system

Abstract

We provide the system. [Solution] A means of providing a terminal with user operation means for inputting travel preference information, A means of using intelligent processing to analyze input travel preference information and generate multiple travel suggestions, A display means for showing generated travel suggestions and allowing users to select from them, A means of automatically performing the booking procedure based on the selected travel suggestion, A means of notifying the user that the reservation has been completed, A means of providing suggestions based on the user's current location using location information, 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 and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When planning and making a reservation for a trip, it is generally time-consuming to select a destination and schedule, manage a budget, and complete reservation procedures. Also, when a user only has vague travel wishes, it is difficult to make a specific plan. Furthermore, in order to make a reservation at the optimal price, it is necessary to compare and consider a lot of information, which is also a burden for the user. Thus, it is an issue to reduce the complicated procedures and the labor of information collection involved in trip planning and reservation, and to provide a plan that easily meets the user's demands.

Means for Solving the Problems

[0005] The present invention provides a means for providing a user interface for inputting travel preference information into a user terminal, and means for using artificial intelligence to analyze the input travel preference information and generate multiple travel suggestions. It also provides means for displaying the generated travel suggestions on the terminal and allowing the user to select one. Furthermore, by providing a system that includes means for automatically performing reservation procedures based on the selected travel suggestion and means for notifying the user that the reservation has been completed, it is possible to present the optimal travel plan while reducing the effort involved in travel planning. As a result, users can easily obtain a concrete travel plan from vague requests and complete various arrangements at the optimal price.

[0006] A "user interface" is a display and input method that allows a user to input or manipulate information through a device.

[0007] "Travel preference information" refers to information that indicates the conditions, purpose, budget, etc., that the user desires regarding their trip.

[0008] "Artificial intelligence" is a technology that gives computers the ability to perform intelligent actions similar to those of humans. In this context, it refers to the function of analyzing information based on input data and generating suggestions.

[0009] "Travel suggestions" refer to a list of travel plans and itineraries generated based on the user's preferences.

[0010] "Booking procedures" refer to the process of securing airline tickets, accommodations, and activities based on travel proposals.

[0011] A "notification" is a means of communicating information to inform the user that a reservation has been completed and provides details about it. [Brief explanation of the drawing]

[0012] [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 a data processing device and a 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] This 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] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0013] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

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

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

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

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

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

[0019] 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."

[0020] [First Embodiment]

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

[0022] 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.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0027] 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.

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

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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".

[0033] This invention provides a system that allows users to easily plan and book trips. This system takes user requests as input, presents a variety of options based on those requests, and then allows users to book using the most suitable option. The following describes embodiments of the system based on this invention.

[0034] User request input

[0035] Users enter their travel requests using a dedicated application on their device. This interface is intuitive and allows users to input or select parameters such as travel destination, budget, duration, and desired activities.

[0036] Requirements analysis and plan generation

[0037] The server receives information sent by the user and analyzes it using artificial intelligence. This helps to concretize the user's vague requests and generate multiple travel suggestions. The generated suggestions are compiled by referencing various databases and take into account seasonal factors, budget, travel dates, and other considerations.

[0038] Process example

[0039] For example, if a user enters "I want to visit historical sites in Europe during my summer vacation," the server can analyze this request and generate a travel plan for cities in Europe that include historical sites, such as Rome, Athens, or Paris. In addition, it would include details such as accommodations in each city, flight options, and local tours.

[0040] Proposal presentation and selection

[0041] The device visually displays travel suggestions retrieved from the server to the user. Users can compare the details of these suggestions and select the one best suited to their travel plans. Customization of options based on the selected plan is also possible.

[0042] Reservations and notifications

[0043] Based on the selected travel plan, the server initiates the booking process for flights and accommodations. It automatically selects options using multiple online booking services to ensure the best price. This allows users to finalize their ideal travel plan without unnecessary hassle. Once the booking is complete, the user is notified of the details and provided with necessary information via their device.

[0044] This system reduces the complexity and time-consuming processes associated with typical travel planning, allowing users to easily proceed with their travel plans.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The user accesses a dedicated application on their device and enters their travel requests. On the interface, the user enters or selects information such as destination, budget, desired dates, and desired activities.

[0048] Step 2:

[0049] The terminal sends the information entered by the user to the server. The data is encrypted and securely transferred to the server.

[0050] Step 3:

[0051] The server analyzes the received information. Using artificial intelligence, it processes the user's input information using natural language and extracts specific travel-related needs. At the same time, it sets search queries based on the entered conditions.

[0052] Step 4:

[0053] The server accesses external travel databases to search for and retrieve travel destinations and itineraries that meet the user's needs. This includes flight information, accommodation options, and local activity options. Taking seasonal factors and current price trends into account, it generates several optimal itineraries.

[0054] Step 5:

[0055] The server sends the generated plan to the device. The device receives it and presents it to the user in a visual format using travel plan comparison tables and maps.

[0056] Step 6:

[0057] The user selects a travel plan of interest from the presented options and enters their selection into the device. The device then sends the selection to the server.

[0058] Step 7:

[0059] The server initiates the booking process based on the travel plan selected by the user. It uses external booking service APIs to check flight and accommodation availability and confirm the booking. It also compares with other services to obtain the lowest price for options.

[0060] Step 8:

[0061] Once the booking is complete, the server sends the booking details to the device. The device receives this and sends a notification to the user. The notification includes information about the booked flight, accommodation details, and planned activities.

[0062] Step 9:

[0063] Users can check notifications through their devices and make additional options or changes as needed. This allows for final confirmation and adjustment of travel plans.

[0064] (Example 1)

[0065] 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."

[0066] Traditional travel planning systems typically required users to spend a significant amount of time and effort inputting information, and subsequent suggestions and booking procedures were often cumbersome. As a result, it was difficult to easily create an ideal travel plan, and price and itinerary optimizations were often not adequately performed.

[0067] 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.

[0068] In this invention, the server includes means for providing an information processing device with a user interface for inputting travel preference information, means for using a machine learning model to analyze the input travel preference information and generate multiple travel suggestions, and means for providing a function for the user to customize the suggested travel plan. This makes it possible for the user to quickly and efficiently select the optimal travel plan and automate the booking process.

[0069] "Travel preference information" refers to information that describes the user's planned travel requirements, such as destination, budget, duration, and desired activities.

[0070] "User interface" refers to the operation screens or tools provided to an information processing device for the user to input or retrieve information.

[0071] A "machine learning model" refers to a computer program that has the ability to automatically learn from data and perform specific tasks.

[0072] "External booking services" refer to third-party platforms or services that provide online booking services, allowing users to book hotels, airline tickets, and other similar items.

[0073] "Means of selecting the optimal price" refers to a process or function that automatically selects the most favorable price from multiple price options based on the given conditions.

[0074] A "prompt" is a sentence that instructs a machine learning model to perform a specific task, and is usually generated based on the input data.

[0075] This invention provides an information processing system that enables users to efficiently plan and book trips. This system is implemented through a process in which users input travel preference information via a user interface on a terminal, send it to a server, and analyze it.

[0076] Upon receiving information, the server uses a generative AI model to analyze the input data. This analysis generates multiple travel suggestions based on the traveler's preferences and conditions. In this process, the server accesses external databases to gather the latest information on accommodations, transportation, activities, etc., and designs the optimal suggestion considering seasonal factors and budget.

[0077] The device presents the generated travel suggestions to the user in a visually easy-to-understand format. The user then compares the suggestions based on this information and selects the plan that interests them. Furthermore, the user can utilize a customization function to adjust the details of the trip to suit their own needs.

[0078] For example, if a user wants to visit historical tourist destinations during their summer vacation, a prompt such as "The user is looking for historical sites for a trip to Europe in the summer of 2023" will be generated. Based on this prompt, the server can use a model to formulate and suggest appropriate tourist destinations and plans.

[0079] Ultimately, the server makes the booking directly based on the selected travel proposal. This process utilizes multiple external booking services and automatically selects the option with the best price and conditions. This allows users to skip complex booking procedures and easily plan and book their trips.

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] Users enter their travel preferences through a user interface on their device. Input fields include destination, budget, travel duration, and desired activities. This information serves to collect the user's specific travel preferences as digital data. When the user presses the "Submit" button, this data is sent to the server.

[0083] Step 2:

[0084] The server receives travel preference information from the terminal. The received data is first checked for formatting, and then analyzed using a generative AI model. This model generates prompt sentences, taking a sentence like "The user is looking for historical sites for a trip to Europe in the summer of 2023" as input. Using this prompt, the server prepares to generate suggestions that match the user's preferences.

[0085] Step 3:

[0086] The server inputs prompt sentences into a generation AI model, which then generates multiple travel suggestions based on these prompts. During this process, it retrieves information on accommodations, transportation, and tourist attractions from an external travel database. The database is searched based on the analyzed prompt sentences, and a suitable travel plan is constructed. The output is a list of multiple travel suggestions that match the user's criteria.

[0087] Step 4:

[0088] The server sends the proposed travel plans to the device. The device uses this information to present it to the user in a visually easy-to-understand format. The user can scroll through the travel suggestions to review and compare the information. Details such as cost and itinerary are also displayed for each plan. The user chooses the most appealing option from the presented information.

[0089] Step 5:

[0090] Users can further customize their selected travel plan. This step allows them to adjust the length of stay and add or remove specific activities. This interactive process ensures that a travel plan perfectly matches the user's preferences.

[0091] Step 6:

[0092] The server initiates the booking process based on the customized travel plan ultimately selected by the user. This process cross-checks multiple external booking services to select the booking with the best price and conditions. Based on this, the booking is automatically confirmed. The output is the confirmed booking information.

[0093] Step 7:

[0094] Once the booking is complete, the server notifies the user of the information. The device then displays the user's confirmed itinerary, confirmation number, and hotel and flight details. This allows the user to easily understand their entire travel plan and prepare the necessary documents.

[0095] (Application Example 1)

[0096] 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."

[0097] Planning and booking a trip is often cumbersome, requiring the comparison and evaluation of numerous options and information. Furthermore, it's often impossible to receive suggestions for the most suitable tourist destinations and activities based on the user's location. Therefore, there is a need for a system that efficiently plans trips and enhances the travel experience at the destination.

[0098] 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.

[0099] In this invention, the server includes means for providing a terminal with user operation means for inputting travel preference information; means for using intelligent processing to analyze the input travel preference information and generate multiple travel suggestions; means for displaying the generated travel suggestions and making them selectable by the user; and means for providing suggestions based on the user's current location using location information. This enables the user to efficiently plan their trip and obtain an optimal sightseeing experience based on location information.

[0100] "Travel preference information" refers to information in which users specifically express their desires regarding travel, and includes elements such as destination, budget, and duration.

[0101] "User operation means" refers to the general term for interfaces and devices provided for users to input information via a terminal.

[0102] "Intelligent processing" is the process of analyzing input data and generating information to support decision-making, utilizing technologies such as machine learning and artificial intelligence.

[0103] "Display means" refers to devices or software interfaces for providing information to users visually, and includes screens and displays.

[0104] "Location information" refers to data that indicates the user's current location, obtained using a device, and is information that identifies a region based on latitude and longitude.

[0105] "Means of providing suggestions" refers to methods and processes for presenting users with appropriate options and information, thereby encouraging users to make the best choice.

[0106] This invention is implemented as a system that efficiently supports travel planning. The server provides a user operation means for users to input travel preference information from their terminals. This user operation means operates on smartphones and personal computers and has an interface that allows users to intuitively input destinations, budgets, travel itineraries, etc.

[0107] The server uses intelligent processing to analyze travel preference information submitted by users. This intelligent processing employs machine learning algorithms to generate optimal travel suggestions from the database, creating multiple options based on the user's criteria.

[0108] The generated travel suggestions are provided to the user via a display device and are visually presented on a smartphone or screen. Users can compare and consider the suggested travel plans and choose the option that best suits their preferences.

[0109] Furthermore, the server utilizes location information to provide a means of suggesting the latest tourist and event information based on the user's current location. This makes it possible to suggest local events and tourist attractions at travel destinations in real time.

[0110] The booking process is handled by an automated system that collaborates with multiple external booking services to select the best price and complete the booking without requiring manual intervention. Once the booking is complete, the user's device is notified and provided with detailed travel information.

[0111] For example, if a user enters "I want to visit a nearby cultural heritage site next weekend," the server can identify the nearest notable cultural heritage site and instantly suggest a plan including transportation and accommodation. An example of a prompt would be, "Please suggest nearby cultural heritage sites I would like to visit next weekend and generate a travel plan including transportation."

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The user enters their travel preferences using a device.

[0115] The input includes travel destination, budget, travel dates, and desired activities. The entered data is sent from the terminal to the server.

[0116] Step 2:

[0117] The server analyzes the received travel preference information.

[0118] In this analysis process, a generative AI model is used to process user input data and extract highly relevant information. Specifically, data processing involves narrowing down possible travel plans based on budget and schedule.

[0119] Step 3:

[0120] The server uses intelligent processing to generate travel suggestions.

[0121] The server uses the analyzed information to create multiple travel plans by referring to a database. Factors such as seasonality, discount information, and popular tourist attractions are taken into consideration during this process.

