system

Abstract

We provide the system. [Solution] A recognition means for receiving travel conditions from users via voice, A data collection means for searching and obtaining information on tourist resources and accommodation resources via communication means based on the travel conditions of collected users, A schedule generation method that automatically generates and sequences travel itineraries using an AI model based on acquired information, A means for automatically making reservations for tourist attractions and accommodations according to the generated travel itinerary, A display means that notifies the user of automatically generated travel itinerary and reservation information through voice output and visual display, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance 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 making a travel plan, users have to investigate the destination in detail and manually collect information on the availability of accommodation facilities and tourist facilities, which currently requires a great deal of time and effort. In addition, there is also a risk of missing attractive spots at the destination, or making a reservation at a high price or arranging an inappropriate schedule. Due to such problems, it is difficult to execute an efficient and highly satisfactory travel plan.

Means for Solving the Problems

[0005] This invention provides a system in which a generating AI model automatically collects regional information and creates an optimal travel schedule tailored to the user's preferences, based on the user's input of travel conditions. This enables automated reservations based on information on tourist facilities and accommodations, resulting in efficient and hassle-free travel planning. In particular, it aims to eliminate inconveniences in travel planning by providing users with suitable options through reservations using an interface with partner facilities.

[0006] A "user" refers to an individual or group that plans a trip and enters travel conditions through this system.

[0007] "Travel conditions" refer to information such as destination, travel itinerary, budget, and interests that users enter when planning a trip.

[0008] "Collection means" refers to a component that has the function of searching for and obtaining information on tourist facilities and accommodations based on the travel conditions entered by the user.

[0009] A "generative AI model" refers to artificial intelligence technology that automatically generates an appropriate travel schedule based on travel conditions and collected information.

[0010] A "schedule generation means" is a component that has the function of creating a travel schedule using a generation AI model.

[0011] A "reservation processing means" is a component that has the function of automatically executing reservations for tourist facilities and accommodations based on the generated travel schedule.

[0012] A "notification display means" is a component that has a display function for conveying automatically generated travel schedules and reservation information to the user.

[0013] "External interface" refers to the means of communication used to exchange information with partner facilities when processing reservations. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a labeled 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.

[0018] In the following embodiments, a labeled RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a labeled 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, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system for efficiently planning travel and providing users with the optimal travel experience. This system is implemented using multiple means. First, the user inputs their travel conditions into a terminal. These conditions include destination, travel dates, budget, interests, etc. The input interface is designed to process this data quickly.

[0036] Next, the server searches a database of affiliated tourist facilities and accommodations based on the travel conditions entered by the user, and also collects relevant information from the internet. What is important here is that this information collection is carried out efficiently and comprehensively, and that the latest tourist information and availability can be obtained.

[0037] Subsequently, the server automatically generates a travel schedule, or "travel itinerary," based on the user's interests, using the collected information via a generative AI model. This AI model considers multiple variables to select the most suitable destinations and optimize the itinerary for the user. For example, for a user interested in history and culture, it generates a schedule incorporating temples and museums selected as destinations.

[0038] Next, the server automatically executes reservations with partner facilities using an external interface based on the generated bookmark. This eliminates the need for users to individually manage multiple reservation sites, allowing for efficient, one-stop reservation completion.

[0039] Finally, the device displays the automatically generated travel schedule and booking information to the user. This allows the user to see the entire plan at a glance and make manual adjustments if necessary.

[0040] As an example, consider a scenario where a user plans a four-day trip to Kyoto. The user inputs the conditions: "cultural experience," "budget of 150,000 yen," and "two people." The server selects historical and cultural sites worth visiting and creates a travel schedule, such as "Kiyomizu-dera Temple and Kinkaku-ji Temple" on day one and "Arashiyama and Fushimi Inari Taisha Shrine" on day two, and automatically makes reservations for the accompanying accommodations. The terminal displays the generated schedule, allowing the user to check the details and ensure a satisfying trip.

[0041] Thus, this invention utilizes advanced data processing and AI technology to create a system that significantly reduces the effort required from users while providing a highly satisfying travel experience.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The user enters travel conditions such as destination, itinerary, budget, and interests into the terminal's input interface. The terminal formats the entered data and generates a request to send to the server.

