system

Abstract

We provide the system. [Solution] A means for inputting the user's travel preferences, A means of sending user input information to the server, A server-side means including an algorithm that analyzes the user information sent and generates travel destination suggestions based on it, A means of sending the generated suggestions to the user, A means of displaying the proposed information 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 method for controlling a persona chatbot, which is performed by at least one processor, 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 as a 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 a conventional travel recommendation system, there is a problem that it is difficult to obtain recommendations that accurately correspond to the travel destinations and interests desired by users. For example, it was difficult to provide a single recommendation that satisfied all of the interests of a user with multiple interests at once. Also, with simple keyword searches, it is often impossible to read the potential needs of users and reach the information they truly seek. As a result, users often require a great deal of time and effort when planning a trip, and the results are often unsatisfactory.

Means for Solving the Problems

[0005] To solve the above problems, the present invention provides a system that analyzes user input information and generates optimal travel destination suggestions based on that information. This system includes the following means: First, it provides a means for the user to input their travel preferences and sends that input information to the server. Next, the server analyzes the transmitted information and executes an algorithm to generate travel destination suggestions. The server also obtains information related to the user's input from a database or external API, and the AI ​​generates suggestions based on that information. After that, the generated suggestions are sent to the user and finally displayed on the user's terminal. As a result, the user can receive suggestions that allow them to select a travel destination intuitively and efficiently, and the effort required for travel planning can be significantly reduced.

[0006] "User" refers to travelers or prospective travelers who use the system.

[0007] "Travel preferences" refer to the travel destination, sightseeing spots and local products of interest, and other travel conditions entered by the user.

[0008] "Means of input" refers to the interface or device that users use to input their travel preferences.

[0009] A "server" refers to a computer system that receives input information from users, analyzes it, and generates suggestions.

[0010] "Means of transmission" refers to communication means or technologies for sending user input information to a server.

[0011] "Analysis" refers to the process of understanding user input and extracting the information necessary to generate travel destination suggestions.

[0012] An "algorithm" refers to a series of computational procedures and methods used to generate optimal travel destination suggestions based on user input.

[0013] "Generating suggestions" refers to creating specific travel destinations and sightseeing plans based on the user's travel preferences.

[0014] A "database" refers to an information management system that stores relevant information such as travel destinations, tourist attractions, local products, and trend information.

[0015] An "external API" refers to a programmatic interface used to retrieve information by interacting with external services or databases.

[0016] "AI" refers to programs and methods that use artificial intelligence technology to generate optimal travel suggestions based on user preferences.

[0017] "Means of display" refers to interfaces or devices that visually present the suggested content sent from the server to the user. [Brief explanation of the drawing]

[0018] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8]It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] 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 Example 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

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the language used in the following description will be explained. <00\\00109> In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of 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.

[0022] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] 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).

[0025] 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."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] 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.

[0037] 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.

[0038] 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".

[0039] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[0040] System Configuration

[0041] 1. User input reception

[0042] Terminal:

[0043] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[0044] 2. Data transmission

[0045] Terminal:

[0046] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[0047] 3. Information Processing and Proposal Generation

[0048] server:

[0049] The server receives requests sent from terminals. The received data is analyzed, and semantic analysis and natural language processing techniques are used to select tourist destinations, local products, and trendy spots based on the user's preferences. Based on the analysis results, the server retrieves relevant information by referring to an internal database or external API. An AI algorithm is then used to generate optimal travel suggestions.

[0050] 4. Submit Proposal

[0051] server:

[0052] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about specific tourist destinations, local products, and trendy spots.

[0053] 5. Display results

[0054] Terminal:

[0055] The suggestions received from the server are displayed on the terminal. Users can then use these suggestions to create their own travel plans. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[0056] Specific example

[0057] This example illustrates how a user might use the system to request travel destination suggestions.

[0058] User input example

[0059] The user (let's call him / her Yamada) enters the following information.

[0060] Travel destination: Tokyo

[0061] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0062] Data transmission

[0063] The following information is sent from the terminal to the server.

[0064] json

[0065] {

[0066] "destination": "Tokyo",

[0067] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0068] }

[0069] Information processing and proposal generation

[0070] The server analyzes this information and generates the next suggestion.

[0071] Historical building: Senso-ji Temple

[0072] Sweets: Tokyo Banana

[0073] Newest tourist attraction: teamLab Planets

[0074] Proposal submission and results display

[0075] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[0076] Travel destination: Tokyo

[0077] Recommended tourist destinations

[0078] 1. Senso-ji Temple (Historical Building)

[0079] Details: One of Tokyo's most famous historical buildings.

[0080] 2. Tokyo Banana (Sweets)

[0081] Details: A representative Tokyo sweet, perfect as a souvenir.

[0082] 3. teamLab Planets (a new tourist attraction)

[0083] Details: A spot where you can experience the cutting edge of digital art.

[0084] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's preferences.

[0085] The following describes the processing flow.

[0086] Step 1:

[0087] User:

[0088] The user accesses an interface for creating a travel plan. The interface takes the form of a website or mobile application. The user enters information such as destination, interests, budget, and duration. For example, they might enter "Destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist attractions."

[0089] Step 2:

[0090] Terminal:

[0091] The system receives user input and validates it. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[0092] Step 3:

[0093] Terminal:

[0094] The REST API is used to send user input information to the server. An example of the data sent is as follows:

[0095] json

[0096] {

[0097] "destination": "Tokyo",

[0098] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0099] }

[0100] Step 4:

[0101] server:

[0102] The system receives requests sent from the terminal. It parses the JSON data and extracts key information such as "destination" and "interests". In this example, it extracts "destination: Tokyo" and "interests: historical buildings, sweets, latest tourist spots".

[0103] Step 5:

[0104] server:

[0105] We use semantic analysis and natural language processing techniques to understand user interests. Based on this, we refer to databases and external APIs to obtain information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[0106] Step 6:

[0107] server:

[0108] Based on the collected information, an AI algorithm is used to generate travel suggestions. By combining appropriate tourist destinations with detailed information, the system creates the most suitable travel plan for the user. In this case, for example, "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets" might be suggested.

[0109] Step 7:

[0110] server:

[0111] The generated travel suggestions are converted into JSON response data and sent to the terminal. The response data includes the names and details of each tourist destination.

[0112] Step 8:

[0113] Terminal:

[0114] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[0115] Travel destination: Tokyo

[0116] Recommended tourist destinations

[0117] 1. Senso-ji Temple (Historical Building)

[0118] Details: One of Tokyo's most famous historical buildings.

[0119] 2. Tokyo Banana (Sweets)

[0120] Details: A representative Tokyo sweet, perfect as a souvenir.

[0121] 3. teamLab Planets (a new tourist attraction)

[0122] Details: A spot where you can experience the cutting edge of digital art.

[0123] Step 9:

[0124] User:

[0125] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[0126] (Example 1)

[0127] 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."

[0128] In modern travel planning, users find it difficult to choose the right tourist destination from a vast amount of information. Furthermore, there is a lack of systems that suggest optimal travel destinations based on individual user interests and preferences. As a result, travel planning becomes complex and time-consuming.

[0129] 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.

[0130] In this invention, the server includes terminal means for inputting the user's travel preferences, communication means for transmitting the user's input information to the server, information processing means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it, transmission means for transmitting the generated travel suggestions to the user's terminal, and display means for visually displaying the suggested information to the user. This makes it possible to suggest optimal travel destinations based on the user's interests and preferences.

[0131] A "user" refers to an individual who uses the system to request travel destination suggestions.

[0132] "Travel preferences" refer to the user's requests regarding travel, such as desired destinations, tourist attractions of interest, budget, and duration.

[0133] "Terminal means" refers to a device used by users to input their travel preferences and receive information, such as a personal computer or smartphone.

[0134] "Communication methods" refer to communication protocols and technologies used to send information from a user's terminal to a server, including, for example, REST APIs and HTTP requests using the internet.

[0135] "Information processing means" refers to software and algorithms used by a server to analyze information sent by a user and generate travel destination suggestions.

[0136] "Transmission means" refers to the functions and technologies used to send generated travel suggestions from the server to the user's terminal.

[0137] "Display means" refers to an interface for visually presenting suggested travel information to the user, and includes, for example, the user interface of a web page or mobile application.

[0138] A "travel suggestion system" refers to a system that includes a series of means (terminal means, communication means, information processing means, transmission means, display means) for suggesting the most suitable travel destination based on information input by the user.

[0139] "Related data" refers to travel-related information and data obtained from internal databases or external sources based on user input.

[0140] "Generative artificial intelligence algorithms" refer to machine learning models and AI technologies used to analyze acquired relevant data and generate optimal travel suggestions.

[0141] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[0142] The main components of the system are as follows:

[0143] User input reception

[0144] Terminal:

[0145] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This input is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[0146] Specific example:

[0147] The user (let's call him Yamada) enters the following information:

[0148] Travel destination: Tokyo

[0149] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0150] Sending input data

[0151] Terminal:

[0152] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[0153] Specific example:

[0154] Examples of data sent from the terminal to the server:

[0155] json

[0156] {

[0157] "destination": "Tokyo",

[0158] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0159] }

[0160] Data reception and analysis

[0161] server:

[0162] The server receives requests sent from terminals. After receiving the data, it performs format checks and content analysis. Using semantic analysis and natural language processing techniques, it retrieves data from internal databases or external sources to identify tourist destinations, local products, and trendy spots based on the user's preferences.

[0163] Specific example:

[0164] The system analyzes the received data and retrieves relevant data from its internal database. Specifically, it extracts entries that match the criteria "Travel destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist spots."

[0165] Proposal generation

[0166] server:

[0167] Based on the analyzed data, a generative AI model is used to generate optimal travel suggestions. The generative AI model takes into account the user's interests and past travel data to select the most appropriate travel destination.

[0168] Specific example:

[0169] Specific suggestions generated by the server:

[0170] Historical building: Senso-ji Temple

[0171] Sweets: Tokyo Banana

[0172] Newest tourist attraction: teamLab Planets

[0173] Submit a proposal

[0174] server:

[0175] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about tourist attractions, local products, and trendy spots.

[0176] Specific example:

[0177] Data sent from the server to the terminal:

[0178] json

[0179] {

[0180] "destination": "Tokyo",

[0181] "recommendations": [

[0182] {

[0183] "type": "Historical building",

[0184] "name": "Senso-ji Temple",

[0185] "details": "One of Tokyo's most famous historical buildings."

[0186] },

[0187] {

[0188] "type": "Sweets",

[0189] "name": "Tokyo Banana",

[0190] "details": "A representative Tokyo sweet, perfect as a souvenir."

[0191] },

[0192] {

[0193] "type": "Latest tourist spots",

[0194] "name": "teamLab Planets",

[0195] "details": "A spot where you can experience the cutting edge of digital art."

[0196] }

[0197] ]

[0198] }

[0199] Display of proposal results

[0200] Terminal:

[0201] The suggestions received from the server are displayed on the terminal. Users can then create their own travel plans based on these suggestions. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[0202] Specific example:

[0203] Example of how the device will appear to the user:

[0204] Travel destination: Tokyo

[0205] Recommended tourist destinations

[0206] 1. Senso-ji Temple (historical building)

[0207] Details: One of Tokyo's most famous historical buildings.

[0208] 2. Tokyo Banana (Sweets)

[0209] Details: A representative Tokyo sweet, perfect as a souvenir.

[0210] 3. teamLab Planets (a new tourist attraction)

[0211] Details: A spot where you can experience the cutting edge of digital art.

[0212] Example of a prompt

[0213] Example prompts for generating travel suggestions:

[0214] Please generate travel destination suggestions based on the following information.

[0215] Travel destination: Tokyo

[0216] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0217] As described above, a system is realized that efficiently and accurately suggests the most suitable travel destination based on the user's input preferences. This system can be used on various devices and supports the user's travel planning.

[0218] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0219] Step 1: The user enters their travel preferences.

[0220] The user accesses the terminal's interface and enters their travel preferences (e.g., cities they want to visit, tourist attractions of interest, local products, and the latest tourist spots). The user's input data (e.g., "Destination: Tokyo," "Interests: Historical buildings, sweets, and the latest tourist spots") is received and processed by the terminal.

[0221] Step 2: Send the input data to the server.

[0222] The terminal converts the information entered by the user into JSON format. The converted data is sent to the server using a REST API or HTTP request. The input data becomes the request body in JSON format and is sent to the server.

[0223] Step 3: Receive data, perform format check, and analyze content.

[0224] The server receives JSON data sent from the terminal. It checks the format of the received data and parses its contents. Specifically, it processes the data to identify relevant tourist destinations based on "Destination: Tokyo" and "Interests: Historical buildings, sweets, latest tourist spots."

[0225] Step 4: Obtain relevant data from internal databases and external sources.

[0226] Based on the analyzed data, the server references internal databases and external APIs to retrieve relevant information. For example, it collects data related to "Tokyo," "historical buildings," "sweets," and "the latest tourist spots."

[0227] Step 5: Generate proposals using a generative AI model.

[0228] The server uses a generative AI model to generate optimal travel suggestions based on the acquired relevant data. The generative AI model takes into account the user's interests and past travel data, and uses relevant tourist destination data to perform data calculations for recommended travel destinations (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets).

[0229] Step 6: Convert the generated proposal to JSON format and send it to the terminal.

[0230] The server converts the generated travel suggestions into a JSON response. The converted data is sent to the terminal via a transmission method. The data sent to the terminal includes details of tourist destinations, local products, and trendy spots based on the user's interests (e.g., information on "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets").

[0231] Step 7: Display the proposed results on the terminal.

[0232] The terminal parses the JSON data received from the server and displays it visually to the user. The display format is a clear and well-organized list, including detailed information and images for each tourist destination. Based on the displayed information, the user can create their own travel plan.

[0233] (Application Example 1)

[0234] 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."

[0235] In modern travel planning, users spend a great deal of time and effort gathering information and selecting the optimal destination. Furthermore, simply presenting information about a destination has limitations in motivating users to actually visit that place. Moreover, in today's world where remote travel experiences are increasingly common, the potential of virtual pre-experiences is often overlooked.

[0236] 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.

[0237] In this invention, the server includes means for experiencing travel suggestions generated based on user input within a virtual environment, server-side means including an algorithm that analyzes transmitted user information and generates travel destination suggestions based on it, and means for displaying the suggested information to the user. This allows the user not only to obtain optimal travel destination suggestions but also to experience those suggested destinations in advance within the virtual environment.

[0238] "Means for inputting user travel preferences" refers to providing an interface for users to input their travel preferences and requests to the system.

[0239] "Means for sending user input information to a server" refers to means for transferring information entered by a user on a terminal to a server via a network.

[0240] "Server-side means including an algorithm that analyzes the user's information sent and generates travel destination suggestions based on it" refers to a server-side processing system that uses an algorithm to analyze the information received from the user and generate optimal travel destination suggestions based on the analysis results.

[0241] "Means for sending generated suggestions to the user" refers to the means for sending travel destination suggestions generated on the server side back to the user's terminal.

[0242] "Means for displaying suggested information to the user" refers to means for displaying suggested travel destinations sent from the server in a format that the user can easily view.

[0243] "A means of experiencing travel suggestions generated based on user input within a virtual environment" refers to a method that uses virtual reality or augmented reality technology to simulate and virtually experience travel destination suggestions based on user input.

[0244] The system for realizing this invention is configured as follows: The user accesses the system using smart glasses or a head-mounted display. Here, Oculus Rift and Microsoft HoloLens® are used as examples.

[0245] Acceptance of user input

[0246] Users input their travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel through the smart glasses' UI. This information is transmitted from the device to the server in real time.

[0247] Information processing and proposal generation

[0248] The server receives and analyzes the user information sent to it. This analysis utilizes generative AI models such as OpenAI (registered trademark) and employs advanced natural language processing techniques. In particular, it generates prompt sentences selected based on the user's input and then suggests the most suitable travel destination based on these prompts.

[0249] Data acquisition and proposal generation

[0250] Based on the analysis results, the server retrieves relevant information by referencing internal databases and external APIs. Based on the retrieved information, it generates prompt messages to suggest appropriate travel destinations, as follows:

[0251] Example of a prompt:

[0252] "Destination: Tokyo. Please suggest tourist attractions that focus on historical buildings and sweets."

[0253] Proposal display and virtual experience provision

[0254] Suggestions generated from the server are sent to the user's device. The user can then visually and interactively experience information about the suggested travel destinations through smart glasses or a head-mounted display. This allows the user to check destinations in a virtual environment beforehand and develop the optimal travel plan.

[0255] Specific example:

[0256] For example, if a user inputs "I like historical buildings and sweets in Tokyo," the AI ​​model will generate a prompt such as "Please suggest some historical buildings and sweets that I would recommend visiting in Tokyo." Based on this, the server will make specific suggestions such as Senso-ji Temple and Tokyo Banana, and allow users to experience these places within a virtual environment.

[0257] This system not only suggests travel destinations to users, but also enriches their travel planning through pre-experiences in a virtual environment. This invention significantly improves the efficiency and satisfaction users feel when choosing actual travel destinations.

[0258] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0259] Step 1: User input

[0260] Users wear smart glasses or a head-mounted display and input travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel. This input includes specific data such as destination, interests, budget, and duration.

[0261] input:

[0262] Travel destination: Tokyo

[0263] Interests: Historical buildings, sweets

[0264] Budget: 50,000 yen

[0265] Number of days: 3 days

[0266] output:

[0267] Input data in JSON format

[0268] Step 2: Sending data to the server

[0269] The terminal sends the information entered by the user to the server in JSON format. REST APIs and HTTP requests are used for data transmission.

[0270] input:

[0271] User input information (output from Step 1)

[0272] output:

[0273] JSON formatted data sent to the server

[0274] Step 3: Information analysis and prompt generation

[0275] The server analyzes the user's input information and generates appropriate prompt sentences using a generative AI model. Here, a natural language processing algorithm understands the user's wishes and creates prompt sentences that generate the optimal suggestions.

[0276] input:

[0277] JSON formatted data sent to the server

[0278] Operation:

[0279] Analysis of JSON data

[0280] Generation of prompt sentences (e.g., "Please propose recommended spots related to historical buildings and sweets in Tokyo.")[[]]END]]

[0281] Output:

[0282] Generated prompt sentence

[0283] Step 4: Reference to external database or API

[0284] Based on the generated prompt sentence, the server refers to an internal database or an external API to obtain relevant travel destination information.

[0285] Input:

[0286] Generated prompt sentence

[0287] <00009--08>Operation:

[0288] Obtaining relevant information from the database or external API (e.g., tourist attractions, local specialties, latest spots of travel destinations)

[0289] Output:

[0290] Obtained relevant information

[0291] Step 5: Generation of proposals

[0292] Based on the obtained relevant information, the server generates proposals for the optimal travel destinations. In this process, a generation AI model determines the content of the proposals.

[0293] [[ID=5--]] Input:

[0294] Obtained relevant information

[0295] Operation:

[0296] Generation of proposed content (e.g., Sensoji Temple, Tokyo Banana, teamLab Planets)

[0297] Output:

[0298] Generated travel destination proposal

[0299] Step 6: Sending the proposal to the user

[0300] The server converts the generated proposal back into a JSON-formatted response and sends it to the user's terminal.

[0301] Input:

[0302] Generated travel destination proposal

[0303] Operation:

[0304] Conversion to JSON format

[0305] Sending to the user terminal

[0306] Output:

[0307] Proposal data in JSON format sent to the terminal

[0308] Step 7: Display of proposed content and virtual experience<​​​​​​​​​​​​​​​​​​​​​​​

[0315] output:

[0316] User feedback from virtual experiences

[0317] 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.

[0318] The following describes a specific embodiment of a user-generated travel destination suggestion system that incorporates an emotion engine. This system takes user preferences and emotions regarding travel as input and generates optimal travel destination suggestions based on that input.

[0319] System Configuration

[0320] 1. User input reception

[0321] Terminal:

[0322] Users access an interface for creating travel plans and input their travel preferences (e.g., cities they want to visit, tourist attractions and local products they are interested in, the latest tourist spots, etc.). The interface also features an emotion engine that recognizes the user's emotions from their input and actions. The input form includes fields such as destination, interests, budget, number of days, and current mood.