[0122] Step 4:

[0123] The server sends the generated travel suggestions to the terminal.

[0124] The proposals are formatted for display on the user's device and made presentable as visually organized information.

[0125] Step 5:

[0126] The user reviews and selects a travel suggestion displayed on their device.

[0127] Users can compare the details of the offered plans and select the one that best suits their needs. Their selection is then sent to the server as a user decision.

[0128] Step 6:

[0129] The server will initiate the booking process based on the selected travel plan.

[0130] It integrates with multiple booking services via APIs to automate bookings at the best price and conditions. This process involves data exchange with external systems.

[0131] Step 7:

[0132] The server notifies the terminal that the reservation is complete.

[0133] Finally, confirmation information for the completed reservation is sent to the user's device, and the user is notified so they know that their travel preparations are complete.

[0134] 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.

[0135] This invention provides a travel planning and booking system that takes user emotions into consideration. This system recognizes the user's emotions when they express their travel preferences using an emotion engine, and generates a personalized travel plan.

[0136] User requests and emotional input

[0137] Through a dedicated application on their device, users can input their travel requests and communicate their emotions via facial expression recognition and voice analysis. This emotional input includes data based on peaceful states such as "I need relaxation" and excited states such as "I want to seek adventure."

[0138] Emotion recognition and plan generation

[0139] The server uses an emotion engine to analyze the user's current emotional state. This analysis helps to deeply understand the user's intentions and generate travel plans that match them. For example, a user seeking relaxation might be offered plans involving hot springs or quiet resorts. A user seeking adventure might be offered plans incorporating trekking or active tours.

[0140] Presentation of travel plans

[0141] The device presents users with travel plans optimized based on their emotions. These plans, in addition to standard suggestions, reflect the user's emotional state, offering more personalized options.

[0142] Reservation procedures and notifications

[0143] Based on the selected plan, the server automatically processes the booking at the most optimal price. The emotion engine monitors the user's emotional state during the booking process and provides suggestions and options to reduce burden and stress. Once the booking is complete, the terminal notifies the user of the details and provides necessary information in a timely manner.

[0144] This system allows travelers to incorporate their emotions into their travel plans, resulting in a more personalized travel experience. Furthermore, by streamlining the booking process, it minimizes user anxiety and stress.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] The user launches a dedicated application on their device and enters their travel preferences and objectives. During this process, the device captures the user's facial expressions with its camera to acquire emotional data and uses its microphone to record voice patterns for emotional analysis from the conversation.

[0148] Step 2:

[0149] The terminal sends text information entered by the user and emotion recognition data to the server. The data includes facial expression recognition information and speech recognition results.

[0150] Step 3:

[0151] The server analyzes the received data and uses an emotion engine to evaluate the user's emotional state. Based on this evaluation, it infers the user's desires from their emotions, such as whether they are looking for a relaxing trip or an adventurous one, and sets a corresponding plan concept.

[0152] Step 4:

[0153] The server searches a diverse travel database and generates travel plans tailored to the user's emotions and preferences. For example, if the emotion of relaxation is recognized, it will generate plans for hot spring resorts and hotels with massages. If it is determined that the user is adventurous, it will create plans that include rafting and safari tours.

[0154] Step 5:

[0155] The server sends the generated travel plans to the device. The device visually organizes these plans and displays them to the user. Each plan lists detailed itineraries, pricing information, and perks.

[0156] Step 6:

[0157] The user reviews the presented plans and selects the one that interests them most. In this selection process, the device utilizes emotion recognition data to provide timely support messages if the user experiences anxiety or hesitation during the selection process.

[0158] Step 7:

[0159] The server executes the necessary booking procedures based on the plan confirmed by the user. The emotion engine also runs during the booking process, providing guidance to alleviate user stress and detecting and responding to situations where additional options can be added.

[0160] Step 8:

[0161] Once the reservation is complete, the server sends details and a completion notification to the device. The device then displays notifications to the user at appropriate times, providing content that reinforces the key points of the plan that the user was particularly interested in.

[0162] In this way, the system takes the user's emotional state into consideration and smoothly supports them from travel planning to booking completion, thereby providing an optimized travel experience for each individual user.

[0163] (Example 2)

[0164] 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".

[0165] Traditional travel plan generation systems offer suggestions based on user preferences and requirements, but they fail to provide travel plans that take into account the user's emotional state. As a result, users often struggle to obtain travel experiences that reflect their inner needs. Furthermore, there were insufficient mechanisms to alleviate stress and anxiety during the booking process.

[0166] 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.

[0167] In this invention, the server includes means for inputting the user's emotional state, means for analyzing the input emotional data and generating travel suggestions that match the user's emotions using artificial intelligence, and means for displaying optimized travel suggestions based on the analyzed emotional data and making them selectable by the user. This makes it possible to provide travel plans that take the user's emotions into consideration and to reduce stress and anxiety during the booking process.

[0168] "User emotional state" refers to data that describes the traveler's specific inner feelings and psychological condition.

[0169] "Analyzing emotional data" is the process of processing information about emotions that has been input and giving it meaning.

[0170] "Generative artificial intelligence" refers to a program that mimics human knowledge and judgment on a computer system, generating and processing data according to specific purposes.

[0171] A "travel suggestion" is a plan that includes suggested travel information tailored to the user's needs and conditions.

[0172] An "optimized travel suggestion" refers to a travel plan that has been adjusted to best suit the user's emotional state and various conditions.

[0173] "Automated booking process" refers to a process where the system proceeds in a way that completes the booking without user intervention.

[0174] "Monitoring emotions" refers to continuously measuring and recording changes in the user's emotional state during the booking process.

[0175] "External booking services" refer to external booking systems or providers that exist outside the system and are used for making travel reservations.

[0176] This invention relates to a system that generates travel suggestions that reflect the user's emotions and automates the booking process. The system mainly consists of the user's terminal, a server, and a working artificial intelligence engine.

[0177] Terminal role

[0178] Users input their travel preferences and current emotions using a dedicated application on their device. Emotion input utilizes facial expression recognition via the camera and voice analysis technology via the microphone. This allows for a deeper understanding of the user's specific needs. For example, if a user smiles at the camera, the emotion "I want to relax" is recognized, and if they input "I want to go to a seaside resort" via voice, this data is collected.

[0179] Server Role

[0180] The server analyzes emotional data transmitted from the terminal. Using an emotional analysis engine, it quantifies the user's emotional state and, based on that data, utilizes a generative AI model to generate a suitable travel plan. The generative AI model learns from accumulated data and can provide travel suggestions that are best suited to the user's emotions.

[0181] The generated travel plans are personalized, reflecting the results of the emotion analysis. Users seeking relaxation will be offered hot spring resort trips, while adventurous users will be suggested trekking tours and similar activities.

[0182] Specific example

[0183] When user A inputs emotional data indicating they "seek relaxation," the server processes it and provides a travel plan to a hot spring resort.

[0184] If user B expresses a desire for an adventure, the server will suggest an active tour in a nature-rich location.

[0185] Example of a prompt

[0186] "Generate travel plan suggestions that are ideal for users seeking relaxation."

[0187] "Please provide active itineraries for adventure-loving users."

[0188] Based on the user's selection, the server automatically connects with external booking services to find the best price and complete the reservation. Finally, the terminal notifies the user of the reservation completion and provides detailed information about the trip. This system allows users to experience a customized trip that perfectly matches their emotions.

[0189] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0190] Step 1:

[0191] Users input their travel preferences and emotional state using a dedicated app on their device. This input utilizes facial expression recognition via the camera and voice analysis via the microphone. If a user smiles, indicating they want to relax, facial expression data is captured. Similarly, if they speak "seaside resort" via voice input, voice data is obtained. This data is then sent to a server.

[0192] Step 2:

[0193] The server analyzes the received emotional data using an emotion engine. The input consists of facial expressions and voice data, which are used to quantify the user's emotional state and obtain analysis results. For example, if the emotional score for "relaxed" is high, a corresponding travel category is identified. This analysis result is then used as the source data for subsequent plan generation.

[0194] Step 3:

[0195] The server uses a generative AI model to generate travel plans based on the analysis results. The input for this step is the result of sentiment analysis, and the optimal travel plan is generated accordingly. For example, if relaxation is requested, a plan including hot springs and beach resorts will be created. The generated plan is stored in a database to be presented to the user.

[0196] Step 4:

[0197] The terminal displays travel plans sent from the server on the screen. The input for this step is travel plan data from the server. The user can review the plans and select the ones that interest them. The screen may list options such as "Hot Spring Resort Plan" or "Tropical Beach Tour," and detailed information can be viewed.

[0198] Step 5:

[0199] Based on the travel plan selected by the user, the server automatically proceeds with the booking process. This process communicates with an external booking service, selecting the most suitable option and completing the reservation. The selected plan is used as input, and the booking details are generated as output. This automation allows users to complete the process smoothly.

[0200] Step 6:

[0201] The terminal notifies the user of the booking completion. The input is booking completion data from the server, and the output is a notification containing the booking number and travel details. This allows the user to obtain all the information necessary to prepare for their trip. The notification pops up on the screen and includes a link to the details page.

[0202] (Application Example 2)

[0203] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0204] Traditional travel planning systems made travel suggestions based on simple data input without considering the user's emotions, making it difficult to provide a truly satisfying travel experience. Furthermore, they lacked flexibility, failing to suggest tourist destinations that matched the user's mood in real time.

[0205] 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.

[0206] In this invention, the server includes means for providing a user interface to a terminal for inputting travel preference information and emotional information; means for analyzing the input travel preference information and emotional information and using artificial intelligence to generate multiple travel suggestions; and means for collecting tourist destination information and generating suggestions in real time based on the user's emotions. This enables customized travel suggestions that reflect the user's emotions and tourist destination suggestions that are in line with the user's real-time preferences.

[0207] "Travel preference information" refers to information that allows travelers to specify their expectations and desires, such as destination, duration, budget, and purpose of travel.

[0208] "Emotional information" refers to information about a user's emotional state at a given time, obtained from their facial expressions, tone of voice, and other similar data.

[0209] A "user interface" is the interface on a terminal that a user uses to input information or receive suggestions from a system.

[0210] "Artificial intelligence" is a technology that analyzes large amounts of data and automatically generates appropriate travel suggestions based on the user's wishes and emotions.

[0211] "Tourist information" refers to information about geographical or cultural places that may be of interest to tourists.

[0212] "Generating suggestions in real time" is a process that provides the most suitable suggestions immediately based on the user's current state.

[0213] To implement this invention, the user must first install a dedicated application on a device such as a smartphone or smart glasses. This application provides a user interface for inputting travel preference information and emotional information. The user inputs travel preference information such as destination, purpose of travel, and budget, while emotional information is also acquired through facial expression recognition and voice analysis.

[0214] The device uses a camera and microphone to capture facial expressions and voice, and analyzes emotional states in real time. This information is sent to a server and analyzed by an emotion engine. In this process, facial expression recognition libraries such as OpenCV and DeepFace using Python, and TENSORFLOW® for voice analysis are utilized. As a result, travel suggestions tailored to the user's emotional state are generated and presented on the device.

[0215] The server uses artificial intelligence to collect and analyze tourist destination information in order to provide customized travel plans based on travel preferences and emotional information. This allows it to suggest the most suitable tourist destinations and activities in real time, tailored to the user's current emotions. For example, if the user wants to relax, it might suggest a quiet park or cafe, and if they are looking for active activities, it might suggest a sports event or a live event.

[0216] For example, if the emotion recognition system determines that a user is in a relaxed state while walking around town, it will suggest a nearby cafe or a quiet park. This allows the user to have a sightseeing experience optimized for their current mood.

[0217] An example of a prompt to input into the generating AI model would be, "My current emotional state is one of relaxation, so please recommend some relaxing tourist spots." This prompt instructs the system to generate the optimal plan based on the user's real-time needs.

[0218] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0219] Step 1:

[0220] The user launches a dedicated application on their device and enters their travel preferences. This includes entering information such as the purpose of the trip, budget, and places they wish to visit into a form. Simultaneously, the device's camera and microphone activate, collecting the user's facial expressions and voice. This data becomes the input information and is converted into digital data as a preprocessing step for facial expression recognition and voice analysis.

[0221] Step 2:

[0222] The device analyzes the collected facial expressions and audio data. Specifically, it uses OpenCV's face detection function and the DeepFace library to analyze the user's emotions. TensorFlow is used to capture tone and intonation from the audio and supplement the emotional information. Through this data processing, an output representing the user's current emotional state is generated.

[0223] Step 3:

[0224] The device sends analyzed emotional information and travel preference information to the server. The server uses artificial intelligence based on the received information to generate travel suggestions. It extracts travel destinations and activities that match the user's emotions from a tourist destination information database and performs data calculations to generate suggestions that are suitable for the user.

[0225] Step 4:

[0226] The server sends the generated travel suggestions to the terminal. The terminal presents the user with multiple suggestions through its display interface. The user selects their preferred travel plan from the displayed suggestions. This selection becomes the input for the next process.

[0227] Step 5:

[0228] Based on the travel plan selected by the user, the server automatically handles the booking process. It accesses multiple external booking services and performs data calculations to select the best price and conditions. The selection results are output as confirmed booking information.