[0045] Step 2:

[0046] The server searches a database of affiliated tourist facilities and accommodations based on the travel conditions received from the user, and retrieves information on available facilities that match the conditions. At the same time, it also obtains the latest tourist events and review ratings by collecting relevant information from the internet using a crawler.

[0047] Step 3:

[0048] The server uses an AI model generated based on collected facility information and user input conditions to create a travel schedule optimized for the user. In this process, the AI ​​model determines the priority of destinations based on the user's interests and proposes a schedule that considers efficient travel routes.

[0049] Step 4:

[0050] Based on the generated travel schedule, the server sends booking requests via API to partner facilities and service providers, automatically executing the necessary reservations for accommodations and activities. The server confirms the success of the booking and records this fact.

[0051] Step 5:

[0052] The server compiles all reservation statuses and generated bookmarks, and creates a package that notifies the user. This information includes details of the reservations made and is sent to the terminal.

[0053] Step 6:

[0054] The device displays the notified travel schedule and booking details on the user interface. Users can review this information and make manual corrections or additional requests as needed. They can also easily review the entire travel schedule, ensuring that their travel plans are efficiently constructed.

[0055] (Example 1)

[0056] 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."

[0057] When planning a trip, users often find it difficult to create an optimal travel schedule that suits their needs from a vast amount of information. Furthermore, booking individual facilities and services is time-consuming and complicated, making travel preparation extremely cumbersome.

[0058] 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.

[0059] In this invention, the server includes means including an information input device, means including a data acquisition device, and means including a schedule creation device. This allows users to easily input conditions and enables the automatic generation of an optimal travel schedule and comprehensive booking processing based on those conditions.

[0060] An "information input device" is a means of providing an interface that allows users to easily input travel conditions.

[0061] A "data acquisition device" is a means of collecting and providing information on tourist destinations and accommodations based on the user's travel conditions.

[0062] A "schedule creation device" is a means of automatically creating a travel plan using a generation AI model based on acquired information.

[0063] A "reservation processing device" is a means of automatically executing reservations for affiliated tourist destinations and facilities via external communication methods, according to the generated travel plan.

[0064] A "notification device" is a means of visually presenting automatically generated travel plans and reservation information to the user.

[0065] This invention is a system that enables users to efficiently plan their trips and provides them with an optimal travel experience. This system is implemented primarily through various means, including servers, terminals, and users.

[0066] First, the user enters their travel details into the terminal. The terminal provides a particularly user-friendly interface, allowing users to easily input their destination, travel dates, budget, interests, and other information. The software used is an input assistance tool based on advanced UI design.

[0067] Next, the server uses an information input device to collect information on partner tourist facilities and accommodations based on the conditions entered by the user, using a data acquisition device. Data collection is carried out via the internet or internal company APIs. Here, the server uses state-of-the-art information update technology to obtain the latest tourist information and facility availability.

[0068] Furthermore, the server utilizes a generative AI model to analyze the collected information and automatically generate travel schedules based on the user's interests. The generative AI model used integrates historical data with real-time information and creates schedules using optimization algorithms. An example of a prompt message is, "Please suggest a travel schedule that emphasizes cultural experiences within the budget."

[0069] Next, the server utilizes the reservation processing unit to automatically execute reservations with partner facilities via external communication methods, based on the generated schedule. This process eliminates the need for users to visit multiple reservation sites, enabling centralized reservation management.

[0070] Ultimately, the device visually presents the automatically generated travel schedule and booking information to the user via a notification device. This allows the user to grasp the entire travel plan at a glance and adjust the schedule as needed.

[0071] This invention significantly reduces the time and effort users spend creating complex travel plans, resulting in a more satisfying travel experience.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user enters their travel conditions into the terminal. This includes destination, travel dates, budget, interests, and other details. The terminal provides a user-friendly interface to reduce the effort required for input. The user's conditions are then digitized and used for subsequent processing. The input data is sent to the server as a request.

[0075] Step 2:

[0076] The server receives data entered by the user and uses a data acquisition device to collect information on tourist destinations and accommodations from external databases and the internet. This information collection efficiently obtains current availability and the latest tourist information via APIs. The acquired data is then used for analysis by an AI model in the next step.