[0323] 2. Data transmission

[0324] Terminal:

[0325] The system receives user input and emotion information recognized by the emotion engine, and validates the input. It verifies that the necessary information and emotion data have been entered correctly, converts the data to JSON format, and prepares it for transmission.

[0326] 3. Information transmission

[0327] Terminal:

[0328] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[0329] json

[0330] {

[0331] "destination": "Tokyo",

[0332] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0333] "emotion": "excitement"

[0334] }

[0335] 4. Information Analysis and Proposal Generation

[0336] server:

[0337] The server receives the request sent from the terminal. It parses the data in JSON format and extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[0338] 5. Obtaining related information

[0339] server:

[0340] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[0341] 6. Emotion-based proposal adjustment

[0342] server:

[0343] Based on the collected information, the AI ​​algorithm generates travel suggestions, adjusting them based on the user's emotions as recognized by the emotion engine. For example, a user who is "excited" will be suggested more active tourist spots.

[0344] 7. Submit Proposal

[0345] server:

[0346] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[0347] 8. Results display

[0348] Terminal:

[0349] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[0350] Travel destination: Tokyo

[0351] Recommended tourist destinations

[0352] 1. Senso-ji Temple (Historical Building)

[0353] Details: One of Tokyo's most famous historical buildings.

[0354] 2. Tokyo Banana (Sweets)

[0355] Details: A representative Tokyo sweet, perfect as a souvenir.

[0356] 3. teamLab Planets (a new tourist attraction)

[0357] Details: A spot where you can experience the cutting edge of digital art.

[0358] Specific example

[0359] This example illustrates how a user might use the system to request travel destination suggestions.

[0360] User input example

[0361] The user (let's call him Mr. Sato) enters the following information.

[0362] Travel destination: Tokyo

[0363] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0364] Current mood: "Excited"

[0365] Data transmission

[0366] The following information is sent from the terminal to the server.

[0367] json

[0368] {

[0369] "destination": "Tokyo",

[0370] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0371] "emotion": "excitement"

[0372] }

[0373] Information analysis and proposal generation

[0374] The server analyzes this information and generates the next suggestion.

[0375] Historical building: Senso-ji Temple

[0376] Sweets: Tokyo Banana

[0377] Newest tourist attraction: teamLab Planets

[0378] Proposal submission and results display

[0379] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[0380] Travel destination: Tokyo

[0381] Recommended tourist destinations

[0382] 1. Senso-ji Temple (Historical Building)

[0383] Details: One of Tokyo's most famous historical buildings.

[0384] 2. Tokyo Banana (Sweets)

[0385] Details: A representative Tokyo sweet, perfect as a souvenir.

[0386] 3. teamLab Planets (a new tourist attraction)

[0387] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[0388] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's input preferences and emotions.

[0389] The following describes the processing flow.

[0390] Step 1:

[0391] User:

[0392] Users access an interface for creating travel plans and enter their travel preferences (destination, areas of interest, local products, latest tourist attractions, etc.). They also enter their current mood or feelings (e.g., "excited"). The input form includes text boxes and dropdown lists.

[0393] Step 2:

[0394] Terminal:

[0395] The system receives user input and validates the input content and sentiment data. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[0396] Step 3:

[0397] Terminal:

[0398] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[0399] json

[0400] {

[0401] "destination": "Tokyo",

[0402] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0403] "emotion": "excitement"

[0404] }

[0405] Step 4:

[0406] server:

[0407] The system receives requests sent from the terminal and parses the data in JSON format. It extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[0408] Step 5:

[0409] server:

[0410] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[0411] Step 6:

[0412] server:

[0413] Based on the collected information, an AI algorithm is used to generate travel suggestions. The emotion engine then adjusts the suggestions based on the user's recognized emotions. For example, a user who is "excited" will be suggested more active and exciting tourist spots.

[0414] Step 7:

[0415] server:

[0416] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[0417] Step 8:

[0418] Terminal:

[0419] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[0420] Travel destination: Tokyo

[0421] Recommended tourist destinations

[0422] 1. Senso-ji Temple (Historical Building)

[0423] Details: One of Tokyo's most famous historical buildings.

[0424] 2. Tokyo Banana (Sweets)

[0425] Details: A representative Tokyo sweet, perfect as a souvenir.

[0426] 3. teamLab Planets (a new tourist attraction)

[0427] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[0428] Step 9:

[0429] User:

[0430] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[0431] (Example 2)

[0432] 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".

[0433] Conventional travel suggestion systems offer suggestions based on user preferences, but they do not provide specific and personalized suggestions that take into account the user's emotions. As a result, they are unable to suggest travel destinations and tourist spots that match the user's current mood, and improving the user experience remains a challenge.

[0434] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0435] In this invention, the server includes means for analyzing user input information and emotional information and generating travel destination suggestions based on that information, means for obtaining relevant information from a database or external API, and means for adjusting the suggestion content based on the user's emotions. This makes it possible to suggest appropriate travel destinations and tourist spots that match the user's current emotions.

[0436] A "user" refers to a person who inputs information into the system to receive suggestions for travel destinations and tourist spots.

[0437] "Travel preferences" refer to specific requests and interests of users, such as cities they want to visit, tourist destinations, local products, and the latest tourist spots.

[0438] "Emotions" refers to the user's current mood or emotional state, and includes emotions such as "excitement" and "enjoyment."

[0439] An "emotion engine" refers to a software component that has the function of recognizing and analyzing emotions from user input and actions.

[0440] A "server" refers to a computer system that receives information sent by users, analyzes it, and generates suggestions.

[0441] A "database" refers to a data storage system used to store information about travel destinations and tourist spots based on user interests.

[0442] An "external API" refers to an application program interface used to retrieve information from an external data source.

[0443] "AI algorithms" refer to artificial intelligence technology that generates optimal suggestions based on the user's wishes and emotions.

[0444] "Suggestions" refer to recommendations for travel destinations and tourist spots generated based on user input and emotions.

[0445] "JSON format" refers to a data format used to structure user input information and sentiment information and send it to a server.

[0446] "Response data" refers to the formalized data that the server generates and sends to the terminal.

[0447] "Parsing" refers to the process of analyzing response data received from a server and converting it into a format that can be displayed on the user interface.

[0448] Modes for carrying out the invention

[0449] The travel suggestion system according to the present invention is a system that takes the user's travel preferences and emotions as input and generates optimal travel destination suggestions based on them. This system consists of a terminal, a server, an emotion engine, and an AI algorithm.

[0450] User input reception

[0451] Users access a travel plan creation interface via their device. The interface displays forms for inputting information such as destination, interests, budget, duration, and current mood. By entering this information, the system obtains the user's preferences and interests. The interface also incorporates an emotion engine, which recognizes emotions from the user's input and actions.

[0452] Information validation and preparation for transmission

[0453] The information entered by the user and the sentiment information recognized by the sentiment engine are validated on the device. If validation is successful, this information is converted to JSON format and ready to be sent to the server.

[0454] Server-based information analysis

[0455] The server receives JSON data sent from the terminal. The server analyzes this data and extracts key information such as "travel destination," "interests," and "emotions." Based on this, it performs a detailed analysis of the user's requests and emotions.

[0456] Obtaining related information

[0457] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions. Based on this, it retrieves information about relevant travel destinations and tourist spots using databases and external APIs. For example, it collects detailed information about "historical buildings," "sweets," and "the latest tourist attractions" from the database.

[0458] Adjusting emotionally driven proposals

[0459] The server uses an AI algorithm to generate travel suggestions based on the collected information. During this process, the suggestion is adjusted based on the user's emotions, as analyzed by the emotion engine. For example, a user who is "excited" will be advised to visit active and exciting tourist spots.

[0460] Proposal generation and submission

[0461] The generated travel suggestions are converted back into JSON format and sent from the server to the terminal. The response data includes the names of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[0462] Display of proposal results

[0463] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, if "Tokyo" is suggested as a travel destination, "famous temples" are displayed as historical buildings, "local specialties" as sweets, and "digital art facilities" as the latest tourist attractions.

[0464] Specific example

[0465] For example, the user enters the following prompt into the system:

[0466] "Travel destination: Tokyo, Interests: Historical buildings, sweets, new tourist attractions, Current mood: Excited"

[0467] As a result, the server generates and sends the following suggestion to the terminal:

[0468] "Travel destination: Tokyo, Recommended tourist spots:"

[0469] 1. Famous temples (historical buildings)

[0470] Details: One of Tokyo's most famous historical buildings.

[0471] 2. Local specialties (sweets)

[0472] Details: A representative Tokyo sweet, perfect as a souvenir.

[0473] 3. Digital art facilities (the latest tourist attractions)

[0474] Details: A spot where you can experience the cutting edge of digital art.

[0475] In this way, the present invention provides effective travel suggestions based on the user's wishes and emotions.

[0476] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0477] Step 1:

[0478] User input reception

[0479] The user accesses an interface for creating a travel plan and enters information such as destination, interests, budget, duration, and current mood. Once the user has finished entering information, the device collects this information, and the emotion engine recognizes the user's emotions from their input and actions. Input data may include, for example, "Destination: Tokyo," "Interests: Historical buildings, sweets, new tourist attractions," and "Current mood: Excited." The output provides information about the user's preferences and emotions.

[0480] Step 2:

[0481] Information validation and preparation for transmission

[0482] The device validates the information entered by the user and the sentiment information recognized by the sentiment engine. If validation is successful, the device converts this information into JSON format and prepares it for transmission. Specific validation processes include checking whether the travel destination is available and whether interest items are specified. Input consists of user-entered preference information and sentiment information, and output is validated data in JSON format.

[0483] Step 3:

[0484] Sending input data to the server

[0485] The device sends validated JSON-formatted input data and sentiment information to the server using a REST API. For example, the following JSON data is sent:

[0486] json

[0487] {

[0488] "destination": "Tokyo",

[0489] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0490] "emotion": "excitement"

[0491] }

[0492] The input is validated JSON data, and the output is data sent to the server.

[0493] Step 4:

[0494] Server-based information analysis

[0495] The server receives JSON data sent from the terminal and performs analysis. Specifically, it extracts key information related to "travel destination," "interests," and "emotions." For example, the server might extract information such as "travel destination: Tokyo," "interests: historical buildings, sweets, latest tourist spots," and "emotions: excitement." The input is the received JSON data, and the output is the extracted key information.

[0496] Step 5:

[0497] Server retrieves relevant information

[0498] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions, and then retrieves relevant information by referencing databases and external APIs. For example, it can collect detailed information from the database about "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo." The input is analyzed key information, and the output is related tourist destination data.

[0499] Step 6:

[0500] Adjusting emotionally driven proposals

[0501] The server generates travel suggestions using an AI algorithm based on the collected relevant information. At this time, the suggestions are adjusted based on the user's emotions, as analyzed by the emotion engine. For example, for a user who is "excited," active and dynamic tourist spots are prioritized. The input consists of relevant tourist destination data and emotion information, and the output is adjusted travel suggestions.

[0502] Step 7:

[0503] Proposal generation and submission

[0504] The server converts the generated travel suggestions back into JSON format and sends them to the terminal. For example, the response data might include the names and details of each tourist destination, as well as specific suggestions based on the user's mood. The input is the adjusted travel suggestions, and the output is the response data converted into JSON format, which is sent to the terminal.

[0505] Step 8:

[0506] Display of proposal results

[0507] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, it might look like this:

[0508] Travel destination: Tokyo

[0509] Recommended tourist destinations

[0510] 1. Famous temples (historical buildings)

[0511] Details: One of Tokyo's most famous historical buildings.

[0512] 2. Local specialties (sweets)

[0513] Details: A representative Tokyo sweet, perfect as a souvenir.

[0514] 3. Digital art facilities (the latest tourist attractions)

[0515] Details: A spot where you can experience the cutting edge of digital art.

[0516] The input is response data received from the server, and the output is a visual suggestion display for the user.

[0517] (Application Example 2)

[0518] 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."

[0519] Conventional travel suggestion systems have the problem of not being able to provide optimal suggestions that match the user's real-time mood and emotions, because they suggest travel destinations without considering the user's emotional state. Furthermore, especially in autonomous vehicles, there is a need to provide appropriate suggestions instantly in order to offer a safe and comfortable travel experience while also facilitating travel planning.

[0520] 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. In this invention, the server includes means for inputting the user's travel preferences, means for transmitting the user's input information to the server, means including an algorithm for analyzing the transmitted user information and generating travel destination suggestions based thereon, means for transmitting the generated suggestions to the user, means for displaying the suggested information to the user, means including an emotion engine for recognizing the user's emotions, and means for adjusting travel destination suggestions based on the user's emotion information. This makes it possible to suggest the optimal travel destination according to the user's real-time emotional state.

[0521] "Means for inputting user travel preferences" refers to an interface for users to input information such as their travel destination, interests, budget, and duration.

[0522] "Means for sending user input information to a server" refers to communication methods that have the function of appropriately formatting information entered by a user and sending it to a server via the internet.

[0523] "Means including an algorithm that analyzes user information submitted and generates travel destination suggestions based on that information" refers to a program or algorithm for analyzing user input information and generating appropriate travel destination suggestions.

[0524] "Means for sending generated suggestions to the user" refers to communication means that have the function of sending travel destination suggestions generated on the server back to the user's terminal.

[0525] "Means of displaying suggested information to the user" refers to displays and user interfaces that show received travel destination suggestions in a format that is easy for the user to understand.

[0526] "Means including an emotion engine that recognizes user emotions" refers to a system for analyzing and recognizing user emotions from user input and actions.

[0527] "Means for adjusting travel destination suggestions based on user sentiment information" refers to programs or algorithms that adjust suggestions based on recognized user sentiment and present the most suitable travel destination.

[0528] The following describes the detailed configuration of the system that realizes this application example. This system is built on the "Smart Trip Navigator" smartphone application installed in autonomous vehicles.

[0529] System Configuration

[0530] Hardware and software

[0531] The system of this invention uses the following hardware and software.

[0532] Hardware: In-vehicle displays installed in autonomous vehicles, smartphones

[0533] Software: Python (Flask framework), Google Cloud Natural Language API, MongoDB

[0534] Program generation content

[0535] In this system, terminals (smartphones and in-car displays) installed in autonomous vehicles receive data from users and send it to a server. The server analyzes the received data and processes it to suggest appropriate travel destinations. The following describes each process.

[0536] Processing at the terminal

[0537] 1. User Input: The terminal has a means for users to input their travel preferences, allowing them to enter their destination, interests, budget, duration, and desired mood (e.g., "relax").

[0538] 2. Data validation: Verify that the user's input information is entered correctly and convert the necessary information into JSON format.

[0539] 3. Data transmission: The validated data is sent to the server using the REST API.

[0540] Processing on the server

[0541] 4. Data reception and analysis: The server receives JSON-formatted data sent from the terminal and analyzes it using "means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it."

[0542] 5. Obtaining related information: Obtain relevant tourist spots and information from external APIs such as the Google Cloud Natural Language API and databases (MongoDB).

[0543] 6. Emotion-Based Suggestion Adjustment: Using "means including an emotion engine that recognizes the user's emotions," travel destination suggestions are adjusted based on the recognized emotions. For example, if the emotion is "relaxed," relaxing tourist spots will be suggested.

[0544] 7. Submit Proposal: Convert the generated proposal back into JSON format and send it to the terminal.

[0545] Displaying results on the device

[0546] 8. Display of Results: The suggested data received from the server is parsed and displayed on the in-car display or smartphone in a user-friendly format using the "means for displaying suggested information to the user."

[0547] Specific example

[0548] This example demonstrates how a user can use the system to request travel destination suggestions while inside an autonomous vehicle.

[0549] User input example:

[0550] Travel destination: Osaka

[0551] Interests: Food, beaches, events

[0552] Current mood: Relaxed

[0553] Examples of analysis and proposal generation on the server:

[0554] Travel destination: Osaka

[0555] Interests: Food, beaches, events

[0556] Emotion: Relax

[0557] Proposal details:

[0558] 1. Dotonbori - A spot where you can enjoy Osaka's rich food culture.

[0559] 2. "Nanko Sunset Beach" - A relaxing beach perfect for enjoying the sunset.

[0560] 3. "Osaka Castle Hall" - A venue where many concerts and events are held.

[0561] Example of a prompt

[0562] The following is an example of a prompt message for generating suggestions based on user data.

[0563] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[0564] Destination: Osaka

[0565] Interests: Food, beaches, events

[0566] Mood: Relaxed

[0567] Thus, the present invention realizes a system that provides accurate and timely suggestions for travel destinations within an autonomous vehicle, based on user input information and emotions.

[0568] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0569] Step 1:

[0570] Users input information such as their travel destination, interests, budget, duration, and feelings. Specifically, they use a smartphone app or in-car display interface to input information such as "Osaka," "Gourmet," "Seaside," "Events," and "Relaxation." The input data is triaged and passed on to the next step.

[0571] Step 2:

[0572] The terminal validates the user's input information. It checks whether the input information is accurate and whether there is any missing or inappropriate information. For example, it checks whether the entered destination is a valid place name and whether the interest category is correct.

[0573] Step 3:

[0574] The device converts the validated data into JSON format and sends it to the server. Specifically, it uses a REST API to send JSON data like the following to the server.

[0575] json

[0576] {

[0577] "destination": "Osaka",

[0578] "interests": ["Gourmet", "Seaside", "Events"]

[0579] "emotion": "relax"

[0580] }

[0581] Step 4:

[0582] The server receives and parses the JSON data sent from the terminal. Specifically, it parses the data and extracts the "destination," "interests," and "emotion" fields. The analysis results are saved for use in the next step.

[0583] Step 5:

[0584] The server collects relevant information based on the acquired data. Specifically, it references databases such as Google Cloud Natural Language API and MongoDB, as well as external APIs, to collect the following data:

[0585] "Dotonbori" (Gourmet)

[0586] "Nanko Sunset Beach" (seaside)

[0587] "Osaka Castle Hall" (event)

[0588] Step 6:

[0589] The server generates suggestions using an emotion engine based on the collected information. Specifically, it uses an AI algorithm (such as Scikit-learn) to suggest relaxing spots based on the user's emotional state, for example, prioritizing relaxing spots for a user who is "relaxed." The generated suggestions are saved in the following format.

[0590] json

[0591] {

[0592] "recommended_spots": [

[0593] {

[0594] "name": "Dotonbori",

[0595] "category": "Gourmet",

[0596] "details": "A spot where you can enjoy Osaka's rich food culture."

[0597] },

[0598] {

[0599] "name": "Nanko Sunset Beach",

[0600] "category": "Seaside",

[0601] "details": "A relaxing beach perfect for enjoying the sunset."

[0602] },

[0603] {

[0604] "name": "Osaka-jo Hall",

[0605] "category": "event",

[0606] "details": "A facility where many concerts and events are held."

[0607] }

[0608] ]

[0609] }

[0610] Step 7:

[0611] The server converts the generated suggestions into JSON format and sends them to the device. Specifically, it uses a REST API to send the suggestion data back to the device.

[0612] Step 8:

[0613] The device parses the received suggestion data. Specifically, it extracts "recommended_spots" from the JSON data and displays it on the in-car display or smartphone in a user-friendly format. An example of the display is shown below.

[0614] Travel destination: Osaka

[0615] Recommended tourist destinations

[0616] 1. Dotonbori (Gourmet)

[0617] Details: A spot where you can enjoy Osaka's rich food culture.

[0618] 2. Nanko Sunset Beach (Seaside)

[0619] Details: A relaxing beach perfect for enjoying the sunset.

[0620] 3. Osaka-jo Hall (Event)

[0621] Details: A venue where many concerts and events are held.

[0622] Example of a prompt:

[0623] The following is an example of a prompt message for generating suggestions based on user data.

[0624] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[0625] Destination: Osaka

[0626] Interests: Food, beaches, events

[0627] Mood: Relaxed

[0628] This prompt allows the system to automatically generate the most suitable suggestions for the user.

[0629] 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.

[0630] 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.

[0631] 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.