[0229] Step 6:

[0230] The server notifies the terminal that the reservation is complete. The terminal displays the plan details and reservation information to the user and informs them that the necessary procedures have been completed. This ensures that the user has a smooth reservation experience.

[0231] 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.

[0232] Data generation model 58 is a type of 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.

[0233] 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.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] 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.

[0237] 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).

[0238] 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.

[0239] 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.

[0240] 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).

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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".

[0247] This invention provides a system that allows users to easily plan and book trips. This system takes user requests as input, presents a variety of options based on those requests, and then allows users to book using the most suitable option. The following describes embodiments of the system based on this invention.

[0248] User request input

[0249] Users enter their travel requests using a dedicated application on their device. This interface is intuitive and allows users to input or select parameters such as travel destination, budget, duration, and desired activities.

[0250] Requirements analysis and plan generation

[0251] The server receives information sent by the user and analyzes it using artificial intelligence. This helps to concretize the user's vague requests and generate multiple travel suggestions. The generated suggestions are compiled by referencing various databases and take into account seasonal factors, budget, travel dates, and other considerations.

[0252] Process example

[0253] For example, if a user enters "I want to visit historical sites in Europe during my summer vacation," the server can analyze this request and generate a travel plan for cities in Europe that include historical sites, such as Rome, Athens, or Paris. In addition, it would include details such as accommodations in each city, flight options, and local tours.

[0254] Proposal presentation and selection

[0255] The device visually displays travel suggestions retrieved from the server to the user. Users can compare the details of these suggestions and select the one best suited to their travel plans. Customization of options based on the selected plan is also possible.

[0256] Reservations and notifications

[0257] Based on the selected travel plan, the server initiates the booking process for flights and accommodations. It automatically selects options using multiple online booking services to ensure the best price. This allows users to finalize their ideal travel plan without unnecessary hassle. Once the booking is complete, the user is notified of the details and provided with necessary information via their device.

[0258] This system reduces the complexity and time-consuming processes associated with typical travel planning, allowing users to easily proceed with their travel plans.

[0259] The following describes the processing flow.

[0260] Step 1:

[0261] The user accesses a dedicated application on their device and enters their travel requests. On the interface, the user enters or selects information such as destination, budget, desired dates, and desired activities.

[0262] Step 2:

[0263] The terminal sends the information entered by the user to the server. The data is encrypted and securely transferred to the server.

[0264] Step 3:

[0265] The server analyzes the received information. Using artificial intelligence, it processes the user's input information using natural language and extracts specific travel-related needs. At the same time, it sets search queries based on the entered conditions.

[0266] Step 4:

[0267] The server accesses external travel databases to search for and retrieve travel destinations and itineraries that meet the user's needs. This includes flight information, accommodation options, and local activity options. Taking seasonal factors and current price trends into account, it generates several optimal itineraries.

[0268] Step 5:

[0269] The server sends the generated plan to the device. The device receives it and presents it to the user in a visual format using travel plan comparison tables and maps.

[0270] Step 6:

[0271] The user selects a travel plan of interest from the presented options and enters their selection into the device. The device then sends the selection to the server.

[0272] Step 7:

[0273] The server initiates the booking process based on the travel plan selected by the user. It uses external booking service APIs to check flight and accommodation availability and confirm the booking. It also compares with other services to obtain the lowest price for options.

[0274] Step 8:

[0275] Once the booking is complete, the server sends the booking details to the device. The device receives this and sends a notification to the user. The notification includes information about the booked flight, accommodation details, and planned activities.

[0276] Step 9:

[0277] Users can check notifications through their devices and make additional options or changes as needed. This allows for final confirmation and adjustment of travel plans.

[0278] (Example 1)

[0279] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0280] In a conventional travel planning system, it was common for users to spend a lot of time and effort inputting information, and subsequent proposal and reservation procedures also required complicated operations. As a result, it was difficult to easily formulate an ideal travel plan, and in many cases, price and schedule optimization were not sufficiently carried out.

[0281] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0282] In this invention, the server includes means for providing a user interface for inputting travel wish information to an information processing device, means for analyzing the input travel wish information and using a machine learning model to generate a plurality of travel proposals, and means for providing a function for customizing the travel plan proposed to the user. Thereby, it becomes possible for the user to quickly and efficiently select an optimal travel plan and automate the process up to reservation.

[0283] "Travel wish information" refers to information such as the destination, budget, travel period, and desired activities related to the travel planned by the user.

[0284] "User interface" refers to an operation screen or tool provided in an information processing device for the user to input or acquire information.

[0285] "Machine learning model" refers to a computer program that automatically learns from data and has the ability to execute specific tasks.

[0286] "External reservation service" refers to a third-party platform or service that provides reservation services online, and it is possible to make reservations for hotels, airline tickets, etc.

[0287] The means for selecting the optimal price refers to a process or function that automatically selects the price most advantageous to the conditions from a plurality of price options.

[0288] A "prompt sentence" is a sentence that gives instructions to a machine learning model to execute a specific task, and is usually generated based on input data.

[0289] The present invention provides an information processing system for a user to efficiently plan and book a trip. This system is realized through a process of inputting travel wish information through a user interface on a terminal, sending it to a server, and analyzing it.

[0290] When the server receives information, it analyzes the input data using a generated AI model. Through this analysis, a plurality of travel proposals based on travel wishes and conditions are generated. In this process, the server accesses an external database to collect the latest information on accommodation, transportation, activities, etc., and designs an optimal proposal considering seasonal factors and budgets.

[0291] The terminal presents the generated travel proposals to the user in a visually easy-to-understand form. The user compares the proposal contents based on this information and selects a plan of interest. In addition, the user can use the function of customizing the proposed plan to adjust the details of the trip according to their own convenience.

[0292] As a specific example, when the user wishes to visit a historical tourist destination during the summer vacation, an input such as "The user is looking for historical sites in a trip to Europe in the summer of 2023." is generated as a prompt sentence. Based on this prompt sentence, the server can use the model to formulate and propose appropriate tourist destinations and plans.

[0293] Ultimately, the server makes the booking directly based on the selected travel proposal. This process utilizes multiple external booking services and automatically selects the option with the best price and conditions. This allows users to skip complex booking procedures and easily plan and book their trips.

[0294] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0295] Step 1:

[0296] Users enter their travel preferences through a user interface on their device. Input fields include destination, budget, travel duration, and desired activities. This information serves to collect the user's specific travel preferences as digital data. When the user presses the "Submit" button, this data is sent to the server.

[0297] Step 2:

[0298] The server receives travel preference information from the terminal. The received data is first checked for formatting, and then analyzed using a generative AI model. This model generates prompt sentences, taking a sentence like "The user is looking for historical sites for a trip to Europe in the summer of 2023" as input. Using this prompt, the server prepares to generate suggestions that match the user's preferences.

[0299] Step 3:

[0300] The server inputs prompt sentences into a generation AI model, which then generates multiple travel suggestions based on these prompts. During this process, it retrieves information on accommodations, transportation, and tourist attractions from an external travel database. The database is searched based on the analyzed prompt sentences, and a suitable travel plan is constructed. The output is a list of multiple travel suggestions that match the user's criteria.

[0301] Step 4:

[0302] The server sends the proposed travel plan to the terminal. The terminal uses this information and presents it to the user in a visually easy-to-understand format. The user can scroll through the travel proposals to view and compare the information. Also, details such as costs and schedules are displayed for each plan. The user selects the most attractive option from the presented information.

[0303] Step 5:

[0304] Based on the selected travel plan, the user can further customize it. In this step, the user can adjust the number of staying days, add or remove specific activities. Through this interactive operation, a travel plan that fully meets the user's wishes is formulated.

[0305] Step 6:

[0306] Based on the customized travel plan finally selected by the user, the server starts the reservation procedure. In this procedure, multiple external reservation services are cross-checked, and a reservation with the optimal price and conditions is selected. Then, based on this, the reservation is automatically confirmed. The output is the confirmed reservation information.

[0307] Step 7:

[0308] When the reservation is completed, the server notifies the terminal of the information. The terminal displays the confirmed itinerary, confirmation number, hotel and flight information to the user. This enables the user to easily grasp the entire travel plan and prepare the necessary documents.

[0309] (Application Example 1)

[0310] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0311] Planning and booking a trip is often cumbersome, requiring the comparison and evaluation of numerous options and information. Furthermore, it's often impossible to receive suggestions for the most suitable tourist destinations and activities based on the user's location. Therefore, there is a need for a system that efficiently plans trips and enhances the travel experience at the destination.

[0312] 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.

[0313] In this invention, the server includes means for providing a terminal with user operation means for inputting travel preference information; means for using intelligent processing to analyze the input travel preference information and generate multiple travel suggestions; means for displaying the generated travel suggestions and making them selectable by the user; and means for providing suggestions based on the user's current location using location information. This enables the user to efficiently plan their trip and obtain an optimal sightseeing experience based on location information.

[0314] "Travel preference information" refers to information in which users specifically express their desires regarding travel, and includes elements such as destination, budget, and duration.

[0315] "User operation means" refers to the general term for interfaces and devices provided for users to input information via a terminal.

[0316] "Intelligent processing" is the process of analyzing input data and generating information to support decision-making, utilizing technologies such as machine learning and artificial intelligence.

[0317] "Display means" refers to devices or software interfaces for providing information to users visually, and includes screens and displays.

[0318] "Location information" refers to data that indicates the user's current location, obtained using a device, and is information that identifies a region based on latitude and longitude.

[0319] "Means of providing suggestions" refers to methods and processes for presenting users with appropriate options and information, thereby encouraging users to make the best choice.

[0320] This invention is implemented as a system that efficiently supports travel planning. The server provides a user operation means for users to input travel preference information from their terminals. This user operation means operates on smartphones and personal computers and has an interface that allows users to intuitively input destinations, budgets, travel itineraries, etc.

[0321] The server uses intelligent processing to analyze travel preference information submitted by users. This intelligent processing employs machine learning algorithms to generate optimal travel suggestions from the database, creating multiple options based on the user's criteria.

[0322] The generated travel suggestions are provided to the user via a display device and are visually presented on a smartphone or screen. Users can compare and consider the suggested travel plans and choose the option that best suits their preferences.

[0323] Furthermore, the server utilizes location information to provide a means of suggesting the latest tourist and event information based on the user's current location. This makes it possible to suggest local events and tourist attractions at travel destinations in real time.

[0324] The booking process is handled by an automated system that collaborates with multiple external booking services to select the best price and complete the booking without requiring manual intervention. Once the booking is complete, the user's device is notified and provided with detailed travel information.

[0325] For example, if a user enters "I want to visit a nearby cultural heritage site next weekend," the server can identify the nearest notable cultural heritage site and instantly suggest a plan including transportation and accommodation. An example of a prompt would be, "Please suggest nearby cultural heritage sites I would like to visit next weekend and generate a travel plan including transportation."

[0326] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0327] Step 1:

[0328] The user enters their travel preferences using a device.

[0329] The input includes travel destination, budget, travel dates, and desired activities. The entered data is sent from the terminal to the server.

[0330] Step 2:

[0331] The server analyzes the received travel preference information.

[0332] In this analysis process, a generative AI model is used to process user input data and extract highly relevant information. Specifically, data processing involves narrowing down possible travel plans based on budget and schedule.

[0333] Step 3:

[0334] The server uses intelligent processing to generate travel suggestions.

[0335] The server uses the analyzed information to create multiple travel plans by referring to a database. Factors such as seasonality, discount information, and popular tourist attractions are taken into consideration during this process.

[0336] Step 4:

[0337] The server sends the generated travel suggestions to the terminal.

[0338] The proposals are formatted for display on the user's device and made presentable as visually organized information.

[0339] Step 5:

[0340] The user reviews and selects a travel suggestion displayed on their device.

[0341] Users can compare the details of the offered plans and select the one that best suits their needs. Their selection is then sent to the server as a user decision.

[0342] Step 6:

[0343] The server will initiate the booking process based on the selected travel plan.

[0344] It integrates with multiple booking services via APIs to automate bookings at the best price and conditions. This process involves data exchange with external systems.

[0345] Step 7:

[0346] The server notifies the terminal that the reservation is complete.

[0347] Finally, confirmation information for the completed reservation is sent to the user's device, and the user is notified so they know that their travel preparations are complete.

[0348] 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.

[0349] This invention provides a travel planning and booking system that takes user emotions into consideration. This system recognizes the user's emotions when they express their travel preferences using an emotion engine, and generates a personalized travel plan.

[0350] User requests and emotional input

[0351] Through a dedicated application on their device, users can input their travel requests and communicate their emotions via facial expression recognition and voice analysis. This emotional input includes data based on peaceful states such as "I need relaxation" and excited states such as "I want to seek adventure."

[0352] Emotion recognition and plan generation

[0353] The server uses an emotion engine to analyze the user's current emotional state. This analysis helps to deeply understand the user's intentions and generate travel plans that match them. For example, a user seeking relaxation might be offered plans involving hot springs or quiet resorts. A user seeking adventure might be offered plans incorporating trekking or active tours.

[0354] Presentation of travel plans

[0355] The device presents users with travel plans optimized based on their emotions. These plans, in addition to standard suggestions, reflect the user's emotional state, offering more personalized options.