[0077] Step 3:

[0078] The server uses a generative AI model to automatically generate a travel schedule tailored to the user's interests based on the collected information. The prompt used is, "Please select the main tourist attractions at your destination, prioritizing cultural experiences." The AI ​​model analyzes the input data and outputs candidate travel plans best suited to the user. As a result, an AI-adjusted schedule is created.

[0079] Step 4:

[0080] The server uses the generated travel plan schedule to automatically execute reservations at partner facilities via external communication methods using a reservation processing unit. Specifically, it accesses the reservation API of each facility, inputs the necessary reservation information, and obtains a reservation confirmation. This eliminates the need for users to make individual reservations.

[0081] Step 5:

[0082] The terminal receives the generated schedule and reservation information sent from the server and displays it to the user. This display allows the user to see the overall picture of the trip and make changes to the schedule on the terminal if necessary. The user can then make final confirmations based on the displayed information and prepare for the trip.

[0083] (Application Example 1)

[0084] 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."

[0085] Planning a trip can be burdensome for users, as it requires organizing a lot of information. Furthermore, the time-consuming process of individual bookings and information searches hinders efficient travel planning. There is a growing need to provide users with a more intuitive interface through voice control.

[0086] 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.

[0087] In this invention, the server includes recognition means for receiving travel conditions from the user by voice, data collection means for searching and acquiring information on tourist and accommodation resources via communication means based on the collected travel conditions of the user, and schedule generation means for automatically generating and ordering a travel itinerary using a generation AI model based on the acquired information. This enables efficient and intuitive travel planning through voice control.

[0088] "Recognition means" refers to a technological device that receives travel conditions from the user as voice data and converts that voice data into text data.

[0089] "Communication means" refers to network connection devices used to acquire information on tourism and accommodation resources from external databases for the purpose of data collection.

[0090] A "schedule generation method" is a processor that uses a generation AI model based on acquired information to automatically generate a travel itinerary and determine the optimal order.

[0091] A "display means" is a device that notifies the user of automatically generated travel itineraries and reservation information via voice output or screen display.

[0092] The system for implementing the present invention is configured as a voice-controlled travel planning assistant. The server collects travel conditions as input data from the user through speech recognition technology. Specifically, it analyzes the user's voice information using the Google® Speech-to-Text API and converts the travel conditions into text format.

[0093] This text data is transmitted via communication to a data collection module on the server. This module searches external databases related to tourism and accommodation resources via the internet and collects the latest relevant information.

[0094] Next, the server uses a generative AI model based on the acquired information to create a travel itinerary that reflects the user's interests. This generative AI model employs OpenAI's GPT model, among others, enabling the automatic construction of the itinerary schedule. For example, if the user inputs the prompt, "I want to visit tourist spots with my family next weekend," the AI ​​model will consider popular tourist destinations and generate an optimal order of visits and timetable.

[0095] The generated travel itinerary and booking information are notified to the user's device via visual display and audio output. Google Text-to-Speech technology is used to provide information as audio or display it on the screen. Users can review this information and take further action using voice commands.

[0096] For example, if you use a prompt like, "We want to take a day trip with four people this weekend and visit some tourist attractions," the system will select appropriate spots and automatically generate a travel plan. This process allows users to efficiently prepare for their trip.

[0097] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0098] Step 1:

[0099] The user inputs their travel preferences via voice. A speech recognition module uses the Google Speech-to-Text API to convert this input voice into text data. The output is text data indicating the user's travel conditions. Specifically, a microphone device is used to collect the user's speech.

[0100] Step 2:

[0101] The user sends text data to the server. The server uses this data to search external databases of tourist and accommodation resources via communication. The input is the user's text data, used as a search query for the external database. The output is tourist and accommodation resource information as search results. Specifically, data is exchanged between the server and the database via an internet connection.

[0102] Step 3:

[0103] The server processes the acquired tourist resource information and accommodation resource information, inputs it into a generating AI model, and generates a travel itinerary. The inputs are tourist resource information, accommodation resource information, and user interest information. Using a generating AI model (such as OpenAI's GPT model), it outputs a travel itinerary including places to visit and a time schedule. Specifically, it supplies data to the model, performs processing, and automatically generates the optimal travel plan.

