0478] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0479] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0480] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0481] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0482] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0483] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0484] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0485] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0486] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0487] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. The following describes the program processing of this system and a specific example in natural language.

[0488] System Overview

[0489] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external database.

[0490] Program Processing Description

[0491] 1. Collection of input information

[0492] The user enters detailed information such as their travel destination, mood, leisure activities, desired food, and budget on the application screen.

[0493] The device collects and temporarily stores information entered by the user.

[0494] 2. Sending data

[0495] The terminal sends the collected user input information to the server.

[0496] The server analyzes the received data and interprets the user's request.

[0497] 3. Information Analysis and Plan Generation

[0498] The server searches external databases based on user input and collects relevant travel information.

[0499] Generative artificial intelligence uses collected data to generate travel plans that are optimal for the user's needs. Specifically, it selects the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired cuisine, and leisure activities.

[0500] 4. Sending and displaying plans

[0501] The server sends the generated travel plan to the device.

[0502] The device displays the received travel plan to the user.

[0503] Specific example

[0504] User input information

[0505] The user enters "Tokyo," "relax," "feel nature," "sushi," and "budget of 50,000 yen."

[0506] Example of plan generation

[0507] 1. Restaurant Search

[0508] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[0509] 2. Search for tourist destinations

[0510] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[0511] 3. Search for accommodations

[0512] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[0513] 4. Creating a travel plan

[0514] The generative artificial intelligence will create a specific schedule for days 1 through 3 based on the above conditions. For example, on day 1, it might suggest dinner at a sushi restaurant in Ginza, on day 2, a visit to Ueno Zoo and a sushi lunch, and on day 3, a visit to Senso-ji Temple and accommodation.

[0515] Suggestions for users

[0516] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[0517] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] The user enters detailed travel information. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, and budget from text boxes or dropdown menus on the application screen.

[0521] Step 2:

[0522] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user in variables or data storage.

[0523] Step 3:

[0524] The device converts the collected information into JSON or XML format and sends it to the server. Specifically, it sends the data to the server using HTTP requests.

[0525] Step 4:

[0526] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables.

[0527] Step 5:

[0528] The server searches an external database to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist attraction information, and accommodation information from the external database.

[0529] Step 6:

[0530] Based on data acquired by the server, generative artificial intelligence is used to generate the optimal travel plan. Specifically, the user's input information and acquired data are passed to an algorithm, which selects restaurants, tourist destinations, and accommodations that meet the criteria, and then creates a travel schedule.

[0531] Step 7:

[0532] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to send the data back to the device.

[0533] Step 8:

[0534] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format.

[0535] Step 9:

[0536] Users review the proposed plan and, if necessary, view further details or proceed with the booking process. Specifically, links are set up in each plan section, so that clicking them opens the booking site or detailed information page.

[0537] (Example 1)

[0538] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0539] Traditional travel planning systems require users to individually gather information and create their own plans, which is very time-consuming. Furthermore, if the collected information is insufficient, it becomes difficult to create an optimal travel plan. Thus, there is a challenge in that it is difficult for users to easily obtain high-quality travel plans.

[0540] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0541] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure, meals, and budget; means for transmitting the collected user input information to an information processing device; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan to a display device; and means for displaying the transmitted travel plan to the user. This makes it possible for users to easily and quickly obtain a high-quality, optimal travel plan.

[0542] A "travel destination" refers to a geographical location that the user wishes to visit.

[0543] "Mood" refers to the user's hopes and desires regarding their mental state and atmosphere during their trip.

[0544] "Leisure" refers to the activities and recreation that users want to enjoy while traveling.

[0545] "Meals" refers to the dishes and foods that the user wants to eat during their trip.

[0546] "Budget" refers to the amount of money a user plans to spend on a trip.

[0547] A "user" is someone who intends to use a travel plan.

[0548] "Input information" refers to the detailed travel information that the user provides to the system.

[0549] An "information processing device" is a device used to process data collected from users.

[0550] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate results based on specific input data.

[0551] A "travel plan" refers to suggestions and schedules related to a user's trip.

[0552] A "display device" is a device used to display the generated travel plan to the user.

[0553] A "data repository" is a database or API used to retrieve information from external sources in order to generate travel plans.

[0554] A "food and beverage establishment" refers to a shop or restaurant where users eat.

[0555] A "tourist attraction" refers to a tourist destination or landmark that users should visit.

[0556] "Accommodation facilities" refer to hotels, guesthouses, and other accommodations where users can stay.

[0557] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. This system includes several main components. Specific embodiments are described below.

[0558] System Overview

[0559] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external data repository.

[0560] Collect input information

[0561] The user enters detailed information such as travel destination, mood, leisure activities, meals, and budget through the application screen. For example, consider a case where the user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," and "Budget of 50,000 yen."

[0562] The device collects and temporarily stores information entered by the user. This typically involves using the local storage of a mobile device or PC. The device then converts the stored information into JSON format to facilitate subsequent data transmission and analysis.

[0563] Data transmission and analysis

[0564] The terminal sends the collected user input information to the server. Here, the data is transmitted securely using the HTTPS protocol. The server analyzes the received data and interprets the user's requests. Specifically, the data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[0565] Use of external data repositories

[0566] Based on the user's requests, the server searches external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and collects relevant travel information. For example, using the conditions "Tokyo" and "sushi," it retrieves data on highly-rated sushi restaurants using the Tabelog API. Similarly, using the conditions "Tokyo" and "experience nature," it retrieves data on tourist destinations rich in nature using the TripAdvisor API.

[0567] Travel plan generation

[0568] The server passes the collected data to the generative artificial intelligence (AI). Specifically, it inputs JSON data as prompts into the AI. The AI ​​then generates the optimal travel plan based on the input data. For example, the prompts can be set as follows:

[0569] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[0570] Proposed plan:

[0571] Day 1: Dinner at a sushi restaurant in Ginza

[0572] Day 2: Ueno Zoo and sushi lunch

[0573] Day 3: Visit to Senso-ji Temple and accommodation

[0574] Generative artificial intelligence generates and proposes travel plans that are best suited to the user's needs.

[0575] Sending and displaying plans

[0576] The server sends the generated travel plan to the device. Typically, an HTTP POST request is used for this transmission. The device then displays the received travel plan on the application screen. A user interface (e.g., an application using React or Flutter) is often used here.

[0577] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[0578] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0579] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0580] Step 1: Collecting input information

[0581] Users enter detailed information such as their travel destination, mood, leisure activities, meals, and budget through the application screen.

[0582] Input: Detailed travel information entered by the user (e.g., "Tokyo", "Relax", "Experience nature", "Sushi", "Budget 50,000 yen")

[0583] Output: Collected user input information

[0584] The device temporarily stores the information entered by the user.

[0585] Operation: Saves data to the local storage of mobile devices or PCs.

[0586] The device converts the saved information into JSON format.

[0587] Operation: Converts input information into JSON format data to prepare for subsequent processing.

[0588] Step 2: Send

[0589] The terminal sends the collected user input information to the server.

[0590] Operation: Securely transmits data using the HTTPS protocol.

[0591] Input: User input information converted to JSON format

[0592] Output: User input information sent to the server

[0593] The server analyzes the received data and interprets the user's request.

[0594] Operation: Data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[0595] Input: User input information in JSON format received

[0596] Output: Information on analyzed user requests

[0597] Step 3: Using an external data repository

[0598] Based on the user's requests, the server searches external data repositories and collects relevant travel information.

[0599] Operation: Sends requests to external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and retrieves the necessary information.

[0600] Input: Information about the analyzed user requests

[0601] Output: Travel information retrieved from an external data repository

[0602] Specific example:

[0603] The server uses the Tabelog API to retrieve data on highly-rated sushi restaurants based on the conditions "Tokyo" and "sushi".

[0604] The server uses the TripAdvisor API to retrieve data on tourist destinations rich in nature, based on the conditions of "Tokyo" and "experiencing nature."

[0605] Step 4: Creating a travel plan

[0606] The server passes the collected data to a generative artificial intelligence.

[0607] Operation: Inputs JSON formatted data as a prompt into a generative artificial intelligence system.

[0608] Input: Travel information retrieved from an external data repository

[0609] Output: Travel plan generated by generative artificial intelligence

[0610] Generative artificial intelligence generates the optimal travel plan based on input data.

[0611] Specific example:

[0612] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[0613] Proposed plan:

[0614] Day 1: Dinner at a sushi restaurant in Ginza

[0615] Day 2: Ueno Zoo and sushi lunch

[0616] Day 3: Visit to Senso-ji Temple and accommodation

[0617] Step 5: Submit and view your plan

[0618] The server sends the generated travel plan to the device.

[0619] Operation: Sends travel plans using an HTTP POST request.

[0620] Input: Travel plan generated by a generative artificial intelligence system

[0621] Output: Travel plan sent to the terminal

[0622] The device displays the received travel plan to the user.

[0623] Operation: Displays travel plans through a user interface (e.g., an application using React or Flutter).

[0624] Input: Travel plan sent from the server

[0625] Output: Travel plan displayed to the user

[0626] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[0627] (Application Example 1)

[0628] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0629] When planning a trip, it is time-consuming and burdensome for users to manually gather a lot of information and create a plan. Furthermore, there is a lack of means to provide real-time information during the trip, making it difficult to obtain local navigation and recommendations.

[0630] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0631] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure activities, desired meals, and budget; means for transmitting the collected user input information to the server; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan and real-time information to the user device; and means for displaying the transmitted travel plan and real-time information to the user and providing navigation and additional information. As a result, the user can efficiently and easily plan a trip and obtain necessary information in real time while traveling.

[0632] "User device" is a general term for terminal devices used by users, and includes smartphones, tablets, smart glasses, etc.

[0633] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates the optimal travel plan based on user input.

[0634] A "travel plan" refers to a detailed plan of what a user will do during their trip, including elements such as destination, sightseeing spots, accommodations, restaurants, and budget.

[0635] "Real-time information" refers to providing users with the latest data and navigation information at any given time while they are traveling.

[0636] "Navigation" refers to a function that guides the user to the optimal route and steps to their destination based on their current location.

[0637] An "external database" is an external source of information used to generate travel plans, and includes information on tourist attractions, restaurants, accommodations, etc.

[0638] A "tourist destination" refers to a place or region in a travel destination that is worth visiting, and includes natural landscapes, historical buildings, cultural facilities, and so on.

[0639] "Eating establishments" refer to places where customers eat, and include restaurants, cafes, and diners.

[0640] "Accommodation" refers to the place where a user stays during their trip, and includes hotels, inns, guesthouses, and so on.

[0641] This invention relates to a system that uses generative artificial intelligence to propose an optimal travel plan based on the input of detailed travel information. Its specific configuration and operation are described below.

[0642] System Overview

[0643] This system aims to provide users with efficient and real-time information for planning and executing their travel plans. Its main components include user devices, servers, generative artificial intelligence, and external databases.

[0644] Program Processing Description

[0645] 1. Collection of input information

[0646] The user enters detailed information such as travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. The user device temporarily stores this entered information.

[0647] 2. Sending data

[0648] The user device sends the collected user input information to a server in the cloud. The server analyzes the received data and interprets the user's requests.

[0649] 3. Information analysis and travel plan generation

[0650] The server searches an external database based on the user's input and collects relevant travel information. Generative artificial intelligence then uses this collected data to generate a travel plan optimized for the user's needs. Specifically, it selects the best restaurants, tourist attractions, and accommodations based on the travel destination, budget, meals, and leisure activities.

[0651] 4. Provision of real-time information

[0652] The server sends real-time information to the user's device along with the generated travel plan. For example, it can use AR functionality to provide local information and navigation to the user's smart glasses.

[0653] 5. Presentation of travel plan and navigation

[0654] The user device displays the generated travel plan and real-time information to the user. Furthermore, it uses navigation functions to support the user's actions at the destination and presents additional information and recommendations.

[0655] Specific example

[0656] The user enters their travel preferences into their smartphone, such as "Destination: Tokyo, I want to relax, I want to go somewhere with nature, I want to eat sushi, budget: 50,000 yen." Based on this information, the server generates a travel plan, selecting information such as highly-rated sushi restaurants in Ginza, Ueno Zoo, and Senso-ji Temple. It also lists and presents multiple accommodation options within the budget. Furthermore, upon arrival at the destination, smart glasses use augmented reality (AR) to display the optimal route and timely recommendations in real time.

[0657] Example of a prompt

[0658] "Please suggest a travel plan for Tokyo, where I want to relax, experience nature, eat sushi, and have a budget of 50,000 yen."

[0659] With this configuration, the system allows users to simply input travel information, and the generative artificial intelligence utilizes advanced technology to provide an optimal travel plan. Furthermore, it can enhance the user's travel experience by providing on-site navigation and real-time information.

[0660] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0661] Step 1:

[0662] Users input detailed information such as their travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. This input information is temporarily stored in a database within the user device. Specifically, text data is collected through the user device's interface.

[0663] Input: Detailed information entered by the user, such as travel destination, mood, leisure activities, desired meals, and budget.

[0664] Output: Detailed information data stored on the user's device

[0665] Step 2:

[0666] The user device sends the collected user input information to a server in the cloud. During transmission, the information stored in the database inside the user device is sent to the server via an API request.

[0667] Input: Detailed information data stored on the user's device

[0668] Output: Detailed information data sent to a server in the cloud.

[0669] Step 3:

[0670] The server analyzes the received data and interprets the user's requests. Based on the received information, it understands the travel experience the user desires and sets search criteria accordingly.

[0671] Input: Detailed information data sent to a server in the cloud.

[0672] Output: Search criteria interpreted from user requests

[0673] Step 4:

[0674] The server searches external databases based on user input and collects relevant travel information. Specifically, it retrieves information on restaurants, tourist attractions, accommodations, etc., via APIs.