[0356] Reservation procedures and notifications

[0357] Based on the selected plan, the server automatically processes the booking at the most optimal price. The emotion engine monitors the user's emotional state during the booking process and provides suggestions and options to reduce burden and stress. Once the booking is complete, the terminal notifies the user of the details and provides necessary information in a timely manner.

[0358] This system allows travelers to incorporate their emotions into their travel plans, resulting in a more personalized travel experience. Furthermore, by streamlining the booking process, it minimizes user anxiety and stress.

[0359] The following describes the processing flow.

[0360] Step 1:

[0361] The user launches a dedicated application on their device and enters their travel preferences and objectives. During this process, the device captures the user's facial expressions with its camera to acquire emotional data and uses its microphone to record voice patterns for emotional analysis from the conversation.

[0362] Step 2:

[0363] The terminal sends text information entered by the user and emotion recognition data to the server. The data includes facial expression recognition information and speech recognition results.

[0364] Step 3:

[0365] The server analyzes the received data and uses an emotion engine to evaluate the user's emotional state. Based on this evaluation, it infers the user's desires from their emotions, such as whether they are looking for a relaxing trip or an adventurous one, and sets a corresponding plan concept.

[0366] Step 4:

[0367] The server searches a diverse travel database and generates travel plans tailored to the user's emotions and preferences. For example, if the emotion of relaxation is recognized, it will generate plans for hot spring resorts and hotels with massages. If it is determined that the user is adventurous, it will create plans that include rafting and safari tours.

[0368] Step 5:

[0369] The server sends the generated travel plans to the device. The device visually organizes these plans and displays them to the user. Each plan lists detailed itineraries, pricing information, and perks.

[0370] Step 6:

[0371] The user reviews the presented plans and selects the one that interests them most. In this selection process, the device utilizes emotion recognition data to provide timely support messages if the user experiences anxiety or hesitation during the selection process.

[0372] Step 7:

[0373] The server executes the necessary booking procedures based on the plan confirmed by the user. The emotion engine also runs during the booking process, providing guidance to alleviate user stress and detecting and responding to situations where additional options can be added.

[0374] Step 8:

[0375] Once the reservation is complete, the server sends details and a completion notification to the device. The device then displays notifications to the user at appropriate times, providing content that reinforces the key points of the plan that the user was particularly interested in.

[0376] In this way, the system takes the user's emotional state into consideration and smoothly supports them from travel planning to booking completion, thereby providing an optimized travel experience for each individual user.

[0377] (Example 2)

[0378] 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".

[0379] Traditional travel plan generation systems offer suggestions based on user preferences and requirements, but they fail to provide travel plans that take into account the user's emotional state. As a result, users often struggle to obtain travel experiences that reflect their inner needs. Furthermore, there were insufficient mechanisms to alleviate stress and anxiety during the booking process.

[0380] 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.

[0381] In this invention, the server includes means for inputting the user's emotional state, means for analyzing the input emotional data and generating travel suggestions that match the user's emotions using artificial intelligence, and means for displaying optimized travel suggestions based on the analyzed emotional data and making them selectable by the user. This makes it possible to provide travel plans that take the user's emotions into consideration and to reduce stress and anxiety during the booking process.

[0382] "User emotional state" refers to data that describes the traveler's specific inner feelings and psychological condition.

[0383] "Analyzing emotional data" is the process of processing information about emotions that has been input and giving it meaning.

[0384] "Generative artificial intelligence" refers to a program that mimics human knowledge and judgment on a computer system, generating and processing data according to specific purposes.

[0385] A "travel suggestion" is a plan that includes suggested travel information tailored to the user's needs and conditions.

[0386] An "optimized travel suggestion" refers to a travel plan that has been adjusted to best suit the user's emotional state and various conditions.

[0387] "Automated booking process" refers to a process where the system proceeds in a way that completes the booking without user intervention.

[0388] "Monitoring emotions" refers to continuously measuring and recording changes in the user's emotional state during the booking process.

[0389] "External booking services" refer to external booking systems or providers that exist outside the system and are used for making travel reservations.

[0390] This invention relates to a system that generates travel suggestions that reflect the user's emotions and automates the booking process. The system mainly consists of the user's terminal, a server, and a working artificial intelligence engine.

[0391] Terminal role

[0392] Users input their travel preferences and current emotions using a dedicated application on their device. Emotion input utilizes facial expression recognition via the camera and voice analysis technology via the microphone. This allows for a deeper understanding of the user's specific needs. For example, if a user smiles at the camera, the emotion "I want to relax" is recognized, and if they input "I want to go to a seaside resort" via voice, this data is collected.

[0393] Server Role

[0394] The server analyzes emotional data transmitted from the terminal. Using an emotional analysis engine, it quantifies the user's emotional state and, based on that data, utilizes a generative AI model to generate a suitable travel plan. The generative AI model learns from accumulated data and can provide travel suggestions that are best suited to the user's emotions.

[0395] The generated travel plans are personalized, reflecting the results of the emotion analysis. Users seeking relaxation will be offered hot spring resort trips, while adventurous users will be suggested trekking tours and similar activities.

[0396] Specific example

[0397] When user A inputs emotional data indicating they "seek relaxation," the server processes it and provides a travel plan to a hot spring resort.

[0398] If user B expresses a desire for an adventure, the server will suggest an active tour in a nature-rich location.

[0399] Example of a prompt

[0400] "Generate travel plan suggestions that are ideal for users seeking relaxation."

[0401] "Please provide active itineraries for adventure-loving users."

[0402] Based on the user's selection, the server automatically connects with external booking services to find the best price and complete the reservation. Finally, the terminal notifies the user of the reservation completion and provides detailed information about the trip. This system allows users to experience a customized trip that perfectly matches their emotions.

[0403] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0404] Step 1:

[0405] Users input their travel preferences and emotional state using a dedicated app on their device. This input utilizes facial expression recognition via the camera and voice analysis via the microphone. If a user smiles, indicating they want to relax, facial expression data is captured. Similarly, if they speak "seaside resort" via voice input, voice data is obtained. This data is then sent to a server.

[0406] Step 2:

[0407] The server analyzes the received emotional data using an emotion engine. The input consists of facial expressions and voice data, which are used to quantify the user's emotional state and obtain analysis results. For example, if the emotional score for "relaxed" is high, a corresponding travel category is identified. This analysis result is then used as the source data for subsequent plan generation.

[0408] Step 3:

[0409] The server uses a generative AI model to generate travel plans based on the analysis results. The input for this step is the result of sentiment analysis, and the optimal travel plan is generated accordingly. For example, if relaxation is requested, a plan including hot springs and beach resorts will be created. The generated plan is stored in a database to be presented to the user.

[0410] Step 4:

[0411] The terminal displays travel plans sent from the server on the screen. The input for this step is travel plan data from the server. The user can review the plans and select the ones that interest them. The screen may list options such as "Hot Spring Resort Plan" or "Tropical Beach Tour," and detailed information can be viewed.

[0412] Step 5:

[0413] Based on the travel plan selected by the user, the server automatically proceeds with the booking process. This process communicates with an external booking service, selecting the most suitable option and completing the reservation. The selected plan is used as input, and the booking details are generated as output. This automation allows users to complete the process smoothly.

[0414] Step 6:

[0415] The terminal notifies the user of the booking completion. The input is booking completion data from the server, and the output is a notification containing the booking number and travel details. This allows the user to obtain all the information necessary to prepare for their trip. The notification pops up on the screen and includes a link to the details page.

[0416] (Application Example 2)

[0417] 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."

[0418] Traditional travel planning systems made travel suggestions based on simple data input without considering the user's emotions, making it difficult to provide a truly satisfying travel experience. Furthermore, they lacked flexibility, failing to suggest tourist destinations that matched the user's mood in real time.

[0419] 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.

[0420] In this invention, the server includes means for providing a user interface to a terminal for inputting travel preference information and emotional information; means for analyzing the input travel preference information and emotional information and using artificial intelligence to generate multiple travel suggestions; and means for collecting tourist destination information and generating suggestions in real time based on the user's emotions. This enables customized travel suggestions that reflect the user's emotions and tourist destination suggestions that are in line with the user's real-time preferences.

[0421] "Travel preference information" refers to information that allows travelers to specify their expectations and desires, such as destination, duration, budget, and purpose of travel.

[0422] "Emotional information" refers to information about a user's emotional state at a given time, obtained from their facial expressions, tone of voice, and other similar data.

[0423] A "user interface" is the interface on a terminal that a user uses to input information or receive suggestions from a system.

[0424] "Artificial intelligence" is a technology that analyzes large amounts of data and automatically generates appropriate travel suggestions based on the user's wishes and emotions.

[0425] "Tourist information" refers to information about geographical or cultural places that may be of interest to tourists.

[0426] "Generating suggestions in real time" is a process that provides the most suitable suggestions immediately based on the user's current state.

[0427] To implement this invention, the user must first install a dedicated application on a device such as a smartphone or smart glasses. This application provides a user interface for inputting travel preference information and emotional information. The user inputs travel preference information such as destination, purpose of travel, and budget, while emotional information is also acquired through facial expression recognition and voice analysis.

[0428] The device uses its camera and microphone to capture facial expressions and voice, and analyzes emotional states in real time. This information is sent to a server and analyzed by an emotion engine. This process utilizes facial expression recognition libraries such as OpenCV and DeepFace using Python, and TensorFlow for voice analysis. As a result, travel suggestions tailored to the user's emotional state are generated and presented on the device.

[0429] The server uses artificial intelligence to collect and analyze tourist destination information in order to provide customized travel plans based on travel preferences and emotional information. This allows it to suggest the most suitable tourist destinations and activities in real time, tailored to the user's current emotions. For example, if the user wants to relax, it might suggest a quiet park or cafe, and if they are looking for active activities, it might suggest a sports event or a live event.

[0430] For example, if the emotion recognition system determines that a user is in a relaxed state while walking around town, it will suggest a nearby cafe or a quiet park. This allows the user to have a sightseeing experience optimized for their current mood.

[0431] An example of a prompt to input into the generating AI model would be, "My current emotional state is one of relaxation, so please recommend some relaxing tourist spots." This prompt instructs the system to generate the optimal plan based on the user's real-time needs.

[0432] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0433] Step 1:

[0434] The user launches a dedicated application on their device and enters their travel preferences. This includes entering information such as the purpose of the trip, budget, and places they wish to visit into a form. Simultaneously, the device's camera and microphone activate, collecting the user's facial expressions and voice. This data becomes the input information and is converted into digital data as a preprocessing step for facial expression recognition and voice analysis.

[0435] Step 2:

[0436] The device analyzes the collected facial expressions and audio data. Specifically, it uses OpenCV's face detection function and the DeepFace library to analyze the user's emotions. TensorFlow is used to capture tone and intonation from the audio and supplement the emotional information. Through this data processing, an output representing the user's current emotional state is generated.

[0437] Step 3:

[0438] The device sends analyzed emotional information and travel preference information to the server. The server uses artificial intelligence based on the received information to generate travel suggestions. It extracts travel destinations and activities that match the user's emotions from a tourist destination information database and performs data calculations to generate suggestions that are suitable for the user.

[0439] Step 4:

[0440] The server sends the generated travel suggestions to the terminal. The terminal presents the user with multiple suggestions through its display interface. The user selects their preferred travel plan from the displayed suggestions. This selection becomes the input for the next process.

[0441] Step 5:

[0442] Based on the travel plan selected by the user, the server automatically handles the booking process. It accesses multiple external booking services and performs data calculations to select the best price and conditions. The selection results are output as confirmed booking information.

[0443] Step 6:

[0444] The server notifies the terminal that the reservation is complete. The terminal displays the plan details and reservation information to the user and informs them that the necessary procedures have been completed. This ensures that the user has a smooth reservation experience.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] [Third Embodiment]

[0449] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0450] 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.

[0451] 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).

[0452] 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.

[0453] 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.

[0454] 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).

[0455] 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.

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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".

[0461] This invention provides a system that allows users to easily plan and book trips. This system takes user requests as input, presents a variety of options based on those requests, and then allows users to book using the most suitable option. The following describes embodiments of the system based on this invention.

[0462] User request input

[0463] Users enter their travel requests using a dedicated application on their device. This interface is intuitive and allows users to input or select parameters such as travel destination, budget, duration, and desired activities.

[0464] Requirements analysis and plan generation

[0465] The server receives information sent by the user and analyzes it using artificial intelligence. This helps to concretize the user's vague requests and generate multiple travel suggestions. The generated suggestions are compiled by referencing various databases and take into account seasonal factors, budget, travel dates, and other considerations.

[0466] Process example

[0467] For example, if a user enters "I want to visit historical sites in Europe during my summer vacation," the server can analyze this request and generate a travel plan for cities in Europe that include historical sites, such as Rome, Athens, or Paris. In addition, it would include details such as accommodations in each city, flight options, and local tours.

[0468] Proposal presentation and selection

[0469] The device visually displays travel suggestions retrieved from the server to the user. Users can compare the details of these suggestions and select the one best suited to their travel plans. Customization of options based on the selected plan is also possible.