[0632] [Second Embodiment]

[0633] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0634] 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.

[0635] 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).

[0636] 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.

[0637] 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.

[0638] 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).

[0639] 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.

[0640] 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.

[0641] 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.

[0642] 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.

[0643] 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.

[0644] 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".

[0645] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[0646] System Configuration

[0647] 1. User input reception

[0648] Terminal:

[0649] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[0650] 2. Data transmission

[0651] Terminal:

[0652] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[0653] 3. Information Processing and Proposal Generation

[0654] server:

[0655] The server receives requests sent from terminals. The received data is analyzed, and semantic analysis and natural language processing techniques are used to select tourist destinations, local products, and trendy spots based on the user's preferences. Based on the analysis results, the server retrieves relevant information by referring to an internal database or external API. An AI algorithm is then used to generate optimal travel suggestions.

[0656] 4. Submit Proposal

[0657] server:

[0658] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about specific tourist destinations, local products, and trendy spots.

[0659] 5. Display results

[0660] Terminal:

[0661] The suggestions received from the server are displayed on the terminal. Users can then use these suggestions to create their own travel plans. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[0662] Specific example

[0663] This example illustrates how a user might use the system to request travel destination suggestions.

[0664] User input example

[0665] The user (let's call him / her Yamada) enters the following information.

[0666] Travel destination: Tokyo

[0667] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0668] Data transmission

[0669] The following information is sent from the terminal to the server.

[0670] json

[0671] {

[0672] "destination": "Tokyo",

[0673] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0674] }

[0675] Information processing and proposal generation

[0676] The server analyzes this information and generates the next suggestion.

[0677] Historical building: Senso-ji Temple

[0678] Sweets: Tokyo Banana

[0679] Newest tourist attraction: teamLab Planets

[0680] Proposal submission and results display

[0681] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[0682] Travel destination: Tokyo

[0683] Recommended tourist destinations

[0684] 1. Senso-ji Temple (Historical Building)

[0685] Details: One of Tokyo's most famous historical buildings.

[0686] 2. Tokyo Banana (Sweets)

[0687] Details: A representative Tokyo sweet, perfect as a souvenir.

[0688] 3. teamLab Planets (a new tourist attraction)

[0689] Details: A spot where you can experience the cutting edge of digital art.

[0690] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's preferences.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] User:

[0694] The user accesses an interface for creating a travel plan. The interface takes the form of a website or mobile application. The user enters information such as destination, interests, budget, and duration. For example, they might enter "Destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist attractions."

[0695] Step 2:

[0696] Terminal:

[0697] The system receives user input and validates it. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[0698] Step 3:

[0699] Terminal:

[0700] The REST API is used to send user input information to the server. An example of the data sent is as follows:

[0701] json

[0702] {

[0703] "destination": "Tokyo",

[0704] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0705] }

[0706] Step 4:

[0707] server:

[0708] The system receives requests sent from the terminal. It parses the JSON data and extracts key information such as "destination" and "interests". In this example, it extracts "destination: Tokyo" and "interests: historical buildings, sweets, latest tourist spots".

[0709] Step 5:

[0710] server:

[0711] We use semantic analysis and natural language processing techniques to understand user interests. Based on this, we refer to databases and external APIs to obtain information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[0712] Step 6:

[0713] server:

[0714] Based on the collected information, an AI algorithm is used to generate travel suggestions. By combining appropriate tourist destinations with detailed information, the system creates the most suitable travel plan for the user. In this case, for example, "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets" might be suggested.

[0715] Step 7:

[0716] server:

[0717] The generated travel suggestions are converted into JSON response data and sent to the terminal. The response data includes the names and details of each tourist destination.

[0718] Step 8:

[0719] Terminal:

[0720] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[0721] Travel destination: Tokyo

[0722] Recommended tourist destinations

[0723] 1. Senso-ji Temple (Historical Building)

[0724] Details: One of Tokyo's most famous historical buildings.

[0725] 2. Tokyo Banana (Sweets)

[0726] Details: A representative Tokyo sweet, perfect as a souvenir.

[0727] 3. teamLab Planets (a new tourist attraction)

[0728] Details: A spot where you can experience the cutting edge of digital art.

[0729] Step 9:

[0730] User:

[0731] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[0732] (Example 1)

[0733] 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."

[0734] In modern travel planning, users find it difficult to choose the right tourist destination from a vast amount of information. Furthermore, there is a lack of systems that suggest optimal travel destinations based on individual user interests and preferences. As a result, travel planning becomes complex and time-consuming.

[0735] 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.

[0736] In this invention, the server includes terminal means for inputting the user's travel preferences, communication means for transmitting the user's input information to the server, information processing means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it, transmission means for transmitting the generated travel suggestions to the user's terminal, and display means for visually displaying the suggested information to the user. This makes it possible to suggest optimal travel destinations based on the user's interests and preferences.

[0737] A "user" refers to an individual who uses the system to request travel destination suggestions.

[0738] "Travel preferences" refer to the user's requests regarding travel, such as desired destinations, tourist attractions of interest, budget, and duration.

[0739] "Terminal means" refers to a device used by users to input their travel preferences and receive information, such as a personal computer or smartphone.

[0740] "Communication methods" refer to communication protocols and technologies used to send information from a user's terminal to a server, including, for example, REST APIs and HTTP requests using the internet.

[0741] "Information processing means" refers to software and algorithms used by a server to analyze information sent by a user and generate travel destination suggestions.

[0742] "Transmission means" refers to the functions and technologies used to send generated travel suggestions from the server to the user's terminal.

[0743] "Display means" refers to an interface for visually presenting suggested travel information to the user, and includes, for example, the user interface of a web page or mobile application.

[0744] A "travel suggestion system" refers to a system that includes a series of means (terminal means, communication means, information processing means, transmission means, display means) for suggesting the most suitable travel destination based on information input by the user.

[0745] "Related data" refers to travel-related information and data obtained from internal databases or external sources based on user input.

[0746] "Generative artificial intelligence algorithms" refer to machine learning models and AI technologies used to analyze acquired relevant data and generate optimal travel suggestions.

[0747] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[0748] The main components of the system are as follows:

[0749] User input reception

[0750] Terminal:

[0751] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This input is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[0752] Specific example:

[0753] The user (let's call him Yamada) enters the following information:

[0754] Travel destination: Tokyo

[0755] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0756] Sending input data

[0757] Terminal:

[0758] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[0759] Specific example:

[0760] Examples of data sent from the terminal to the server:

[0761] json

[0762] {

[0763] "destination": "Tokyo",

[0764] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[0765] }

[0766] Data reception and analysis

[0767] server:

[0768] The server receives requests sent from terminals. After receiving the data, it performs format checks and content analysis. Using semantic analysis and natural language processing techniques, it retrieves data from internal databases or external sources to identify tourist destinations, local products, and trendy spots based on the user's preferences.

[0769] Specific example:

[0770] The system analyzes the received data and retrieves relevant data from its internal database. Specifically, it extracts entries that match the criteria "Travel destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist spots."

[0771] Proposal generation

[0772] server:

[0773] Based on the analyzed data, a generative AI model is used to generate optimal travel suggestions. The generative AI model takes into account the user's interests and past travel data to select the most appropriate travel destination.

[0774] Specific example:

[0775] Specific suggestions generated by the server:

[0776] Historical building: Senso-ji Temple

[0777] Sweets: Tokyo Banana

[0778] Newest tourist attraction: teamLab Planets

[0779] Submit a proposal

[0780] server:

[0781] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about tourist attractions, local products, and trendy spots.

[0782] Specific example:

[0783] Data sent from the server to the terminal:

[0784] json

[0785] {

[0786] "destination": "Tokyo",

[0787] "recommendations": [

[0788] {

[0789] "type": "Historical building",

[0790] "name": "Senso-ji Temple",

[0791] "details": "One of Tokyo's most famous historical buildings."

[0792] },

[0793] {

[0794] "type": "Sweets",

[0795] "name": "Tokyo Banana",

[0796] "details": "A representative Tokyo sweet, perfect as a souvenir."

[0797] },

[0798] {

[0799] "type": "Latest tourist spots",

[0800] "name": "teamLab Planets",

[0801] "details": "A spot where you can experience the cutting edge of digital art."

[0802] }

[0803] ]

[0804] }

[0805] Display of proposal results

[0806] Terminal:

[0807] The suggestions received from the server are displayed on the terminal. Users can then create their own travel plans based on these suggestions. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[0808] Specific example:

[0809] Example of how the device will appear to the user:

[0810] Travel destination: Tokyo

[0811] Recommended tourist destinations

[0812] 1. Senso-ji Temple (historical building)

[0813] Details: One of Tokyo's most famous historical buildings.

[0814] 2. Tokyo Banana (Sweets)

[0815] Details: A representative Tokyo sweet, perfect as a souvenir.

[0816] 3. teamLab Planets (a new tourist attraction)

[0817] Details: A spot where you can experience the cutting edge of digital art.

[0818] Example of a prompt

[0819] Example prompts for generating travel suggestions:

[0820] Please generate travel destination suggestions based on the following information.

[0821] Travel destination: Tokyo

[0822] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0823] As described above, a system is realized that efficiently and accurately suggests the most suitable travel destination based on the user's input preferences. This system can be used on various devices and supports the user's travel planning.

[0824] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0825] Step 1: The user enters their travel preferences.

[0826] The user accesses the terminal's interface and enters their travel preferences (e.g., cities they want to visit, tourist attractions of interest, local products, and the latest tourist spots). The user's input data (e.g., "Destination: Tokyo," "Interests: Historical buildings, sweets, and the latest tourist spots") is received and processed by the terminal.

[0827] Step 2: Send the input data to the server.

[0828] The terminal converts the information entered by the user into JSON format. The converted data is sent to the server using a REST API or HTTP request. The input data becomes the request body in JSON format and is sent to the server.

[0829] Step 3: Receive data, perform format check, and analyze content.

[0830] The server receives JSON data sent from the terminal. It checks the format of the received data and parses its contents. Specifically, it processes the data to identify relevant tourist destinations based on "Destination: Tokyo" and "Interests: Historical buildings, sweets, latest tourist spots."

[0831] Step 4: Obtain relevant data from internal databases and external sources.

[0832] Based on the analyzed data, the server references internal databases and external APIs to retrieve relevant information. For example, it collects data related to "Tokyo," "historical buildings," "sweets," and "the latest tourist spots."

[0833] Step 5: Generate proposals using a generative AI model.

[0834] The server uses a generative AI model to generate optimal travel suggestions based on the acquired relevant data. The generative AI model takes into account the user's interests and past travel data, and uses relevant tourist destination data to perform data calculations for recommended travel destinations (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets).

[0835] Step 6: Convert the generated proposal to JSON format and send it to the terminal.

[0836] The server converts the generated travel suggestions into a JSON response. The converted data is sent to the terminal via a transmission method. The data sent to the terminal includes details of tourist destinations, local products, and trendy spots based on the user's interests (e.g., information on "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets").

[0837] Step 7: Display the proposed results on the terminal.

[0838] The terminal parses the JSON data received from the server and displays it visually to the user. The display format is a clear and well-organized list, including detailed information and images for each tourist destination. Based on the displayed information, the user can create their own travel plan.

[0839] (Application Example 1)

[0840] 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."

[0841] In modern travel planning, users spend a great deal of time and effort gathering information and selecting the optimal destination. Furthermore, simply presenting information about a destination has limitations in motivating users to actually visit that place. Moreover, in today's world where remote travel experiences are increasingly common, the potential of virtual pre-experiences is often overlooked.

[0842] 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.

[0843] In this invention, the server includes means for experiencing travel suggestions generated based on user input within a virtual environment, server-side means including an algorithm that analyzes transmitted user information and generates travel destination suggestions based on it, and means for displaying the suggested information to the user. This allows the user not only to obtain optimal travel destination suggestions but also to experience those suggested destinations in advance within the virtual environment.

[0844] "Means for inputting user travel preferences" refers to providing an interface for users to input their travel preferences and requests to the system.

[0845] "Means for sending user input information to a server" refers to means for transferring information entered by a user on a terminal to a server via a network.

[0846] "Server-side means including an algorithm that analyzes the user's information sent and generates travel destination suggestions based on it" refers to a server-side processing system that uses an algorithm to analyze the information received from the user and generate optimal travel destination suggestions based on the analysis results.

[0847] "Means for sending generated suggestions to the user" refers to the means for sending travel destination suggestions generated on the server side back to the user's terminal.

[0848] "Means for displaying suggested information to the user" refers to means for displaying suggested travel destinations sent from the server in a format that the user can easily view.

[0849] "A means of experiencing travel suggestions generated based on user input within a virtual environment" refers to a method that uses virtual reality or augmented reality technology to simulate and virtually experience travel destination suggestions based on user input.

[0850] The system for realizing this invention is configured as follows: The user accesses the system using smart glasses or a head-mounted display. Here, Oculus Rift and Microsoft HoloLens are used as examples.

[0851] Acceptance of user input

[0852] Users input their travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel through the smart glasses' UI. This information is transmitted from the device to the server in real time.

[0853] Information processing and proposal generation

[0854] The server receives and analyzes the user's information. This analysis utilizes generative AI models such as OpenAI and employs advanced natural language processing techniques. In particular, it generates prompt sentences selected based on the user's input and then suggests the most suitable travel destination based on these prompts.

[0855] Data acquisition and proposal generation

[0856] Based on the analysis results, the server retrieves relevant information by referencing internal databases and external APIs. Based on the retrieved information, it generates prompt messages to suggest appropriate travel destinations, as follows:

[0857] Example of a prompt:

[0858] "Destination: Tokyo. Please suggest tourist attractions that focus on historical buildings and sweets."

[0859] Proposal display and virtual experience provision

[0860] Suggestions generated from the server are sent to the user's device. The user can then visually and interactively experience information about the suggested travel destinations through smart glasses or a head-mounted display. This allows the user to check destinations in a virtual environment beforehand and develop the optimal travel plan.

[0861] Specific example:

[0862] For example, if a user inputs "I like historical buildings and sweets in Tokyo," the AI ​​model will generate a prompt such as "Please suggest some historical buildings and sweets that I would recommend visiting in Tokyo." Based on this, the server will make specific suggestions such as Senso-ji Temple and Tokyo Banana, and allow users to experience these places within a virtual environment.

[0863] This system not only suggests travel destinations to users, but also enriches their travel planning through pre-experiences in a virtual environment. This invention significantly improves the efficiency and satisfaction users feel when choosing actual travel destinations.

[0864] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0865] Step 1: User input

[0866] Users wear smart glasses or a head-mounted display and input travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel. This input includes specific data such as destination, interests, budget, and duration.

[0867] input:

[0868] Travel destination: Tokyo

[0869] Interests: Historical buildings, sweets

[0870] Budget: 50,000 yen

[0871] Number of days: 3 days

[0872] output:

[0873] Input data in JSON format

[0874] Step 2: Sending data to the server

[0875] The terminal sends the information entered by the user to the server in JSON format. REST APIs and HTTP requests are used for data transmission.

[0876] input:

[0877] User input information (output from Step 1)

[0878] output:

[0879] JSON formatted data sent to the server

[0880] Step 3: Information analysis and prompt generation

[0881] The server analyzes the user's input information and generates appropriate prompt sentences using a generative AI model. Here, a natural language processing algorithm understands the user's wishes and creates prompt sentences that generate the optimal suggestions.

[0882] input:

[0883] JSON formatted data sent to the server

[0884] Operation:

[0885] Parsing JSON data

[0886] Generating prompt statements (for example, "Please suggest recommended spots in Tokyo related to historical buildings and sweets.")

[0887] output:

[0888] Generated prompt message

[0889] Step 4: Referencing an external database or API

[0890] Based on the generated prompt, the server consults an internal database or an external API to retrieve relevant travel destination information.

[0891] input:

[0892] Generated prompt message

[0893] Operation:

[0894] Retrieving relevant information from databases and external APIs (e.g., tourist attractions, local products, latest spots in your travel destination)

[0895] output:

[0896] Related information obtained

[0897] Step 5: Proposal Generation

[0898] The server generates optimal travel destination suggestions based on the relevant information it has acquired. In this process, a generation AI model determines the content of the suggestions.

[0899] input:

[0900] Related information obtained

[0901] Operation:

[0902] Generating proposals (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets)

[0903] output:

[0904] Generated travel destination suggestions

[0905] Step 6: Send the proposal to the user

[0906] The server converts the generated proposal back into a JSON response and sends it to the user's terminal.

[0907] input:

[0908] Generated travel destination suggestions

[0909] Operation:

[0910] Conversion to JSON format

[0911] Sending to the user terminal

[0912] output:

[0913] Proposal data in JSON format sent to the terminal

[0914] Step 7: Display of proposed content and virtual experience

[0915] Users visually review the received suggestions through smart glasses or a head-mounted display and experience them within a virtual environment.

[0916] input:

[0917] Proposal data in JSON format sent to the terminal

[0918] Operation:

[0919] Visual representation of the proposal

[0920] Experience within a virtual environment

[0921] output:

[0922] User feedback from virtual experiences

[0923] 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.

[0924] The following describes a specific embodiment of a user-generated travel destination suggestion system that incorporates an emotion engine. This system takes user preferences and emotions regarding travel as input and generates optimal travel destination suggestions based on that input.

[0925] System Configuration

[0926] 1. User input reception

[0927] Terminal:

[0928] Users access an interface for creating travel plans and input their travel preferences (e.g., cities they want to visit, tourist attractions and local products they are interested in, the latest tourist spots, etc.). The interface also features an emotion engine that recognizes the user's emotions from their input and actions. The input form includes fields such as destination, interests, budget, number of days, and current mood.

[0929] 2. Data transmission

[0930] Terminal:

[0931] The system receives user input and emotion information recognized by the emotion engine, and validates the input. It verifies that the necessary information and emotion data have been entered correctly, converts the data to JSON format, and prepares it for transmission.

[0932] 3. Information transmission

[0933] Terminal:

[0934] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[0935] json

[0936] {

[0937] "destination": "Tokyo",

[0938] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0939] "emotion": "excitement"

[0940] }

[0941] 4. Information Analysis and Proposal Generation

[0942] server:

[0943] The server receives the request sent from the terminal. It parses the data in JSON format and extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[0944] 5. Obtaining related information

[0945] server:

[0946] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[0947] 6. Emotion-based proposal adjustment

[0948] server:

[0949] Based on the collected information, the AI ​​algorithm generates travel suggestions, adjusting them based on the user's emotions as recognized by the emotion engine. For example, a user who is "excited" will be suggested more active tourist spots.

[0950] 7. Submit Proposal

[0951] server:

[0952] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[0953] 8. Results display

[0954] Terminal:

[0955] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[0956] Travel destination: Tokyo

[0957] Recommended tourist destinations

[0958] 1. Senso-ji Temple (Historical Building)

[0959] Details: One of Tokyo's most famous historical buildings.

[0960] 2. Tokyo Banana (Sweets)

[0961] Details: A representative Tokyo sweet, perfect as a souvenir.

[0962] 3. teamLab Planets (a new tourist attraction)

[0963] Details: A spot where you can experience the cutting edge of digital art.

[0964] Specific example

[0965] This example illustrates how a user might use the system to request travel destination suggestions.

[0966] User input example

[0967] The user (let's call him Mr. Sato) enters the following information.

[0968] Travel destination: Tokyo

[0969] Interests: Historical buildings, sweets, and the latest tourist attractions.

[0970] Current mood: "Excited"

[0971] Data transmission

[0972] The following information is sent from the terminal to the server.

[0973] json

[0974] {

[0975] "destination": "Tokyo",

[0976] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[0977] "emotion": "excitement"

[0978] }

[0979] Information analysis and proposal generation

[0980] The server analyzes this information and generates the next suggestion.

[0981] Historical building: Senso-ji Temple

[0982] Sweets: Tokyo Banana

[0983] Newest tourist attraction: teamLab Planets

[0984] Proposal submission and results display

[0985] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[0986] Travel destination: Tokyo

[0987] Recommended tourist destinations

[0988] 1. Senso-ji Temple (Historical Building)

[0989] Details: One of Tokyo's most famous historical buildings.