[0675] Input: Search criteria interpreted from user requests

[0676] Output: Travel information retrieved from an external database

[0677] Step 5:

[0678] Generative artificial intelligence generates optimal travel plans tailored to the user's needs based on collected travel information. Specifically, it combines collected information on restaurants, tourist attractions, and accommodations to create a travel schedule that matches the user's preferences and budget.

[0679] Input: Travel information obtained from an external database

[0680] Output: Generated travel plan

[0681] Step 6:

[0682] The server sends real-time information to the user's device along with the generated travel plan. This real-time information includes local weather information, traffic conditions, and the latest event information.

[0683] Input: Generated travel plan

[0684] Output: Travel plans and real-time information sent to the user's device.

[0685] Step 7:

[0686] The user device displays the received travel plan and real-time information to the user. Furthermore, it uses navigation functionality to provide route guidance and additional recommendations based on the user's current location. When using smart glasses, augmented reality (AR) functionality is used to display local information and navigation information.

[0687] Input: Travel plans and real-time information sent to the user's device.

[0688] Output: Travel plan and real-time information displayed to the user.

[0689] Through the above processing steps, users can efficiently plan their trips and always have access to the latest information while traveling. As an example of a specific prompt to the generating AI model, the following is used: "Please suggest a travel plan for Tokyo, where I want to relax, where I can experience nature, where I want to eat sushi, and with a budget of 50,000 yen."

[0690] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0691] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest the optimal travel plan based on the user's input of detailed travel information and emotional information. The following describes the program processing of this system and a specific example in natural language.

[0692] System Overview

[0693] This system collects user input and emotional information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include a terminal, a server, generative artificial intelligence, an emotional engine, and an external database.

[0694] Program Processing Description

[0695] 1. Collection of input information

[0696] Users input detailed information such as their travel destination, mood, leisure activities, desired food, budget, and emotional information on the application screen.

[0697] The device collects and temporarily stores information entered by the user.

[0698] 2. Sending data

[0699] The terminal converts the collected user input information and sentiment information into JSON or XML format and sends it to the server.

[0700] The server analyzes the received data and interprets the user's requests and emotions.

[0701] 3. Information Analysis and Plan Generation

[0702] The server searches external databases and collects relevant travel information based on user input and sentiment information.

[0703] Generative artificial intelligence and an emotion engine use collected data to generate travel plans that are optimally suited to the user's requests and emotions. Specifically, they select the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired food, leisure activities, and emotions.

[0704] 4. Sending and displaying plans

[0705] The server converts the generated travel plan into JSON or XML format and sends it to the terminal.

[0706] The device analyzes the received travel plan and displays it on the application screen.

[0707] Specific example

[0708] User input information

[0709] The user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[0710] Example of plan generation

[0711] 1. Restaurant Search

[0712] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[0713] The emotional engine further filters out shops with a quiet and relaxing atmosphere that are considered good for stress relief.

[0714] 2. Search for tourist destinations

[0715] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[0716] The emotional engine selects quiet, natural spots where you can relax.

[0717] 3. Search for accommodations

[0718] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[0719] The emotional engine selects accommodations in quiet environments suitable for stress relief.

[0720] 4. Creating a travel plan

[0721] The generative artificial intelligence and emotion engine will create a specific schedule for days 1 through 3 based on the above conditions. For example, day 1 might include dinner at a quiet sushi restaurant in Ginza, day 2 might involve a visit to Ueno Zoo and a stroll through relaxing nature spots, and day 3 might include a visit to Senso-ji Temple and the selection of accommodation suitable for stress relief.

[0722] Suggestions for users

[0723] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[0724] In this way, by simply having the user input detailed travel information and emotional information, the generative artificial intelligence and emotion engine analyze all the information and provide an optimal travel plan that also takes the user's emotions into consideration, significantly reducing the effort required from the user and enabling a more satisfying travel experience. With this system, users can easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0725] The following describes the processing flow.

[0726] Step 1:

[0727] The user enters travel details and emotional information on the application screen. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, budget, and emotional information (e.g., want to relax, relieve stress) from text boxes or dropdown menus.

[0728] Step 2:

[0729] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user. For example, it collects data such as "Tokyo" for travel destination, "Relaxed" for mood, and "Stress Relief" for emotional information.

[0730] Step 3:

[0731] The device collects information, converts it into JSON or XML format, and sends it to the server. Specifically, it sends data to the server using HTTP requests. An example of the format sent is {"destination": "Tokyo", "mood": "relax", "activity": "nature", "food": "sushi", "budget": "50000", "emotion": "stress relief"}.

[0732] Step 4:

[0733] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables. For example, it might store information such as travel destination "Tokyo," mood "relaxed," and emotional information "stress relief" in variables.

[0734] Step 5:

[0735] The server searches external databases to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist information, and accommodation information from external databases. For example, it might search for "Tokyo sushi" using the Tabelog API and "Tokyo nature tourist spots" using the TripAdvisor API.

[0736] Step 6:

[0737] The server uses an emotion engine to analyze the user's emotional information. Specifically, the emotion engine filters restaurants, tourist destinations, and accommodations based on emotions such as "stress relief," suggesting relaxing environments.

[0738] Step 7:

[0739] Generative artificial intelligence generates the optimal travel plan based on the user's input information and emotional information. Specifically, it selects restaurants, tourist attractions, and accommodations that meet the criteria and creates a detailed schedule for each day. For example, on day 1, it might include dinner at a quiet sushi restaurant in Ginza, on day 2, a visit to Ueno Zoo and a stroll through a relaxing nature spot, and on day 3, a visit to Senso-ji Temple and a quiet accommodation.

[0740] Step 8:

[0741] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to return the data to the device. An example format is: {"day1": {"arrival_time": "13:00", "dinner": "Sushi restaurant in Ginza", "cost": 15000}, "day2": {"morning": "Ueno Zoo", "lunch": "Quiet sushi lunch", "afternoon": "Relaxing nature spot", "cost": 5000}, "day3": {"morning": "Senso-ji Temple", "afternoon": "Quiet accommodation", "cost": 10000}}

[0742] Step 9:

[0743] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format. For example, it might display "Sushi restaurant in Ginza" for dinner on day 1, and "Ueno Zoo" for the morning of day 2.

[0744] Step 10:

[0745] The user reviews the suggested plan and, if necessary, checks further details or proceeds with the booking process. Specifically, links are set up for each plan item, so that clicking them opens the booking site or detailed information page. For example, clicking the "Sushi restaurant in Ginza" link will open the restaurant's booking page.

[0746] (Example 2)

[0747] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0748] Conventional travel plan generation systems require users to manually create detailed travel plans, which is time-consuming and laborious. Furthermore, it is often difficult to create plans that take into account the user's emotional state and specific requests, resulting in unsatisfactory plans. This invention aims to increase user satisfaction by automatically generating optimal travel plans based on user input and emotional information.

[0749] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's travel destination, mood, leisure, meals, budget, and emotional information; means for temporarily storing the input information on the terminal; means for converting the stored information into JSON or XML format and sending it to the server; means for analyzing the information received by the server and collecting relevant travel information using an external database; means for generating an optimal travel plan based on the collected information and the user's emotional state using generative artificial intelligence and an emotional engine; means for converting the generated travel plan into JSON or XML format and sending it to the terminal; and means for displaying the transmitted travel plan on the terminal's application screen. This makes it possible to automatically generate an optimal travel plan based on the user's input information and emotional information, saving the user time and providing a higher level of satisfaction.

[0750] "User input information" refers to all information that the user enters into the application screen, including travel destination, mood, leisure activities, meals, budget, and emotional information.

[0751] A "terminal" refers to a device used by a user to input information and send it to a server, and includes smartphones, tablets, and personal computers.

[0752] A "server" is a computer system that receives user input information, analyzes it, and performs all the necessary backend processing to generate a travel plan.

[0753] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a text format that is easy for both humans and machines to read.

[0754] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structurally representing data.

[0755] "Generative artificial intelligence" refers to an artificial intelligence model used to generate optimal travel plans by analyzing user input information and emotional information.

[0756] An "emotion engine" is a software component used to interpret a user's emotional state and select the optimal travel plan elements based on that information.

[0757] An "external database" is an external data source that provides travel information, restaurant information, accommodation information, etc., and can be accessed by the server via an API.

[0758] A "travel plan" is a travel schedule and activity plan generated based on the user's input information and emotional information, and includes specific information such as restaurants, tourist destinations, and accommodations.

[0759] The "application screen" is a software interface used by users to input travel details and sentiment information and to review the generated travel plan.

[0760] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest an optimal travel plan based on the user's input of detailed travel information and emotional information. The system of this invention includes a terminal, a server, generative artificial intelligence, an emotion engine, and an external database. The implementation of this system is described in detail below.

[0761] 1. Collecting user input information

[0762] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The input method involves filling in each field on a form displayed on the screen. For example, information such as "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief" might be entered.

[0763] 2. Information storage and transmission

[0764] The terminal collects user input in real time and temporarily stores it in memory. The collected data is then converted to JSON or XML format. The converted data is sent to the server via an HTTP POST request.

[0765] 3. Information analysis on the server

[0766] The server deserializes the data received from the terminal and converts it into an internal data structure. Next, it searches external databases and collects relevant travel information based on the user's input. Specifically, it uses the Tabelog API and Google Maps API to obtain restaurant information and the TripAdvisor API and Google Maps API to collect tourist destination information.

[0767] 4. Creating a travel plan

[0768] The server uses generative artificial intelligence and an emotion engine to generate the optimal travel plan based on collected travel information and user sentiment data. The generative AI creates a travel schedule tailored to the user's specific requests, while the emotion engine selects restaurants, tourist destinations, and accommodations that are best suited to the user's emotional state.

[0769] Examples of specific prompt messages include the following:

[0770] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[0771] 5. Sending and displaying plans

[0772] The generated travel plan is converted back into JSON or XML format and sent to the terminal as an HTTP response. The terminal parses the received data and displays the travel plan to the user on the application screen. This display uses a graphical interface that includes detailed information and links.

[0773] For example, the following travel plan might be generated:

[0774] Day 1: Dinner at a quiet sushi restaurant in Ginza

[0775] Day 2: A relaxing stroll through nature in Ueno Park.

[0776] Day 3: Visit Senso-ji Temple and stay at accommodation suitable for stress relief.

[0777] This system allows generative artificial intelligence and an emotion engine to automatically generate the optimal travel plan based on the information entered by the user, saving the user time and providing a higher level of satisfaction.

[0778] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0779] Step 1:

[0780] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The information entered by the user is entered into a form and sent to the device when the submit button is clicked. This input information includes things like "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[0781] Input: User input of travel destination, mood, leisure, food, budget, and emotional information.

[0782] Output: Sending the input information to the terminal.

[0783] Specific actions:

[0784] The user enters information into each field and clicks the submit button.

[0785] The terminal verifies the input content and checks for any input errors.

[0786] Step 2:

[0787] The terminal collects user input in real time and temporarily stores it in memory. The collected information is converted to either JSON or XML format. For example, in the case of JSON format, the "JSON.stringify" function is used.

[0788] Input: Collected user input information

[0789] Output: Data converted to JSON or XML format.

[0790] Specific actions:

[0791] The terminal uses the "JSON.stringify" function to convert the input information into JSON format.

[0792] Step 3:

[0793] The terminal sends the converted data to the server. Specifically, the data is sent using an HTTP POST request.

[0794] Input: User input data converted to JSON or XML format.

[0795] Output: Data to send to the server

[0796] Specific actions:

[0797] The terminal sends data to the server using the "fetch" function.

[0798] Step 4:

[0799] The server deserializes the data received from the terminal and converts it into an internal data structure. Specifically, it analyzes the data structure and separates user input information from sentiment information.

[0800] Input: Data in JSON or XML format sent from the device.

[0801] Output: User input information converted to an internal data structure

[0802] Specific actions:

[0803] The server uses the "JSON.parse" function to deserialize the received data.

[0804] Step 5:

[0805] Based on the analyzed data, the server uses external database APIs (e.g., Tabelog API, Google Maps API, TripAdvisor API) to collect travel information related to the user's input.

[0806] Input: User input information converted to an internal data structure

[0807] Output: Related travel information retrieved from an external database

[0808] Specific actions:

[0809] The server retrieves restaurant information via the Tabelog API and collects tourist information using the Google Maps API.

[0810] Step 6:

[0811] The server's generative AI and emotion engine generate the optimal travel plan based on collected travel information and user emotion information. The generative AI creates a specific travel schedule, while the emotion engine selects elements that are most appropriate for the user's emotions.

[0812] Input: Relevant travel information obtained from an external database, user sentiment information

[0813] Output: Optimal travel plan

[0814] Specific actions:

[0815] The server sends the following prompt to the generative artificial intelligence to generate the schedule:

[0816] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[0817] Step 7:

[0818] The server converts the generated travel plan back into JSON or XML format and sends it to the terminal as an HTTP response.

[0819] Input: Generated travel plan

[0820] Output: Plan data converted to JSON or XML format.

[0821] Specific actions:

[0822] The server uses the "JSON.stringify" function to convert the travel plan into JSON format and sends it to the terminal in the HTTP response.

[0823] Step 8:

[0824] The device analyzes the received travel plan and displays it to the user on the application screen. The display method includes a graphical interface with detailed information and links.

[0825] Input: Travel plan data in JSON format sent from the server.

[0826] Output: Display of travel plan for the user

[0827] Specific actions:

[0828] The device parses the received JSON data and displays the travel plan graphically to the user.