[0470] Reservations and notifications

[0471] Based on the selected travel plan, the server initiates the booking process for flights and accommodations. It automatically selects options using multiple online booking services to ensure the best price. This allows users to finalize their ideal travel plan without unnecessary hassle. Once the booking is complete, the user is notified of the details and provided with necessary information via their device.

[0472] This system reduces the complexity and time-consuming processes associated with typical travel planning, allowing users to easily proceed with their travel plans.

[0473] The following describes the processing flow.

[0474] Step 1:

[0475] The user accesses a dedicated application on their device and enters their travel requests. On the interface, the user enters or selects information such as destination, budget, desired dates, and desired activities.

[0476] Step 2:

[0477] The terminal sends the information entered by the user to the server. The data is encrypted and securely transferred to the server.

[0478] Step 3:

[0479] The server analyzes the received information. Using artificial intelligence, it processes the user's input information using natural language and extracts specific travel-related needs. At the same time, it sets search queries based on the entered conditions.

[0480] Step 4:

[0481] The server accesses external travel databases to search for and retrieve travel destinations and itineraries that meet the user's needs. This includes flight information, accommodation options, and local activity options. Taking seasonal factors and current price trends into account, it generates several optimal itineraries.

[0482] Step 5:

[0483] The server sends the generated plan to the device. The device receives it and presents it to the user in a visual format using travel plan comparison tables and maps.

[0484] Step 6:

[0485] The user selects a travel plan of interest from the presented options and enters their selection into the device. The device then sends the selection to the server.

[0486] Step 7:

[0487] The server initiates the booking process based on the travel plan selected by the user. It uses external booking service APIs to check flight and accommodation availability and confirm the booking. It also compares with other services to obtain the lowest price for options.

[0488] Step 8:

[0489] Once the booking is complete, the server sends the booking details to the device. The device receives this and sends a notification to the user. The notification includes information about the booked flight, accommodation details, and planned activities.

[0490] Step 9:

[0491] Users can check notifications through their devices and make additional options or changes as needed. This allows for final confirmation and adjustment of travel plans.

[0492] (Example 1)

[0493] 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."

[0494] Traditional travel planning systems typically required users to spend a significant amount of time and effort inputting information, and subsequent suggestions and booking procedures were often cumbersome. As a result, it was difficult to easily create an ideal travel plan, and price and itinerary optimizations were often not adequately performed.

[0495] 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.

[0496] In this invention, the server includes means for providing an information processing device with a user interface for inputting travel preference information, means for using a machine learning model to analyze the input travel preference information and generate multiple travel suggestions, and means for providing a function for the user to customize the suggested travel plan. This makes it possible for the user to quickly and efficiently select the optimal travel plan and automate the booking process.

[0497] "Travel preference information" refers to information that describes the user's planned travel requirements, such as destination, budget, duration, and desired activities.

[0498] "User interface" refers to the operation screens or tools provided to an information processing device for the user to input or retrieve information.

[0499] A "machine learning model" refers to a computer program that has the ability to automatically learn from data and perform specific tasks.

[0500] "External booking services" refer to third-party platforms or services that provide online booking services, allowing users to book hotels, airline tickets, and other similar items.

[0501] "Means of selecting the optimal price" refers to a process or function that automatically selects the most favorable price from multiple price options based on the given conditions.

[0502] A "prompt" is a sentence that instructs a machine learning model to perform a specific task, and is usually generated based on the input data.

[0503] This invention provides an information processing system that enables users to efficiently plan and book trips. This system is implemented through a process in which users input travel preference information via a user interface on a terminal, send it to a server, and analyze it.

[0504] Upon receiving information, the server uses a generative AI model to analyze the input data. This analysis generates multiple travel suggestions based on the traveler's preferences and conditions. In this process, the server accesses external databases to gather the latest information on accommodations, transportation, activities, etc., and designs the optimal suggestion considering seasonal factors and budget.

[0505] The device presents the generated travel suggestions to the user in a visually easy-to-understand format. The user then compares the suggestions based on this information and selects the plan that interests them. Furthermore, the user can utilize a customization function to adjust the details of the trip to suit their own needs.

[0506] For example, if a user wants to visit historical tourist destinations during their summer vacation, a prompt such as "The user is looking for historical sites for a trip to Europe in the summer of 2023" will be generated. Based on this prompt, the server can use a model to formulate and suggest appropriate tourist destinations and plans.

[0507] Ultimately, the server makes the booking directly based on the selected travel proposal. This process utilizes multiple external booking services and automatically selects the option with the best price and conditions. This allows users to skip complex booking procedures and easily plan and book their trips.

[0508] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0509] Step 1:

[0510] Users enter their travel preferences through a user interface on their device. Input fields include destination, budget, travel duration, and desired activities. This information serves to collect the user's specific travel preferences as digital data. When the user presses the "Submit" button, this data is sent to the server.

[0511] Step 2:

[0512] The server receives travel preference information from the terminal. The received data is first checked for formatting, and then analyzed using a generative AI model. This model generates prompt sentences, taking a sentence like "The user is looking for historical sites for a trip to Europe in the summer of 2023" as input. Using this prompt, the server prepares to generate suggestions that match the user's preferences.

[0513] Step 3:

[0514] The server inputs prompt sentences into a generation AI model, which then generates multiple travel suggestions based on these prompts. During this process, it retrieves information on accommodations, transportation, and tourist attractions from an external travel database. The database is searched based on the analyzed prompt sentences, and a suitable travel plan is constructed. The output is a list of multiple travel suggestions that match the user's criteria.

[0515] Step 4:

[0516] The server sends the proposed travel plans to the device. The device uses this information to present it to the user in a visually easy-to-understand format. The user can scroll through the travel suggestions to review and compare the information. Details such as cost and itinerary are also displayed for each plan. The user chooses the most appealing option from the presented information.

[0517] Step 5:

[0518] Users can further customize their selected travel plan. This step allows them to adjust the length of stay and add or remove specific activities. This interactive process ensures that a travel plan perfectly matches the user's preferences.

[0519] Step 6:

[0520] The server initiates the booking process based on the customized travel plan ultimately selected by the user. This process cross-checks multiple external booking services to select the booking with the best price and conditions. Based on this, the booking is automatically confirmed. The output is the confirmed booking information.

[0521] Step 7:

[0522] Once the booking is complete, the server notifies the user of the information. The device then displays the user's confirmed itinerary, confirmation number, and hotel and flight details. This allows the user to easily understand their entire travel plan and prepare the necessary documents.

[0523] (Application Example 1)

[0524] 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."

[0525] Planning and booking a trip is often cumbersome, requiring the comparison and evaluation of numerous options and information. Furthermore, it's often impossible to receive suggestions for the most suitable tourist destinations and activities based on the user's location. Therefore, there is a need for a system that efficiently plans trips and enhances the travel experience at the destination.

[0526] 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.

[0527] In this invention, the server includes means for providing a terminal with user operation means for inputting travel preference information; means for using intelligent processing to analyze the input travel preference information and generate multiple travel suggestions; means for displaying the generated travel suggestions and making them selectable by the user; and means for providing suggestions based on the user's current location using location information. This enables the user to efficiently plan their trip and obtain an optimal sightseeing experience based on location information.

[0528] "Travel preference information" refers to information in which users specifically express their desires regarding travel, and includes elements such as destination, budget, and duration.

[0529] "User operation means" refers to the general term for interfaces and devices provided for users to input information via a terminal.

[0530] "Intelligent processing" is the process of analyzing input data and generating information to support decision-making, utilizing technologies such as machine learning and artificial intelligence.

[0531] "Display means" refers to devices or software interfaces for providing information to users visually, and includes screens and displays.

[0532] "Location information" refers to data that indicates the user's current location, obtained using a device, and is information that identifies a region based on latitude and longitude.

[0533] "Means of providing suggestions" refers to methods and processes for presenting users with appropriate options and information, thereby encouraging users to make the best choice.

[0534] This invention is implemented as a system that efficiently supports travel planning. The server provides a user operation means for users to input travel preference information from their terminals. This user operation means operates on smartphones and personal computers and has an interface that allows users to intuitively input destinations, budgets, travel itineraries, etc.

[0535] The server uses intelligent processing to analyze travel preference information submitted by users. This intelligent processing employs machine learning algorithms to generate optimal travel suggestions from the database, creating multiple options based on the user's criteria.

[0536] The generated travel suggestions are provided to the user via a display device and are visually presented on a smartphone or screen. Users can compare and consider the suggested travel plans and choose the option that best suits their preferences.

[0537] Furthermore, the server utilizes location information to provide a means of suggesting the latest tourist and event information based on the user's current location. This makes it possible to suggest local events and tourist attractions at travel destinations in real time.

[0538] The booking process is handled by an automated system that collaborates with multiple external booking services to select the best price and complete the booking without requiring manual intervention. Once the booking is complete, the user's device is notified and provided with detailed travel information.

[0539] For example, if a user enters "I want to visit a nearby cultural heritage site next weekend," the server can identify the nearest notable cultural heritage site and instantly suggest a plan including transportation and accommodation. An example of a prompt would be, "Please suggest nearby cultural heritage sites I would like to visit next weekend and generate a travel plan including transportation."

[0540] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0541] Step 1:

[0542] The user enters their travel preferences using a device.

[0543] The input includes travel destination, budget, travel dates, and desired activities. The entered data is sent from the terminal to the server.

[0544] Step 2:

[0545] The server analyzes the received travel preference information.

[0546] In this analysis process, a generative AI model is used to process user input data and extract highly relevant information. Specifically, data processing involves narrowing down possible travel plans based on budget and schedule.

[0547] Step 3:

[0548] The server uses intelligent processing to generate travel suggestions.

[0549] The server uses the analyzed information to create multiple travel plans by referring to a database. Factors such as seasonality, discount information, and popular tourist attractions are taken into consideration during this process.

[0550] Step 4:

[0551] The server sends the generated travel suggestions to the terminal.

[0552] The proposals are formatted for display on the user's device and made presentable as visually organized information.

[0553] Step 5:

[0554] The user reviews and selects a travel suggestion displayed on their device.

[0555] Users can compare the details of the offered plans and select the one that best suits their needs. Their selection is then sent to the server as a user decision.

[0556] Step 6:

[0557] The server will initiate the booking process based on the selected travel plan.

[0558] It integrates with multiple booking services via APIs to automate bookings at the best price and conditions. This process involves data exchange with external systems.

[0559] Step 7:

[0560] The server notifies the terminal that the reservation is complete.

[0561] Finally, confirmation information for the completed reservation is sent to the user's device, and the user is notified so they know that their travel preparations are complete.

[0562] 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.

[0563] This invention provides a travel planning and booking system that takes user emotions into consideration. This system recognizes the user's emotions when they express their travel preferences using an emotion engine, and generates a personalized travel plan.

[0564] User requests and emotional input

[0565] Through a dedicated application on their device, users can input their travel requests and communicate their emotions via facial expression recognition and voice analysis. This emotional input includes data based on peaceful states such as "I need relaxation" and excited states such as "I want to seek adventure."

[0566] Emotion recognition and plan generation

[0567] The server uses an emotion engine to analyze the user's current emotional state. This analysis helps to deeply understand the user's intentions and generate travel plans that match them. For example, a user seeking relaxation might be offered plans involving hot springs or quiet resorts. A user seeking adventure might be offered plans incorporating trekking or active tours.

[0568] Presentation of travel plans

[0569] The device presents users with travel plans optimized based on their emotions. These plans, in addition to standard suggestions, reflect the user's emotional state, offering more personalized options.

[0570] Reservation procedures and notifications

[0571] Based on the selected plan, the server automatically processes the booking at the most optimal price. The emotion engine monitors the user's emotional state during the booking process and provides suggestions and options to reduce burden and stress. Once the booking is complete, the terminal notifies the user of the details and provides necessary information in a timely manner.

[0572] This system allows travelers to incorporate their emotions into their travel plans, resulting in a more personalized travel experience. Furthermore, by streamlining the booking process, it minimizes user anxiety and stress.

[0573] The following describes the processing flow.

[0574] Step 1:

[0575] The user launches a dedicated application on their device and enters their travel preferences and objectives. During this process, the device captures the user's facial expressions with its camera to acquire emotional data and uses its microphone to record voice patterns for emotional analysis from the conversation.

[0576] Step 2:

[0577] The terminal sends text information entered by the user and emotion recognition data to the server. The data includes facial expression recognition information and speech recognition results.

[0578] Step 3:

[0579] The server analyzes the received data and uses an emotion engine to evaluate the user's emotional state. Based on this evaluation, it infers the user's desires from their emotions, such as whether they are looking for a relaxing trip or an adventurous one, and sets a corresponding plan concept.

[0580] Step 4:

[0581] The server searches a diverse travel database and generates travel plans tailored to the user's emotions and preferences. For example, if the emotion of relaxation is recognized, it will generate plans for hot spring resorts and hotels with massages. If it is determined that the user is adventurous, it will create plans that include rafting and safari tours.

[0582] Step 5:

[0583] The server sends the generated travel plans to the device. The device visually organizes these plans and displays them to the user. Each plan lists detailed itineraries, pricing information, and perks.