[0104] Step 4:

[0105] The server provides the generated travel itinerary and booking information to the terminal. The output is travel itinerary information displayed both audibly and visually. Specifically, it is provided as audio using Google Text-to-Speech, and the travel itinerary is visually displayed to the user using the display.

[0106] Step 5:

[0107] The user reviews the travel plan and makes modifications as needed. Details can be adjusted using voice commands or touch controls. The output is the final travel plan. Specifically, the user sends feedback and modification instructions to the server via their device.

[0108] 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.

[0109] This invention provides a novel system that recognizes a user's emotions and optimizes travel plans based on them. First, when a user inputs travel conditions, the terminal acquires text or voice data using an input interface. At this stage, an emotion engine is incorporated and analyzes the user's current emotional state from their writing and tone of voice. For example, if the user inputs "excited," the system recognizes a positive emotion.

[0110] Next, the server accesses a database of partner tourist attractions and accommodations, including the user's emotional data, to collect available information. The emotional engine uses the collected emotional data to generate a travel schedule best suited to the user's experience. In this process, if the user's emotions are negative, the AI ​​model adjusts to prioritize relaxing tourist destinations and activities.

[0111] The server provides a flexible plan along with the generated travel schedule, including options that respond to changes in the user's emotions. For example, if the user is feeling stressed, it might recommend visiting natural tourist spots or relaxing hot springs.

[0112] Subsequently, the server utilizes an emotion engine to automatically confirm reservations for suggested destinations and accommodations via an external interface. These reservations are made considering the user's emotional state, taking into account the time and location that aligns with their mood.

[0113] Finally, the device displays the generated travel schedule and booking information in a warm, user-friendly interface that responds to the user's emotions. This allows the user to feel confident about the entire travel plan and begin a satisfying trip.

[0114] For example, suppose a user plans a special relaxation trip for the weekend. The emotion engine recognizes that the user is a little tired, and therefore the AI ​​suggests a stay at a quiet resort, generates a schedule incorporating yoga and spa experiences, and makes the relevant reservations. The schedule displayed on the device is then confirmed as a plan that will provide the user with peace of mind.

[0115] This system provides a personalized experience based on the user's emotions, supporting travel preparations in a more user-centric way.

[0116] The following describes the processing flow.

[0117] Step 1:

[0118] The user begins planning a trip, entering travel conditions such as destination, dates, budget, and interests. The device collects this information and uses an emotion engine to analyze the user's current emotional state from their input and voice. For example, if the user enters something like "I want to have a fun trip," it is recognized as a positive emotion.

[0119] Step 2:

[0120] The terminal sends the entered travel conditions and analyzed sentiment data to the server. Based on the received information, the server searches a database of partner tourist facilities and accommodations and retrieves information that matches the conditions. The sentiment data here influences the search algorithm, prioritizing the selection of fun or relaxing places that match the user's current mood.

[0121] Step 3:

[0122] The server uses a generative AI model to generate a travel schedule based on acquired facility information and emotional data. In this process, the AI ​​model optimizes destinations based on the user's emotions and incorporates activities and experiences tailored to their emotional state. If the user is feeling stressed, it suggests relaxation programs such as healing spots, fitness classes, or yoga.

[0123] Step 4:

[0124] The server processes bookings according to the generated travel schedule. If the emotion engine determines that adjustments to bookings are needed for specific times or locations, bookings that meet those conditions are automatically made through an external interface. For example, a spa booking might be scheduled for the evening to provide a relaxing environment.

[0125] Step 5:

[0126] The server compiles the final travel schedule and completed booking information and sends it to the terminal. It may also provide additional advice and supplementary information based on emotional responses, suggesting them to the user.

[0127] Step 6:

[0128] The device uses notification displays to provide a warm and welcoming experience, employing designs and language tailored to the user's emotional state, guiding them to review their travel plans. By viewing the displayed schedule, users can prepare for departure with a sense of calm and renewed anticipation for their trip.

[0129] In this way, the entire system is designed to optimize planning around the user's emotions, resulting in a more fulfilling travel experience.

[0130] (Example 2)

[0131] 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".