[0829] (Application Example 2)

[0830] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0831] Traditional content delivery services have struggled to provide personalized content tailored to users' interests and emotions. In particular, they lack mechanisms to suggest optimal content based on the specific emotional state a user is currently experiencing. As a result, users have to expend considerable effort to find content that matches their interests and mood, leading to decreased satisfaction.

[0832] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0833] In this invention, the server includes means for collecting user interest topics and current sentiment information, means for transmitting the collected user input information to the server, means for generating optimal content using generative artificial intelligence based on the user input information, means for transmitting the generated content to a terminal, and means for displaying the transmitted content to the user. This makes it possible to automatically suggest optimal content that matches the user's interests and sentiments.

[0834] "Topics of interest" refer to specific fields or themes that a user is interested in.

[0835] "Emotional information" refers to data that indicates the user's current mood and emotional state.

[0836] "Means of collection" refers to the methods and systems used to acquire and store information entered by users.

[0837] A "server" is a computer system that receives user input information and performs processing and analysis on it.

[0838] "Means of transmission" refers to methods or functions for transferring acquired information to other systems or terminals.

[0839] "Generative artificial intelligence" refers to algorithms and models that generate information tailored to user needs based on large amounts of data.

[0840] "Optimal content" refers to information and media that best match the user's interests and emotions.

[0841] A "terminal" is a device that a user uses to input information or view suggested information.

[0842] "Means of display" refers to methods or systems for providing generated information to users visually.

[0843] An "external database" is an external information resource used for searching and referencing information entered by the user.

[0844] "Music, video, or text" refers to various media content provided according to the user's interests and emotions.

[0845] This invention is a system that collects user interest topics and current sentiment information, and proposes optimal content using generative artificial intelligence and an external database. The program processing and details of this system are described below.

[0846] Program Processing Description

[0847] Hardware and software configuration

[0848] 1. Hardware

[0849] Device: Smartphone (iOS / Android compatible)

[0850] Server: A computer server (one with processing speed and storage capacity)

[0851] 2. Software

[0852] Smartphone application: Developed using React Native

[0853] Server-side applications: Server applications using Node.js

[0854] Generative artificial intelligence models: For example, OpenAI's GPT-3

[0855] Sentiment analysis engine: For example, IBM Watson's Sentiment Analysis

[0856] External database APIs: YouTube API, Spotify API, Google Books API, etc.

[0857] System operation

[0858] 1. Collection of user information

[0859] Users input their areas of interest (music, movies, reading, etc.) and their current emotional state (want to relax, want to feel energized, etc.) through a smartphone app.

[0860] The terminal converts the input information into JSON format and stores it temporarily.

[0861] 2. Sending data

[0862] The terminal sends the collected user input information to the server. Real-time data communication is achieved by using the Axios library for transmission.

[0863] 3. Analysis of Information

[0864] The server analyzes the received data and, based on that analysis, uses a combination of a generative artificial intelligence model (such as GPT-3) and an emotion analysis engine.

[0865] The generative artificial intelligence searches external databases based on topics of interest, and the sentiment analysis engine selects the most suitable content based on the user's emotional information.

[0866] 4. Content generation and transmission

[0867] The server generates the most suitable content, converts the recommendation list into JSON format, and sends it to the terminal.

[0868] The device analyzes the recommendation list and displays it in a way that the user can visually confirm.

[0869] Specific example

[0870] User input information

[0871] If the user enters "movie" and "want to relax".

[0872] Example of a prompt

[0873] The user entered "movie" and "want to relax." Please recommend a movie that is perfect for relaxation.

[0874] Examples of content recommendations

[0875] 1. Movie Search

[0876] The server uses external database APIs (such as the YouTube API and Netflix API) to collect movie lists based on the criterion of "relaxing movies."

[0877] The emotion analysis engine selects the best candidates from among "relaxing" movies, and a generative artificial intelligence model organizes them.

[0878] 2. Music Search

[0879] The server uses the Spotify API to collect playlists categorized as "relaxing music."

[0880] The emotion analysis engine selects the most suitable music album or playlist for the feeling of wanting to relax.

[0881] Display to the user

[0882] The device displays a generated list of recommended content to the user, allowing them to watch movies or play music on the spot.

[0883] This makes it possible to create a system that automatically provides the most suitable content simply by the user inputting their areas of interest and emotional information.

[0884] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0885] Step 1:

[0886] Collection of user information

[0887] Users use a smartphone app to input topics of interest (e.g., movies, music, reading) and their current emotional state (e.g., want to relax, want to feel energized).

[0888] Input: User-entered topics of interest and sentiment information.

[0889] Output: User information converted to JSON format.

[0890] Specific operation: A form for entering topics of interest and sentiment information is displayed through the user interface. Once the user enters the information and presses the submit button, the data is converted into JSON format.

[0891] Step 2:

[0892] Sending data

[0893] The terminal sends the collected user input information to the server.

[0894] Input: User information in JSON format.

[0895] Output: Data sent to the server.

[0896] Specific operation: The terminal uses the Axios library to send JSON-formatted data to the server-side endpoint via asynchronous communication.

[0897] Step 3:

[0898] Information analysis

[0899] The server analyzes the received data, identifies topics of interest to the user, and evaluates sentiment information.

[0900] Input: JSON formatted data sent to the server.

[0901] Output: Analysis results based on user interest and sentiment information.

[0902] Specific operation: The server parses the received JSON data and passes it to a generative artificial intelligence model and sentiment analysis engine to analyze the topics of interest and sentiment information.

[0903] Step 4:

[0904] Content generation

[0905] The server uses generative artificial intelligence and sentiment analysis engines to generate optimal content.

[0906] Input: Analyzed user interest topics and sentiment information.

[0907] Output: A list of recommended content that is best suited for your needs.

[0908] Specific operation: Interest topics and sentiment information are input into prompts of a generative artificial intelligence model (such as GPT-3), and the system uses an external database API to collect and generate optimal content.

[0909] Step 5:

[0910] Send content

[0911] The server converts the generated content recommendation list into JSON format and sends it to the terminal.

[0912] Input: A list of recommended content that is best suited for your needs.

[0913] Output: JSON formatted data sent to the terminal.

[0914] Specific operation: Serialize the recommendation list into JSON format and send it to the endpoint on the terminal side.

[0915] Step 6:

[0916] Display content

[0917] The device analyzes the received content recommendation list and displays it visually to the user.

[0918] Input: JSON formatted data sent to the terminal.

[0919] Output: A list of content recommendations displayed visually to the user.

[0920] Specific operation: The device parses the received JSON data and displays detailed content information in the user interface. The user can then watch recommended movies or play music.

[0921] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0922] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0923] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0924] [Third Embodiment]

[0925] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0926] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0927] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0928] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0929] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0930] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0931] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0932] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0933] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0934] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0935] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0936] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0937] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. The following describes the program processing of this system and a specific example in natural language.

[0938] System Overview

[0939] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external database.

[0940] Program Processing Description

[0941] 1. Collection of input information

[0942] The user enters detailed information such as their travel destination, mood, leisure activities, desired food, and budget on the application screen.

[0943] The device collects and temporarily stores information entered by the user.

[0944] 2. Sending data

[0945] The terminal sends the collected user input information to the server.

[0946] The server analyzes the received data and interprets the user's request.

[0947] 3. Information Analysis and Plan Generation

[0948] The server searches external databases based on user input and collects relevant travel information.

[0949] Generative artificial intelligence uses collected data to generate travel plans that are optimal for the user's needs. Specifically, it selects the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired cuisine, and leisure activities.

[0950] 4. Sending and displaying plans

[0951] The server sends the generated travel plan to the device.

[0952] The device displays the received travel plan to the user.

[0953] Specific example

[0954] User input information

[0955] The user enters "Tokyo," "relax," "feel nature," "sushi," and "budget of 50,000 yen."

[0956] Example of plan generation

[0957] 1. Restaurant Search

[0958] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[0959] 2. Search for tourist destinations

[0960] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[0961] 3. Search for accommodations

[0962] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[0963] 4. Creating a travel plan

[0964] The generative artificial intelligence will create a specific schedule for days 1 through 3 based on the above conditions. For example, on day 1, it might have dinner at a sushi restaurant in Ginza; on day 2, it might visit Ueno Zoo and have a sushi lunch; and on day 3, it might visit Senso-ji Temple and select accommodation.

[0965] Suggestions for users

[0966] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[0967] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[0968] The following describes the processing flow.

[0969] Step 1:

[0970] The user enters detailed travel information. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, and budget from text boxes or dropdown menus on the application screen.

[0971] Step 2:

[0972] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user in variables or data storage.

[0973] Step 3:

[0974] The device converts the collected information into JSON or XML format and sends it to the server. Specifically, it sends the data to the server using HTTP requests.

[0975] Step 4:

[0976] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables.

[0977] Step 5:

[0978] The server searches an external database to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist attraction information, and accommodation information from the external database.

[0979] Step 6:

[0980] Based on data acquired by the server, generative artificial intelligence is used to generate the optimal travel plan. Specifically, the user's input information and acquired data are passed to an algorithm, which selects restaurants, tourist destinations, and accommodations that meet the criteria, and then creates a travel schedule.

[0981] Step 7:

[0982] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to send the data back to the device.

[0983] Step 8:

[0984] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format.

[0985] Step 9:

[0986] Users review the proposed plan and, if necessary, view further details or proceed with the booking process. Specifically, links are set up in each plan item so that clicking them opens the booking site or detailed information page.

[0987] (Example 1)

[0988] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0989] Traditional travel planning systems require users to individually gather information and create their own plans, which is very time-consuming. Furthermore, if the collected information is insufficient, it becomes difficult to create an optimal travel plan. Thus, there is a challenge in that it is difficult for users to easily obtain high-quality travel plans.

[0990] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0991] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure, meals, and budget; means for transmitting the collected user input information to an information processing device; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan to a display device; and means for displaying the transmitted travel plan to the user. This makes it possible for users to easily and quickly obtain a high-quality, optimal travel plan.

[0992] A "travel destination" refers to a geographical location that the user wishes to visit.

[0993] "Mood" refers to the user's hopes and desires regarding their mental state and atmosphere during their trip.

[0994] "Leisure" refers to the activities and recreation that users want to enjoy while traveling.

[0995] "Meals" refers to the dishes and foods that the user wants to eat during their trip.

[0996] "Budget" refers to the amount of money a user plans to spend on a trip.

[0997] A "user" is someone who intends to use a travel plan.

[0998] "Input information" refers to the detailed travel information that the user provides to the system.

[0999] An "information processing device" is a device used to process data collected from users.

[1000] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate results based on specific input data.

[1001] A "travel plan" refers to suggestions and schedules related to a user's trip.

[1002] A "display device" is a device used to display the generated travel plan to the user.

[1003] A "data repository" is a database or API used to retrieve information from external sources in order to generate travel plans.

[1004] A "food and beverage establishment" refers to a shop or restaurant where users eat.

[1005] A "tourist attraction" refers to a tourist destination or landmark that users should visit.

[1006] "Accommodation facilities" refer to hotels, guesthouses, and other accommodations where users can stay.

[1007] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. This system includes several main components. Specific embodiments are described below.

[1008] System Overview

[1009] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external data repository.

[1010] Collect input information

[1011] The user enters detailed information such as travel destination, mood, leisure activities, meals, and budget through the application screen. For example, consider a case where the user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," and "Budget of 50,000 yen."

[1012] The device collects and temporarily stores information entered by the user. This typically involves using the local storage of a mobile device or PC. The device then converts the stored information into JSON format to facilitate subsequent data transmission and analysis.

[1013] Data transmission and analysis

[1014] The terminal sends the collected user input information to the server. Here, the data is transmitted securely using the HTTPS protocol. The server analyzes the received data and interprets the user's requests. Specifically, the data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[1015] Use of external data repositories

[1016] Based on the user's requests, the server searches external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and collects relevant travel information. For example, using the conditions "Tokyo" and "sushi," it retrieves data on highly-rated sushi restaurants using the Tabelog API. Similarly, using the conditions "Tokyo" and "experience nature," it retrieves data on tourist destinations rich in nature using the TripAdvisor API.

[1017] Travel plan generation

[1018] The server passes the collected data to the generative artificial intelligence (AI). Specifically, it inputs JSON data as prompts into the AI. The AI ​​then generates the optimal travel plan based on the input data. For example, the prompts can be set as follows:

[1019] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[1020] Proposed plan:

[1021] Day 1: Dinner at a sushi restaurant in Ginza

[1022] Day 2: Ueno Zoo and sushi lunch

[1023] Day 3: Visit to Senso-ji Temple and accommodation

[1024] Generative artificial intelligence generates and proposes travel plans that are best suited to the user's needs.

[1025] Sending and displaying plans

[1026] The server sends the generated travel plan to the device. Typically, an HTTP POST request is used for this transmission. The device then displays the received travel plan on the application screen. A user interface (e.g., an application using React or Flutter) is often used here.

[1027] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[1028] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[1029] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1030] Step 1: Collecting input information

[1031] Users enter detailed information such as their travel destination, mood, leisure activities, meals, and budget through the application screen.

[1032] Input: Detailed travel information entered by the user (e.g., "Tokyo", "Relax", "Experience nature", "Sushi", "Budget 50,000 yen")

[1033] Output: Collected user input information

[1034] The device temporarily stores the information entered by the user.

[1035] Operation: Saves data to the local storage of mobile devices or PCs.

[1036] The device converts the saved information into JSON format.

[1037] Operation: Converts input information into JSON format data to prepare for subsequent processing.

[1038] Step 2: Send

[1039] The terminal sends the collected user input information to the server.

[1040] Operation: Securely transmits data using the HTTPS protocol.

[1041] Input: User input information converted to JSON format

[1042] Output: User input information sent to the server

[1043] The server analyzes the received data and interprets the user's request.