[0584] Step 6:

[0585] The user reviews the presented plans and selects the one that interests them most. In this selection process, the device utilizes emotion recognition data to provide timely support messages if the user experiences anxiety or hesitation during the selection process.

[0586] Step 7:

[0587] The server executes the necessary booking procedures based on the plan confirmed by the user. The emotion engine also runs during the booking process, providing guidance to alleviate user stress and detecting and responding to situations where additional options can be added.

[0588] Step 8:

[0589] Once the reservation is complete, the server sends details and a completion notification to the device. The device then displays notifications to the user at appropriate times, providing content that reinforces the key points of the plan that the user was particularly interested in.

[0590] In this way, the system takes the user's emotional state into consideration and smoothly supports them from travel planning to booking completion, thereby providing an optimized travel experience for each individual user.

[0591] (Example 2)

[0592] 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."

[0593] Traditional travel plan generation systems offer suggestions based on user preferences and requirements, but they fail to provide travel plans that take into account the user's emotional state. As a result, users often struggle to obtain travel experiences that reflect their inner needs. Furthermore, there were insufficient mechanisms to alleviate stress and anxiety during the booking process.

[0594] 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.

[0595] In this invention, the server includes means for inputting the user's emotional state, means for analyzing the input emotional data and generating travel suggestions that match the user's emotions using artificial intelligence, and means for displaying optimized travel suggestions based on the analyzed emotional data and making them selectable by the user. This makes it possible to provide travel plans that take the user's emotions into consideration and to reduce stress and anxiety during the booking process.

[0596] "User emotional state" refers to data that describes the traveler's specific inner feelings and psychological condition.

[0597] "Analyzing emotional data" is the process of processing information about emotions that has been input and giving it meaning.

[0598] "Generative artificial intelligence" refers to a program that mimics human knowledge and judgment on a computer system, generating and processing data according to specific purposes.

[0599] A "travel suggestion" is a plan that includes suggested travel information tailored to the user's needs and conditions.

[0600] An "optimized travel suggestion" refers to a travel plan that has been adjusted to best suit the user's emotional state and various conditions.

[0601] "Automated booking process" refers to a process where the system proceeds in a way that completes the booking without user intervention.

[0602] "Monitoring emotions" refers to continuously measuring and recording changes in the user's emotional state during the booking process.

[0603] "External booking services" refer to external booking systems or providers that exist outside the system and are used for making travel reservations.

[0604] This invention relates to a system that generates travel suggestions that reflect the user's emotions and automates the booking process. The system mainly consists of the user's terminal, a server, and a working artificial intelligence engine.

[0605] Terminal role

[0606] Users input their travel preferences and current emotions using a dedicated application on their device. Emotion input utilizes facial expression recognition via the camera and voice analysis technology via the microphone. This allows for a deeper understanding of the user's specific needs. For example, if a user smiles at the camera, the emotion "I want to relax" is recognized, and if they input "I want to go to a seaside resort" via voice, this data is collected.

[0607] Server Role

[0608] The server analyzes emotional data transmitted from the terminal. Using an emotional analysis engine, it quantifies the user's emotional state and, based on that data, utilizes a generative AI model to generate a suitable travel plan. The generative AI model learns from accumulated data and can provide travel suggestions that are best suited to the user's emotions.

[0609] The generated travel plans are personalized, reflecting the results of the emotion analysis. Users seeking relaxation will be offered hot spring resort trips, while adventurous users will be suggested trekking tours and similar activities.

[0610] Specific example

[0611] When user A inputs emotional data indicating they "seek relaxation," the server processes it and provides a travel plan to a hot spring resort.

[0612] If user B expresses a desire for an adventure, the server will suggest an active tour in a nature-rich location.

[0613] Example of a prompt

[0614] "Generate travel plan suggestions that are ideal for users seeking relaxation."

[0615] "Please provide active itineraries for adventure-loving users."

[0616] Based on the user's selection, the server automatically connects with external booking services to find the best price and complete the reservation. Finally, the terminal notifies the user of the reservation completion and provides detailed information about the trip. This system allows users to experience a customized trip that perfectly matches their emotions.

[0617] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0618] Step 1:

[0619] Users input their travel preferences and emotional state using a dedicated app on their device. This input utilizes facial expression recognition via the camera and voice analysis via the microphone. If a user smiles, indicating they want to relax, facial expression data is captured. Similarly, if they speak "seaside resort" via voice input, voice data is obtained. This data is then sent to a server.

[0620] Step 2:

[0621] The server analyzes the received emotional data using an emotion engine. The input consists of facial expressions and voice data, which are used to quantify the user's emotional state and obtain analysis results. For example, if the emotional score for "relaxed" is high, a corresponding travel category is identified. This analysis result is then used as the source data for subsequent plan generation.

[0622] Step 3:

[0623] The server uses a generative AI model to generate travel plans based on the analysis results. The input for this step is the result of sentiment analysis, and the optimal travel plan is generated accordingly. For example, if relaxation is requested, a plan including hot springs and beach resorts will be created. The generated plan is stored in a database to be presented to the user.

[0624] Step 4:

[0625] The terminal displays travel plans sent from the server on the screen. The input for this step is travel plan data from the server. The user can review the plans and select the ones that interest them. The screen may list options such as "Hot Spring Resort Plan" or "Tropical Beach Tour," and detailed information can be viewed.

[0626] Step 5:

[0627] Based on the travel plan selected by the user, the server automatically proceeds with the booking process. This process communicates with an external booking service, selecting the most suitable option and completing the reservation. The selected plan is used as input, and the booking details are generated as output. This automation allows users to complete the process smoothly.

[0628] Step 6:

[0629] The terminal notifies the user of the booking completion. The input is booking completion data from the server, and the output is a notification containing the booking number and travel details. This allows the user to obtain all the information necessary to prepare for their trip. The notification pops up on the screen and includes a link to the details page.

[0630] (Application Example 2)

[0631] 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."

[0632] Traditional travel planning systems made travel suggestions based on simple data input without considering the user's emotions, making it difficult to provide a truly satisfying travel experience. Furthermore, they lacked flexibility, failing to suggest tourist destinations that matched the user's mood in real time.

[0633] 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.

[0634] In this invention, the server includes means for providing a user interface to a terminal for inputting travel preference information and emotional information; means for analyzing the input travel preference information and emotional information and using artificial intelligence to generate multiple travel suggestions; and means for collecting tourist destination information and generating suggestions in real time based on the user's emotions. This enables customized travel suggestions that reflect the user's emotions and tourist destination suggestions that are in line with the user's real-time preferences.

[0635] "Travel preference information" refers to information that allows travelers to specify their expectations and desires, such as destination, duration, budget, and purpose of travel.

[0636] "Emotional information" refers to information about a user's emotional state at a given time, obtained from their facial expressions, tone of voice, and other similar data.

[0637] A "user interface" is the interface on a terminal that a user uses to input information or receive suggestions from a system.

[0638] "Artificial intelligence" is a technology that analyzes large amounts of data and automatically generates appropriate travel suggestions based on the user's wishes and emotions.

[0639] "Tourist information" refers to information about geographical or cultural places that may be of interest to tourists.

[0640] "Generating suggestions in real time" is a process that provides the most suitable suggestions immediately based on the user's current state.

[0641] To implement this invention, the user must first install a dedicated application on a device such as a smartphone or smart glasses. This application provides a user interface for inputting travel preference information and emotional information. The user inputs travel preference information such as destination, purpose of travel, and budget, while emotional information is also acquired through facial expression recognition and voice analysis.

[0642] The device uses its camera and microphone to capture facial expressions and voice, and analyzes emotional states in real time. This information is sent to a server and analyzed by an emotion engine. This process utilizes facial expression recognition libraries such as OpenCV and DeepFace using Python, and TensorFlow for voice analysis. As a result, travel suggestions tailored to the user's emotional state are generated and presented on the device.

[0643] The server uses artificial intelligence to collect and analyze tourist destination information in order to provide customized travel plans based on travel preferences and emotional information. This allows it to suggest the most suitable tourist destinations and activities in real time, tailored to the user's current emotions. For example, if the user wants to relax, it might suggest a quiet park or cafe, and if they are looking for active activities, it might suggest a sports event or a live event.

[0644] For example, if the emotion recognition system determines that a user is in a relaxed state while walking around town, it will suggest a nearby cafe or a quiet park. This allows the user to have a sightseeing experience optimized for their current mood.

[0645] An example of a prompt to input into the generating AI model would be, "My current emotional state is one of relaxation, so please recommend some relaxing tourist spots." This prompt instructs the system to generate the optimal plan based on the user's real-time needs.

[0646] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0647] Step 1:

[0648] The user launches a dedicated application on their device and enters their travel preferences. This includes entering information such as the purpose of the trip, budget, and places they wish to visit into a form. Simultaneously, the device's camera and microphone activate, collecting the user's facial expressions and voice. This data becomes the input information and is converted into digital data as a preprocessing step for facial expression recognition and voice analysis.

[0649] Step 2:

[0650] The device analyzes the collected facial expressions and audio data. Specifically, it uses OpenCV's face detection function and the DeepFace library to analyze the user's emotions. TensorFlow is used to capture tone and intonation from the audio and supplement the emotional information. Through this data processing, an output representing the user's current emotional state is generated.

[0651] Step 3:

[0652] The device sends analyzed emotional information and travel preference information to the server. The server uses artificial intelligence based on the received information to generate travel suggestions. It extracts travel destinations and activities that match the user's emotions from a tourist destination information database and performs data calculations to generate suggestions that are suitable for the user.

[0653] Step 4:

[0654] The server sends the generated travel suggestions to the terminal. The terminal presents the user with multiple suggestions through its display interface. The user selects their preferred travel plan from the displayed suggestions. This selection becomes the input for the next process.

[0655] Step 5:

[0656] Based on the travel plan selected by the user, the server automatically handles the booking process. It accesses multiple external booking services and performs data calculations to select the best price and conditions. The selection results are output as confirmed booking information.

[0657] Step 6:

[0658] The server notifies the terminal that the reservation is complete. The terminal displays the plan details and reservation information to the user and informs them that the necessary procedures have been completed. This ensures that the user has a smooth reservation experience.

[0659] 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.

[0660] 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.

[0661] 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.

[0662] [Fourth Embodiment]

[0663] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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).

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] 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".

[0676] This invention provides a system that allows users to easily plan and book trips. This system takes user requests as input, presents a variety of options based on those requests, and then allows users to book using the most suitable option. The following describes embodiments of the system based on this invention.

[0677] User request input

[0678] Users enter their travel requests using a dedicated application on their device. This interface is intuitive and allows users to input or select parameters such as travel destination, budget, duration, and desired activities.

[0679] Requirements analysis and plan generation

[0680] The server receives information sent by the user and analyzes it using artificial intelligence. This helps to concretize the user's vague requests and generate multiple travel suggestions. The generated suggestions are compiled by referencing various databases and take into account seasonal factors, budget, travel dates, and other considerations.

[0681] Process example

[0682] For example, if a user enters "I want to visit historical sites in Europe during my summer vacation," the server can analyze this request and generate a travel plan for cities in Europe that include historical sites, such as Rome, Athens, or Paris. In addition, it would include details such as accommodations in each city, flight options, and local tours.

[0683] Proposal presentation and selection

[0684] The device visually displays travel suggestions retrieved from the server to the user. Users can compare the details of these suggestions and select the one best suited to their travel plans. Customization of options based on the selected plan is also possible.

[0685] Reservations and notifications

[0686] Based on the selected travel plan, the server initiates the booking process for flights and accommodations. It automatically selects options using multiple online booking services to ensure the best price. This allows users to finalize their ideal travel plan without unnecessary hassle. Once the booking is complete, the user is notified of the details and provided with necessary information via their device.

[0687] This system reduces the complexity and time-consuming processes associated with typical travel planning, allowing users to easily proceed with their travel plans.

[0688] The following describes the processing flow.

[0689] Step 1:

[0690] The user accesses a dedicated application on their device and enters their travel requests. On the interface, the user enters or selects information such as destination, budget, desired dates, and desired activities.

[0691] Step 2:

[0692] The terminal sends the information entered by the user to the server. The data is encrypted and securely transferred to the server.

[0693] Step 3:

[0694] The server analyzes the received information. Using artificial intelligence, it processes the user's input information using natural language and extracts specific travel-related needs. At the same time, it sets search queries based on the entered conditions.

[0695] Step 4:

[0696] The server accesses external travel databases to search for and retrieve travel destinations and itineraries that meet the user's needs. This includes flight information, accommodation options, and local activity options. Taking seasonal factors and current price trends into account, it generates several optimal itineraries.

[0697] Step 5:

[0698] The server sends the generated plan to the device. The device receives it and presents it to the user in a visual format using travel plan comparison tables and maps.

[0699] Step 6:

[0700] The user selects a travel plan of interest from the presented options and enters their selection into the device. The device then sends the selection to the server.

[0701] Step 7:

[0702] The server initiates the booking process based on the travel plan selected by the user. It uses external booking service APIs to check flight and accommodation availability and confirm the booking. It also compares with other services to obtain the lowest price for options.

[0703] Step 8:

[0704] Once the booking is complete, the server sends the booking details to the device. The device receives this and sends a notification to the user. The notification includes information about the booked flight, accommodation details, and planned activities.