[0132] When planning a trip, there is a challenge in creating optimal travel plans for users because information and schedules are not adequately provided that take into account the impact of users' emotions on the travel experience. Conventional systems do not reflect emotions in planning, making it difficult to increase user satisfaction.

[0133] 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.

[0134] In this invention, the server includes data collection means, emotion analysis means, and information acquisition means. This makes it possible to automatically generate a travel schedule that takes the user's emotions into consideration.

[0135] "Data collection means" refers to a device or software that receives travel conditions from users and records that information in digital format.

[0136] An "emotion analysis system" is a system that identifies emotional states using natural language processing and speech recognition technologies based on data collected from users.

[0137] "Information acquisition means" refers to a device or program that retrieves information about tourist facilities and accommodations from an external database based on analyzed sentiment data.

[0138] A "schedule generation method" is a device or software that performs the process of automatically creating a travel schedule using a generation AI model based on acquired information and sentiment data.

[0139] A "reservation processing system" is a system that automatically executes reservations for tourist facilities and accommodations based on a generated travel schedule, via an external connection.

[0140] A "notification display means" is a device or software that visually displays automatically generated travel schedules and reservation information in a manner that takes into consideration the user's feelings.

[0141] To implement this invention, it is necessary to construct a system that integrates emotion recognition and travel planning optimization. This system generates an optimal travel schedule and automatically makes reservations based on the user's travel conditions and emotional state. The system configuration and the technologies used are described in detail below.

[0142] At the heart of the system is a terminal for collecting data and analyzing emotions. Users input travel details through the terminal, which are captured as text or audio data. This data is sent to software that functions as an emotion analysis tool, where natural language processing techniques are used to analyze emotional states. Audio data is converted to text by dedicated speech recognition software.

[0143] The acquired sentiment data and travel condition data are processed by the server. The server retrieves appropriate tourist facilities and accommodation information from an external database via an information acquisition mechanism. SQL queries are used in this process to efficiently extract the necessary information.

[0144] The server then utilizes a schedule generation mechanism to automatically create a travel schedule using a generating AI model. Based on the prompt text, the AI ​​model generates an optimized plan from the collected information and analyzed sentiment data. In this plan, active activities are appropriately selected for positive emotions, and relaxing activities are appropriately selected for negative emotions.

[0145] For example, when a user plans a special trip seeking relaxation, the emotion engine recognizes that the user is fatigued. In this case, the AI ​​suggests a schedule that includes a stay at a quiet resort and yoga and spa experiences, and arranges the bookings. A specific example of a prompt might be, "The user is seeking relaxation. Please plan a trip that includes yoga and spa treatments in a quiet location to help them recover from fatigue."

[0146] Finally, the device uses notification display methods to show travel schedules and booking information in a way that is sensitive to the user's emotions. The user interface employs a warm design, aiming to make the overall travel experience more satisfying. This system design allows users to enjoy an emotionally-based, personalized travel experience.

[0147] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0148] Step 1:

[0149] The user enters travel requirements into the terminal. Input can be done as text or voice data. In the case of voice input, the terminal uses speech recognition software to convert the voice to text. The entered data is sent to the server by a data collection system.

[0150] Step 2:

[0151] The terminal sends the input data to the sentiment analysis device. The sentiment analysis device uses natural language processing technology to analyze the user's emotional state from the text or converted audio data. The output of this analysis is data indicating the user's emotional state, and may be labeled, for example, as "positive" or "negative."

[0152] Step 3:

[0153] The server receives the emotional data obtained through analysis and uses information acquisition tools to retrieve information on suitable tourist destinations and accommodations from an external database. Here, SQL queries are used to identify candidates based on emotional state and travel conditions. The output is a list of relevant facilities and tourist destinations.

[0154] Step 4:

[0155] The server utilizes a schedule generation mechanism to input prompt messages into the AI ​​model. These prompt messages might take the form of, for example, "The user is seeking relaxation; please plan a trip that includes yoga and spa treatments in a quiet location." Based on this, the AI ​​model automatically generates an optimal travel schedule using the input facility information and sentiment data. The schedule includes the order of visits and specific activities.

[0156] Step 5:

[0157] The server automatically makes reservations for tourist attractions and facilities via external connections, using a reservation processing mechanism according to the generated travel schedule. An API is used, and reservations are confirmed and completed in real time. As a result, reservation information that matches the schedule is output.