[1044] Operation: Data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[1045] Input: User input information in JSON format received

[1046] Output: Information on analyzed user requests

[1047] Step 3: Using an external data repository

[1048] Based on the user's requests, the server searches external data repositories and collects relevant travel information.

[1049] Operation: Sends requests to external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and retrieves the necessary information.

[1050] Input: Information about the analyzed user requests

[1051] Output: Travel information retrieved from an external data repository

[1052] Specific example:

[1053] The server uses the Tabelog API to retrieve data on highly-rated sushi restaurants based on the conditions "Tokyo" and "sushi".

[1054] The server uses the TripAdvisor API to retrieve data on tourist destinations rich in nature, based on the conditions of "Tokyo" and "experiencing nature."

[1055] Step 4: Creating a travel plan

[1056] The server passes the collected data to a generative artificial intelligence.

[1057] Operation: Inputs JSON formatted data as a prompt into a generative artificial intelligence.

[1058] Input: Travel information retrieved from an external data repository

[1059] Output: Travel plan generated by a generative artificial intelligence system

[1060] Generative artificial intelligence generates the optimal travel plan based on input data.

[1061] Specific example:

[1062] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[1063] Proposed plan:

[1064] Day 1: Dinner at a sushi restaurant in Ginza

[1065] Day 2: Ueno Zoo and sushi lunch

[1066] Day 3: Visit to Senso-ji Temple and accommodation

[1067] Step 5: Submit and view your plan

[1068] The server sends the generated travel plan to the device.

[1069] Operation: Sends travel plans using an HTTP POST request.

[1070] Input: Travel plan generated by a generative artificial intelligence system

[1071] Output: Travel plan sent to the terminal

[1072] The device displays the received travel plan to the user.

[1073] Operation: Displays travel plans through a user interface (e.g., an application using React or Flutter).

[1074] Input: Travel plan sent from the server

[1075] Output: Travel plan displayed to the user

[1076] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[1077] (Application Example 1)

[1078] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1079] When planning a trip, it is time-consuming and burdensome for users to manually gather a lot of information and create a plan. Furthermore, there is a lack of means to provide real-time information during the trip, making it difficult to obtain local navigation and recommendations.

[1080] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1081] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure activities, desired meals, and budget; means for transmitting the collected user input information to the server; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan and real-time information to the user device; and means for displaying the transmitted travel plan and real-time information to the user and providing navigation and additional information. As a result, the user can efficiently and easily plan a trip and obtain necessary information in real time while traveling.

[1082] "User device" is a general term for terminal devices used by users, and includes smartphones, tablets, smart glasses, etc.

[1083] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates the optimal travel plan based on user input.

[1084] A "travel plan" refers to a detailed plan of what a user will do during their trip, including elements such as destination, sightseeing spots, accommodations, restaurants, and budget.

[1085] "Real-time information" refers to providing users with the latest data and navigation information at any given time while they are traveling.

[1086] "Navigation" refers to a function that guides the user to the optimal route and steps to their destination based on their current location.

[1087] An "external database" is an external source of information used to generate travel plans, and includes information on tourist attractions, restaurants, accommodations, etc.

[1088] A "tourist destination" refers to a place or region in a travel destination that is worth visiting, and includes natural landscapes, historical buildings, cultural facilities, and so on.

[1089] "Eating establishments" refer to places where customers eat, and include restaurants, cafes, and diners.

[1090] "Accommodation" refers to the place where a user stays during their trip, and includes hotels, inns, guesthouses, and so on.

[1091] This invention relates to a system that uses generative artificial intelligence to propose an optimal travel plan based on the input of detailed travel information. Its specific configuration and operation are described below.

[1092] System Overview

[1093] This system aims to provide users with efficient and real-time information for planning and executing their travel plans. Its main components include user devices, servers, generative artificial intelligence, and external databases.

[1094] Program Processing Description

[1095] 1. Collection of input information

[1096] The user enters detailed information such as travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. The user device temporarily stores this entered information.

[1097] 2. Sending data

[1098] The user device sends the collected user input information to a server in the cloud. The server analyzes the received data and interprets the user's requests.

[1099] 3. Information analysis and travel plan generation

[1100] The server searches an external database based on the user's input and collects relevant travel information. Generative artificial intelligence then uses this collected data to generate a travel plan optimized for the user's needs. Specifically, it selects the best restaurants, tourist attractions, and accommodations based on the travel destination, budget, meals, and leisure activities.

[1101] 4. Provision of real-time information

[1102] The server sends real-time information to the user's device along with the generated travel plan. For example, it can use AR functionality to provide local information and navigation to the user's smart glasses.

[1103] 5. Presentation of travel plan and navigation

[1104] The user device displays the generated travel plan and real-time information to the user. Furthermore, it uses navigation functions to support the user's actions at the destination and presents additional information and recommendations.

[1105] Specific example

[1106] The user enters their travel preferences into their smartphone, such as "Destination: Tokyo, I want to relax, I want to go somewhere with nature, I want to eat sushi, budget: 50,000 yen." Based on this information, the server generates a travel plan, selecting information such as highly-rated sushi restaurants in Ginza, Ueno Zoo, and Senso-ji Temple. It also lists and presents multiple accommodation options within the budget. Furthermore, upon arrival at the destination, smart glasses use augmented reality (AR) to display the optimal route and timely recommendations in real time.

[1107] Example of a prompt

[1108] "Please suggest a travel plan for Tokyo, where I want to relax, experience nature, eat sushi, and have a budget of 50,000 yen."

[1109] With this configuration, the system allows users to simply input travel information, and the generative artificial intelligence utilizes advanced technology to provide an optimal travel plan. Furthermore, it can enhance the user's travel experience by providing on-site navigation and real-time information.

[1110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1111] Step 1:

[1112] Users input detailed information such as their travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. This input information is temporarily stored in a database within the user device. Specifically, text data is collected through the user device's interface.

[1113] Input: Detailed information entered by the user, such as travel destination, mood, leisure activities, desired meals, and budget.

[1114] Output: Detailed information data stored on the user's device

[1115] Step 2:

[1116] The user device sends the collected user input information to a server in the cloud. During transmission, the information stored in the database within the user device is sent to the server via an API request.

[1117] Input: Detailed information data stored on the user's device

[1118] Output: Detailed information data sent to a server in the cloud.

[1119] Step 3:

[1120] The server analyzes the received data and interprets the user's requests. Based on the received information, it understands the travel experience the user desires and sets search criteria accordingly.

[1121] Input: Detailed information data sent to a server in the cloud.

[1122] Output: Search criteria interpreted from user requests

[1123] Step 4:

[1124] The server searches external databases based on user input and collects relevant travel information. Specifically, it retrieves information on restaurants, tourist attractions, accommodations, etc., via APIs.

[1125] Input: Search criteria interpreted from user requests

[1126] Output: Travel information retrieved from an external database

[1127] Step 5:

[1128] Generative artificial intelligence generates optimal travel plans tailored to the user's needs based on collected travel information. Specifically, it combines collected information on restaurants, tourist attractions, and accommodations to create a travel schedule that matches the user's preferences and budget.

[1129] Input: Travel information obtained from an external database

[1130] Output: Generated travel plan

[1131] Step 6:

[1132] The server sends real-time information to the user's device along with the generated travel plan. This real-time information includes local weather information, traffic conditions, and the latest event information.

[1133] Input: Generated travel plan

[1134] Output: Travel plans and real-time information sent to the user's device.

[1135] Step 7:

[1136] The user device displays the received travel plan and real-time information to the user. Furthermore, it uses navigation functionality to provide route guidance and additional recommendations based on the user's current location. When using smart glasses, augmented reality (AR) functionality is used to display local information and navigation information.

[1137] Input: Travel plans and real-time information sent to the user's device.

[1138] Output: Travel plan and real-time information displayed to the user.

[1139] Through the above processing steps, users can efficiently plan their trips and always have access to the latest information while traveling. As an example of a specific prompt to the generating AI model, the following is used: "Please suggest a travel plan for Tokyo, where I want to relax, where I can experience nature, where I want to eat sushi, and with a budget of 50,000 yen."

[1140] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1141] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest the optimal travel plan based on the user's input of detailed travel information and emotional information. The following describes the program processing of this system and a specific example in natural language.

[1142] System Overview

[1143] This system collects user input information and emotional data, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include a terminal, a server, generative artificial intelligence, an emotional engine, and an external database.

[1144] Program Processing Description

[1145] 1. Collection of input information

[1146] Users input detailed information such as their travel destination, mood, leisure activities, desired food, budget, and emotional information on the application screen.

[1147] The device collects and temporarily stores information entered by the user.

[1148] 2. Sending data

[1149] The terminal converts the collected user input information and sentiment information into JSON or XML format and sends it to the server.

[1150] The server analyzes the received data and interprets the user's requests and emotions.

[1151] 3. Information Analysis and Plan Generation

[1152] The server searches external databases and collects relevant travel information based on user input and sentiment information.

[1153] Generative artificial intelligence and an emotion engine use collected data to generate travel plans that are optimally suited to the user's requests and emotions. Specifically, they select the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired food, leisure activities, and emotions.

[1154] 4. Sending and displaying plans

[1155] The server converts the generated travel plan into JSON or XML format and sends it to the terminal.

[1156] The device analyzes the received travel plan and displays it on the application screen.

[1157] Specific example

[1158] User input information

[1159] The user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[1160] Example of plan generation

[1161] 1. Restaurant Search

[1162] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[1163] The emotional engine further filters out shops with a quiet and relaxing atmosphere that are considered good for stress relief.

[1164] 2. Search for tourist destinations

[1165] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[1166] The emotional engine selects quiet, natural spots where you can relax.

[1167] 3. Search for accommodations

[1168] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[1169] The emotional engine selects accommodations in quiet environments suitable for stress relief.

[1170] 4. Creating a travel plan

[1171] The generative artificial intelligence and emotion engine will create a specific schedule for days 1 through 3 based on the above conditions. For example, day 1 might include dinner at a quiet sushi restaurant in Ginza, day 2 might involve a visit to Ueno Zoo and a stroll through relaxing nature spots, and day 3 might include a visit to Senso-ji Temple and the selection of accommodation suitable for stress relief.

[1172] Suggestions for users

[1173] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[1174] In this way, by simply having the user input detailed travel information and emotional information, the generative artificial intelligence and emotion engine analyze all the information and provide an optimal travel plan that also takes the user's emotions into consideration, significantly reducing the effort required from the user and enabling a more satisfying travel experience. With this system, users can easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[1175] The following describes the processing flow.

[1176] Step 1:

[1177] The user enters travel details and emotional information on the application screen. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, budget, and emotional information (e.g., want to relax, relieve stress) from text boxes or dropdown menus.

[1178] Step 2:

[1179] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user. For example, it collects data such as "Tokyo" for travel destination, "Relaxed" for mood, and "Stress Relief" for emotional information.

[1180] Step 3:

[1181] The device collects information, converts it into JSON or XML format, and sends it to the server. Specifically, it sends data to the server using HTTP requests. An example of the format sent is {"destination": "Tokyo", "mood": "relax", "activity": "nature", "food": "sushi", "budget": "50000", "emotion": "stress relief"}.

[1182] Step 4:

[1183] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables. For example, it might store information such as travel destination "Tokyo," mood "relaxed," and emotional information "stress relief" in variables.

[1184] Step 5:

[1185] The server searches external databases to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist information, and accommodation information from external databases. For example, it might search for "Tokyo sushi" using the Tabelog API and "Tokyo nature tourist spots" using the TripAdvisor API.

[1186] Step 6:

[1187] The server uses an emotion engine to analyze the user's emotional information. Specifically, the emotion engine filters restaurants, tourist destinations, and accommodations based on emotions such as "stress relief," suggesting relaxing environments.

[1188] Step 7:

[1189] Generative artificial intelligence generates the optimal travel plan based on the user's input information and emotional information. Specifically, it selects restaurants, tourist attractions, and accommodations that meet the criteria and creates a detailed schedule for each day. For example, on day 1, it might include dinner at a quiet sushi restaurant in Ginza, on day 2, a visit to Ueno Zoo and a stroll through a relaxing nature spot, and on day 3, a visit to Senso-ji Temple and a quiet accommodation.

[1190] Step 8:

[1191] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to return the data to the device. An example format is: {"day1": {"arrival_time": "13:00", "dinner": "Sushi restaurant in Ginza", "cost": 15000}, "day2": {"morning": "Ueno Zoo", "lunch": "Quiet sushi lunch", "afternoon": "Relaxing nature spot", "cost": 5000}, "day3": {"morning": "Senso-ji Temple", "afternoon": "Quiet accommodation", "cost": 10000}}

[1192] Step 9:

[1193] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format. For example, it might display "Sushi restaurant in Ginza" for dinner on day 1, and "Ueno Zoo" for the morning of day 2.

[1194] Step 10:

[1195] The user reviews the suggested plan and, if necessary, checks further details or proceeds with the booking process. Specifically, links are set up for each plan item, so that clicking them opens the booking site or detailed information page. For example, clicking the "Sushi restaurant in Ginza" link will open the restaurant's booking page.

[1196] (Example 2)

[1197] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1198] Conventional travel plan generation systems require users to manually create detailed travel plans, which is time-consuming and laborious. Furthermore, it is often difficult to create plans that take into account the user's emotional state and specific requests, resulting in unsatisfactory plans. This invention aims to increase user satisfaction by automatically generating optimal travel plans based on user input and emotional information.