[0990] 2. Tokyo Banana (Sweets)

[0991] Details: A representative Tokyo sweet, perfect as a souvenir.

[0992] 3. teamLab Planets (a new tourist attraction)

[0993] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[0994] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's input preferences and emotions.

[0995] The following describes the processing flow.

[0996] Step 1:

[0997] User:

[0998] Users access an interface for creating travel plans and enter their travel preferences (destination, areas of interest, local products, latest tourist attractions, etc.). They also enter their current mood or feelings (e.g., "excited"). The input form includes text boxes and dropdown lists.

[0999] Step 2:

[1000] Terminal:

[1001] The system receives user input and validates the input content and sentiment data. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[1002] Step 3:

[1003] Terminal:

[1004] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[1005] json

[1006] {

[1007] "destination": "Tokyo",

[1008] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1009] "emotion": "excitement"

[1010] }

[1011] Step 4:

[1012] server:

[1013] The system receives requests sent from the terminal and parses the data in JSON format. It extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[1014] Step 5:

[1015] server:

[1016] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[1017] Step 6:

[1018] server:

[1019] Based on the collected information, an AI algorithm is used to generate travel suggestions. The emotion engine then adjusts the suggestions based on the user's recognized emotions. For example, a user who is "excited" will be suggested more active and exciting tourist spots.

[1020] Step 7:

[1021] server:

[1022] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[1023] Step 8:

[1024] Terminal:

[1025] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[1026] Travel destination: Tokyo

[1027] Recommended tourist destinations

[1028] 1. Senso-ji Temple (Historical Building)

[1029] Details: One of Tokyo's most famous historical buildings.

[1030] 2. Tokyo Banana (Sweets)

[1031] Details: A representative Tokyo sweet, perfect as a souvenir.

[1032] 3. teamLab Planets (a new tourist attraction)

[1033] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[1034] Step 9:

[1035] User:

[1036] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[1037] (Example 2)

[1038] 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".

[1039] Conventional travel suggestion systems offer suggestions based on user preferences, but they do not provide specific and personalized suggestions that take into account the user's emotions. As a result, they are unable to suggest travel destinations and tourist spots that match the user's current mood, and improving the user experience remains a challenge.

[1040] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1041] In this invention, the server includes means for analyzing user input information and emotional information and generating travel destination suggestions based on that information, means for obtaining relevant information from a database or external API, and means for adjusting the suggestion content based on the user's emotions. This makes it possible to suggest appropriate travel destinations and tourist spots that match the user's current emotions.

[1042] A "user" refers to someone who inputs information into the system to receive suggestions for travel destinations and tourist spots.

[1043] "Travel preferences" refer to specific requests and interests of users, such as cities they want to visit, tourist destinations, local products, and the latest tourist spots.

[1044] "Emotions" refers to the user's current mood or emotional state, and includes emotions such as "excitement" and "enjoyment."

[1045] An "emotion engine" refers to a software component that has the function of recognizing and analyzing emotions from user input and actions.

[1046] A "server" refers to a computer system that receives information sent by users, analyzes it, and generates suggestions.

[1047] A "database" refers to a data storage system used to store information about travel destinations and tourist spots based on user interests.

[1048] An "external API" refers to an application program interface used to retrieve information from an external data source.

[1049] "AI algorithms" refer to artificial intelligence technology that generates optimal suggestions based on the user's wishes and emotions.

[1050] "Suggestions" refer to recommendations for travel destinations and tourist spots generated based on user input and emotions.

[1051] "JSON format" refers to a data format used to structure user input information and sentiment information and send it to a server.

[1052] "Response data" refers to the formalized data that the server sends to the terminal, containing the generated suggestions.

[1053] "Parsing" refers to the process of analyzing response data received from a server and converting it into a format that can be displayed on the user interface.

[1054] Modes for carrying out the invention

[1055] The travel suggestion system according to the present invention is a system that takes the user's travel preferences and emotions as input and generates optimal travel destination suggestions based on them. This system consists of a terminal, a server, an emotion engine, and an AI algorithm.

[1056] User input reception

[1057] Users access a travel plan creation interface via their device. The interface displays forms for inputting information such as destination, interests, budget, duration, and current mood. By entering this information, the system obtains the user's preferences and interests. The interface also incorporates an emotion engine, which recognizes emotions from the user's input and actions.

[1058] Information validation and preparation for transmission

[1059] The information entered by the user and the sentiment information recognized by the sentiment engine are validated on the device. If validation is successful, this information is converted to JSON format and ready to be sent to the server.

[1060] Server-based information analysis

[1061] The server receives JSON data sent from the terminal. The server analyzes this data and extracts key information such as "travel destination," "interests," and "emotions." Based on this, it performs a detailed analysis of the user's requests and emotions.

[1062] Obtaining related information

[1063] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions. Based on this, it retrieves information about relevant travel destinations and tourist spots using databases and external APIs. For example, it collects detailed information about "historical buildings," "sweets," and "the latest tourist attractions" from the database.

[1064] Adjusting emotionally driven proposals

[1065] The server uses an AI algorithm to generate travel suggestions based on the collected information. During this process, the suggestion is adjusted based on the user's emotions, as analyzed by the emotion engine. For example, a user who is "excited" will be advised to visit active and exciting tourist spots.

[1066] Proposal generation and submission

[1067] The generated travel suggestions are converted back into JSON format and sent from the server to the terminal. The response data includes the names of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[1068] Display of proposal results

[1069] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, if "Tokyo" is suggested as a travel destination, "famous temples" are displayed as historical buildings, "local specialties" as sweets, and "digital art facilities" as the latest tourist attractions.

[1070] Specific example

[1071] For example, the user enters the following prompt into the system:

[1072] "Travel destination: Tokyo, Interests: Historical buildings, sweets, new tourist attractions, Current mood: Excited"

[1073] As a result, the server generates and sends the following suggestion to the terminal:

[1074] "Travel destination: Tokyo, Recommended tourist spots:"

[1075] 1. Famous temples (historical buildings)

[1076] Details: One of Tokyo's most famous historical buildings.

[1077] 2. Local specialties (sweets)

[1078] Details: A representative Tokyo sweet, perfect as a souvenir.

[1079] 3. Digital art facilities (the latest tourist attractions)

[1080] Details: A spot where you can experience the cutting edge of digital art.

[1081] In this way, the present invention provides effective travel suggestions based on the user's wishes and emotions.

[1082] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1083] Step 1:

[1084] User input reception

[1085] The user accesses an interface for creating a travel plan and enters information such as destination, interests, budget, duration, and current mood. Once the user has finished entering information, the device collects this information, and the emotion engine recognizes the user's emotions from their input and actions. Input data may include, for example, "Destination: Tokyo," "Interests: Historical buildings, sweets, new tourist attractions," and "Current mood: Excited." The output provides information about the user's preferences and emotions.

[1086] Step 2:

[1087] Information validation and preparation for transmission

[1088] The device validates the information entered by the user and the sentiment information recognized by the sentiment engine. If validation is successful, the device converts this information into JSON format and prepares it for transmission. Specific validation processes include checking whether the travel destination is available and whether interest items are specified. Input consists of user-entered preference information and sentiment information, and output is validated data in JSON format.

[1089] Step 3:

[1090] Sending input data to the server

[1091] The device sends validated JSON-formatted input data and sentiment information to the server using a REST API. For example, the following JSON data is sent:

[1092] json

[1093] {

[1094] "destination": "Tokyo",

[1095] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1096] "emotion": "excitement"

[1097] }

[1098] The input is validated JSON data, and the output is data sent to the server.

[1099] Step 4:

[1100] Server-based information analysis

[1101] The server receives JSON data sent from the terminal and performs analysis. Specifically, it extracts key information related to "travel destination," "interests," and "emotions." For example, the server might extract information such as "travel destination: Tokyo," "interests: historical buildings, sweets, latest tourist spots," and "emotions: excitement." The input is the received JSON data, and the output is the extracted key information.

[1102] Step 5:

[1103] Server retrieves relevant information

[1104] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions, and then retrieves relevant information by referencing databases and external APIs. For example, it can collect detailed information from the database about "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo." The input is analyzed key information, and the output is related tourist destination data.

[1105] Step 6:

[1106] Adjusting emotionally driven proposals

[1107] The server generates travel suggestions using an AI algorithm based on the collected relevant information. At this time, the suggestions are adjusted based on the user's emotions, as analyzed by the emotion engine. For example, for a user who is "excited," active and dynamic tourist spots are prioritized. The input consists of relevant tourist destination data and emotion information, and the output is adjusted travel suggestions.

[1108] Step 7:

[1109] Proposal generation and submission

[1110] The server converts the generated travel suggestions back into JSON format and sends them to the terminal. For example, the response data might include the names and details of each tourist destination, as well as specific suggestions based on the user's mood. The input is the adjusted travel suggestions, and the output is the response data converted into JSON format, which is sent to the terminal.

[1111] Step 8:

[1112] Display of proposal results

[1113] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, it might look like this:

[1114] Travel destination: Tokyo

[1115] Recommended tourist destinations

[1116] 1. Famous temples (historical buildings)

[1117] Details: One of Tokyo's most famous historical buildings.

[1118] 2. Local specialties (sweets)

[1119] Details: A representative Tokyo sweet, perfect as a souvenir.

[1120] 3. Digital art facilities (the latest tourist attractions)

[1121] Details: A spot where you can experience the cutting edge of digital art.

[1122] The input is response data received from the server, and the output is a visual suggestion display for the user.

[1123] (Application Example 2)

[1124] 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."

[1125] Conventional travel suggestion systems have the problem of not being able to provide optimal suggestions that match the user's real-time mood and emotions, because they suggest travel destinations without considering the user's emotional state. Furthermore, especially in autonomous vehicles, there is a need to provide appropriate suggestions instantly in order to offer a safe and comfortable travel experience while also facilitating travel planning.

[1126] 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. In this invention, the server includes means for inputting the user's travel preferences, means for transmitting the user's input information to the server, means including an algorithm for analyzing the transmitted user information and generating travel destination suggestions based thereon, means for transmitting the generated suggestions to the user, means for displaying the suggested information to the user, means including an emotion engine for recognizing the user's emotions, and means for adjusting travel destination suggestions based on the user's emotion information. This makes it possible to suggest the optimal travel destination according to the user's real-time emotional state.

[1127] "Means for inputting user travel preferences" refers to an interface for users to input information such as their travel destination, interests, budget, and duration.

[1128] "Means for sending user input information to a server" refers to communication methods that have the function of appropriately formatting information entered by a user and sending it to a server via the internet.

[1129] "Means including an algorithm that analyzes user information submitted and generates travel destination suggestions based on that information" refers to a program or algorithm for analyzing user input information and generating appropriate travel destination suggestions.

[1130] "Means for sending generated suggestions to the user" refers to communication means that have the function of sending travel destination suggestions generated on the server back to the user's terminal.

[1131] "Means of displaying suggested information to the user" refers to displays and user interfaces that show received travel destination suggestions in a format that is easy for the user to understand.

[1132] "Means including an emotion engine that recognizes user emotions" refers to a system for analyzing and recognizing user emotions from user input and actions.

[1133] "Means for adjusting travel destination suggestions based on user sentiment information" refers to programs or algorithms that adjust suggestions based on recognized user sentiment and present the most suitable travel destination.

[1134] The following describes the detailed configuration of the system that realizes this application example. This system is built on the "Smart Trip Navigator" smartphone application installed in autonomous vehicles.

[1135] System Configuration

[1136] Hardware and software

[1137] The system of this invention uses the following hardware and software.

[1138] Hardware: In-vehicle displays installed in autonomous vehicles, smartphones

[1139] Software: Python (Flask framework), Google Cloud Natural Language API, MongoDB

[1140] Program generation content

[1141] In this system, terminals (smartphones and in-vehicle displays) installed in autonomous vehicles receive data from users and transmit it to a server. The server analyzes the received data and processes it to suggest appropriate travel destinations. The following describes each process.

[1142] Processing at the terminal

[1143] 1. User Input: The terminal has a means for users to input their travel preferences, allowing them to enter their destination, interests, budget, duration, and desired mood (e.g., "relax").

[1144] 2. Data validation: Verify that the user's input information is entered correctly and convert the necessary information into JSON format.

[1145] 3. Data transmission: The validated data is sent to the server using the REST API.

[1146] Processing on the server

[1147] 4. Data reception and analysis: The server receives JSON-formatted data sent from the terminal and analyzes it using "means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it."

[1148] 5. Obtaining related information: Obtain relevant tourist spots and information from external APIs such as the Google Cloud Natural Language API and databases (MongoDB).

[1149] 6. Emotion-Based Suggestion Adjustment: Using "means including an emotion engine that recognizes the user's emotions," travel destination suggestions are adjusted based on the recognized emotions. For example, if the emotion is "relaxed," relaxing tourist spots will be suggested.

[1150] 7. Submit Proposal: Convert the generated proposal back into JSON format and send it to the terminal.

[1151] Displaying results on the device

[1152] 8. Display of Results: The suggested data received from the server is parsed and displayed on the in-car display or smartphone in a user-friendly format using the "means for displaying suggested information to the user."

[1153] Specific example

[1154] This example demonstrates how a user can use the system to request travel destination suggestions while inside an autonomous vehicle.

[1155] User input example:

[1156] Travel destination: Osaka

[1157] Interests: Food, beaches, events

[1158] Current mood: Relaxed

[1159] Examples of analysis and proposal generation on the server:

[1160] Travel destination: Osaka

[1161] Interests: Food, beaches, events

[1162] Emotion: Relax

[1163] Proposal details:

[1164] 1. Dotonbori - A spot where you can enjoy Osaka's rich food culture.

[1165] 2. "Nanko Sunset Beach" - A relaxing beach perfect for enjoying the sunset.

[1166] 3. "Osaka Castle Hall" - A venue where many concerts and events are held.

[1167] Example of a prompt

[1168] The following is an example of a prompt message for generating suggestions based on user data.

[1169] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[1170] Destination: Osaka

[1171] Interests: Food, beaches, events

[1172] Mood: Relaxed

[1173] Thus, the present invention realizes a system that provides accurate and timely suggestions for travel destinations within an autonomous vehicle, based on user input information and emotions.

[1174] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1175] Step 1:

[1176] Users input information such as their travel destination, interests, budget, duration, and feelings. Specifically, they use a smartphone app or in-car display interface to input information such as "Osaka," "Gourmet," "Seaside," "Events," and "Relaxation." The input data is triaged and passed on to the next step.

[1177] Step 2:

[1178] The terminal validates the user's input information. It checks whether the input information is accurate and whether there is any missing or inappropriate information. For example, it checks whether the entered destination is a valid place name and whether the interest category is correct.

[1179] Step 3:

[1180] The device converts the validated data into JSON format and sends it to the server. Specifically, it uses a REST API to send JSON data like the following to the server.

[1181] json

[1182] {

[1183] "destination": "Osaka",

[1184] "interests": ["Gourmet", "Seaside", "Events"]

[1185] "emotion": "relax"

[1186] }

[1187] Step 4:

[1188] The server receives and parses the JSON data sent from the terminal. Specifically, it parses the data and extracts the "destination," "interests," and "emotion" fields. The analysis results are saved for use in the next step.

[1189] Step 5:

[1190] The server collects relevant information based on the acquired data. Specifically, it references databases such as Google Cloud Natural Language API and MongoDB, as well as external APIs, to collect the following data:

[1191] "Dotonbori" (Gourmet)

[1192] "Nanko Sunset Beach" (seaside)

[1193] "Osaka Castle Hall" (event)

[1194] Step 6:

[1195] The server generates suggestions using an emotion engine based on the collected information. Specifically, it uses an AI algorithm (such as Scikit-learn) to suggest relaxing spots based on the user's emotional state, for example, prioritizing relaxing spots for a user who is "relaxed." The generated suggestions are saved in the following format.

[1196] json

[1197] {

[1198] "recommended_spots": [

[1199] {

[1200] "name": "Dotonbori",

[1201] "category": "Gourmet",

[1202] "details": "A spot where you can enjoy Osaka's rich food culture."

[1203] },

[1204] {

[1205] "name": "Nanko Sunset Beach",

[1206] "category": "Seaside",

[1207] "details": "A relaxing beach perfect for enjoying the sunset."

[1208] },

[1209] {

[1210] "name": "Osaka-jo Hall",

[1211] "category": "event",

[1212] "details": "A facility where many concerts and events are held."

[1213] }

[1214] ]

[1215] }

[1216] Step 7:

[1217] The server converts the generated suggestions into JSON format and sends them to the device. Specifically, it uses a REST API to send the suggestion data back to the device.

[1218] Step 8:

[1219] The device parses the received suggestion data. Specifically, it extracts "recommended_spots" from the JSON data and displays it on the in-car display or smartphone in a user-friendly format. An example of the display is shown below.

[1220] Travel destination: Osaka

[1221] Recommended tourist destinations

[1222] 1. Dotonbori (Gourmet)

[1223] Details: A spot where you can enjoy Osaka's rich food culture.

[1224] 2. Nanko Sunset Beach (Seaside)

[1225] Details: A relaxing beach perfect for enjoying the sunset.

[1226] 3. Osaka-jo Hall (Event)

[1227] Details: A venue where many concerts and events are held.

[1228] Example of a prompt:

[1229] The following is an example of a prompt message for generating suggestions based on user data.

[1230] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[1231] Destination: Osaka

[1232] Interests: Food, beaches, events

[1233] Mood: Relaxed

[1234] This prompt allows the system to automatically generate the most suitable suggestions for the user.

[1235] 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.

[1236] 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.

[1237] 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.

[1238] [Third Embodiment]

[1239] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1240] 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.

[1241] 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).

[1242] 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.

[1243] 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.

[1244] 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).

[1245] 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.

[1246] 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.

[1247] 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.

[1248] 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.

[1249] 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.

[1250] 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".

[1251] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[1252] System Configuration

[1253] 1. User input reception

[1254] Terminal:

[1255] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[1256] 2. Data transmission

[1257] Terminal:

[1258] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[1259] 3. Information Processing and Proposal Generation

[1260] server:

[1261] The server receives requests sent from terminals. The received data is analyzed, and semantic analysis and natural language processing techniques are used to select tourist destinations, local products, and trendy spots based on the user's preferences. Based on the analysis results, the server retrieves relevant information by referring to an internal database or external API. An AI algorithm is then used to generate optimal travel suggestions.

[1262] 4. Submit Proposal

[1263] server:

[1264] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about specific tourist destinations, local products, and trendy spots.

[1265] 5. Display results

[1266] Terminal:

[1267] The suggestions received from the server are displayed on the terminal. Users can then use these suggestions to create their own travel plans. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[1268] Specific example

[1269] This example illustrates how a user might use the system to request travel destination suggestions.

[1270] User input example

[1271] The user (let's call him / her Yamada) enters the following information.

[1272] Travel destination: Tokyo

[1273] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1274] Data transmission

[1275] The following information is sent from the terminal to the server.

[1276] json

[1277] {

[1278] "destination": "Tokyo",

[1279] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1280] }

[1281] Information processing and proposal generation

[1282] The server analyzes this information and generates the next suggestion.

[1283] Historical building: Senso-ji Temple

[1284] Sweets: Tokyo Banana

[1285] Newest tourist attraction: teamLab Planets

[1286] Proposal submission and results display

[1287] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[1288] Travel destination: Tokyo

[1289] Recommended tourist destinations

[1290] 1. Senso-ji Temple (Historical Building)

[1291] Details: One of Tokyo's most famous historical buildings.

[1292] 2. Tokyo Banana (Sweets)

[1293] Details: A representative Tokyo sweet, perfect as a souvenir.

[1294] 3. teamLab Planets (a new tourist attraction)

[1295] Details: A spot where you can experience the cutting edge of digital art.

[1296] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's preferences.

[1297] The following describes the processing flow.

[1298] Step 1:

[1299] User:

[1300] The user accesses an interface for creating a travel plan. The interface takes the form of a website or mobile application. The user enters information such as destination, interests, budget, and duration. For example, they might enter "Destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist attractions."