[0705] Step 9:

[0706] Users can check notifications through their devices and make additional options or changes as needed. This allows for final confirmation and adjustment of travel plans.

[0707] (Example 1)

[0708] 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".

[0709] Traditional travel planning systems typically required users to spend a significant amount of time and effort inputting information, and subsequent suggestions and booking procedures were often cumbersome. As a result, it was difficult to easily create an ideal travel plan, and price and itinerary optimizations were often not adequately performed.

[0710] 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.

[0711] In this invention, the server includes means for providing an information processing device with a user interface for inputting travel preference information, means for using a machine learning model to analyze the input travel preference information and generate multiple travel suggestions, and means for providing a function for the user to customize the suggested travel plan. This makes it possible for the user to quickly and efficiently select the optimal travel plan and automate the booking process.

[0712] "Travel preference information" refers to information that describes the user's planned travel requirements, such as destination, budget, duration, and desired activities.

[0713] "User interface" refers to the operation screens or tools provided to an information processing device for the user to input or retrieve information.

[0714] A "machine learning model" refers to a computer program that has the ability to automatically learn from data and perform specific tasks.

[0715] "External booking services" refer to third-party platforms or services that provide online booking services, allowing users to book hotels, airline tickets, and other similar items.

[0716] "Means of selecting the optimal price" refers to a process or function that automatically selects the most favorable price from multiple price options based on the given conditions.

[0717] A "prompt" is a sentence that instructs a machine learning model to perform a specific task, and is usually generated based on the input data.

[0718] This invention provides an information processing system that enables users to efficiently plan and book trips. This system is implemented through a process in which users input travel preference information via a user interface on a terminal, send it to a server, and analyze it.

[0719] Upon receiving information, the server uses a generative AI model to analyze the input data. This analysis generates multiple travel suggestions based on the traveler's preferences and conditions. In this process, the server accesses external databases to gather the latest information on accommodations, transportation, activities, etc., and designs the optimal suggestion considering seasonal factors and budget.

[0720] The device presents the generated travel suggestions to the user in a visually easy-to-understand format. The user then compares the suggestions based on this information and selects the plan that interests them. Furthermore, the user can utilize a customization function to adjust the details of the trip to suit their own needs.

[0721] For example, if a user wants to visit historical tourist destinations during their summer vacation, a prompt such as "The user is looking for historical sites for a trip to Europe in the summer of 2023" will be generated. Based on this prompt, the server can use a model to formulate and suggest appropriate tourist destinations and plans.

[0722] Ultimately, the server makes the booking directly based on the selected travel proposal. This process utilizes multiple external booking services and automatically selects the option with the best price and conditions. This allows users to skip complex booking procedures and easily plan and book their trips.

[0723] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0724] Step 1:

[0725] Users enter their travel preferences through a user interface on their device. Input fields include destination, budget, travel duration, and desired activities. This information serves to collect the user's specific travel preferences as digital data. When the user presses the "Submit" button, this data is sent to the server.

[0726] Step 2:

[0727] The server receives travel preference information from the terminal. The received data is first checked for formatting, and then analyzed using a generative AI model. This model generates prompt sentences, taking a sentence like "The user is looking for historical sites for a trip to Europe in the summer of 2023" as input. Using this prompt, the server prepares to generate suggestions that match the user's preferences.

[0728] Step 3:

[0729] The server inputs prompt sentences into a generation AI model, which then generates multiple travel suggestions based on these prompts. During this process, it retrieves information on accommodations, transportation, and tourist attractions from an external travel database. The database is searched based on the analyzed prompt sentences, and a suitable travel plan is constructed. The output is a list of multiple travel suggestions that match the user's criteria.

[0730] Step 4:

[0731] The server sends the proposed travel plans to the device. The device uses this information to present it to the user in a visually easy-to-understand format. The user can scroll through the travel suggestions to review and compare the information. Details such as cost and itinerary are also displayed for each plan. The user chooses the most appealing option from the presented information.

[0732] Step 5:

[0733] Users can further customize their selected travel plan. This step allows them to adjust the length of stay and add or remove specific activities. This interactive process ensures that a travel plan perfectly matches the user's preferences.

[0734] Step 6:

[0735] The server initiates the booking process based on the customized travel plan ultimately selected by the user. This process cross-checks multiple external booking services to select the booking with the best price and conditions. Based on this, the booking is automatically confirmed. The output is the confirmed booking information.

[0736] Step 7:

[0737] Once the booking is complete, the server notifies the user of the information. The device then displays the user's confirmed itinerary, confirmation number, and hotel and flight details. This allows the user to easily understand their entire travel plan and prepare the necessary documents.

[0738] (Application Example 1)

[0739] 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".

[0740] Planning and booking a trip is often cumbersome, requiring the comparison and evaluation of numerous options and information. Furthermore, it's often impossible to receive suggestions for the most suitable tourist destinations and activities based on the user's location. Therefore, there is a need for a system that efficiently plans trips and enhances the travel experience at the destination.

[0741] 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.

[0742] In this invention, the server includes means for providing a terminal with user operation means for inputting travel preference information; means for using intelligent processing to analyze the input travel preference information and generate multiple travel suggestions; means for displaying the generated travel suggestions and making them selectable by the user; and means for providing suggestions based on the user's current location using location information. This enables the user to efficiently plan their trip and obtain an optimal sightseeing experience based on location information.

[0743] "Travel preference information" refers to information in which users specifically express their desires regarding travel, and includes elements such as destination, budget, and duration.

[0744] "User operation means" refers to the general term for interfaces and devices provided for users to input information via a terminal.

[0745] "Intelligent processing" is the process of analyzing input data and generating information to support decision-making, utilizing technologies such as machine learning and artificial intelligence.

[0746] "Display means" refers to devices or software interfaces for providing information to users visually, and includes screens and displays.

[0747] "Location information" refers to data that indicates the user's current location, obtained using a device, and is information that identifies a region based on latitude and longitude.

[0748] "Means of providing suggestions" refers to methods and processes for presenting users with appropriate options and information, thereby encouraging users to make the best choice.

[0749] This invention is implemented as a system that efficiently supports travel planning. The server provides a user operation means for users to input travel preference information from their terminals. This user operation means operates on smartphones and personal computers and has an interface that allows users to intuitively input destinations, budgets, travel itineraries, etc.

[0750] The server uses intelligent processing to analyze travel preference information submitted by users. This intelligent processing employs machine learning algorithms to generate optimal travel suggestions from the database, creating multiple options based on the user's criteria.

[0751] The generated travel suggestions are provided to the user via a display device and are visually presented on a smartphone or screen. Users can compare and consider the suggested travel plans and choose the option that best suits their preferences.

[0752] Furthermore, the server utilizes location information to provide a means of suggesting the latest tourist and event information based on the user's current location. This makes it possible to suggest local events and tourist attractions at travel destinations in real time.

[0753] The booking process is handled by an automated system that collaborates with multiple external booking services to select the best price and complete the booking without requiring manual intervention. Once the booking is complete, the user's device is notified and provided with detailed travel information.

[0754] For example, if a user enters "I want to visit a nearby cultural heritage site next weekend," the server can identify the nearest notable cultural heritage site and instantly suggest a plan including transportation and accommodation. An example of a prompt would be, "Please suggest nearby cultural heritage sites I would like to visit next weekend and generate a travel plan including transportation."

[0755] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0756] Step 1:

[0757] The user enters their travel preferences using a device.

[0758] The input includes travel destination, budget, travel dates, and desired activities. The entered data is sent from the terminal to the server.

[0759] Step 2:

[0760] The server analyzes the received travel preference information.

[0761] In this analysis process, a generative AI model is used to process user input data and extract highly relevant information. Specifically, data processing involves narrowing down possible travel plans based on budget and schedule.

[0762] Step 3:

[0763] The server uses intelligent processing to generate travel suggestions.

[0764] The server uses the analyzed information to create multiple travel plans by referring to a database. Factors such as seasonality, discount information, and popular tourist attractions are taken into consideration during this process.

[0765] Step 4:

[0766] The server sends the generated travel suggestions to the terminal.

[0767] The proposals are formatted for display on the user's device and made presentable as visually organized information.

[0768] Step 5:

[0769] The user reviews and selects a travel suggestion displayed on their device.

[0770] Users can compare the details of the offered plans and select the one that best suits their needs. Their selection is then sent to the server as a user decision.

[0771] Step 6:

[0772] The server will initiate the booking process based on the selected travel plan.

[0773] It integrates with multiple booking services via APIs to automate bookings at the best price and conditions. This process involves data exchange with external systems.

[0774] Step 7:

[0775] The server notifies the terminal that the reservation is complete.

[0776] Finally, confirmation information for the completed reservation is sent to the user's device, and the user is notified so they know that their travel preparations are complete.

[0777] 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.

[0778] This invention provides a travel planning and booking system that takes user emotions into consideration. This system recognizes the user's emotions when they express their travel preferences using an emotion engine, and generates a personalized travel plan.

[0779] User requests and emotional input

[0780] Through a dedicated application on their device, users can input their travel requests and communicate their emotions via facial expression recognition and voice analysis. This emotional input includes data based on peaceful states such as "I need relaxation" and excited states such as "I want to seek adventure."

[0781] Emotion recognition and plan generation

[0782] The server uses an emotion engine to analyze the user's current emotional state. This analysis helps to deeply understand the user's intentions and generate travel plans that match them. For example, a user seeking relaxation might be offered plans involving hot springs or quiet resorts. A user seeking adventure might be offered plans incorporating trekking or active tours.

[0783] Presentation of travel plans

[0784] The device presents users with travel plans optimized based on their emotions. These plans, in addition to standard suggestions, reflect the user's emotional state, offering more personalized options.

[0785] Reservation procedures and notifications

[0786] Based on the selected plan, the server automatically processes the booking at the most optimal price. The emotion engine monitors the user's emotional state during the booking process and provides suggestions and options to reduce burden and stress. Once the booking is complete, the terminal notifies the user of the details and provides necessary information in a timely manner.

[0787] This system allows travelers to incorporate their emotions into their travel plans, resulting in a more personalized travel experience. Furthermore, by streamlining the booking process, it minimizes user anxiety and stress.

[0788] The following describes the processing flow.

[0789] Step 1:

[0790] The user launches a dedicated application on their device and enters their travel preferences and objectives. During this process, the device captures the user's facial expressions with its camera to acquire emotional data and uses its microphone to record voice patterns for emotional analysis from the conversation.

[0791] Step 2:

[0792] The terminal sends text information entered by the user and emotion recognition data to the server. The data includes facial expression recognition information and speech recognition results.

[0793] Step 3:

[0794] The server analyzes the received data and uses an emotion engine to evaluate the user's emotional state. Based on this evaluation, it infers the user's desires from their emotions, such as whether they are looking for a relaxing trip or an adventurous one, and sets a corresponding plan concept.

[0795] Step 4:

[0796] The server searches a diverse travel database and generates travel plans tailored to the user's emotions and preferences. For example, if the emotion of relaxation is recognized, it will generate plans for hot spring resorts and hotels with massages. If it is determined that the user is adventurous, it will create plans that include rafting and safari tours.

[0797] Step 5:

[0798] The server sends the generated travel plans to the device. The device visually organizes these plans and displays them to the user. Each plan lists detailed itineraries, pricing information, and perks.

[0799] Step 6:

[0800] The user reviews the presented plans and selects the one that interests them most. In this selection process, the device utilizes emotion recognition data to provide timely support messages if the user experiences anxiety or hesitation during the selection process.

[0801] Step 7:

[0802] The server executes the necessary booking procedures based on the plan confirmed by the user. The emotion engine also runs during the booking process, providing guidance to alleviate user stress and detecting and responding to situations where additional options can be added.

[0803] Step 8:

[0804] Once the reservation is complete, the server sends details and a completion notification to the device. The device then displays notifications to the user at appropriate times, providing content that reinforces the key points of the plan that the user was particularly interested in.

[0805] In this way, the system takes the user's emotional state into consideration and smoothly supports them from travel planning to booking completion, thereby providing an optimized travel experience for each individual user.

[0806] (Example 2)

[0807] 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".

[0808] Traditional travel plan generation systems offer suggestions based on user preferences and requirements, but they fail to provide travel plans that take into account the user's emotional state. As a result, users often struggle to obtain travel experiences that reflect their inner needs. Furthermore, there were insufficient mechanisms to alleviate stress and anxiety during the booking process.

[0809] 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.

[0810] In this invention, the server includes means for inputting the user's emotional state, means for analyzing the input emotional data and generating travel suggestions that match the user's emotions using artificial intelligence, and means for displaying optimized travel suggestions based on the analyzed emotional data and making them selectable by the user. This makes it possible to provide travel plans that take the user's emotions into consideration and to reduce stress and anxiety during the booking process.

[0811] "User emotional state" refers to data that describes the traveler's specific inner feelings and psychological condition.

[0812] "Analyzing emotional data" is the process of processing information about emotions that has been input and giving it meaning.

[0813] "Generative artificial intelligence" refers to a program that mimics human knowledge and judgment on a computer system, generating and processing data according to specific purposes.