[0158] Step 6:

[0159] The device uses notification display methods to show the user their travel schedule and booking information. The display design is thoughtfully tailored to the user's emotional state and is designed to be visually pleasing. This display allows the user to review the entire plan and proceed with travel preparations.

[0160] (Application Example 2)

[0161] 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".

[0162] In modern times, travel planning has become complex due to the wide range of options and vast amounts of information available. Furthermore, it is difficult to automatically create and flexibly adapt travel plans optimized to the individual emotions and interests of travelers. Conventional systems often provide uniform plans without adequately considering travelers' emotions and individual needs, resulting in outcomes that do not maximize traveler satisfaction. This invention aims to solve these problems and provide travelers with individually optimized travel planning.

[0163] 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.

[0164] In this invention, the server includes information gathering means for receiving travel conditions from users, data gathering means for searching and obtaining information on tourist facilities and accommodations based on the collected travel conditions and emotional state of the users, schedule generation means for automatically generating a travel schedule using a generation AI model based on the acquired information and emotional data, reservation processing means for automatically executing reservations for tourist facilities and accommodations in conjunction with current information and environmental data, and notification display means for displaying the automatically generated travel schedule and reservation information in an interface that takes into account the user's emotions. This makes it possible to provide personalized travel plans based on the traveler's emotions and interests, thereby increasing the flexibility and satisfaction of the planning.

[0165] "Information gathering means" refers to input devices and software used to obtain travel conditions and emotional states from users.

[0166] "Data collection means" refers to devices or processes that collect information on tourist facilities and accommodations from a database based on acquired travel conditions and emotional states.

[0167] A "generative AI model" refers to artificial intelligence technology that analyzes acquired data and automatically creates an appropriate travel schedule.

[0168] "Schedule generation method" refers to the process of automatically creating an optimal schedule based on the user's travel purpose and emotions using a generation AI model.

[0169] "Reservation processing means" refers to devices or programs that automatically make reservations for tourist facilities and accommodations based on a generated travel schedule, taking into account current events and environmental data.

[0170] "Notification display means" refers to a method of displaying generated travel schedules and reservation information on the device in a way that takes the user's feelings into consideration.

[0171] "Emotional state" refers to information that indicates a user's psychological condition or mood, and is data obtained through voice, text, etc.

[0172] This invention is a system that generates travel plans based on the user's emotional state. This system primarily runs on devices such as smartphones and is supported by algorithms on a cloud server. The device acquires travel conditions, voice, and text data from the user. Smartphone hardware such as microphones and cameras are used for information gathering, and sentiment analysis tools such as the Google Cloud Natural Language API are employed for natural language processing.

[0173] Data collected by the device is sent to a cloud server via the internet. The server searches for and retrieves information on tourist facilities and accommodations based on the user's emotional state and travel conditions. Data retrieval is managed by a database system on Amazon Web Services (AWS®), and the generating AI model utilizes machine learning frameworks such as TENSORFLOW® and PyTorch to automatically generate travel schedules.

[0174] The schedule generation system analyzes collected information and emotional data to create a travel plan that includes the most suitable destinations and activities for the user. The generated schedule provides flexible planning that can accommodate future changes in emotions. It also takes current events and environmental data into consideration to proceed with the optimal schedule and booking process.

[0175] For example, if a user enters "I'm looking for a new experience," the system recognizes this feeling as a positive sense of adventure and suggests art exhibitions or new restaurants in the city. Reservations are automatically made with the relevant facilities, and the results are displayed on the terminal with an interface that takes the user's feelings into consideration.

[0176] An example of a prompt to input into the generating AI model is: "The user wants to have a new experience this weekend. Analyze their emotions and suggest the best travel plan for them. Please include information on local events in the plan and handle the arrangements."

[0177] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0178] Step 1:

[0179] The device collects travel conditions and emotional states from the user. Voice and text are used as input, and this data is analyzed for emotion and text using the Google Cloud Natural Language API, with the results obtained as output. This analysis identifies the user's current emotional state.