[1301] Step 2:

[1302] Terminal:

[1303] The system receives user input and validates it. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[1304] Step 3:

[1305] Terminal:

[1306] The REST API is used to send user input information to the server. An example of the data sent is as follows:

[1307] json

[1308] {

[1309] "destination": "Tokyo",

[1310] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1311] }

[1312] Step 4:

[1313] server:

[1314] The system receives requests sent from the terminal. It parses the JSON data and extracts key information such as "destination" and "interests". In this example, it extracts "destination: Tokyo" and "interests: historical buildings, sweets, latest tourist spots".

[1315] Step 5:

[1316] server:

[1317] We use semantic analysis and natural language processing techniques to understand user interests. Based on this, we refer to databases and external APIs to obtain information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[1318] Step 6:

[1319] server:

[1320] Based on the collected information, an AI algorithm is used to generate travel suggestions. By combining appropriate tourist destinations with detailed information, the system creates the most suitable travel plan for the user. In this case, for example, "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets" might be suggested.

[1321] Step 7:

[1322] server:

[1323] The generated travel suggestions are converted into JSON response data and sent to the terminal. The response data includes the names and details of each tourist destination.

[1324] Step 8:

[1325] Terminal:

[1326] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[1327] Travel destination: Tokyo

[1328] Recommended tourist destinations

[1329] 1. Senso-ji Temple (Historical Building)

[1330] Details: One of Tokyo's most famous historical buildings.

[1331] 2. Tokyo Banana (Sweets)

[1332] Details: A representative Tokyo sweet, perfect as a souvenir.

[1333] 3. teamLab Planets (a new tourist attraction)

[1334] Details: A spot where you can experience the cutting edge of digital art.

[1335] Step 9:

[1336] User:

[1337] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[1338] (Example 1)

[1339] 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."

[1340] In modern travel planning, users find it difficult to choose the right tourist destination from a vast amount of information. Furthermore, there is a lack of systems that suggest optimal travel destinations based on individual user interests and preferences. As a result, travel planning becomes complex and time-consuming.

[1341] 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.

[1342] In this invention, the server includes terminal means for inputting the user's travel preferences, communication means for transmitting the user's input information to the server, information processing means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it, transmission means for transmitting the generated travel suggestions to the user's terminal, and display means for visually displaying the suggested information to the user. This makes it possible to suggest optimal travel destinations based on the user's interests and preferences.

[1343] A "user" refers to an individual who uses the system to request travel destination suggestions.

[1344] "Travel preferences" refer to the user's requests regarding travel, such as desired destinations, tourist spots of interest, budget, and duration.

[1345] "Terminal means" refers to a device used by a user to input their travel preferences and receive information, such as a personal computer or smartphone.

[1346] "Communication methods" refer to communication protocols and technologies used to send information from a user's terminal to a server, including, for example, REST APIs and HTTP requests using the internet.

[1347] "Information processing means" refers to software and algorithms used by a server to analyze information sent by a user and generate travel destination suggestions.

[1348] "Transmission means" refers to the functions and technologies used to send generated travel suggestions from the server to the user's terminal.

[1349] "Display means" refers to an interface for visually presenting suggested travel information to the user, and includes, for example, the user interface of a web page or mobile application.

[1350] A "travel suggestion system" refers to a system that includes a series of means (terminal means, communication means, information processing means, transmission means, display means) for suggesting the most suitable travel destination based on information input by the user.

[1351] "Related data" refers to travel-related information and data obtained from internal databases or external sources based on user input.

[1352] "Generative artificial intelligence algorithms" refer to machine learning models and AI technologies used to analyze acquired relevant data and generate optimal travel suggestions.

[1353] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[1354] The main components of the system are as follows:

[1355] User input reception

[1356] Terminal:

[1357] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This input is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[1358] Specific example:

[1359] The user (let's call him Yamada) enters the following information:

[1360] Travel destination: Tokyo

[1361] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1362] Sending input data

[1363] Terminal:

[1364] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[1365] Specific example:

[1366] Examples of data sent from the terminal to the server:

[1367] json

[1368] {

[1369] "destination": "Tokyo",

[1370] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1371] }

[1372] Data reception and analysis

[1373] server:

[1374] The server receives requests sent from terminals. After receiving the data, it performs format checks and content analysis. Using semantic analysis and natural language processing techniques, it retrieves data from internal databases or external sources to identify tourist destinations, local products, and trendy spots based on the user's preferences.

[1375] Specific example:

[1376] The system analyzes the received data and retrieves relevant data from its internal database. Specifically, it extracts entries that match the criteria "Travel destination: Tokyo" and "Interests: Historical buildings, sweets, latest tourist spots."

[1377] Proposal generation

[1378] server:

[1379] Based on the analyzed data, a generative AI model is used to generate optimal travel suggestions. The generative AI model takes into account the user's interests and past travel data to select the most appropriate travel destination.

[1380] Specific example:

[1381] Specific suggestions generated by the server:

[1382] Historical building: Senso-ji Temple

[1383] Sweets: Tokyo Banana

[1384] Newest tourist attraction: teamLab Planets

[1385] Submit a proposal

[1386] server:

[1387] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about tourist attractions, local products, and trendy spots.

[1388] Specific example:

[1389] Data sent from the server to the terminal:

[1390] json

[1391] {

[1392] "destination": "Tokyo",

[1393] "recommendations": [

[1394] {

[1395] "type": "Historical building",

[1396] "name": "Senso-ji Temple",

[1397] "details": "One of Tokyo's most famous historical buildings."

[1398] },

[1399] {

[1400] "type": "Sweets",

[1401] "name": "Tokyo Banana",

[1402] "details": "A representative Tokyo sweet, perfect as a souvenir."

[1403] },

[1404] {

[1405] "type": "Latest tourist spots",

[1406] "name": "teamLab Planets",

[1407] "details": "A spot where you can experience the cutting edge of digital art."

[1408] }

[1409] ]

[1410] }

[1411] Display of proposal results

[1412] Terminal:

[1413] The suggestions received from the server are displayed on the terminal. Users can then create their own travel plans based on these suggestions. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[1414] Specific example:

[1415] Example of how the device will appear to the user:

[1416] Travel destination: Tokyo

[1417] Recommended tourist destinations

[1418] 1. Senso-ji Temple (historical building)

[1419] Details: One of Tokyo's most famous historical buildings.

[1420] 2. Tokyo Banana (Sweets)

[1421] Details: A representative Tokyo sweet, perfect as a souvenir.

[1422] 3. teamLab Planets (a new tourist attraction)

[1423] Details: A spot where you can experience the cutting edge of digital art.

[1424] Example of a prompt

[1425] Example prompts for generating travel suggestions:

[1426] Please generate travel destination suggestions based on the following information.

[1427] Travel destination: Tokyo

[1428] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1429] As described above, a system is realized that efficiently and accurately suggests the most suitable travel destination based on the user's input preferences. This system can be used on various devices and supports the user's travel planning.

[1430] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1431] Step 1: The user enters their travel preferences.

[1432] The user accesses the terminal's interface and enters their travel preferences (e.g., cities they want to visit, tourist attractions of interest, local products, and the latest tourist spots). The user's input data (e.g., "Destination: Tokyo," "Interests: Historical buildings, sweets, and the latest tourist spots") is received and processed by the terminal.

[1433] Step 2: Send the input data to the server.

[1434] The terminal converts the information entered by the user into JSON format. The converted data is sent to the server using a REST API or HTTP request. The input data becomes the request body in JSON format and is sent to the server.

[1435] Step 3: Receive data, perform format check, and analyze content.

[1436] The server receives JSON data sent from the terminal. It checks the format of the received data and parses its contents. Specifically, it processes the data to identify relevant tourist destinations based on "Destination: Tokyo" and "Interests: Historical buildings, sweets, latest tourist spots."

[1437] Step 4: Obtain relevant data from internal databases and external sources.

[1438] Based on the analyzed data, the server references internal databases and external APIs to retrieve relevant information. For example, it collects data related to "Tokyo," "historical buildings," "sweets," and "the latest tourist spots."

[1439] Step 5: Generate proposals using a generative AI model.

[1440] The server uses a generative AI model to generate optimal travel suggestions based on the acquired relevant data. The generative AI model takes into account the user's interests and past travel data, and uses relevant tourist destination data to perform data calculations for recommended travel destinations (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets).

[1441] Step 6: Convert the generated proposal to JSON format and send it to the terminal.

[1442] The server converts the generated travel suggestions into a JSON response. The converted data is sent to the terminal via a transmission method. The data sent to the terminal includes details of tourist destinations, local products, and trendy spots based on the user's interests (e.g., information on "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets").

[1443] Step 7: Display the proposed results on the terminal.

[1444] The terminal parses the JSON data received from the server and displays it visually to the user. The display format is a clear and well-organized list, including detailed information and images for each tourist destination. Based on the displayed information, the user can create their own travel plan.

[1445] (Application Example 1)

[1446] 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."

[1447] In modern travel planning, users spend a great deal of time and effort gathering information and selecting the optimal destination. Furthermore, simply presenting information about a destination has limitations in motivating users to actually visit that place. Moreover, in today's world where remote travel experiences are increasingly common, the potential of virtual pre-experiences is often overlooked.

[1448] 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.

[1449] In this invention, the server includes means for experiencing travel suggestions generated based on user input within a virtual environment, server-side means including an algorithm that analyzes transmitted user information and generates travel destination suggestions based on it, and means for displaying the suggested information to the user. This allows the user not only to obtain optimal travel destination suggestions but also to experience those suggested destinations in advance within the virtual environment.

[1450] "Means for inputting user travel preferences" refers to providing an interface for users to input their travel preferences and requests to the system.

[1451] "Means for sending user input information to a server" refers to means for transferring information entered by a user on a terminal to a server via a network.

[1452] "Server-side means including an algorithm that analyzes the user's information sent and generates travel destination suggestions based on it" refers to a server-side processing system that uses an algorithm to analyze the information received from the user and generate optimal travel destination suggestions based on the analysis results.

[1453] "Means for sending generated suggestions to the user" refers to the means for sending travel destination suggestions generated on the server side back to the user's terminal.

[1454] "Means for displaying suggested information to the user" refers to means for displaying suggested travel destinations sent from the server in a format that the user can easily view.

[1455] "A means of experiencing travel suggestions generated based on user input within a virtual environment" refers to a method that uses virtual reality or augmented reality technology to simulate and virtually experience travel destination suggestions based on user input.

[1456] The system for realizing this invention is configured as follows: The user accesses the system using smart glasses or a head-mounted display. Here, Oculus Rift and Microsoft HoloLens are used as examples.

[1457] Acceptance of user input

[1458] Users input their travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel through the smart glasses' UI. This information is transmitted from the device to the server in real time.

[1459] Information processing and proposal generation

[1460] The server receives and analyzes the user's information. This analysis utilizes generative AI models such as OpenAI and employs advanced natural language processing techniques. In particular, it generates prompt sentences selected based on the user's input and then suggests the most suitable travel destination based on these prompts.

[1461] Data acquisition and proposal generation

[1462] Based on the analysis results, the server retrieves relevant information by referencing internal databases and external APIs. Based on the retrieved information, it generates prompt messages to suggest appropriate travel destinations, as follows:

[1463] Example of a prompt:

[1464] "Destination: Tokyo. Please suggest tourist attractions that focus on historical buildings and sweets."

[1465] Proposal display and virtual experience provision

[1466] Suggestions generated from the server are sent to the user's device. The user can then visually and interactively experience information about the suggested travel destinations through smart glasses or a head-mounted display. This allows the user to check destinations in a virtual environment beforehand and develop the optimal travel plan.

[1467] Specific example:

[1468] For example, if a user inputs "I like historical buildings and sweets in Tokyo," the AI ​​model will generate a prompt such as "Please suggest some historical buildings and sweets that I would recommend visiting in Tokyo." Based on this, the server will make specific suggestions such as Senso-ji Temple and Tokyo Banana, and allow users to experience these places within a virtual environment.

[1469] This system not only suggests travel destinations to users, but also enriches their travel planning through pre-experiences in a virtual environment. This invention significantly improves the efficiency and satisfaction users feel when choosing actual travel destinations.

[1470] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1471] Step 1: User input

[1472] Users wear smart glasses or a head-mounted display and input travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel. This input includes specific data such as destination, interests, budget, and duration.

[1473] input:

[1474] Travel destination: Tokyo

[1475] Interests: Historical buildings, sweets

[1476] Budget: 50,000 yen

[1477] Number of days: 3 days

[1478] output:

[1479] Input data in JSON format

[1480] Step 2: Sending data to the server

[1481] The terminal sends the information entered by the user to the server in JSON format. REST APIs and HTTP requests are used for data transmission.

[1482] input:

[1483] User input information (output from Step 1)

[1484] output:

[1485] JSON formatted data sent to the server

[1486] Step 3: Information analysis and prompt generation

[1487] The server analyzes the user's input information and generates appropriate prompt sentences using a generative AI model. Here, a natural language processing algorithm understands the user's wishes and creates prompt sentences that generate the optimal suggestions.

[1488] input:

[1489] JSON formatted data sent to the server

[1490] Operation:

[1491] Parsing JSON data

[1492] Generating prompt statements (for example, "Please suggest recommended spots in Tokyo related to historical buildings and sweets.")

[1493] output:

[1494] Generated prompt message

[1495] Step 4: Referencing an external database or API

[1496] Based on the generated prompt, the server consults an internal database or an external API to retrieve relevant travel destination information.

[1497] input:

[1498] Generated prompt message

[1499] Operation:

[1500] Retrieving relevant information from databases and external APIs (e.g., tourist attractions, local products, latest spots in your travel destination)

[1501] output:

[1502] Related information obtained

[1503] Step 5: Proposal Generation

[1504] The server generates optimal travel destination suggestions based on the relevant information it has acquired. In this process, a generation AI model determines the content of the suggestions.

[1505] input:

[1506] Related information obtained

[1507] Operation:

[1508] Generating proposals (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets)

[1509] output:

[1510] Generated travel destination suggestions

[1511] Step 6: Send the proposal to the user

[1512] The server converts the generated proposal back into a JSON response and sends it to the user's terminal.

[1513] input:

[1514] Generated travel destination suggestions

[1515] Operation:

[1516] Conversion to JSON format

[1517] Sending to the user terminal

[1518] output:

[1519] Proposal data in JSON format sent to the terminal

[1520] Step 7: Display of proposed content and virtual experience

[1521] Users visually review the received suggestions through smart glasses or a head-mounted display and experience them within a virtual environment.

[1522] input:

[1523] Proposal data in JSON format sent to the terminal

[1524] Operation:

[1525] Visual representation of the proposal

[1526] Experience within a virtual environment

[1527] output:

[1528] User feedback from virtual experiences

[1529] 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.

[1530] The following describes a specific embodiment of a user-generated travel destination suggestion system that incorporates an emotion engine. This system takes user preferences and emotions regarding travel as input and generates optimal travel destination suggestions based on that input.

[1531] System Configuration

[1532] 1. User input reception

[1533] Terminal:

[1534] Users access an interface for creating travel plans and input their travel preferences (e.g., cities they want to visit, tourist attractions and local products they are interested in, the latest tourist spots, etc.). The interface also features an emotion engine that recognizes the user's emotions from their input and actions. The input form includes fields such as destination, interests, budget, number of days, and current mood.

[1535] 2. Data transmission

[1536] Terminal:

[1537] The system receives user input and emotion information recognized by the emotion engine, and validates the input. It verifies that the necessary information and emotion data have been entered correctly, converts the data to JSON format, and prepares it for transmission.

[1538] 3. Information transmission

[1539] Terminal:

[1540] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[1541] json

[1542] {

[1543] "destination": "Tokyo",

[1544] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1545] "emotion": "excitement"

[1546] }

[1547] 4. Information Analysis and Proposal Generation

[1548] server:

[1549] The server receives the request sent from the terminal. It parses the data in JSON format and extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[1550] 5. Obtaining related information

[1551] server:

[1552] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[1553] 6. Emotion-based proposal adjustment

[1554] server:

[1555] Based on the collected information, the AI ​​algorithm generates travel suggestions, adjusting them based on the user's emotions as recognized by the emotion engine. For example, a user who is "excited" will be suggested more active tourist spots.

[1556] 7. Submit Proposal

[1557] server:

[1558] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[1559] 8. Results display

[1560] Terminal:

[1561] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[1562] Travel destination: Tokyo

[1563] Recommended tourist destinations

[1564] 1. Senso-ji Temple (Historical Building)

[1565] Details: One of Tokyo's most famous historical buildings.

[1566] 2. Tokyo Banana (Sweets)

[1567] Details: A representative Tokyo sweet, perfect as a souvenir.

[1568] 3. teamLab Planets (a new tourist attraction)

[1569] Details: A spot where you can experience the cutting edge of digital art.

[1570] Specific example

[1571] This example illustrates how a user might use the system to request travel destination suggestions.

[1572] User input example

[1573] The user (let's call him Mr. Sato) enters the following information.

[1574] Travel destination: Tokyo

[1575] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1576] Current mood: "Excited"

[1577] Data transmission

[1578] The following information is sent from the terminal to the server.

[1579] json

[1580] {

[1581] "destination": "Tokyo",

[1582] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1583] "emotion": "excitement"

[1584] }

[1585] Information analysis and proposal generation

[1586] The server analyzes this information and generates the next suggestion.

[1587] Historical building: Senso-ji Temple

[1588] Sweets: Tokyo Banana

[1589] Newest tourist attraction: teamLab Planets

[1590] Proposal submission and results display

[1591] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[1592] Travel destination: Tokyo

[1593] Recommended tourist destinations

[1594] 1. Senso-ji Temple (Historical Building)

[1595] Details: One of Tokyo's most famous historical buildings.

[1596] 2. Tokyo Banana (Sweets)

[1597] Details: A representative Tokyo sweet, perfect as a souvenir.

[1598] 3. teamLab Planets (a new tourist attraction)

[1599] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[1600] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's input preferences and emotions.

[1601] The following describes the processing flow.

[1602] Step 1:

[1603] User:

[1604] Users access an interface for creating travel plans and enter their travel preferences (destination, areas of interest, local products, latest tourist attractions, etc.). They also enter their current mood or feelings (e.g., "excited"). The input form includes text boxes and dropdown lists.

[1605] Step 2:

[1606] Terminal:

[1607] The system receives user input and validates the input content and sentiment data. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[1608] Step 3:

[1609] Terminal:

[1610] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[1611] json

[1612] {

[1613] "destination": "Tokyo",

[1614] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1615] "emotion": "excitement"

[1616] }

[1617] Step 4:

[1618] server:

[1619] The system receives requests sent from the terminal and parses the data in JSON format. It extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[1620] Step 5:

[1621] server:

[1622] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[1623] Step 6:

[1624] server:

[1625] Based on the collected information, an AI algorithm is used to generate travel suggestions. The emotion engine then adjusts the suggestions based on the user's recognized emotions. For example, a user who is "excited" will be suggested more active and exciting tourist spots.

[1626] Step 7:

[1627] server:

[1628] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[1629] Step 8:

[1630] Terminal:

[1631] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[1632] Travel destination: Tokyo

[1633] Recommended tourist destinations

[1634] 1. Senso-ji Temple (Historical Building)

[1635] Details: One of Tokyo's most famous historical buildings.

[1636] 2. Tokyo Banana (Sweets)

[1637] Details: A representative Tokyo sweet, perfect as a souvenir.

[1638] 3. teamLab Planets (a new tourist attraction)

[1639] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[1640] Step 9:

[1641] User:

[1642] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[1643] (Example 2)

[1644] 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."

[1645] Conventional travel suggestion systems offer suggestions based on user preferences, but they do not provide specific and personalized suggestions that take into account the user's emotions. As a result, they are unable to suggest travel destinations and tourist spots that match the user's current mood, and improving the user experience remains a challenge.

[1646] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1647] In this invention, the server includes means for analyzing user input information and emotional information and generating travel destination suggestions based on that information, means for obtaining relevant information from a database or external API, and means for adjusting the suggestion content based on the user's emotions. This makes it possible to suggest appropriate travel destinations and tourist spots that match the user's current emotions.