[1199] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's travel destination, mood, leisure, meals, budget, and emotional information; means for temporarily storing the input information on the terminal; means for converting the stored information into JSON or XML format and sending it to the server; means for analyzing the information received by the server and collecting relevant travel information using an external database; means for generating an optimal travel plan based on the collected information and the user's emotional state using generative artificial intelligence and an emotional engine; means for converting the generated travel plan into JSON or XML format and sending it to the terminal; and means for displaying the transmitted travel plan on the terminal's application screen. This makes it possible to automatically generate an optimal travel plan based on the user's input information and emotional information, saving the user time and providing a higher level of satisfaction.

[1200] "User input information" refers to all information that the user enters into the application screen, including travel destination, mood, leisure activities, meals, budget, and emotional information.

[1201] A "terminal" refers to a device used by a user to input information and send it to a server, and includes smartphones, tablets, and personal computers.

[1202] A "server" is a computer system that receives user input information, analyzes it, and performs all the necessary backend processing to generate a travel plan.

[1203] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a text format that is easy for both humans and machines to read.

[1204] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structurally representing data.

[1205] "Generative artificial intelligence" refers to an artificial intelligence model used to generate optimal travel plans by analyzing user input information and emotional information.

[1206] An "emotion engine" is a software component used to interpret a user's emotional state and select the optimal travel plan elements based on that information.

[1207] An "external database" is an external data source that provides travel information, restaurant information, accommodation information, etc., and can be accessed by the server via an API.

[1208] A "travel plan" is a travel schedule and activity plan generated based on the user's input information and emotional information, and includes specific information such as restaurants, tourist destinations, and accommodations.

[1209] The "application screen" is a software interface used by users to input travel details and sentiment information and to review the generated travel plan.

[1210] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest an optimal travel plan based on the user's input of detailed travel information and emotional information. The system of this invention includes a terminal, a server, generative artificial intelligence, an emotion engine, and an external database. The implementation of this system is described in detail below.

[1211] 1. Collecting user input information

[1212] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The input method involves filling in each field on a form displayed on the screen. For example, information such as "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief" might be entered.

[1213] 2. Information storage and transmission

[1214] The terminal collects user input in real time and temporarily stores it in memory. The collected data is then converted to JSON or XML format. The converted data is sent to the server via an HTTP POST request.

[1215] 3. Information analysis on the server

[1216] The server deserializes the data received from the terminal and converts it into an internal data structure. Next, it searches external databases and collects relevant travel information based on the user's input. Specifically, it uses the Tabelog API and Google Maps API to obtain restaurant information and the TripAdvisor API and Google Maps API to collect tourist destination information.

[1217] 4. Creating a travel plan

[1218] The server uses generative artificial intelligence and an emotion engine to generate the optimal travel plan based on collected travel information and user sentiment data. The generative AI creates a travel schedule tailored to the user's specific requests, while the emotion engine selects restaurants, tourist destinations, and accommodations that are best suited to the user's emotional state.

[1219] Examples of specific prompt messages include the following:

[1220] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[1221] 5. Sending and displaying plans

[1222] The generated travel plan is converted back into JSON or XML format and sent to the terminal as an HTTP response. The terminal parses the received data and displays the travel plan to the user on the application screen. This display uses a graphical interface that includes detailed information and links.

[1223] For example, the following travel plan might be generated:

[1224] Day 1: Dinner at a quiet sushi restaurant in Ginza

[1225] Day 2: A relaxing stroll through nature in Ueno Park.

[1226] Day 3: Visit Senso-ji Temple and stay at accommodation suitable for stress relief.

[1227] This system allows generative artificial intelligence and an emotion engine to automatically generate the optimal travel plan based on the information entered by the user, saving the user time and providing a higher level of satisfaction.

[1228] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1229] Step 1:

[1230] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The information entered by the user is entered into a form and sent to the device when the submit button is clicked. This input information includes things like "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[1231] Input: User input of travel destination, mood, leisure, food, budget, and emotional information.

[1232] Output: Sending the input information to the terminal.

[1233] Specific actions:

[1234] The user enters information into each field and clicks the submit button.

[1235] The terminal verifies the input content and checks for any input errors.

[1236] Step 2:

[1237] The terminal collects user input in real time and temporarily stores it in memory. The collected information is converted to either JSON or XML format. For example, in the case of JSON format, the "JSON.stringify" function is used.

[1238] Input: Collected user input information

[1239] Output: Data converted to JSON or XML format.

[1240] Specific actions:

[1241] The terminal uses the "JSON.stringify" function to convert the input information into JSON format.

[1242] Step 3:

[1243] The terminal sends the converted data to the server. Specifically, the data is sent using an HTTP POST request.

[1244] Input: User input data converted to JSON or XML format.

[1245] Output: Data to send to the server

[1246] Specific actions:

[1247] The terminal sends data to the server using the "fetch" function.

[1248] Step 4:

[1249] The server deserializes the data received from the terminal and converts it into an internal data structure. Specifically, it analyzes the data structure and separates user input information from sentiment information.

[1250] Input: Data in JSON or XML format sent from the device.

[1251] Output: User input information converted to an internal data structure

[1252] Specific actions:

[1253] The server uses the "JSON.parse" function to deserialize the received data.

[1254] Step 5:

[1255] Based on the analyzed data, the server uses external database APIs (e.g., Tabelog API, Google Maps API, TripAdvisor API) to collect travel information related to the user's input.

[1256] Input: User input information converted to an internal data structure

[1257] Output: Related travel information retrieved from an external database

[1258] Specific actions:

[1259] The server retrieves restaurant information via the Tabelog API and collects tourist information using the Google Maps API.

[1260] Step 6:

[1261] The server's generative AI and emotion engine generate the optimal travel plan based on collected travel information and user emotion information. The generative AI creates a specific travel schedule, while the emotion engine selects elements that best suit the user's emotions.

[1262] Input: Relevant travel information obtained from an external database, user sentiment information

[1263] Output: Optimal travel plan

[1264] Specific actions:

[1265] The server sends the following prompt to the generative artificial intelligence to generate the schedule:

[1266] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[1267] Step 7:

[1268] The server converts the generated travel plan back into JSON or XML format and sends it to the terminal as an HTTP response.

[1269] Input: Generated travel plan

[1270] Output: Plan data converted to JSON or XML format.

[1271] Specific actions:

[1272] The server uses the "JSON.stringify" function to convert the travel plan into JSON format and sends it to the terminal in the HTTP response.

[1273] Step 8:

[1274] The device analyzes the received travel plan and displays it to the user on the application screen. The display method includes a graphical interface with detailed information and links.

[1275] Input: Travel plan data in JSON format sent from the server.

[1276] Output: Display of travel plan for the user

[1277] Specific actions:

[1278] The device parses the received JSON data and displays the travel plan graphically to the user.

[1279] (Application Example 2)

[1280] Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[1281] Traditional content delivery services have struggled to provide personalized content tailored to users' interests and emotions. In particular, they lack mechanisms to suggest optimal content based on the specific emotional state a user is currently experiencing. As a result, users have to expend considerable effort to find content that matches their interests and mood, leading to decreased satisfaction.

[1282] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1283] In this invention, the server includes means for collecting user interest topics and current sentiment information, means for transmitting the collected user input information to the server, means for generating optimal content using generative artificial intelligence based on the user input information, means for transmitting the generated content to a terminal, and means for displaying the transmitted content to the user. This makes it possible to automatically suggest optimal content that matches the user's interests and sentiments.

[1284] "Topics of interest" refer to specific fields or themes that a user is interested in.

[1285] "Emotional information" refers to data that indicates the user's current mood and emotional state.

[1286] "Means of collection" refers to the methods and systems used to acquire and store information entered by users.

[1287] A "server" is a computer system that receives user input information and performs processing and analysis on it.

[1288] "Means of transmission" refers to methods or functions for transferring acquired information to other systems or terminals.

[1289] "Generative artificial intelligence" refers to algorithms and models that generate information tailored to user needs based on large amounts of data.

[1290] "Optimal content" refers to information and media that best match the user's interests and emotions.

[1291] A "terminal" is a device that a user uses to input information or view suggested information.

[1292] "Means of display" refers to methods or systems for providing generated information to users visually.

[1293] An "external database" is an external information resource used for searching and referencing information entered by the user.

[1294] "Music, video, or text" refers to various media content provided according to the user's interests and emotions.

[1295] This invention is a system that collects user interest topics and current sentiment information, and proposes optimal content using generative artificial intelligence and an external database. The program processing and details of this system are described below.

[1296] Program Processing Description

[1297] Hardware and software configuration

[1298] 1. Hardware

[1299] Device: Smartphone (iOS / Android compatible)

[1300] Server: A computer server (one with processing speed and storage capacity)

[1301] 2. Software

[1302] Smartphone application: Developed using React Native

[1303] Server-side applications: Server applications using Node.js

[1304] Generative artificial intelligence models: For example, OpenAI's GPT-3

[1305] Sentiment analysis engine: For example, IBM Watson's Sentiment Analysis

[1306] External database APIs: YouTube API, Spotify API, Google Books API, etc.

[1307] System operation

[1308] 1. Collection of user information

[1309] Users input their areas of interest (music, movies, reading, etc.) and their current emotional state (want to relax, want to feel energized, etc.) through a smartphone app.

[1310] The terminal converts the input information into JSON format and stores it temporarily.

[1311] 2. Sending data

[1312] The terminal sends the collected user input information to the server. Real-time data communication is achieved by using the Axios library for transmission.

[1313] 3. Analysis of Information

[1314] The server analyzes the received data and, based on that analysis, uses a combination of a generative artificial intelligence model (such as GPT-3) and an emotion analysis engine.

[1315] The generative artificial intelligence searches external databases based on topics of interest, and the sentiment analysis engine selects the most suitable content based on the user's emotional information.

[1316] 4. Content generation and transmission

[1317] The server generates the most suitable content, converts the recommendation list into JSON format, and sends it to the terminal.

[1318] The device analyzes the recommendation list and displays it in a way that the user can visually confirm.

[1319] Specific example

[1320] User input information

[1321] If the user enters "movie" and "want to relax".

[1322] Example of a prompt

[1323] The user entered "movie" and "want to relax." Please recommend a movie that is perfect for relaxation.

[1324] Examples of content recommendations

[1325] 1. Movie Search

[1326] The server uses external database APIs (such as the YouTube API and Netflix API) to collect movie lists based on the criterion of "relaxing movies."

[1327] The emotion analysis engine selects the best candidates from among "relaxing" movies, and a generative artificial intelligence model organizes them.

[1328] 2. Music Search

[1329] The server uses the Spotify API to collect playlists categorized as "relaxing music."

[1330] The emotion analysis engine selects the most suitable music album or playlist for the feeling of wanting to relax.

[1331] Display to the user

[1332] The device displays a generated list of recommended content to the user, allowing them to watch movies or play music on the spot.

[1333] This makes it possible to create a system that automatically provides the most suitable content simply by the user inputting their areas of interest and emotional information.

[1334] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1335] Step 1:

[1336] Collection of user information

[1337] Users use a smartphone app to input topics of interest (e.g., movies, music, reading) and their current emotional state (e.g., want to relax, want to feel energized).

[1338] Input: User-entered topics of interest and sentiment information.

[1339] Output: User information converted to JSON format.

[1340] Specific operation: A form for entering topics of interest and sentiment information is displayed through the user interface. Once the user enters the information and presses the submit button, the data is converted into JSON format.

[1341] Step 2:

[1342] Sending data

[1343] The terminal sends the collected user input information to the server.

[1344] Input: User information in JSON format.

[1345] Output: Data sent to the server.

[1346] Specific operation: The terminal uses the Axios library to send JSON-formatted data to the server-side endpoint via asynchronous communication.

[1347] Step 3:

[1348] Information analysis

[1349] The server analyzes the received data, identifies topics of interest to the user, and evaluates sentiment information.

[1350] Input: JSON formatted data sent to the server.

[1351] Output: Analysis results based on user interest and sentiment information.

[1352] Specific operation: The server parses the received JSON data and passes it to a generative artificial intelligence model and sentiment analysis engine to analyze the topics of interest and sentiment information.

[1353] Step 4:

[1354] Content generation

[1355] The server uses generative artificial intelligence and sentiment analysis engines to generate optimal content.

[1356] Input: Analyzed user interest topics and sentiment information.

[1357] Output: A list of recommended content that is best suited for your needs.

[1358] Specific operation: Interest topics and sentiment information are input into prompts of a generative artificial intelligence model (such as GPT-3), and the system uses an external database API to collect and generate optimal content.

[1359] Step 5:

[1360] Send content

[1361] The server converts the generated content recommendation list into JSON format and sends it to the terminal.

[1362] Input: A list of recommended content that is best suited for your needs.

[1363] Output: JSON formatted data sent to the terminal.

[1364] Specific operation: Serialize the recommendation list into JSON format and send it to the endpoint on the terminal side.

[1365] Step 6:

[1366] Display content

[1367] The device analyzes the received content recommendation list and displays it visually to the user.

[1368] Input: JSON formatted data sent to the terminal.

[1369] Output: A list of content recommendations displayed visually to the user.

[1370] Specific operation: The device parses the received JSON data and displays detailed content information in the user interface. The user can then watch recommended movies or play music.

[1371] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1372] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1373] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1374] [Fourth Embodiment]

[1375] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1376] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1377] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1378] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1379] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1380] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1381] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1382] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1383] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1384] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1385] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1386] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1387] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1388] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. The following describes the program processing of this system and a specific example in natural language.

[1389] System Overview

[1390] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external database.

[1391] Program Processing Description

[1392] 1. Collection of input information

[1393] The user enters detailed information such as their travel destination, mood, leisure activities, desired food, and budget on the application screen.

[1394] The device collects and temporarily stores information entered by the user.

[1395] 2. Sending data

[1396] The terminal sends the collected user input information to the server.

[1397] The server analyzes the received data and interprets the user's request.