[0814] A "travel suggestion" is a plan that includes suggested travel information tailored to the user's needs and conditions.

[0815] An "optimized travel suggestion" refers to a travel plan that has been adjusted to best suit the user's emotional state and various conditions.

[0816] "Automated booking process" refers to a process where the system proceeds in a way that completes the booking without user intervention.

[0817] "Monitoring emotions" refers to continuously measuring and recording changes in the user's emotional state during the booking process.

[0818] "External booking services" refer to external booking systems or providers that exist outside the system and are used for making travel reservations.

[0819] This invention relates to a system that generates travel suggestions that reflect the user's emotions and automates the booking process. The system mainly consists of the user's terminal, a server, and a working artificial intelligence engine.

[0820] Terminal role

[0821] Users input their travel preferences and current emotions using a dedicated application on their device. Emotion input utilizes facial expression recognition via the camera and voice analysis technology via the microphone. This allows for a deeper understanding of the user's specific needs. For example, if a user smiles at the camera, the emotion "I want to relax" is recognized, and if they input "I want to go to a seaside resort" via voice, this data is collected.

[0822] Server Role

[0823] The server analyzes emotional data transmitted from the terminal. Using an emotional analysis engine, it quantifies the user's emotional state and, based on that data, utilizes a generative AI model to generate a suitable travel plan. The generative AI model learns from accumulated data and can provide travel suggestions that are best suited to the user's emotions.

[0824] The generated travel plans are personalized, reflecting the results of the emotion analysis. Users seeking relaxation will be offered hot spring resort trips, while adventurous users will be suggested trekking tours and similar activities.

[0825] Specific example

[0826] When user A inputs emotional data indicating they "seek relaxation," the server processes it and provides a travel plan to a hot spring resort.

[0827] If user B expresses a desire for an adventure, the server will suggest an active tour in a nature-rich location.

[0828] Example of a prompt

[0829] "Generate travel plan suggestions that are ideal for users seeking relaxation."

[0830] "Please provide active itineraries for adventure-loving users."

[0831] Based on the user's selection, the server automatically connects with external booking services to find the best price and complete the reservation. Finally, the terminal notifies the user of the reservation completion and provides detailed information about the trip. This system allows users to experience a customized trip that perfectly matches their emotions.

[0832] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0833] Step 1:

[0834] Users input their travel preferences and emotional state using a dedicated app on their device. This input utilizes facial expression recognition via the camera and voice analysis via the microphone. If a user smiles, indicating they want to relax, facial expression data is captured. Similarly, if they speak "seaside resort" via voice input, voice data is obtained. This data is then sent to a server.

[0835] Step 2:

[0836] The server analyzes the received emotional data using an emotion engine. The input consists of facial expressions and voice data, which are used to quantify the user's emotional state and obtain analysis results. For example, if the emotional score for "relaxed" is high, a corresponding travel category is identified. This analysis result is then used as the source data for subsequent plan generation.

[0837] Step 3:

[0838] The server uses a generative AI model to generate travel plans based on the analysis results. The input for this step is the result of sentiment analysis, and the optimal travel plan is generated accordingly. For example, if relaxation is requested, a plan including hot springs and beach resorts will be created. The generated plan is stored in a database to be presented to the user.

[0839] Step 4:

[0840] The terminal displays travel plans sent from the server on the screen. The input for this step is travel plan data from the server. The user can review the plans and select the ones that interest them. The screen may list options such as "Hot Spring Resort Plan" or "Tropical Beach Tour," and detailed information can be viewed.

[0841] Step 5:

[0842] Based on the travel plan selected by the user, the server automatically proceeds with the booking process. This process communicates with an external booking service, selecting the most suitable option and completing the reservation. The selected plan is used as input, and the booking details are generated as output. This automation allows users to complete the process smoothly.

[0843] Step 6:

[0844] The terminal notifies the user of the booking completion. The input is booking completion data from the server, and the output is a notification containing the booking number and travel details. This allows the user to obtain all the information necessary to prepare for their trip. The notification pops up on the screen and includes a link to the details page.

[0845] (Application Example 2)

[0846] 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".

[0847] Traditional travel planning systems made travel suggestions based on simple data input without considering the user's emotions, making it difficult to provide a truly satisfying travel experience. Furthermore, they lacked flexibility, failing to suggest tourist destinations that matched the user's mood in real time.

[0848] 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.

[0849] In this invention, the server includes means for providing a user interface to a terminal for inputting travel preference information and emotional information; means for analyzing the input travel preference information and emotional information and using artificial intelligence to generate multiple travel suggestions; and means for collecting tourist destination information and generating suggestions in real time based on the user's emotions. This enables customized travel suggestions that reflect the user's emotions and tourist destination suggestions that are in line with the user's real-time preferences.

[0850] "Travel preference information" refers to information that allows travelers to specify their expectations and desires, such as destination, duration, budget, and purpose of travel.

[0851] "Emotional information" refers to information about a user's emotional state at a given time, obtained from their facial expressions, tone of voice, and other similar data.

[0852] A "user interface" is the interface on a terminal that a user uses to input information or receive suggestions from a system.

[0853] "Artificial intelligence" is a technology that analyzes large amounts of data and automatically generates appropriate travel suggestions based on the user's wishes and emotions.

[0854] "Tourist information" refers to information about geographical or cultural places that may be of interest to tourists.

[0855] "Generating suggestions in real time" is a process that provides the most suitable suggestions immediately based on the user's current state.

[0856] To implement this invention, the user must first install a dedicated application on a device such as a smartphone or smart glasses. This application provides a user interface for inputting travel preference information and emotional information. The user inputs travel preference information such as destination, purpose of travel, and budget, while emotional information is also acquired through facial expression recognition and voice analysis.

[0857] The device uses its camera and microphone to capture facial expressions and voice, and analyzes emotional states in real time. This information is sent to a server and analyzed by an emotion engine. This process utilizes facial expression recognition libraries such as OpenCV and DeepFace using Python, and TensorFlow for voice analysis. As a result, travel suggestions tailored to the user's emotional state are generated and presented on the device.

[0858] The server uses artificial intelligence to collect and analyze tourist destination information in order to provide customized travel plans based on travel preferences and emotional information. This allows it to suggest the most suitable tourist destinations and activities in real time, tailored to the user's current emotions. For example, if the user wants to relax, it might suggest a quiet park or cafe, and if they are looking for active activities, it might suggest a sports event or a live event.

[0859] For example, if the emotion recognition system determines that a user is in a relaxed state while walking around town, it will suggest a nearby cafe or a quiet park. This allows the user to have a sightseeing experience optimized for their current mood.

[0860] An example of a prompt to input into the generating AI model would be, "My current emotional state is one of relaxation, so please recommend some relaxing tourist spots." This prompt instructs the system to generate the optimal plan based on the user's real-time needs.

[0861] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0862] Step 1:

[0863] The user launches a dedicated application on their device and enters their travel preferences. This includes entering information such as the purpose of the trip, budget, and places they wish to visit into a form. Simultaneously, the device's camera and microphone activate, collecting the user's facial expressions and voice. This data becomes the input information and is converted into digital data as a preprocessing step for facial expression recognition and voice analysis.

[0864] Step 2:

[0865] The device analyzes the collected facial expressions and audio data. Specifically, it uses OpenCV's face detection function and the DeepFace library to analyze the user's emotions. TensorFlow is used to capture tone and intonation from the audio and supplement the emotional information. Through this data processing, an output representing the user's current emotional state is generated.

[0866] Step 3:

[0867] The device sends analyzed emotional information and travel preference information to the server. The server uses artificial intelligence based on the received information to generate travel suggestions. It extracts travel destinations and activities that match the user's emotions from a tourist destination information database and performs data calculations to generate suggestions that are suitable for the user.

[0868] Step 4:

[0869] The server sends the generated travel suggestions to the terminal. The terminal presents the user with multiple suggestions through its display interface. The user selects their preferred travel plan from the displayed suggestions. This selection becomes the input for the next process.

[0870] Step 5:

[0871] Based on the travel plan selected by the user, the server automatically handles the booking process. It accesses multiple external booking services and performs data calculations to select the best price and conditions. The selection results are output as confirmed booking information.

[0872] Step 6:

[0873] The server notifies the terminal that the reservation is complete. The terminal displays the plan details and reservation information to the user and informs them that the necessary procedures have been completed. This ensures that the user has a smooth reservation experience.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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.

[0882] 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."

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] The following is further disclosed regarding the embodiments described above.

[0896] (Claim 1)

[0897] A means of providing a terminal with a user interface for entering travel preference information,

[0898] A means of using artificial intelligence to analyze entered travel preference information and generate multiple travel suggestions,

[0899] A means of displaying generated travel suggestions and providing an interface for the user to select from,

[0900] A means of automatically performing the booking procedure based on the selected travel suggestion,

[0901] A means of notifying the user that the reservation has been completed,

[0902] A system that includes this.

[0903] (Claim 2)

[0904] The system according to claim 1, which takes into account seasonal factors, budget, and discount rates in generating travel proposals.

[0905] (Claim 3)

[0906] The system according to claim 1, which includes a function to select the optimal price by using multiple external reservation services in the reservation procedure.

[0907] "Example 1"

[0908] (Claim 1)

[0909] Means for providing an information processing device with a user interface for inputting travel preference information,

[0910] A means of using a machine learning model to analyze input travel preference information and generate multiple travel suggestions,

[0911] A display means for showing generated travel suggestions and allowing the user to select them,

[0912] A method for automatically completing the booking process based on the selected travel suggestions,

[0913] A means of notifying the user that the reservation has been completed,

[0914] A means to provide a function for users to customize the proposed travel plan,

[0915] A method for selecting the optimal price by using multiple external booking services,

[0916] A system that includes this.

[0917] (Claim 2)

[0918] The system according to claim 1, which takes into account seasonal factors, financial planning, and discount rates in generating travel proposals.

[0919] (Claim 3)

[0920] The system according to claim 1, which includes a function to input the generated prompt sentence into a machine learning model to generate travel suggestions.

[0921] "Application Example 1"

[0922] (Claim 1)

[0923] A means of providing a terminal with user operation means for inputting travel preference information,

[0924] A means of using intelligent processing to analyze input travel preference information and generate multiple travel suggestions,

[0925] A display means for showing generated travel suggestions and allowing users to select from them,

[0926] A means of automatically performing the booking procedure based on the selected travel suggestion,

[0927] A means of notifying the user that the reservation has been completed,

[0928] A means of providing suggestions based on the user's current location using location information,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, which, in generating travel suggestions, takes into account time factors, budget, and discount rates, and proposes the most suitable tourist destinations and activities based on the user's location information.

[0932] (Claim 3)

[0933] The system according to claim 1, which includes a function to use multiple external reservation services in the reservation process and select the optimal price and options based on the user's current location.

[0934] "Example 2 of combining an emotion engine"

[0935] (Claim 1)

[0936] A means for inputting the user's emotional state,

[0937] A means of analyzing input emotional data and generating travel suggestions that match the user's emotions using artificial intelligence,

[0938] A means to display optimized travel suggestions based on analyzed sentiment data and allow users to select from them,

[0939] A means of automatically performing the booking procedure based on the selected travel suggestion,

[0940] A means of monitoring the user's emotions during the booking process and providing suggestions and options,

[0941] A means of notifying users when a reservation is complete and providing emotion-based travel information,

[0942] A system that includes this.

[0943] (Claim 2)

[0944] The system according to claim 1, which takes into account seasonal factors, budget, discount rate, and user emotional state in generating travel suggestions.

[0945] (Claim 3)

[0946] The system according to claim 1, which includes a function to select the optimal price by using multiple external reservation services in the reservation procedure.

[0947] "Application example 2 when combining with an emotional engine"

[0948] (Claim 1)

[0949] A means of providing a terminal with a user interface for inputting travel preference information and emotional information,

[0950] A means of using artificial intelligence to analyze input travel preference and sentiment information and generate multiple travel suggestions,

[0951] A means of displaying generated travel suggestions and providing an interface for the user to select from,

[0952] A means of automatically performing the booking procedure based on the selected travel suggestion,

[0953] A means of notifying the user that the reservation has been completed,

[0954] A means of collecting tourist destination information and generating suggestions in real time based on user sentiment,

[0955] A system that includes this.

[0956] (Claim 2)

[0957] The system according to claim 1, which takes into account seasonal factors, budget, and discount rates in generating travel proposals.

[0958] (Claim 3)

[0959] The system according to claim 1, which includes a function to select the optimal price by using multiple external reservation services in the reservation procedure. [Explanation of Symbols]

[0960] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of providing a terminal with user operation means for inputting travel preference information, A means of using intelligent processing to analyze input travel preference information and generate multiple travel suggestions, A display means for showing generated travel suggestions and allowing users to select from them, A means of automatically performing the booking procedure based on the selected travel suggestion, A means of notifying the user that the reservation has been completed, A means of providing suggestions based on the user's current location using location information, A system that includes this.

2. The system according to claim 1, which, in generating travel suggestions, takes into account time factors, budget, and discount rates, and proposes the most suitable tourist destinations and activities based on the user's location information.

3. The system according to claim 1, which includes a function to use multiple external reservation services in the reservation process and select the optimal price and options based on the user's current location.

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