[1648] A "user" refers to someone who inputs information into the system to receive suggestions for travel destinations and tourist spots.

[1649] "Travel preferences" refer to specific requests and interests of users, such as cities they want to visit, tourist destinations, local products, and the latest tourist spots.

[1650] "Emotions" refers to the user's current mood or emotional state, and includes emotions such as "excitement" and "enjoyment."

[1651] An "emotion engine" refers to a software component that has the function of recognizing and analyzing emotions from user input and actions.

[1652] A "server" refers to a computer system that receives information sent by users, analyzes it, and generates suggestions.

[1653] A "database" refers to a data storage system used to store information about travel destinations and tourist spots based on user interests.

[1654] An "external API" refers to an application program interface used to retrieve information from an external data source.

[1655] "AI algorithms" refer to artificial intelligence technology that generates optimal suggestions based on the user's wishes and emotions.

[1656] "Suggestions" refer to recommendations for travel destinations and tourist spots generated based on user input and emotions.

[1657] "JSON format" refers to a data format used to structure user input information and sentiment information and send it to a server.

[1658] "Response data" refers to the formalized data that the server generates and sends to the terminal.

[1659] "Parsing" refers to the process of analyzing response data received from a server and converting it into a format that can be displayed on the user interface.

[1660] Modes for carrying out the invention

[1661] The travel suggestion system according to the present invention is a system that takes the user's travel preferences and emotions as input and generates optimal travel destination suggestions based on them. This system consists of a terminal, a server, an emotion engine, and an AI algorithm.

[1662] User input reception

[1663] Users access a travel plan creation interface via their device. The interface displays forms for inputting information such as destination, interests, budget, duration, and current mood. By entering this information, the system obtains the user's preferences and interests. The interface also incorporates an emotion engine, which recognizes emotions from the user's input and actions.

[1664] Information validation and preparation for transmission

[1665] The information entered by the user and the sentiment information recognized by the sentiment engine are validated on the device. If validation is successful, this information is converted to JSON format and ready to be sent to the server.

[1666] Server-based information analysis

[1667] The server receives JSON data sent from the terminal. The server analyzes this data and extracts key information such as "travel destination," "interests," and "emotions." Based on this, it performs a detailed analysis of the user's requests and emotions.

[1668] Obtaining related information

[1669] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions. Based on this, it retrieves information about relevant travel destinations and tourist spots using databases and external APIs. For example, it collects detailed information about "historical buildings," "sweets," and "the latest tourist attractions" from the database.

[1670] Adjusting emotionally driven proposals

[1671] The server uses an AI algorithm to generate travel suggestions based on the collected information. During this process, the suggestion is adjusted based on the user's emotions, as analyzed by the emotion engine. For example, a user who is "excited" will be advised to visit active and exciting tourist spots.

[1672] Proposal generation and submission

[1673] The generated travel suggestions are converted back into JSON format and sent from the server to the terminal. The response data includes the names of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[1674] Display of proposal results

[1675] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, if "Tokyo" is suggested as a travel destination, "famous temples" are displayed as historical buildings, "local specialties" as sweets, and "digital art facilities" as the latest tourist attractions.

[1676] Specific example

[1677] For example, the user enters the following prompt into the system:

[1678] "Travel destination: Tokyo, Interests: Historical buildings, sweets, new tourist attractions, Current mood: Excited"

[1679] As a result, the server generates and sends the following suggestion to the terminal:

[1680] "Travel destination: Tokyo, Recommended tourist spots:"

[1681] 1. Famous temples (historical buildings)

[1682] Details: One of Tokyo's most famous historical buildings.

[1683] 2. Local specialties (sweets)

[1684] Details: A representative Tokyo sweet, perfect as a souvenir.

[1685] 3. Digital art facilities (the latest tourist attractions)

[1686] Details: A spot where you can experience the cutting edge of digital art.

[1687] In this way, the present invention provides effective travel suggestions based on the user's wishes and emotions.

[1688] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1689] Step 1:

[1690] User input reception

[1691] The user accesses an interface for creating a travel plan and enters information such as destination, interests, budget, duration, and current mood. Once the user has finished entering information, the device collects this information, and the emotion engine recognizes the user's emotions from their input and actions. Input data may include, for example, "Destination: Tokyo," "Interests: Historical buildings, sweets, new tourist attractions," and "Current mood: Excited." The output provides information about the user's preferences and emotions.

[1692] Step 2:

[1693] Information validation and preparation for transmission

[1694] The device validates the information entered by the user and the sentiment information recognized by the sentiment engine. If validation is successful, the device converts this information into JSON format and prepares it for transmission. Specific validation processes include checking whether the travel destination is available and whether interest items are specified. Input consists of user-entered preference information and sentiment information, and output is validated data in JSON format.

[1695] Step 3:

[1696] Sending input data to the server

[1697] The device sends validated JSON-formatted input data and sentiment information to the server using a REST API. For example, the following JSON data is sent:

[1698] json

[1699] {

[1700] "destination": "Tokyo",

[1701] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[1702] "emotion": "excitement"

[1703] }

[1704] The input is validated JSON data, and the output is data sent to the server.

[1705] Step 4:

[1706] Server-based information analysis

[1707] The server receives JSON data sent from the terminal and performs analysis. Specifically, it extracts key information related to "travel destination," "interests," and "emotions." For example, the server might extract information such as "travel destination: Tokyo," "interests: historical buildings, sweets, latest tourist spots," and "emotions: excitement." The input is the received JSON data, and the output is the extracted key information.

[1708] Step 5:

[1709] Server retrieves relevant information

[1710] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions, and then retrieves relevant information by referencing databases and external APIs. For example, it can collect detailed information from the database about "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo." The input is analyzed key information, and the output is related tourist destination data.

[1711] Step 6:

[1712] Adjusting emotionally driven proposals

[1713] The server generates travel suggestions using an AI algorithm based on the collected relevant information. At this time, the suggestions are adjusted based on the user's emotions, as analyzed by the emotion engine. For example, for a user who is "excited," active and dynamic tourist spots are prioritized. The input consists of relevant tourist destination data and emotion information, and the output is adjusted travel suggestions.

[1714] Step 7:

[1715] Proposal generation and submission

[1716] The server converts the generated travel suggestions back into JSON format and sends them to the terminal. For example, the response data might include the names and details of each tourist destination, as well as specific suggestions based on the user's mood. The input is the adjusted travel suggestions, and the output is the response data converted into JSON format, which is sent to the terminal.

[1717] Step 8:

[1718] Display of proposal results

[1719] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, it might look like this:

[1720] Travel destination: Tokyo

[1721] Recommended tourist destinations

[1722] 1. Famous temples (historical buildings)

[1723] Details: One of Tokyo's most famous historical buildings.

[1724] 2. Local specialties (sweets)

[1725] Details: A representative Tokyo sweet, perfect as a souvenir.

[1726] 3. Digital art facilities (the latest tourist attractions)

[1727] Details: A spot where you can experience the cutting edge of digital art.

[1728] The input is response data received from the server, and the output is a visual suggestion display for the user.

[1729] (Application Example 2)

[1730] 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."

[1731] Conventional travel suggestion systems have the problem of not being able to provide optimal suggestions that match the user's real-time mood and emotions, because they suggest travel destinations without considering the user's emotional state. Furthermore, especially in autonomous vehicles, there is a need to provide appropriate suggestions instantly in order to offer a safe and comfortable travel experience while also facilitating travel planning.

[1732] 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. In this invention, the server includes means for inputting the user's travel preferences, means for transmitting the user's input information to the server, means including an algorithm for analyzing the transmitted user information and generating travel destination suggestions based thereon, means for transmitting the generated suggestions to the user, means for displaying the suggested information to the user, means including an emotion engine for recognizing the user's emotions, and means for adjusting travel destination suggestions based on the user's emotion information. This makes it possible to suggest the optimal travel destination according to the user's real-time emotional state.

[1733] "Means for inputting user travel preferences" refers to an interface for users to input information such as their travel destination, interests, budget, and duration.

[1734] "Means for sending user input information to a server" refers to communication methods that have the function of appropriately formatting information entered by a user and sending it to a server via the internet.

[1735] "Means including an algorithm that analyzes user information submitted and generates travel destination suggestions based on that information" refers to a program or algorithm for analyzing user input information and generating appropriate travel destination suggestions.

[1736] "Means for sending generated suggestions to the user" refers to communication means that have the function of sending travel destination suggestions generated on the server back to the user's terminal.

[1737] "Means of displaying suggested information to the user" refers to displays and user interfaces that show received travel destination suggestions in a format that is easy for the user to understand.

[1738] "Means including an emotion engine that recognizes user emotions" refers to a system for analyzing and recognizing user emotions from user input and actions.

[1739] "Means for adjusting travel destination suggestions based on user sentiment information" refers to programs or algorithms that adjust suggestions based on recognized user sentiment and present the most suitable travel destination.

[1740] The following describes the detailed configuration of the system that realizes this application example. This system is built on the "Smart Trip Navigator" smartphone application installed in autonomous vehicles.

[1741] System Configuration

[1742] Hardware and software

[1743] The system of this invention uses the following hardware and software.

[1744] Hardware: In-vehicle displays installed in autonomous vehicles, smartphones

[1745] Software: Python (Flask framework), Google Cloud Natural Language API, MongoDB

[1746] Program generation content

[1747] In this system, terminals (smartphones and in-vehicle displays) installed in autonomous vehicles receive data from users and transmit it to a server. The server analyzes the received data and processes it to suggest appropriate travel destinations. The following describes each process.

[1748] Processing at the terminal

[1749] 1. User Input: The terminal has a means for users to input their travel preferences, allowing them to enter their destination, interests, budget, duration, and desired mood (e.g., "relax").

[1750] 2. Data validation: Verify that the user's input information is entered correctly and convert the necessary information into JSON format.

[1751] 3. Data transmission: The validated data is sent to the server using the REST API.

[1752] Processing on the server

[1753] 4. Data reception and analysis: The server receives JSON-formatted data sent from the terminal and analyzes it using "means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it."

[1754] 5. Obtaining related information: Obtain relevant tourist spots and information from external APIs such as the Google Cloud Natural Language API and databases (MongoDB).

[1755] 6. Emotion-Based Suggestion Adjustment: Using "means including an emotion engine that recognizes the user's emotions," travel destination suggestions are adjusted based on the recognized emotions. For example, if the emotion is "relaxed," relaxing tourist spots will be suggested.

[1756] 7. Submit Proposal: Convert the generated proposal back into JSON format and send it to the terminal.

[1757] Displaying results on the device

[1758] 8. Display of Results: The suggested data received from the server is parsed and displayed on the in-car display or smartphone in a user-friendly format using the "means for displaying suggested information to the user."

[1759] Specific example

[1760] This example demonstrates how a user can use the system to request travel destination suggestions while inside an autonomous vehicle.

[1761] User input example:

[1762] Travel destination: Osaka

[1763] Interests: Food, beaches, events

[1764] Current mood: Relaxed

[1765] Examples of analysis and proposal generation on the server:

[1766] Travel destination: Osaka

[1767] Interests: Food, beaches, events

[1768] Emotion: Relax

[1769] Proposal details:

[1770] 1. Dotonbori - A spot where you can enjoy Osaka's rich food culture.

[1771] 2. "Nanko Sunset Beach" - A relaxing beach perfect for enjoying the sunset.

[1772] 3. "Osaka Castle Hall" - A venue where many concerts and events are held.

[1773] Example of a prompt

[1774] The following is an example of a prompt message for generating suggestions based on user data.

[1775] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[1776] Destination: Osaka

[1777] Interests: Food, beaches, events

[1778] Mood: Relaxed

[1779] Thus, the present invention realizes a system that provides accurate and timely suggestions for travel destinations within an autonomous vehicle, based on user input information and emotions.

[1780] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1781] Step 1:

[1782] Users input information such as their travel destination, interests, budget, duration, and feelings. Specifically, they use a smartphone app or in-car display interface to input information such as "Osaka," "Gourmet," "Seaside," "Events," and "Relaxation." The input data is triaged and passed on to the next step.

[1783] Step 2:

[1784] The terminal validates the user's input information. It checks whether the input information is accurate and whether there is any missing or inappropriate information. For example, it checks whether the entered destination is a valid place name and whether the interest category is correct.

[1785] Step 3:

[1786] The device converts the validated data into JSON format and sends it to the server. Specifically, it uses a REST API to send JSON data like the following to the server.

[1787] json

[1788] {

[1789] "destination": "Osaka",

[1790] "interests": ["Gourmet", "Seaside", "Events"]

[1791] "emotion": "relax"

[1792] }

[1793] Step 4:

[1794] The server receives and parses the JSON data sent from the terminal. Specifically, it parses the data and extracts the "destination," "interests," and "emotion" fields. The analysis results are saved for use in the next step.

[1795] Step 5:

[1796] The server collects relevant information based on the acquired data. Specifically, it references databases such as Google Cloud Natural Language API and MongoDB, as well as external APIs, to collect the following data:

[1797] "Dotonbori" (Gourmet)

[1798] "Nanko Sunset Beach" (seaside)

[1799] "Osaka Castle Hall" (event)

[1800] Step 6:

[1801] The server generates suggestions using an emotion engine based on the collected information. Specifically, it uses an AI algorithm (such as Scikit-learn) to suggest relaxing spots based on the user's emotional state, for example, prioritizing relaxing spots for a user who is "relaxed." The generated suggestions are saved in the following format.

[1802] json

[1803] {

[1804] "recommended_spots": [

[1805] {

[1806] "name": "Dotonbori",

[1807] "category": "Gourmet",

[1808] "details": "A spot where you can enjoy Osaka's rich food culture."

[1809] },

[1810] {

[1811] "name": "Nanko Sunset Beach",

[1812] "category": "Seaside",

[1813] "details": "A relaxing beach perfect for enjoying the sunset."

[1814] },

[1815] {

[1816] "name": "Osaka-jo Hall",

[1817] "category": "event",

[1818] "details": "A facility where many concerts and events are held."

[1819] }

[1820] ]

[1821] }

[1822] Step 7:

[1823] The server converts the generated suggestions into JSON format and sends them to the device. Specifically, it uses a REST API to send the suggestion data back to the device.

[1824] Step 8:

[1825] The device parses the received suggestion data. Specifically, it extracts "recommended_spots" from the JSON data and displays it on the in-car display or smartphone in a user-friendly format. An example of the display is shown below.

[1826] Travel destination: Osaka

[1827] Recommended tourist destinations

[1828] 1. Dotonbori (Gourmet)

[1829] Details: A spot where you can enjoy Osaka's rich food culture.

[1830] 2. Nanko Sunset Beach (Seaside)

[1831] Details: A relaxing beach perfect for enjoying the sunset.

[1832] 3. Osaka-jo Hall (Event)

[1833] Details: A venue where many concerts and events are held.

[1834] Example of a prompt:

[1835] The following is an example of a prompt message for generating suggestions based on user data.

[1836] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[1837] Destination: Osaka

[1838] Interests: Food, beaches, events

[1839] Mood: Relaxed

[1840] This prompt allows the system to automatically generate the most suitable suggestions for the user.

[1841] 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.

[1842] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[1843] 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.

[1844] [Fourth Embodiment]

[1845] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1846] 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.

[1847] 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).

[1848] 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.

[1849] 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.

[1850] 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).

[1851] 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.

[1852] 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.

[1853] 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.

[1854] 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.

[1855] 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.

[1856] 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.

[1857] 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".

[1858] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[1859] System Configuration

[1860] 1. User input reception

[1861] Terminal:

[1862] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[1863] 2. Data transmission

[1864] Terminal:

[1865] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[1866] 3. Information Processing and Proposal Generation

[1867] server:

[1868] The server receives requests sent from terminals. The received data is analyzed, and semantic analysis and natural language processing techniques are used to select tourist destinations, local products, and trendy spots based on the user's preferences. Based on the analysis results, the server retrieves relevant information by referring to an internal database or external API. An AI algorithm is then used to generate optimal travel suggestions.

[1869] 4. Submit Proposal

[1870] server:

[1871] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about specific tourist destinations, local products, and trendy spots.

[1872] 5. Display results

[1873] Terminal:

[1874] The suggestions received from the server are displayed on the terminal. Users can then use these suggestions to create their own travel plans. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[1875] Specific example

[1876] This example illustrates how a user might use the system to request travel destination suggestions.

[1877] User input example

[1878] The user (let's call him / her Yamada) enters the following information.

[1879] Travel destination: Tokyo

[1880] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1881] Data transmission

[1882] The following information is sent from the terminal to the server.

[1883] json

[1884] {

[1885] "destination": "Tokyo",

[1886] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1887] }

[1888] Information processing and proposal generation

[1889] The server analyzes this information and generates the next suggestion.

[1890] Historical building: Senso-ji Temple

[1891] Sweets: Tokyo Banana

[1892] Newest tourist attraction: teamLab Planets

[1893] Proposal submission and results display

[1894] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[1895] Travel destination: Tokyo

[1896] Recommended tourist destinations

[1897] 1. Senso-ji Temple (Historical Building)

[1898] Details: One of Tokyo's most famous historical buildings.

[1899] 2. Tokyo Banana (Sweets)

[1900] Details: A representative Tokyo sweet, perfect as a souvenir.

[1901] 3. teamLab Planets (a new tourist attraction)

[1902] Details: A spot where you can experience the cutting edge of digital art.

[1903] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's preferences.

[1904] The following describes the processing flow.

[1905] Step 1:

[1906] User:

[1907] The user accesses an interface for creating a travel plan. The interface takes the form of a website or mobile application. The user enters information such as destination, interests, budget, and duration. For example, they might enter "Destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist attractions."

[1908] Step 2:

[1909] Terminal:

[1910] The system receives user input and validates it. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[1911] Step 3:

[1912] Terminal:

[1913] The REST API is used to send user input information to the server. An example of the data sent is as follows:

[1914] json

[1915] {

[1916] "destination": "Tokyo",

[1917] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1918] }

[1919] Step 4:

[1920] server:

[1921] The system receives requests sent from the terminal. It parses the JSON data and extracts key information such as "destination" and "interests". In this example, it extracts "destination: Tokyo" and "interests: historical buildings, sweets, latest tourist spots".

[1922] Step 5:

[1923] server:

[1924] We use semantic analysis and natural language processing techniques to understand user interests. Based on this, we refer to databases and external APIs to obtain information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[1925] Step 6:

[1926] server:

[1927] Based on the collected information, an AI algorithm is used to generate travel suggestions. By combining appropriate tourist destinations with detailed information, the system creates the most suitable travel plan for the user. In this case, for example, "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets" might be suggested.

[1928] Step 7:

[1929] server:

[1930] The generated travel suggestions are converted into JSON response data and sent to the terminal. The response data includes the names and details of each tourist destination.

[1931] Step 8:

[1932] Terminal:

[1933] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[1934] Travel destination: Tokyo

[1935] Recommended tourist destinations

[1936] 1. Senso-ji Temple (Historical Building)

[1937] Details: One of Tokyo's most famous historical buildings.

[1938] 2. Tokyo Banana (Sweets)

[1939] Details: A representative Tokyo sweet, perfect as a souvenir.

[1940] 3. teamLab Planets (a new tourist attraction)

[1941] Details: A spot where you can experience the cutting edge of digital art.

[1942] Step 9:

[1943] User:

[1944] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[1945] (Example 1)

[1946] 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".

[1947] In modern travel planning, users find it difficult to choose the right tourist destination from a vast amount of information. Furthermore, there is a lack of systems that suggest optimal travel destinations based on individual user interests and preferences. As a result, travel planning becomes complex and time-consuming.

[1948] 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.

[1949] In this invention, the server includes terminal means for inputting the user's travel preferences, communication means for transmitting the user's input information to the server, information processing means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it, transmission means for transmitting the generated travel suggestions to the user's terminal, and display means for visually displaying the suggested information to the user. This makes it possible to suggest optimal travel destinations based on the user's interests and preferences.

[1950] A "user" refers to an individual who uses the system to request travel destination suggestions.

[1951] "Travel preferences" refer to the user's requests regarding travel, such as desired destinations, tourist spots of interest, budget, and duration.