[1398] 3. Information Analysis and Plan Generation

[1399] The server searches external databases based on user input and collects relevant travel information.

[1400] Generative artificial intelligence uses collected data to generate travel plans that are optimal for the user's needs. Specifically, it selects the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired cuisine, and leisure activities.

[1401] 4. Sending and displaying plans

[1402] The server sends the generated travel plan to the device.

[1403] The device displays the received travel plan to the user.

[1404] Specific example

[1405] User input information

[1406] The user enters "Tokyo," "relax," "feel nature," "sushi," and "budget of 50,000 yen."

[1407] Example of plan generation

[1408] 1. Restaurant Search

[1409] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[1410] 2. Search for tourist destinations

[1411] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[1412] 3. Search for accommodations

[1413] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[1414] 4. Creating a travel plan

[1415] The generative artificial intelligence will create a specific schedule for days 1 through 3 based on the above conditions. For example, on day 1, it might have dinner at a sushi restaurant in Ginza; on day 2, it might visit Ueno Zoo and have a sushi lunch; and on day 3, it might visit Senso-ji Temple and select accommodation.

[1416] Suggestions for users

[1417] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[1418] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[1419] The following describes the processing flow.

[1420] Step 1:

[1421] The user enters detailed travel information. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, and budget from text boxes or dropdown menus on the application screen.

[1422] Step 2:

[1423] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user in variables or data storage.

[1424] Step 3:

[1425] The device converts the collected information into JSON or XML format and sends it to the server. Specifically, it sends the data to the server using HTTP requests.

[1426] Step 4:

[1427] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables.

[1428] Step 5:

[1429] The server searches an external database to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist attraction information, and accommodation information from the external database.

[1430] Step 6:

[1431] Based on data acquired by the server, generative artificial intelligence is used to generate the optimal travel plan. Specifically, the user's input information and acquired data are passed to an algorithm, which selects restaurants, tourist destinations, and accommodations that meet the criteria, and then creates a travel schedule.

[1432] Step 7:

[1433] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to send the data back to the device.

[1434] Step 8:

[1435] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format.

[1436] Step 9:

[1437] Users review the proposed plan and, if necessary, view further details or proceed with the booking process. Specifically, links are set up in each plan item so that clicking them opens the booking site or detailed information page.

[1438] (Example 1)

[1439] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1440] Traditional travel planning systems require users to individually gather information and create their own plans, which is very time-consuming. Furthermore, if the collected information is insufficient, it becomes difficult to create an optimal travel plan. Thus, there is a challenge in that it is difficult for users to easily obtain high-quality travel plans.

[1441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1442] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure, meals, and budget; means for transmitting the collected user input information to an information processing device; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan to a display device; and means for displaying the transmitted travel plan to the user. This makes it possible for users to easily and quickly obtain a high-quality, optimal travel plan.

[1443] A "travel destination" refers to a geographical location that the user wishes to visit.

[1444] "Mood" refers to the user's hopes and desires regarding their mental state and atmosphere during their trip.

[1445] "Leisure" refers to the activities and recreation that users want to enjoy while traveling.

[1446] "Meals" refers to the dishes and foods that the user wants to eat during their trip.

[1447] "Budget" refers to the amount of money a user plans to spend on a trip.

[1448] A "user" is someone who intends to use a travel plan.

[1449] "Input information" refers to the detailed travel information that the user provides to the system.

[1450] An "information processing device" is a device used to process data collected from users.

[1451] "Generative artificial intelligence" refers to artificial intelligence technology that has the ability to generate results based on specific input data.

[1452] A "travel plan" refers to suggestions and schedules related to a user's trip.

[1453] A "display device" is a device used to display the generated travel plan to the user.

[1454] A "data repository" is a database or API used to retrieve information from external sources in order to generate travel plans.

[1455] A "food and beverage establishment" refers to a shop or restaurant where users eat.

[1456] A "tourist attraction" refers to a tourist destination or landmark that users should visit.

[1457] "Accommodation facilities" refer to hotels, guesthouses, and other accommodations where users can stay.

[1458] This invention relates to a system that uses generative artificial intelligence to suggest the optimal travel plan based on the user's input of travel details. This system includes several main components. Specific embodiments are described below.

[1459] System Overview

[1460] This system collects user input information, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include terminals, servers, generative artificial intelligence, and an external data repository.

[1461] Collect input information

[1462] The user enters detailed information such as travel destination, mood, leisure activities, meals, and budget through the application screen. For example, consider a case where the user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," and "Budget of 50,000 yen."

[1463] The device collects and temporarily stores information entered by the user. This typically involves using the local storage of a mobile device or PC. The device then converts the stored information into JSON format to facilitate subsequent data transmission and analysis.

[1464] Data transmission and analysis

[1465] The terminal sends the collected user input information to the server. Here, the data is transmitted securely using the HTTPS protocol. The server analyzes the received data and interprets the user's requests. Specifically, the data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[1466] Use of external data repositories

[1467] Based on the user's requests, the server searches external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and collects relevant travel information. For example, using the conditions "Tokyo" and "sushi," it retrieves data on highly-rated sushi restaurants using the Tabelog API. Similarly, using the conditions "Tokyo" and "experience nature," it retrieves data on tourist destinations rich in nature using the TripAdvisor API.

[1468] Travel plan generation

[1469] The server passes the collected data to the generative artificial intelligence (AI). Specifically, it inputs JSON data as prompts into the AI. The AI ​​then generates the optimal travel plan based on the input data. For example, the prompts can be set as follows:

[1470] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[1471] Proposed plan:

[1472] Day 1: Dinner at a sushi restaurant in Ginza

[1473] Day 2: Ueno Zoo and sushi lunch

[1474] Day 3: Visit to Senso-ji Temple and accommodation

[1475] Generative artificial intelligence generates and proposes travel plans that are best suited to the user's needs.

[1476] Sending and displaying plans

[1477] The server sends the generated travel plan to the device. Typically, an HTTP POST request is used for this transmission. The device then displays the received travel plan on the application screen. A user interface (e.g., an application using React or Flutter) is often used here.

[1478] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[1479] In this way, users only need to input detailed travel information, and the generative artificial intelligence analyzes all the information and provides the optimal travel plan, significantly reducing the effort required from the user. This system allows users to easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[1480] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1481] Step 1: Collecting input information

[1482] Users enter detailed information such as their travel destination, mood, leisure activities, meals, and budget through the application screen.

[1483] Input: Detailed travel information entered by the user (e.g., "Tokyo", "Relax", "Experience nature", "Sushi", "Budget 50,000 yen")

[1484] Output: Collected user input information

[1485] The device temporarily stores the information entered by the user.

[1486] Operation: Saves data to the local storage of mobile devices or PCs.

[1487] The device converts the saved information into JSON format.

[1488] Operation: Converts input information into JSON format data to prepare for subsequent processing.

[1489] Step 2: Send

[1490] The terminal sends the collected user input information to the server.

[1491] Operation: Securely transmits data using the HTTPS protocol.

[1492] Input: User input information converted to JSON format

[1493] Output: User input information sent to the server

[1494] The server analyzes the received data and interprets the user's request.

[1495] Operation: Data is temporarily stored in a database (e.g., MySQL) and then analyzed.

[1496] Input: User input information in JSON format received

[1497] Output: Information on analyzed user requests

[1498] Step 3: Using an external data repository

[1499] Based on the user's requests, the server searches external data repositories and collects relevant travel information.

[1500] Operation: Sends requests to external data repositories (e.g., Google Maps API, TripAdvisor API, Tabelog API) and retrieves the necessary information.

[1501] Input: Information about the analyzed user requests

[1502] Output: Travel information retrieved from an external data repository

[1503] Specific example:

[1504] The server uses the Tabelog API to retrieve data on highly-rated sushi restaurants based on the conditions "Tokyo" and "sushi".

[1505] The server uses the TripAdvisor API to retrieve data on tourist destinations rich in nature, based on the conditions of "Tokyo" and "experiencing nature."

[1506] Step 4: Creating a travel plan

[1507] The server passes the collected data to a generative artificial intelligence.

[1508] Operation: Inputs JSON formatted data as a prompt into a generative artificial intelligence.

[1509] Input: Travel information retrieved from an external data repository

[1510] Output: Travel plan generated by a generative artificial intelligence system

[1511] Generative artificial intelligence generates the optimal travel plan based on input data.

[1512] Specific example:

[1513] User request: "Tokyo, relaxation, nature-related, sushi, budget 50,000 yen"

[1514] Proposed plan:

[1515] Day 1: Dinner at a sushi restaurant in Ginza

[1516] Day 2: Ueno Zoo and sushi lunch

[1517] Day 3: Visit to Senso-ji Temple and accommodation

[1518] Step 5: Submit and view your plan

[1519] The server sends the generated travel plan to the device.

[1520] Operation: Sends travel plans using an HTTP POST request.

[1521] Input: Travel plan generated by a generative artificial intelligence system

[1522] Output: Travel plan sent to the terminal

[1523] The device displays the received travel plan to the user.

[1524] Operation: Displays travel plans through a user interface (e.g., an application using React or Flutter).

[1525] Input: Travel plan sent from the server

[1526] Output: Travel plan displayed to the user

[1527] Users can review the generated plan and, if they like it, click on links to view details about restaurants and accommodations and make reservations.

[1528] (Application Example 1)

[1529] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1530] When planning a trip, it is time-consuming and burdensome for users to manually gather a lot of information and create a plan. Furthermore, there is a lack of means to provide real-time information during the trip, making it difficult to obtain local navigation and recommendations.

[1531] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1532] In this invention, the server includes means for collecting user input information such as travel destination, mood, leisure activities, desired meals, and budget; means for transmitting the collected user input information to the server; means for generating an optimal travel plan using generative artificial intelligence based on the user input information; means for transmitting the generated travel plan and real-time information to the user device; and means for displaying the transmitted travel plan and real-time information to the user and providing navigation and additional information. As a result, the user can efficiently and easily plan a trip and obtain necessary information in real time while traveling.

[1533] "User device" is a general term for terminal devices used by users, and includes smartphones, tablets, smart glasses, etc.

[1534] "Generative artificial intelligence" refers to artificial intelligence technology that automatically generates the optimal travel plan based on user input.

[1535] A "travel plan" refers to a detailed plan of what a user will do during their trip, including elements such as destination, sightseeing spots, accommodations, restaurants, and budget.

[1536] "Real-time information" refers to providing users with the latest data and navigation information at any given time while they are traveling.

[1537] "Navigation" refers to a function that guides the user to the optimal route and steps to their destination based on their current location.

[1538] An "external database" is an external source of information used to generate travel plans, and includes information on tourist attractions, restaurants, accommodations, etc.

[1539] A "tourist destination" refers to a place or region in a travel destination that is worth visiting, and includes natural landscapes, historical buildings, cultural facilities, and so on.

[1540] "Eating establishments" refer to places where customers eat, and include restaurants, cafes, and diners.

[1541] "Accommodation" refers to the place where a user stays during their trip, and includes hotels, inns, guesthouses, and so on.

[1542] This invention relates to a system that uses generative artificial intelligence to propose an optimal travel plan based on the input of detailed travel information. Its specific configuration and operation are described below.

[1543] System Overview

[1544] This system aims to provide users with efficient and real-time information for planning and executing their travel plans. Its main components include user devices, servers, generative artificial intelligence, and external databases.

[1545] Program Processing Description

[1546] 1. Collection of input information

[1547] The user enters detailed information such as travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. The user device temporarily stores this entered information.

[1548] 2. Sending data

[1549] The user device sends the collected user input information to a server in the cloud. The server analyzes the received data and interprets the user's requests.

[1550] 3. Information analysis and travel plan generation

[1551] The server searches an external database based on the user's input and collects relevant travel information. Generative artificial intelligence then uses this collected data to generate a travel plan optimized for the user's needs. Specifically, it selects the best restaurants, tourist attractions, and accommodations based on the travel destination, budget, meals, and leisure activities.

[1552] 4. Provision of real-time information

[1553] The server sends real-time information to the user's device along with the generated travel plan. For example, it can use AR functionality to provide local information and navigation to the user's smart glasses.

[1554] 5. Presentation of travel plan and navigation

[1555] The user device displays the generated travel plan and real-time information to the user. Furthermore, it uses navigation functions to support the user's actions at the destination and presents additional information and recommendations.

[1556] Specific example

[1557] The user enters their travel preferences into their smartphone, such as "Destination: Tokyo, I want to relax, I want to go somewhere with nature, I want to eat sushi, budget: 50,000 yen." Based on this information, the server generates a travel plan, selecting information such as highly-rated sushi restaurants in Ginza, Ueno Zoo, and Senso-ji Temple. It also lists and presents multiple accommodation options within the budget. Furthermore, upon arrival at the destination, smart glasses use augmented reality (AR) to display the optimal route and timely recommendations in real time.

[1558] Example of a prompt

[1559] "Please suggest a travel plan for Tokyo, where I want to relax, experience nature, eat sushi, and have a budget of 50,000 yen."

[1560] With this configuration, the system allows users to simply input travel information, and the generative artificial intelligence utilizes advanced technology to provide an optimal travel plan. Furthermore, it can enhance the user's travel experience by providing on-site navigation and real-time information.

[1561] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1562] Step 1:

[1563] Users input detailed information such as their travel destination, mood, leisure activities, desired meals, and budget into a user device such as a smartphone or smart glasses. This input information is temporarily stored in a database within the user device. Specifically, text data is collected through the user device's interface.

[1564] Input: Detailed information entered by the user, such as travel destination, mood, leisure activities, desired meals, and budget.

[1565] Output: Detailed information data stored on the user's device

[1566] Step 2:

[1567] The user device sends the collected user input information to a server in the cloud. During transmission, the information stored in the database within the user device is sent to the server via an API request.