[1952] "Terminal means" refers to a device used by a user to input their travel preferences and receive information, such as a personal computer or smartphone.

[1953] "Communication methods" refer to communication protocols and technologies used to send information from a user's terminal to a server, including, for example, REST APIs and HTTP requests using the internet.

[1954] "Information processing means" refers to software and algorithms used by a server to analyze information sent by a user and generate travel destination suggestions.

[1955] "Transmission means" refers to the functions and technologies used to send generated travel suggestions from the server to the user's terminal.

[1956] "Display means" refers to an interface for visually presenting suggested travel information to the user, and includes, for example, the user interface of a web page or mobile application.

[1957] A "travel suggestion system" refers to a system that includes a series of means (terminal means, communication means, information processing means, transmission means, display means) for suggesting the most suitable travel destination based on information input by the user.

[1958] "Related data" refers to travel-related information and data obtained from internal databases or external sources based on user input.

[1959] "Generative artificial intelligence algorithms" refer to machine learning models and AI technologies used to analyze acquired relevant data and generate optimal travel suggestions.

[1960] The following describes a specific implementation of the user travel destination suggestion system. This system takes the user's travel preferences as input and generates optimal travel destination suggestions based on those preferences.

[1961] The main components of the system are as follows:

[1962] User input reception

[1963] Terminal:

[1964] Users access an interface for creating travel plans and enter their travel preferences (e.g., cities they want to visit, places of interest, local products, new tourist attractions, etc.). This input is done through a user interface such as a website or mobile application. The input form includes fields such as destination, interests, budget, and duration.

[1965] Specific example:

[1966] The user (let's call him Yamada) enters the following information:

[1967] Travel destination: Tokyo

[1968] Interests: Historical buildings, sweets, and the latest tourist attractions.

[1969] Sending input data

[1970] Terminal:

[1971] Information entered by the user is sent from the terminal to the server. Data transmission is performed using REST APIs or HTTP requests. In this process, the information entered by the user is converted into a JSON-formatted request body.

[1972] Specific example:

[1973] Examples of data sent from the terminal to the server:

[1974] json

[1975] {

[1976] "destination": "Tokyo",

[1977] "Interests": ["Historical buildings", "Sweets", "Newest tourist attractions"]

[1978] }

[1979] Data reception and analysis

[1980] server:

[1981] The server receives requests sent from terminals. After receiving the data, it performs format checks and content analysis. Using semantic analysis and natural language processing techniques, it retrieves data from internal databases or external sources to identify tourist destinations, local products, and trendy spots based on the user's preferences.

[1982] Specific example:

[1983] The system analyzes the received data and retrieves relevant data from its internal database. Specifically, it extracts entries that match the criteria "Travel destination: Tokyo" and "Interests: Historical buildings, sweets, and the latest tourist spots."

[1984] Proposal generation

[1985] server:

[1986] Based on the analyzed data, a generative AI model is used to generate optimal travel suggestions. The generative AI model takes into account the user's interests and past travel data to select the most appropriate travel destination.

[1987] Specific example:

[1988] Specific suggestions generated by the server:

[1989] Historical building: Senso-ji Temple

[1990] Sweets: Tokyo Banana

[1991] Newest tourist attraction: teamLab Planets

[1992] Submit a proposal

[1993] server:

[1994] The generated travel suggestions are converted back into a JSON response and sent to the terminal. The suggestions include details about tourist attractions, local products, and trendy spots.

[1995] Specific example:

[1996] Data sent from the server to the terminal:

[1997] json

[1998] {

[1999] "destination": "Tokyo",

[2000] "recommendations": [

[2001] {

[2002] "type": "Historical building",

[2003] "name": "Senso-ji Temple",

[2004] "details": "One of Tokyo's most famous historical buildings."

[2005] },

[2006] {

[2007] "type": "Sweets",

[2008] "name": "Tokyo Banana",

[2009] "details": "A representative Tokyo sweet, perfect as a souvenir."

[2010] },

[2011] {

[2012] "type": "Latest tourist spots",

[2013] "name": "teamLab Planets",

[2014] "details": "A spot where you can experience the cutting edge of digital art."

[2015] }

[2016] ]

[2017] }

[2018] Display of proposal results

[2019] Terminal:

[2020] The suggestions received from the server are displayed on the terminal. Users can then create their own travel plans based on these suggestions. The suggestions are displayed in an easy-to-read format and include detailed information and images of each tourist destination.

[2021] Specific example:

[2022] Example of how the device will appear to the user:

[2023] Travel destination: Tokyo

[2024] Recommended tourist destinations

[2025] 1. Senso-ji Temple (historical building)

[2026] Details: One of Tokyo's most famous historical buildings.

[2027] 2. Tokyo Banana (Sweets)

[2028] Details: A representative Tokyo sweet, perfect as a souvenir.

[2029] 3. teamLab Planets (a new tourist attraction)

[2030] Details: A spot where you can experience the cutting edge of digital art.

[2031] Example of a prompt

[2032] Example prompts for generating travel suggestions:

[2033] Please generate travel destination suggestions based on the following information.

[2034] Travel destination: Tokyo

[2035] Interests: Historical buildings, sweets, and the latest tourist attractions.

[2036] As described above, a system is realized that efficiently and accurately suggests the most suitable travel destination based on the user's input preferences. This system can be used on various devices and supports the user's travel planning.

[2037] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2038] Step 1: The user enters their travel preferences.

[2039] The user accesses the terminal's interface and enters their travel preferences (e.g., cities they want to visit, tourist attractions of interest, local products, and the latest tourist spots). The user's input data (e.g., "Destination: Tokyo," "Interests: Historical buildings, sweets, and the latest tourist spots") is received and processed by the terminal.

[2040] Step 2: Send the input data to the server.

[2041] The terminal converts the information entered by the user into JSON format. The converted data is sent to the server using a REST API or HTTP request. The input data becomes the request body in JSON format and is sent to the server.

[2042] Step 3: Receive data, perform format check, and analyze content.

[2043] The server receives JSON data sent from the terminal. It checks the format of the received data and parses its contents. Specifically, it processes the data to identify relevant tourist destinations based on "Destination: Tokyo" and "Interests: Historical buildings, sweets, latest tourist spots."

[2044] Step 4: Obtain relevant data from internal databases and external sources.

[2045] Based on the analyzed data, the server references internal databases and external APIs to retrieve relevant information. For example, it collects data related to "Tokyo," "historical buildings," "sweets," and "the latest tourist spots."

[2046] Step 5: Generate proposals using a generative AI model.

[2047] The server uses a generative AI model to generate optimal travel suggestions based on the acquired relevant data. The generative AI model takes into account the user's interests and past travel data, and uses relevant tourist destination data to perform data calculations for recommended travel destinations (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets).

[2048] Step 6: Convert the generated proposal to JSON format and send it to the terminal.

[2049] The server converts the generated travel suggestions into a JSON response. The converted data is sent to the terminal via a transmission method. The data sent to the terminal includes details of tourist destinations, local products, and trendy spots based on the user's interests (e.g., information on "Senso-ji Temple," "Tokyo Banana," and "teamLab Planets").

[2050] Step 7: Display the proposed results on the terminal.

[2051] The terminal parses the JSON data received from the server and displays it visually to the user. The display format is a clear and well-organized list, including detailed information and images for each tourist destination. Based on the displayed information, the user can create their own travel plan.

[2052] (Application Example 1)

[2053] 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".

[2054] In modern travel planning, users spend a great deal of time and effort gathering information and selecting the optimal destination. Furthermore, simply presenting information about a destination has limitations in motivating users to actually visit that place. Moreover, in today's world where remote travel experiences are increasingly common, the potential of virtual pre-experiences is often overlooked.

[2055] 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.

[2056] In this invention, the server includes means for experiencing travel suggestions generated based on user input within a virtual environment, server-side means including an algorithm that analyzes transmitted user information and generates travel destination suggestions based on it, and means for displaying the suggested information to the user. This allows the user not only to obtain optimal travel destination suggestions but also to experience those suggested destinations in advance within the virtual environment.

[2057] "Means for inputting user travel preferences" refers to providing an interface for users to input their travel preferences and requests to the system.

[2058] "Means for sending user input information to a server" refers to means for transferring information entered by a user on a terminal to a server via a network.

[2059] "Server-side means including an algorithm that analyzes the user's information sent and generates travel destination suggestions based on it" refers to a server-side processing system that uses an algorithm to analyze the information received from the user and generate optimal travel destination suggestions based on the analysis results.

[2060] "Means for sending generated suggestions to the user" refers to the means for sending travel destination suggestions generated on the server side back to the user's terminal.

[2061] "Means for displaying suggested information to the user" refers to means for displaying suggested travel destinations sent from the server in a format that the user can easily view.

[2062] "A means of experiencing travel suggestions generated based on user input within a virtual environment" refers to a method that uses virtual reality or augmented reality technology to simulate and virtually experience travel destination suggestions based on user input.

[2063] The system for realizing this invention is configured as follows: The user accesses the system using smart glasses or a head-mounted display. Here, Oculus Rift and Microsoft HoloLens are used as examples.

[2064] Acceptance of user input

[2065] Users input their travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel through the smart glasses' UI. This information is transmitted from the device to the server in real time.

[2066] Information processing and proposal generation

[2067] The server receives and analyzes the user's information. This analysis utilizes generative AI models such as OpenAI and employs advanced natural language processing techniques. In particular, it generates prompt sentences selected based on the user's input and then suggests the most suitable travel destination based on these prompts.

[2068] Data acquisition and proposal generation

[2069] Based on the analysis results, the server retrieves relevant information by referencing internal databases and external APIs. Based on the retrieved information, it generates prompt messages to suggest appropriate travel destinations, as follows:

[2070] Example of a prompt:

[2071] "Destination: Tokyo. Please suggest tourist attractions that focus on historical buildings and sweets."

[2072] Proposal display and virtual experience provision

[2073] Suggestions generated from the server are sent to the user's device. The user can then visually and interactively experience information about the suggested travel destinations through smart glasses or a head-mounted display. This allows the user to check destinations in a virtual environment beforehand and develop the optimal travel plan.

[2074] Specific example:

[2075] For example, if a user inputs "I like historical buildings and sweets in Tokyo," the AI ​​model will generate a prompt such as "Please suggest some historical buildings and sweets that I would recommend visiting in Tokyo." Based on this, the server will make specific suggestions such as Senso-ji Temple and Tokyo Banana, and allow users to experience these places within a virtual environment.

[2076] This system not only suggests travel destinations to users, but also enriches their travel planning through pre-experiences in a virtual environment. This invention significantly improves the efficiency and satisfaction users feel when choosing actual travel destinations.

[2077] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2078] Step 1: User input

[2079] Users wear smart glasses or a head-mounted display and input travel preferences (destination, interests, budget, duration, etc.) via voice input or touch panel. This input includes specific data such as destination, interests, budget, and duration.

[2080] input:

[2081] Travel destination: Tokyo

[2082] Interests: Historical buildings, sweets

[2083] Budget: 50,000 yen

[2084] Number of days: 3 days

[2085] output:

[2086] Input data in JSON format

[2087] Step 2: Sending data to the server

[2088] The terminal sends the information entered by the user to the server in JSON format. REST APIs and HTTP requests are used for data transmission.

[2089] input:

[2090] User input information (output from Step 1)

[2091] output:

[2092] JSON formatted data sent to the server

[2093] Step 3: Information analysis and prompt generation

[2094] The server analyzes the user's input information and generates appropriate prompt sentences using a generative AI model. Here, a natural language processing algorithm understands the user's wishes and creates prompt sentences that generate optimal suggestions.

[2095] input:

[2096] JSON formatted data sent to the server

[2097] Operation:

[2098] Parsing JSON data

[2099] Generating prompt statements (for example, "Please suggest recommended spots in Tokyo related to historical buildings and sweets.")

[2100] output:

[2101] Generated prompt message

[2102] Step 4: Referencing an external database or API

[2103] Based on the generated prompt, the server consults an internal database or an external API to retrieve relevant travel destination information.

[2104] input:

[2105] Generated prompt message

[2106] Operation:

[2107] Retrieving relevant information from databases and external APIs (e.g., tourist attractions, local products, latest spots in your travel destination)

[2108] output:

[2109] Related information obtained

[2110] Step 5: Proposal Generation

[2111] The server generates optimal travel destination suggestions based on the relevant information it has acquired. In this process, a generation AI model determines the content of the suggestions.

[2112] input:

[2113] Related information obtained

[2114] Operation:

[2115] Generating proposals (e.g., Senso-ji Temple, Tokyo Banana, teamLab Planets)

[2116] output:

[2117] Generated travel destination suggestions

[2118] Step 6: Send the proposal to the user

[2119] The server converts the generated proposal back into a JSON response and sends it to the user's terminal.

[2120] input:

[2121] Generated travel destination suggestions

[2122] Operation:

[2123] Conversion to JSON format

[2124] Sending to the user terminal

[2125] output:

[2126] Proposal data in JSON format sent to the terminal

[2127] Step 7: Display of proposed content and virtual experience

[2128] Users visually review the received suggestions through smart glasses or a head-mounted display and experience them within a virtual environment.

[2129] input:

[2130] Proposal data in JSON format sent to the terminal

[2131] Operation:

[2132] Visual representation of the proposal

[2133] Experience within a virtual environment

[2134] output:

[2135] User feedback from virtual experiences

[2136] 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.

[2137] The following describes a specific embodiment of a user-generated travel destination suggestion system that incorporates an emotion engine. This system takes user preferences and emotions regarding travel as input and generates optimal travel destination suggestions based on that input.

[2138] System Configuration

[2139] 1. User input reception

[2140] Terminal:

[2141] Users access an interface for creating travel plans and input their travel preferences (e.g., cities they want to visit, tourist attractions and local products they are interested in, the latest tourist spots, etc.). The interface also features an emotion engine that recognizes the user's emotions from their input and actions. The input form includes fields such as destination, interests, budget, number of days, and current mood.

[2142] 2. Data transmission

[2143] Terminal:

[2144] The system receives user input and emotion information recognized by the emotion engine, and validates the input. It verifies that the necessary information and emotion data have been entered correctly, converts the data to JSON format, and prepares it for transmission.

[2145] 3. Information transmission

[2146] Terminal:

[2147] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[2148] json

[2149] {

[2150] "destination": "Tokyo",

[2151] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[2152] "emotion": "excitement"

[2153] }

[2154] 4. Information Analysis and Proposal Generation

[2155] server:

[2156] The server receives the request sent from the terminal. It parses the data in JSON format and extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[2157] 5. Obtaining related information

[2158] server:

[2159] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[2160] 6. Emotion-based proposal adjustment

[2161] server:

[2162] Based on the collected information, the AI ​​algorithm generates travel suggestions, adjusting them based on the user's emotions as recognized by the emotion engine. For example, a user who is "excited" will be suggested more active tourist spots.

[2163] 7. Submit Proposal

[2164] server:

[2165] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[2166] 8. Results display

[2167] Terminal:

[2168] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[2169] Travel destination: Tokyo

[2170] Recommended tourist destinations

[2171] 1. Senso-ji Temple (Historical Building)

[2172] Details: One of Tokyo's most famous historical buildings.

[2173] 2. Tokyo Banana (Sweets)

[2174] Details: A representative Tokyo sweet, perfect as a souvenir.

[2175] 3. teamLab Planets (a new tourist attraction)

[2176] Details: A spot where you can experience the cutting edge of digital art.

[2177] Specific example

[2178] This example illustrates how a user might use the system to request travel destination suggestions.

[2179] User input example

[2180] The user (let's call him Mr. Sato) enters the following information.

[2181] Travel destination: Tokyo

[2182] Interests: Historical buildings, sweets, and the latest tourist attractions.

[2183] Current mood: "Excited"

[2184] Data transmission

[2185] The following information is sent from the terminal to the server.

[2186] json

[2187] {

[2188] "destination": "Tokyo",

[2189] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[2190] "emotion": "excitement"

[2191] }

[2192] Information analysis and proposal generation

[2193] The server analyzes this information and generates the next suggestion.

[2194] Historical building: Senso-ji Temple

[2195] Sweets: Tokyo Banana

[2196] Newest tourist attraction: teamLab Planets

[2197] Proposal submission and results display

[2198] The generated suggestions are sent to the terminal and displayed on the user's terminal as follows:

[2199] Travel destination: Tokyo

[2200] Recommended tourist destinations

[2201] 1. Senso-ji Temple (Historical Building)

[2202] Details: One of Tokyo's most famous historical buildings.

[2203] 2. Tokyo Banana (Sweets)

[2204] Details: A representative Tokyo sweet, perfect as a souvenir.

[2205] 3. teamLab Planets (a new tourist attraction)

[2206] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[2207] Thus, the present invention provides a system that efficiently and accurately suggests travel destinations based on the user's input preferences and emotions.

[2208] The following describes the processing flow.

[2209] Step 1:

[2210] User:

[2211] Users access an interface for creating travel plans and enter their travel preferences (destination, areas of interest, local products, latest tourist attractions, etc.). They also enter their current mood or feelings (e.g., "excited"). The input form includes text boxes and dropdown lists.

[2212] Step 2:

[2213] Terminal:

[2214] The system receives user input and validates the input content and sentiment data. It checks for missing information and prompts the user to re-enter information if necessary. If the input is correct, it converts the data to JSON format and prepares it for transmission.

[2215] Step 3:

[2216] Terminal:

[2217] The REST API is used to send user input information and sentiment information to the server. An example of the data sent is as follows:

[2218] json

[2219] {

[2220] "destination": "Tokyo",

[2221] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[2222] "emotion": "excitement"

[2223] }

[2224] Step 4:

[2225] server:

[2226] The system receives requests sent from the terminal and parses the data in JSON format. It extracts key information such as "destination," "interests," and "emotion." In this example, it extracts "destination: Tokyo," "interests: historical buildings, sweets, the latest tourist spots," and "emotion: excitement."

[2227] Step 5:

[2228] server:

[2229] We use semantic analysis and natural language processing techniques to understand users' interests and emotions. Based on this, we refer to databases and external APIs to retrieve information on relevant tourist destinations, local products, and trendy spots. For example, we collect data on "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo."

[2230] Step 6:

[2231] server:

[2232] Based on the collected information, an AI algorithm is used to generate travel suggestions. The emotion engine then adjusts the suggestions based on the user's recognized emotions. For example, a user who is "excited" will be suggested more active and exciting tourist spots.

[2233] Step 7:

[2234] server:

[2235] The generated travel suggestions are converted into JSON response data and sent to the device. The response data includes the name of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[2236] Step 8:

[2237] Terminal:

[2238] The response data received from the server is parsed. The specific suggestions are then formatted to be displayed in the user interface. For example, it might look like this:

[2239] Travel destination: Tokyo

[2240] Recommended tourist destinations

[2241] 1. Senso-ji Temple (Historical Building)

[2242] Details: One of Tokyo's most famous historical buildings.

[2243] 2. Tokyo Banana (Sweets)

[2244] Details: A representative Tokyo sweet, perfect as a souvenir.

[2245] 3. teamLab Planets (a new tourist attraction)

[2246] Details: A spot where you can experience the cutting edge of digital art. Especially recommended for excited users.

[2247] Step 9:

[2248] User:

[2249] Based on the displayed suggestions, you can create your own travel plan. If you are satisfied with the suggestions, you can proceed to book your trip or search for more detailed information.

[2250] (Example 2)

[2251] 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".

[2252] Conventional travel suggestion systems offer suggestions based on user preferences, but they do not provide specific and personalized suggestions that take user emotions into account. As a result, they are unable to suggest travel destinations or tourist spots that match the user's current mood, and improving the user experience remains a challenge.

[2253] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[2254] In this invention, the server includes means for analyzing user input information and emotional information and generating travel destination suggestions based on that information, means for obtaining relevant information from a database or external API, and means for adjusting the suggestion content based on the user's emotions. This makes it possible to suggest appropriate travel destinations and tourist spots that match the user's current emotions.

[2255] A "user" refers to someone who inputs information into the system to receive suggestions for travel destinations and tourist spots.

[2256] "Travel preferences" refer to specific requests and interests of users, such as cities they want to visit, tourist destinations, local products, and the latest tourist spots.

[2257] "Emotions" refers to the user's current mood or emotional state, and includes emotions such as "excitement" and "enjoyment."

[2258] An "emotion engine" refers to a software component that has the function of recognizing and analyzing emotions from user input and actions.

[2259] A "server" refers to a computer system that receives information sent by users, analyzes it, and generates suggestions.

[2260] A "database" refers to a data storage system used to store information about travel destinations and tourist spots based on user interests.

[2261] An "external API" refers to an application program interface used to retrieve information from an external data source.

[2262] "AI algorithms" refer to artificial intelligence technology that generates optimal suggestions based on the user's wishes and emotions.

[2263] "Suggestions" refer to recommendations for travel destinations and tourist spots generated based on user input and emotions.

[2264] "JSON format" refers to a data format used to structure user input information and sentiment information and send it to a server.

[2265] "Response data" refers to the formalized data that the server generates and sends to the terminal.

[2266] "Parsing" refers to the process of analyzing response data received from a server and converting it into a format that can be displayed on the user interface.

[2267] Modes for carrying out the invention

[2268] The travel suggestion system according to the present invention is a system that takes the user's travel preferences and emotions as input and generates optimal travel destination suggestions based on them. This system consists of a terminal, a server, an emotion engine, and an AI algorithm.

[2269] User input reception

[2270] Users access a travel plan creation interface via their device. The interface displays forms for inputting information such as destination, interests, budget, duration, and current mood. By entering this information, the system obtains the user's preferences and interests. The interface also incorporates an emotion engine, which recognizes emotions from the user's input and actions.

[2271] Information validation and preparation for transmission

[2272] The information entered by the user and the sentiment information recognized by the sentiment engine are validated on the device. If validation is successful, this information is converted to JSON format and ready to be sent to the server.

[2273] Server-based information analysis

[2274] The server receives JSON data sent from the terminal. The server analyzes this data and extracts key information such as "travel destination," "interests," and "emotions." Based on this, it performs a detailed analysis of the user's requests and emotions.

[2275] Obtaining related information

[2276] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions. Based on this, it retrieves information about relevant travel destinations and tourist spots using databases and external APIs. For example, it collects detailed information about "historical buildings," "sweets," and "the latest tourist attractions" from the database.

[2277] Adjusting emotionally driven proposals

[2278] The server uses an AI algorithm to generate travel suggestions based on the collected information. During this process, the suggestion is adjusted based on the user's emotions, as analyzed by the emotion engine. For example, a user who is "excited" will be advised to visit active and exciting tourist spots.

[2279] Proposal generation and submission

[2280] The generated travel suggestions are converted back into JSON format and sent from the server to the terminal. The response data includes the names of each tourist destination, detailed information, and specific suggestions based on the user's sentiment.

[2281] Display of proposal results

[2282] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, if "Tokyo" is suggested as a travel destination, "famous temples" are displayed as historical buildings, "local specialties" as sweets, and "digital art facilities" as the latest tourist attractions.

[2283] Specific example

[2284] For example, the user enters the following prompt into the system:

[2285] "Travel destination: Tokyo, Interests: Historical buildings, sweets, new tourist attractions, Current mood: Excited"

[2286] As a result, the server generates and sends the following suggestion to the terminal:

[2287] "Travel destination: Tokyo, Recommended tourist spots:"

[2288] 1. Famous temples (historical buildings)

[2289] Details: One of Tokyo's most famous historical buildings.

[2290] 2. Local specialties (sweets)

[2291] Details: A representative Tokyo sweet, perfect as a souvenir.

[2292] 3. Digital art facilities (the latest tourist attractions)

[2293] Details: A spot where you can experience the cutting edge of digital art.

[2294] In this way, the present invention provides effective travel suggestions based on the user's wishes and emotions.

[2295] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2296] Step 1:

[2297] User input reception

[2298] The user accesses an interface for creating a travel plan and enters information such as destination, interests, budget, duration, and current mood. Once the user has finished entering information, the device collects this information, and the emotion engine recognizes the user's emotions from their input and actions. Input data may include, for example, "Destination: Tokyo," "Interests: Historical buildings, sweets, new tourist attractions," and "Current mood: Excited." The output provides information about the user's preferences and emotions.

[2299] Step 2:

[2300] Information validation and preparation for transmission

[2301] The device validates the information entered by the user and the sentiment information recognized by the sentiment engine. If validation is successful, the device converts this information into JSON format and prepares it for transmission. Specific validation processes include checking whether the travel destination is available and whether interest items are specified. Input consists of user-entered preference information and sentiment information, and output is validated data in JSON format.

[2302] Step 3:

[2303] Sending input data to the server

[2304] The device sends validated JSON-formatted input data and sentiment information to the server using a REST API. For example, the following JSON data is sent:

[2305] json

[2306] {

[2307] "destination": "Tokyo",

[2308] "interests": ["historical buildings", "sweets", "latest tourist attractions"],

[2309] "emotion": "excitement"

[2310] }

[2311] The input is validated JSON data, and the output is data sent to the server.

[2312] Step 4:

[2313] Server-based information analysis

[2314] The server receives JSON data sent from the terminal and performs analysis. Specifically, it extracts key information related to "travel destination," "interests," and "emotions." For example, the server might extract information such as "travel destination: Tokyo," "interests: historical buildings, sweets, latest tourist spots," and "emotions: excitement." The input is the received JSON data, and the output is the extracted key information.

[2315] Step 5:

[2316] Server retrieves relevant information

[2317] The server uses semantic analysis and natural language processing techniques to understand the user's interests and emotions, and then retrieves relevant information by referencing databases and external APIs. For example, it can collect detailed information from the database about "historical buildings in Tokyo," "sweets in Tokyo," and "the latest tourist spots in Tokyo." The input is analyzed key information, and the output is related tourist destination data.

[2318] Step 6:

[2319] Adjusting emotionally driven proposals

[2320] The server generates travel suggestions using an AI algorithm based on the collected relevant information. At this time, the suggestions are adjusted based on the user's emotions, as analyzed by the emotion engine. For example, for a user who is "excited," active and dynamic tourist spots are prioritized. The input consists of relevant tourist destination data and emotion information, and the output is adjusted travel suggestions.

[2321] Step 7:

[2322] Proposal generation and submission

[2323] The server converts the generated travel suggestions back into JSON format and sends them to the terminal. For example, the response data might include the names and details of each tourist destination, as well as specific suggestions based on the user's mood. The input is the adjusted travel suggestions, and the output is the response data converted into JSON format, which is sent to the terminal.

[2324] Step 8:

[2325] Display of proposal results

[2326] The terminal analyzes the response data received from the server and formats it into a format that displays specific suggestions on the user interface. For example, it might be displayed as follows:

[2327] Travel destination: Tokyo

[2328] Recommended tourist destinations

[2329] 1. Famous temples (historical buildings)

[2330] Details: One of Tokyo's most famous historical buildings.

[2331] 2. Local specialties (sweets)

[2332] Details: A representative Tokyo sweet, perfect as a souvenir.

[2333] 3. Digital art facilities (the latest tourist attractions)

[2334] Details: A spot where you can experience the cutting edge of digital art.

[2335] The input is response data received from the server, and the output is a visual suggestion display for the user.

[2336] (Application Example 2)

[2337] 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".

[2338] Conventional travel suggestion systems have the problem of not being able to provide optimal suggestions that match the user's real-time mood and emotions, because they suggest travel destinations without considering the user's emotional state. Furthermore, especially in autonomous vehicles, there is a need to provide appropriate suggestions instantly in order to offer a safe and comfortable travel experience while also facilitating travel planning.

[2339] 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. In this invention, the server includes means for inputting the user's travel preferences, means for transmitting the user's input information to the server, means including an algorithm for analyzing the transmitted user information and generating travel destination suggestions based thereon, means for transmitting the generated suggestions to the user, means for displaying the suggested information to the user, means including an emotion engine for recognizing the user's emotions, and means for adjusting travel destination suggestions based on the user's emotion information. This makes it possible to suggest the optimal travel destination according to the user's real-time emotional state.

[2340] "Means for inputting user travel preferences" refers to an interface for users to input information such as their travel destination, interests, budget, and duration.

[2341] "Means for sending user input information to a server" refers to communication methods that have the function of appropriately formatting information entered by a user and sending it to a server via the internet.

[2342] "Means including an algorithm that analyzes user information submitted and generates travel destination suggestions based on that information" refers to a program or algorithm for analyzing user input information and generating appropriate travel destination suggestions.

[2343] "Means for sending generated suggestions to the user" refers to communication means that have the function of sending travel destination suggestions generated on the server back to the user's terminal.

[2344] "Means of displaying suggested information to the user" refers to displays and user interfaces that show received travel destination suggestions in a format that is easy for the user to understand.

[2345] "Means including an emotion engine that recognizes user emotions" refers to a system for analyzing and recognizing user emotions from user input and actions.

[2346] "Means for adjusting travel destination suggestions based on user sentiment information" refers to programs or algorithms that adjust suggestions based on recognized user sentiment and present the most suitable travel destination.

[2347] The following describes the detailed configuration of the system that realizes this application example. This system is built on the "Smart Trip Navigator" smartphone application installed in autonomous vehicles.

[2348] System Configuration

[2349] Hardware and software

[2350] The system of this invention uses the following hardware and software.

[2351] Hardware: In-vehicle displays installed in autonomous vehicles, smartphones

[2352] Software: Python (Flask framework), Google Cloud Natural Language API, MongoDB

[2353] Program generation content

[2354] In this system, terminals (smartphones and in-car displays) installed in autonomous vehicles receive data from users and send it to a server. The server analyzes the received data and processes it to suggest appropriate travel destinations. The following describes each process.

[2355] Processing at the terminal

[2356] 1. User Input: The terminal has a means for users to input their travel preferences, allowing them to enter their destination, interests, budget, duration, and desired mood (e.g., "relax").

[2357] 2. Data validation: Verify that the user's input information is entered correctly and convert the necessary information into JSON format.

[2358] 3. Data transmission: The validated data is sent to the server using the REST API.

[2359] Processing on the server

[2360] 4. Data reception and analysis: The server receives JSON-formatted data sent from the terminal and analyzes it using "means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it."

[2361] 5. Obtaining related information: Obtain relevant tourist spots and information from external APIs such as the Google Cloud Natural Language API and databases (MongoDB).

[2362] 6. Emotion-Based Suggestion Adjustment: Using "means including an emotion engine that recognizes the user's emotions," travel destination suggestions are adjusted based on the recognized emotions. For example, if the emotion is "relaxed," relaxing tourist spots will be suggested.

[2363] 7. Submit Proposal: Convert the generated proposal back into JSON format and send it to the terminal.

[2364] Displaying results on the device

[2365] 8. Display of Results: The suggested data received from the server is parsed and displayed on the in-car display or smartphone in a user-friendly format using the "means for displaying suggested information to the user."

[2366] Specific example

[2367] This example demonstrates how a user can use the system to request travel destination suggestions while inside an autonomous vehicle.

[2368] User input example:

[2369] Travel destination: Osaka

[2370] Interests: Food, beaches, events

[2371] Current mood: Relaxed

[2372] Examples of analysis and proposal generation on the server:

[2373] Travel destination: Osaka

[2374] Interests: Food, beaches, events

[2375] Emotion: Relax

[2376] Proposal details:

[2377] 1. Dotonbori - A spot where you can enjoy Osaka's rich food culture.

[2378] 2. "Nanko Sunset Beach" - A relaxing beach perfect for enjoying the sunset.

[2379] 3. "Osaka Castle Hall" - A venue where many concerts and events are held.

[2380] Example of a prompt

[2381] The following is an example of a prompt message for generating suggestions based on user data.

[2382] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[2383] Destination: Osaka

[2384] Interests: Food, beaches, events

[2385] Mood: Relaxed

[2386] Thus, the present invention realizes a system that provides accurate and timely suggestions for travel destinations within an autonomous vehicle, based on user input information and emotions.

[2387] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2388] Step 1:

[2389] Users input information such as their travel destination, interests, budget, duration, and feelings. Specifically, they use a smartphone app or in-car display interface to input information such as "Osaka," "Gourmet," "Seaside," "Events," and "Relaxation." The input data is triaged and passed on to the next step.

[2390] Step 2:

[2391] The terminal validates the user's input information. It checks whether the input information is accurate and whether there is any missing or inappropriate information. For example, it checks whether the entered destination is a valid place name and whether the interest category is correct.

[2392] Step 3:

[2393] The device converts the validated data into JSON format and sends it to the server. Specifically, it uses a REST API to send JSON data like the following to the server.

[2394] json

[2395] {

[2396] "destination": "Osaka",

[2397] "interests": ["Gourmet", "Seaside", "Events"]

[2398] "emotion": "relax"

[2399] }

[2400] Step 4:

[2401] The server receives and parses the JSON data sent from the terminal. Specifically, it parses the data and extracts the "destination," "interests," and "emotion" fields. The analysis results are saved for use in the next step.

[2402] Step 5:

[2403] The server collects relevant information based on the acquired data. Specifically, it references databases such as Google Cloud Natural Language API and MongoDB, as well as external APIs, to collect the following data:

[2404] "Dotonbori" (Gourmet)

[2405] "Nanko Sunset Beach" (seaside)

[2406] "Osaka Castle Hall" (event)

[2407] Step 6:

[2408] The server generates suggestions using an emotion engine based on the collected information. Specifically, it uses an AI algorithm (such as Scikit-learn) to suggest relaxing spots based on the user's emotional state, for example, prioritizing relaxing spots for a user who is "relaxed." The generated suggestions are saved in the following format.

[2409] json

[2410] {

[2411] "recommended_spots": [

[2412] {

[2413] "name": "Dotonbori",

[2414] "category": "Gourmet",

[2415] "details": "A spot where you can enjoy Osaka's rich food culture."

[2416] },

[2417] {

[2418] "name": "Nanko Sunset Beach",

[2419] "category": "Seaside",

[2420] "details": "A relaxing beach perfect for enjoying the sunset."

[2421] },

[2422] {

[2423] "name": "Osaka-jo Hall",

[2424] "category": "events",

[2425] "details": "A facility where many concerts and events are held."

[2426] }

[2427] ]

[2428] }

[2429] Step 7:

[2430] The server converts the generated suggestions into JSON format and sends them to the device. Specifically, it uses a REST API to send the suggestion data back to the device.

[2431] Step 8:

[2432] The device parses the received suggestion data. Specifically, it extracts "recommended_spots" from the JSON data and displays it on the in-car display or smartphone in a user-friendly format. An example of the display is shown below.

[2433] Travel destination: Osaka

[2434] Recommended tourist destinations

[2435] 1. Dotonbori (Gourmet)

[2436] Details: A spot where you can enjoy Osaka's rich food culture.

[2437] 2. Nanko Sunset Beach (Seaside)

[2438] Details: A relaxing beach perfect for enjoying the sunset.

[2439] 3. Osaka-jo Hall (Event)

[2440] Details: A venue where many concerts and events are held.

[2441] Example of a prompt:

[2442] The following is an example of a prompt message for generating suggestions based on user data.

[2443] The user has entered their destination, interests, and mood. Please provide the best travel suggestions based on the following information.

[2444] Destination: Osaka

[2445] Interests: Food, beaches, events

[2446] Mood: Relaxed

[2447] This prompt allows the system to automatically generate the most suitable suggestions for the user.

[2448] 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.

[2449] 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.

[2450] 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.

[2451] 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.

[2452] 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.

[2453] 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.

[2454] 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.

[2455] 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.

[2456] 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."

[2457] 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.

[2458] 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.

[2459] 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.

[2460] 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.

[2461] 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.

[2462] 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.

[2463] 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.

[2464] 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.

[2465] 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.

[2466] 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.

[2467] 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.

[2468] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[2469] The following is further disclosed regarding the embodiments described above.

[2470] (Claim 1)

[2471] A means for users to input their travel preferences,

[2472] A means of sending user input information to the server,

[2473] A server-side means including an algorithm that analyzes the user information sent and generates travel destination suggestions based on it,

[2474] A means of sending the generated suggestions to the user,

[2475] A means of displaying the proposed information to the user,

[2476] A system that includes this.

[2477] (Claim 2)

[2478] The system according to claim 1, which retrieves relevant information from a database or external API based on the travel destination and interests entered by the user.

[2479] (Claim 3)

[2480] The system according to claim 1, wherein the AI ​​generates proposals based on the acquired relevant information.

[2481] "Example 1"

[2482] (Claim 1)

[2483] A terminal device for inputting the user's travel preferences,

[2484] A means of communication for sending user input information to the server,

[2485] Information processing means including an algorithm that analyzes the transmitted user information and generates travel destination suggestions based on it,

[2486] A means for sending the generated travel proposal to the user's terminal,

[2487] A display means for visually displaying the proposed information to the user,

[2488] A travel suggestion system that includes this.

[2489] (Claim 2)

[2490] The travel suggestion system according to claim 1, comprising means for obtaining relevant data from an internal database or an external information source based on the travel destination and interests entered by the user.

[2491] (Claim 3)

[2492] A travel suggestion system according to claim 1, comprising means for a generating artificial intelligence algorithm to generate optimal travel suggestions based on acquired relevant data.

[2493] "Application Example 1"

[2494] (Claim 1)

[2495] A means for users to input their travel preferences,

[2496] A means of sending user input information to the server,

[2497] A server-side means including an algorithm that analyzes the user information sent and generates travel destination suggestions based on it,

[2498] A means of sending the generated suggestions to the user,

[2499] A means of displaying the proposed information to the user,

[2500] A means to experience travel suggestions generated based on user input within a virtual environment,

[2501] A system that includes this.

[2502] (Claim 2)

[2503] The system according to claim 1, which retrieves relevant information from a database or external API based on the travel destination and interests entered by the user.

[2504] (Claim 3)

[2505] The system according to claim 1, wherein the AI ​​generates proposals based on the acquired relevant information.

[2506] "Example 2 of combining an emotion engine"

[2507] (Claim 1)

[2508] A means for users to input their travel preferences and feelings,

[2509] A means of sending user input information and emotional information to a server,

[2510] A server-side means including an algorithm that analyzes the transmitted user information and sentiment information and generates travel destination suggestions based on it,

[2511] Means for obtaining relevant information from a database or external API,

[2512] A means of adjusting the content of suggestions based on the user's emotions,

[2513] A means of sending the generated suggestions to the user,

[2514] A means of displaying the proposed information to the user,

[2515] A system that includes this.

[2516] (Claim 2)

[2517] The system according to claim 1, which uses an emotion engine to analyze the user's emotions and reflect them in the suggested content.

[2518] (Claim 3)

[2519] The system according to claim 1, wherein the AI ​​generates suggested content based on the analyzed emotions.

[2520] "Application example 2 when combining with an emotional engine"

[2521] (Claim 1)

[2522] A means for users to input their travel preferences,

[2523] A means of sending user input information to the server,

[2524] A server-side means including an algorithm that analyzes the user information sent and generates travel destination suggestions based on it,

[2525] A means of sending the generated suggestions to the user,

[2526] A means of displaying the proposed information to the user,

[2527] A means including an emotion engine that recognizes the user's emotions,

[2528] A means of adjusting travel destination suggestions based on user sentiment information,

[2529] A system that includes this.

[2530] (Claim 2)

[2531] The system according to claim 1, which retrieves relevant information from a database or external API based on the travel destination and interests entered by the user.

[2532] (Claim 3)

[2533] The system according to claim 1, wherein the AI ​​generates suggested content based on acquired relevant information and adjusts the suggested content based on emotional information. [Explanation of Symbols]

[2534] 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 for users to input their travel preferences, A means of sending user input information to the server, A server-side means including an algorithm that analyzes the user information sent and generates travel destination suggestions based on it, A means of sending the generated suggestions to the user, A means of displaying the proposed information to the user, A system that includes this.

2. The system according to claim 1, which retrieves relevant information from a database or external API based on the travel destination and interests entered by the user.

3. The system according to claim 1, wherein the AI ​​generates a proposal based on the acquired relevant information.

Images