[1568] Input: Detailed information data stored on the user's device

[1569] Output: Detailed information data sent to a server in the cloud.

[1570] Step 3:

[1571] The server analyzes the received data and interprets the user's requests. Based on the received information, it understands the travel experience the user desires and sets search criteria accordingly.

[1572] Input: Detailed information data sent to a server in the cloud.

[1573] Output: Search criteria interpreted from user requests

[1574] Step 4:

[1575] The server searches external databases based on user input and collects relevant travel information. Specifically, it retrieves information on restaurants, tourist attractions, accommodations, etc., via APIs.

[1576] Input: Search criteria interpreted from user requests

[1577] Output: Travel information retrieved from an external database

[1578] Step 5:

[1579] Generative artificial intelligence generates optimal travel plans tailored to the user's needs based on collected travel information. Specifically, it combines collected information on restaurants, tourist attractions, and accommodations to create a travel schedule that matches the user's preferences and budget.

[1580] Input: Travel information obtained from an external database

[1581] Output: Generated travel plan

[1582] Step 6:

[1583] The server sends real-time information to the user's device along with the generated travel plan. This real-time information includes local weather information, traffic conditions, and the latest event information.

[1584] Input: Generated travel plan

[1585] Output: Travel plans and real-time information sent to the user's device.

[1586] Step 7:

[1587] The user device displays the received travel plan and real-time information to the user. Furthermore, it uses navigation functionality to provide route guidance and additional recommendations based on the user's current location. When using smart glasses, augmented reality (AR) functionality is used to display local information and navigation information.

[1588] Input: Travel plans and real-time information sent to the user's device.

[1589] Output: Travel plan and real-time information displayed to the user.

[1590] Through the above processing steps, users can efficiently plan their trips and always have access to the latest information while traveling. As an example of a specific prompt to the generating AI model, the following is used: "Please suggest a travel plan for Tokyo, where I want to relax, where I can experience nature, where I want to eat sushi, and with a budget of 50,000 yen."

[1591] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1592] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest the optimal travel plan based on the user's input of detailed travel information and emotional information. The following describes the program processing of this system and a specific example in natural language.

[1593] System Overview

[1594] This system collects user input information and emotional data, generates an optimal travel plan based on that information, and proposes it to the user. The main components of the system include a terminal, a server, generative artificial intelligence, an emotional engine, and an external database.

[1595] Program Processing Description

[1596] 1. Collection of input information

[1597] Users input detailed information such as their travel destination, mood, leisure activities, desired food, budget, and emotional information on the application screen.

[1598] The device collects and temporarily stores information entered by the user.

[1599] 2. Sending data

[1600] The terminal converts the collected user input information and sentiment information into JSON or XML format and sends it to the server.

[1601] The server analyzes the received data and interprets the user's requests and emotions.

[1602] 3. Information Analysis and Plan Generation

[1603] The server searches external databases and collects relevant travel information based on user input and sentiment information.

[1604] Generative artificial intelligence and an emotion engine use collected data to generate travel plans that are optimally suited to the user's requests and emotions. Specifically, they select the best restaurants, tourist spots, and accommodations based on the travel destination, budget, desired food, leisure activities, and emotions.

[1605] 4. Sending and displaying plans

[1606] The server converts the generated travel plan into JSON or XML format and sends it to the terminal.

[1607] The device analyzes the received travel plan and displays it on the application screen.

[1608] Specific example

[1609] User input information

[1610] The user enters "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[1611] Example of plan generation

[1612] 1. Restaurant Search

[1613] The server uses the Tabelog API and Google Maps API to list multiple highly-rated sushi restaurants based on the conditions of "Tokyo" and "sushi."

[1614] The emotional engine further filters out shops with a quiet and relaxing atmosphere that are considered good for stress relief.

[1615] 2. Search for tourist destinations

[1616] The server uses the TripAdvisor API and Google Maps API to list multiple tourist destinations rich in nature, based on the criteria of being "Tokyo" and "experiencing nature."

[1617] The emotional engine selects quiet, natural spots where you can relax.

[1618] 3. Search for accommodations

[1619] The server uses the Booking.com API and Airbnb API to list multiple highly-rated accommodations in Tokyo with a budget of 50,000 yen or less.

[1620] The emotional engine selects accommodations in quiet environments suitable for stress relief.

[1621] 4. Creating a travel plan

[1622] The generative artificial intelligence and emotion engine will create a specific schedule for days 1 through 3 based on the above conditions. For example, day 1 might include dinner at a quiet sushi restaurant in Ginza, day 2 might involve a visit to Ueno Zoo and a stroll through relaxing nature spots, and day 3 might include a visit to Senso-ji Temple and the selection of accommodation suitable for stress relief.

[1623] Suggestions for users

[1624] The device displays the generated travel plan to the user on the application screen. The user reviews the suggested plan, and if they like it, they are also provided with links to view details and make reservations for restaurants and accommodations.

[1625] In this way, by simply having the user input detailed travel information and emotional information, the generative artificial intelligence and emotion engine analyze all the information and provide an optimal travel plan that also takes the user's emotions into consideration, significantly reducing the effort required from the user and enabling a more satisfying travel experience. With this system, users can easily obtain their ideal travel plan, making travel planning more efficient and enjoyable.

[1626] The following describes the processing flow.

[1627] Step 1:

[1628] The user enters travel details and emotional information on the application screen. Specifically, the user selects information such as travel destination, mood, leisure activities, desired food, budget, and emotional information (e.g., want to relax, relieve stress) from text boxes or dropdown menus.

[1629] Step 2:

[1630] The device collects the information entered. Specifically, it temporarily stores the data from each field entered by the user. For example, it collects data such as "Tokyo" for travel destination, "Relaxed" for mood, and "Stress Relief" for emotional information.

[1631] Step 3:

[1632] The device collects information, converts it into JSON or XML format, and sends it to the server. Specifically, it sends data to the server using HTTP requests. An example of the format sent is {"destination": "Tokyo", "mood": "relax", "activity": "nature", "food": "sushi", "budget": "50000", "emotion": "stress relief"}.

[1633] Step 4:

[1634] The server analyzes the received data. Specifically, the server checks the data format, extracts the necessary fields, and stores them in internal variables. For example, it might store information such as travel destination "Tokyo," mood "relaxed," and emotional information "stress relief" in variables.

[1635] Step 5:

[1636] The server searches external databases to collect relevant information. Specifically, it uses API calls to retrieve restaurant information, tourist information, and accommodation information from external databases. For example, it might search for "Tokyo sushi" using the Tabelog API and "Tokyo nature tourist spots" using the TripAdvisor API.

[1637] Step 6:

[1638] The server uses an emotion engine to analyze the user's emotional information. Specifically, the emotion engine filters restaurants, tourist destinations, and accommodations based on emotions such as "stress relief," suggesting relaxing environments.

[1639] Step 7:

[1640] Generative artificial intelligence generates the optimal travel plan based on the user's input information and emotional information. Specifically, it selects restaurants, tourist attractions, and accommodations that meet the criteria and creates a detailed schedule for each day. For example, on day 1, it might include dinner at a quiet sushi restaurant in Ginza, on day 2, a visit to Ueno Zoo and a stroll through a relaxing nature spot, and on day 3, a visit to Senso-ji Temple and a quiet accommodation.

[1641] Step 8:

[1642] The server generates a travel plan, converts it to JSON or XML format, and sends it to the device. Specifically, it uses an HTTP response to return the data to the device. An example format is: {"day1": {"arrival_time": "13:00", "dinner": "Sushi restaurant in Ginza", "cost": 15000}, "day2": {"morning": "Ueno Zoo", "lunch": "Quiet sushi lunch", "afternoon": "Relaxing nature spot", "cost": 5000}, "day3": {"morning": "Senso-ji Temple", "afternoon": "Quiet accommodation", "cost": 10000}}

[1643] Step 9:

[1644] The device analyzes the received travel plan and displays it on the application screen. Specifically, it binds the data to display layouts and UI elements to present the plan to the user in a visually easy-to-understand format. For example, it might display "Sushi restaurant in Ginza" for dinner on day 1, and "Ueno Zoo" for the morning of day 2.

[1645] Step 10:

[1646] The user reviews the suggested plan and, if necessary, checks further details or proceeds with the booking process. Specifically, links are set up for each plan item, so that clicking them opens the booking site or detailed information page. For example, clicking the "Sushi restaurant in Ginza" link will open the restaurant's booking page.

[1647] (Example 2)

[1648] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1649] Conventional travel plan generation systems require users to manually create detailed travel plans, which is time-consuming and laborious. Furthermore, it is often difficult to create plans that take into account the user's emotional state and specific requests, resulting in unsatisfactory plans. This invention aims to increase user satisfaction by automatically generating optimal travel plans based on user input and emotional information.

[1650] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for inputting the user's travel destination, mood, leisure, meals, budget, and emotional information; means for temporarily storing the input information on the terminal; means for converting the stored information into JSON or XML format and sending it to the server; means for analyzing the information received by the server and collecting relevant travel information using an external database; means for generating an optimal travel plan based on the collected information and the user's emotional state using generative artificial intelligence and an emotional engine; means for converting the generated travel plan into JSON or XML format and sending it to the terminal; and means for displaying the transmitted travel plan on the terminal's application screen. This makes it possible to automatically generate an optimal travel plan based on the user's input information and emotional information, saving the user time and providing a higher level of satisfaction.

[1651] "User input information" refers to all information that the user enters into the application screen, including travel destination, mood, leisure activities, meals, budget, and emotional information.

[1652] A "terminal" refers to a device used by a user to input information and send it to a server, and includes smartphones, tablets, and personal computers.

[1653] A "server" is a computer system that receives user input information, analyzes it, and performs all the necessary backend processing to generate a travel plan.

[1654] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a format for representing data in a text format that is easy for both humans and machines to read.

[1655] "XML format" is an abbreviation for eXtensible Markup Language, a markup language for structurally representing data.

[1656] "Generative artificial intelligence" refers to an artificial intelligence model used to generate optimal travel plans by analyzing user input information and emotional information.

[1657] An "emotion engine" is a software component used to interpret a user's emotional state and select the optimal travel plan elements based on that information.

[1658] An "external database" is an external data source that provides travel information, restaurant information, accommodation information, etc., and can be accessed by the server via an API.

[1659] A "travel plan" is a travel schedule and activity plan generated based on user input and emotional information, and includes specific information such as restaurants, tourist destinations, and accommodations.

[1660] The "application screen" is a software interface used by users to input travel details and sentiment information and to review the generated travel plan.

[1661] This invention relates to a system that uses generative artificial intelligence and an emotion engine to suggest an optimal travel plan based on the user's input of detailed travel information and emotional information. The system of this invention includes a terminal, a server, generative artificial intelligence, an emotion engine, and an external database. The implementation of this system is described in detail below.

[1662] 1. Collecting user input information

[1663] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The input method involves filling in each field on a form displayed on the screen. For example, information such as "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief" might be entered.

[1664] 2. Information storage and transmission

[1665] The terminal collects user input in real time and temporarily stores it in memory. The collected data is then converted to JSON or XML format. The converted data is sent to the server via an HTTP POST request.

[1666] 3. Information analysis on the server

[1667] The server deserializes the data received from the terminal and converts it into an internal data structure. Next, it searches external databases and collects relevant travel information based on the user's input. Specifically, it uses the Tabelog API and Google Maps API to obtain restaurant information and the TripAdvisor API and Google Maps API to collect tourist destination information.

[1668] 4. Creating a travel plan

[1669] The server uses generative artificial intelligence and an emotion engine to generate the optimal travel plan based on collected travel information and user sentiment data. The generative AI creates a travel schedule tailored to the user's specific requests, while the emotion engine selects restaurants, tourist destinations, and accommodations that are best suited to the user's emotional state.

[1670] Examples of specific prompt messages include the following:

[1671] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[1672] 5. Sending and displaying plans

[1673] The generated travel plan is converted back into JSON or XML format and sent to the terminal as an HTTP response. The terminal parses the received data and displays the travel plan to the user on the application screen. This display uses a graphical interface that includes detailed information and links.

[1674] For example, the following travel plan might be generated:

[1675] Day 1: Dinner at a quiet sushi restaurant in Ginza

[1676] Day 2: A relaxing stroll through nature in Ueno Park.

[1677] Day 3: Visit Senso-ji Temple and stay at accommodation suitable for stress relief.

[1678] This system allows generative artificial intelligence and an emotion engine to automatically generate the optimal travel plan based on the information entered by the user, saving the user time and providing a higher level of satisfaction.

[1679] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1680] Step 1:

[1681] Users enter information about their travel destination, mood, leisure activities, meals, budget, and emotions into the application screen. The information entered by the user is entered into a form and sent to the device when the submit button is clicked. This input information includes things like "Tokyo," "Relax," "Enjoy nature," "Sushi," "Budget: 50,000 yen," and "Emotion: Stress relief."

[1682] Input: User input of travel destination, mood, leisure, food, budget, and emotional information.

[1683] Output: Sending the input information to the terminal.

[1684] Specific actions:

[1685] The user enters information into each field and clicks the submit button.

[1686] The terminal verifies the input content and checks for any input errors.

[1687] Step 2:

[1688] The terminal collects user input in real time and temporarily stores it in memory. The collected information is converted to either JSON or XML format. For example, in the case of JSON format, the "JSON.stringify" function is used.

[1689] Input: Collected user input information

[1690] Output: Data converted to JSON or XML format.

[1691] Specific actions:

[1692] The terminal uses the "JSON.stringify" function to convert the input information into JSON format.

[1693] Step 3:

[1694] The terminal sends the converted data to the server. Specifically, the data is sent using an HTTP POST request.

[1695] Input: User input data converted to JSON or XML format.

[1696] Output: Data to send to the server

[1697] Specific actions:

[1698] The terminal sends data to the server using the "fetch" function.

[1699] Step 4:

[1700] The server deserializes the data received from the terminal and converts it into an internal data structure. Specifically, it analyzes the data structure and separates user input information from sentiment information.

[1701] Input: Data in JSON or XML format sent from the device.

[1702] Output: User input information converted to an internal data structure

[1703] Specific actions:

[1704] The server uses the "JSON.parse" function to deserialize the received data.

[1705] Step 5:

[1706] Based on the analyzed data, the server uses external database APIs (e.g., Tabelog API, Google Maps API, TripAdvisor API) to collect travel information related to the user's input.

[1707] Input: User input information converted to an internal data structure

[1708] Output: Related travel information retrieved from an external database

[1709] Specific actions:

[1710] The server retrieves restaurant information via the Tabelog API and collects tourist information using the Google Maps API.

[1711] Step 6:

[1712] The server's generative AI and emotion engine generate the optimal travel plan based on collected travel information and user emotion information. The generative AI creates a specific travel schedule, while the emotion engine selects elements that best suit the user's emotions.

[1713] Input: Relevant travel information obtained from an external database, user sentiment information

[1714] Output: Optimal travel plan

[1715] Specific actions:

[1716] The server sends the following prompt to the generative artificial intelligence to generate the schedule:

[1717] Please generate a 3-day travel plan based on the following conditions: "Tokyo," "Relaxation," "Enjoying Nature," "Sushi," "Budget of 50,000 yen," and "Emotion: Stress Relief."

[1718] Step 7:

[1719] The server converts the generated travel plan back into JSON or XML format and sends it to the terminal as an HTTP response.

[1720] Input: Generated travel plan

[1721] Output: Plan data converted to JSON or XML format.

[1722] Specific actions:

[1723] The server uses the "JSON.stringify" function to convert the travel plan into JSON format and sends it to the terminal in the HTTP response.

[1724] Step 8:

[1725] The device analyzes the received travel plan and displays it to the user on the application screen. The display method includes a graphical interface with detailed information and links.

[1726] Input: Travel plan data in JSON format sent from the server.

[1727] Output: Display of travel plan for the user

[1728] Specific actions:

[1729] The device parses the received JSON data and displays the travel plan graphically to the user.

[1730] (Application Example 2)

[1731] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1732] Traditional content delivery services have struggled to provide personalized content tailored to users' interests and emotions. In particular, they lack mechanisms to suggest optimal content based on the specific emotional state a user is currently experiencing. As a result, users have to expend considerable effort to find content that matches their interests and mood, leading to decreased satisfaction.

[1733] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1734] In this invention, the server includes means for collecting user interest topics and current sentiment information, means for transmitting the collected user input information to the server, means for generating optimal content using generative artificial intelligence based on the user input information, means for transmitting the generated content to a terminal, and means for displaying the transmitted content to the user. This makes it possible to automatically suggest optimal content that matches the user's interests and sentiments.

[1735] "Topics of interest" refer to specific fields or themes that a user is interested in.

[1736] "Emotional information" refers to data that indicates the user's current mood and emotional state.

[1737] "Means of collection" refers to the methods and systems used to acquire and store information entered by users.

[1738] A "server" is a computer system that receives user input information and performs processing and analysis on it.

[1739] "Means of transmission" refers to methods or functions for transferring acquired information to other systems or terminals.

[1740] "Generative artificial intelligence" refers to algorithms and models that generate information tailored to user needs based on large amounts of data.

[1741] "Optimal content" refers to information and media that best match the user's interests and emotions.

[1742] A "terminal" is a device that a user uses to input information or view suggested information.

[1743] "Means of display" refers to methods or systems for providing generated information to users visually.

[1744] An "external database" is an external information resource used for searching and referencing information entered by the user.

[1745] "Music, video, or text" refers to various media content provided according to the user's interests and emotions.

[1746] This invention is a system that collects user interest topics and current sentiment information, and proposes optimal content using generative artificial intelligence and an external database. The program processing and details of this system are described below.

[1747] Program Processing Description

[1748] Hardware and software configuration

[1749] 1. Hardware

[1750] Device: Smartphone (iOS / Android compatible)

[1751] Server: A computer server (one with processing speed and storage capacity)

[1752] 2. Software

[1753] Smartphone application: Developed using React Native

[1754] Server-side applications: Server applications using Node.js

[1755] Generative artificial intelligence models: For example, OpenAI's GPT-3

[1756] Sentiment analysis engine: For example, IBM Watson's Sentiment Analysis

[1757] External database APIs: YouTube API, Spotify API, Google Books API, etc.

[1758] System operation

[1759] 1. Collection of user information

[1760] Users input their areas of interest (music, movies, reading, etc.) and their current emotional state (want to relax, want to feel energized, etc.) through a smartphone app.

[1761] The terminal converts the input information into JSON format and stores it temporarily.

[1762] 2. Sending data

[1763] The terminal sends the collected user input information to the server. Real-time data communication is achieved by using the Axios library for transmission.

[1764] 3. Analysis of Information

[1765] The server analyzes the received data and, based on that analysis, uses a combination of a generative artificial intelligence model (such as GPT-3) and an emotion analysis engine.

[1766] The generative artificial intelligence searches external databases based on topics of interest, and the sentiment analysis engine selects the most suitable content based on the user's emotional information.

[1767] 4. Content generation and transmission

[1768] The server generates the most suitable content, converts the recommendation list into JSON format, and sends it to the terminal.

[1769] The device analyzes the recommendation list and displays it in a way that the user can visually confirm.

[1770] Specific example

[1771] User input information

[1772] If the user enters "movie" and "want to relax".

[1773] Example of a prompt

[1774] The user entered "movie" and "want to relax." Please recommend a movie that is perfect for relaxation.

[1775] Examples of content recommendations

[1776] 1. Movie Search

[1777] The server uses external database APIs (such as the YouTube API and Netflix API) to collect movie lists based on the criterion of "relaxing movies."

[1778] The emotion analysis engine selects the best candidates from among "relaxing" movies, and a generative artificial intelligence model organizes them.

[1779] 2. Music Search

[1780] The server uses the Spotify API to collect playlists categorized as "relaxing music."

[1781] The emotion analysis engine selects the most suitable music album or playlist for the feeling of wanting to relax.

[1782] Display to the user

[1783] The device displays a generated list of recommended content to the user, allowing them to watch movies or play music on the spot.

[1784] This makes it possible to create a system that automatically provides the most suitable content simply by the user inputting their areas of interest and emotional information.

[1785] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1786] Step 1:

[1787] Collection of user information

[1788] Users use a smartphone app to input topics of interest (e.g., movies, music, reading) and their current emotional state (e.g., want to relax, want to feel energized).

[1789] Input: User-entered topics of interest and sentiment information.

[1790] Output: User information converted to JSON format.

[1791] Specific operation: A form for entering topics of interest and sentiment information is displayed through the user interface. Once the user enters the information and presses the submit button, the data is converted into JSON format.

[1792] Step 2:

[1793] Sending data

[1794] The terminal sends the collected user input information to the server.

[1795] Input: User information in JSON format.

[1796] Output: Data sent to the server.

[1797] Specific operation: The terminal uses the Axios library to send JSON-formatted data to the server-side endpoint via asynchronous communication.

[1798] Step 3:

[1799] Information analysis

[1800] The server analyzes the received data, identifies topics of interest to the user, and evaluates sentiment information.

[1801] Input: JSON formatted data sent to the server.

[1802] Output: Analysis results based on user interest and sentiment information.

[1803] Specific operation: The server parses the received JSON data and passes it to a generative artificial intelligence model and sentiment analysis engine to analyze topics of interest and sentiment information.

[1804] Step 4:

[1805] Content generation

[1806] The server uses generative artificial intelligence and sentiment analysis engines to generate optimal content.

[1807] Input: Analyzed user interest topics and sentiment information.

[1808] Output: A list of recommended content that is best suited for your needs.

[1809] Specific operation: Interest topics and sentiment information are input into prompts of a generative artificial intelligence model (such as GPT-3), and the system uses an external database API to collect and generate optimal content.

[1810] Step 5:

[1811] Send content

[1812] The server converts the generated content recommendation list into JSON format and sends it to the terminal.

[1813] Input: A list of recommended content that is best suited for your needs.

[1814] Output: JSON formatted data sent to the terminal.

[1815] Specific operation: Serialize the recommendation list into JSON format and send it to the endpoint on the terminal side.

[1816] Step 6:

[1817] Display content

[1818] The device analyzes the received content recommendation list and displays it visually to the user.

[1819] Input: JSON formatted data sent to the terminal.

[1820] Output: A list of content recommendations displayed visually to the user.

[1821] Specific operation: The device parses the received JSON data and displays detailed content information in the user interface. The user can then watch recommended movies or play music.

[1822] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1823] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1824] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1825] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1826] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1827] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1828] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1829] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1830] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1831] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1832] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1833] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1834] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1835] 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.

[1836] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1837] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1838] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1839] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1840] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1841] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[1842] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[1843] The following is further disclosed regarding the embodiments described above.

[1844] (Claim 1)

[1845] A means of collecting user input information such as travel destination, mood, leisure activities, desired food, budget, etc.

[1846] A means of sending the collected user input information to the server,

[1847] A means for generating an optimal travel plan using generative artificial intelligence based on user input information,

[1848] A means of sending the generated travel plan to the terminal,

[1849] A means of displaying the submitted travel plan to the user,

[1850] A system that includes this.

[1851] (Claim 2)

[1852] The system according to claim 1, further comprising means for using an external database to generate an optimal travel plan based on user input information.

[1853] (Claim 3)

[1854] The system according to claim 1, further comprising means for selecting the most suitable restaurants, tourist destinations, and accommodations within the budget when generating a travel plan.

[1855] "Example 1"

[1856] (Claim 1)

[1857] A means of collecting user input information such as travel destination, mood, leisure, meals, budget, etc.

[1858] A means for transmitting collected user input information to an information processing device,

[1859] A means for generating an optimal travel plan using generative artificial intelligence based on user input information,

[1860] A means for transmitting the generated travel plan to a display device,

[1861] A means of displaying the submitted travel plan to the user,

[1862] A system that includes this.

[1863] (Claim 2)

[1864] The system according to claim 1, further comprising means for using an external data repository to generate an optimal travel plan based on user input information.

[1865] (Claim 3)

[1866] The system according to claim 1, further comprising means for selecting the most suitable dining facilities, sightseeing facilities, and accommodations within the budget when generating a travel plan.

[1867] "Application Example 1"

[1868] (Claim 1)

[1869] A means of collecting user input information such as travel destination, mood, leisure activities, desired meals, budget, etc.

[1870] A means of sending the collected user input information to the server,

[1871] A means for generating an optimal travel plan using generative artificial intelligence based on user input information,

[1872] A means for transmitting the generated travel plan and real-time information to the user device,

[1873] A means for displaying the submitted travel plan and real-time information to the user, and for providing navigation and additional information,

[1874] A system that includes this.

[1875] (Claim 2)

[1876] The system according to claim 1, further comprising means for using an external database to generate an optimal travel plan based on user input information.

[1877] (Claim 3)

[1878] The system according to claim 1, further comprising means for selecting the most suitable restaurants, tourist destinations, and accommodations within the budget based on the budget when generating a travel plan.

[1879] "Example 2 of combining an emotion engine"

[1880] (Claim 1)

[1881] A means for users to input information about their travel destination, mood, leisure, food, budget, and emotions,

[1882] A means of temporarily saving the entered information on the terminal,

[1883] A means of converting the stored information into JSON or XML format and sending it to the server,

[1884] A means of analyzing information received by a server and collecting relevant travel information using an external database,

[1885] A means for generating an optimal travel plan based on collected information and the user's emotional state, using generative artificial intelligence and an emotion engine.

[1886] A means of converting the generated travel plan into JSON or XML format and sending it to the terminal,

[1887] A means of displaying the sent travel plan on the application screen of the device,

[1888] A system that includes this.

[1889] (Claim 2)

[1890] The system according to claim 1, further comprising means for using an external database to generate an optimal travel plan based on user input information and emotional information.

[1891] (Claim 3)

[1892] The system according to claim 1, further comprising means for selecting the best restaurants, tourist destinations, and accommodations within a budget based on budget and sentiment information when generating a travel plan.

[1893] "Application example 2 when combining with an emotional engine"

[1894] (Claim 1)

[1895] Means for gathering information on topics of interest and current sentiment,

[1896] A means of sending the collected user input information to the server,

[1897] A means of generating optimal content using generative artificial intelligence based on user input information,

[1898] A means of sending the generated content to the terminal,

[1899] Means for displaying the submitted content to the user,

[1900] A system that includes this.

[1901] (Claim 2)

[1902] The system according to claim 1, further comprising means for using an external database to generate optimal content based on user input information.

[1903] (Claim 3)

[1904] The system according to claim 1, further comprising means for selecting the most suitable music, video, or text based on emotional information when generating content. [Explanation of Symbols]

[1905] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of collecting user input information such as travel destination, mood, leisure activities, desired food, budget, etc. A means of sending the collected user input information to the server, A means for generating an optimal travel plan using generative artificial intelligence based on user input information, A means of sending the generated travel plan to the terminal, A means of displaying the submitted travel plan to the user, A system that includes this.

2. The system according to claim 1, further comprising means for using an external database to generate an optimal travel plan based on user input information.

3. The system according to claim 1, further comprising means for selecting the most suitable restaurants, tourist destinations, and accommodations within the budget when generating a travel plan.

Images