[0180] Step 2:

[0181] The data analyzed on the terminal is sent to the server via the internet. The server searches for information on tourist facilities and accommodations in a database on AWS based on the received emotional data and travel conditions. It collects data that matches the entered travel conditions and emotional state and provides the results as output.

[0182] Step 3:

[0183] The server uses the acquired information to automatically generate travel schedules using a generative AI model. It utilizes tourist facility data, accommodation data, and sentiment analysis results as inputs, performs schedule calculations based on these, and outputs an optimized schedule.

[0184] Step 4:

[0185] The server processes bookings based on the generated travel schedule, taking into account current events and environmental data. Bookings are automatically executed via an external interface, thereby providing a travel experience tailored to the user. The booking results are returned to the user as output.

[0186] Step 5:

[0187] The device receives schedule and reservation information from the server. This data is displayed through a user-friendly interface. The final output is a customized travel plan provided to the user.

[0188] 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.

[0189] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0190] 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.

[0191] [Second Embodiment]

[0192] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0193] 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.

[0194] 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).

[0195] 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.

[0196] 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.

[0197] 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).

[0198] 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.

[0199] 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.

[0200] 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.

[0201] 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.

[0202] 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.

[0203] 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".

[0204] This invention is a system for efficiently planning travel and providing users with the optimal travel experience. This system is implemented using multiple means. First, the user inputs their travel conditions into a terminal. These conditions include destination, travel dates, budget, interests, etc. The input interface is designed to process this data quickly.

[0205] Next, the server searches a database of affiliated tourist facilities and accommodations based on the travel conditions entered by the user, and also collects relevant information from the internet. What is important here is that this information collection is carried out efficiently and comprehensively, and that the latest tourist information and availability can be obtained.

[0206] Subsequently, the server automatically generates a travel schedule, or "travel itinerary," based on the user's interests, using the collected information via a generative AI model. This AI model considers multiple variables to select the most suitable destinations and optimize the itinerary for the user. For example, for a user interested in history and culture, it generates a schedule incorporating temples and museums selected as destinations.

[0207] Next, the server automatically executes reservations with partner facilities using an external interface based on the generated bookmark. This eliminates the need for users to individually manage multiple reservation sites, allowing for efficient, one-stop reservation completion.

[0208] Finally, the device displays the automatically generated travel schedule and booking information to the user. This allows the user to see the entire plan at a glance and make manual adjustments if necessary.

[0209] As an example, consider a scenario where a user plans a four-day trip to Kyoto. The user inputs the conditions: "cultural experience," "budget of 150,000 yen," and "two people." The server selects historical and cultural sites worth visiting and creates a travel schedule, such as "Kiyomizu-dera Temple and Kinkaku-ji Temple" on day one and "Arashiyama and Fushimi Inari Taisha Shrine" on day two, and automatically makes reservations for the accompanying accommodations. The terminal displays the generated schedule, allowing the user to check the details and ensure a satisfying trip.

[0210] Thus, this invention utilizes advanced data processing and AI technology to create a system that significantly reduces the effort required from users while providing a highly satisfying travel experience.

[0211] The following describes the processing flow.

[0212] Step 1:

[0213] The user enters travel conditions such as destination, itinerary, budget, and interests into the terminal's input interface. The terminal formats the entered data and generates a request to send to the server.

[0214] Step 2:

[0215] The server searches a database of affiliated tourist facilities and accommodations based on the travel conditions received from the user, and retrieves information on available facilities that match the conditions. At the same time, it also obtains the latest tourist events and review ratings by collecting relevant information from the internet using a crawler.

[0216] Step 3:

[0217] The server uses an AI model generated based on collected facility information and user input conditions to create a travel schedule optimized for the user. In this process, the AI ​​model determines the priority of destinations based on the user's interests and proposes a schedule that considers efficient travel routes.

[0218] Step 4:

[0219] Based on the generated travel schedule, the server sends booking requests via API to partner facilities and service providers, automatically executing the necessary reservations for accommodations and activities. The server confirms the success of the booking and records this fact.

[0220] Step 5:

[0221] The server compiles all reservation statuses and generated bookmarks, and creates a package that notifies the user. This information includes details of the reservations made and is sent to the terminal.

[0222] Step 6:

[0223] The device displays the notified travel schedule and booking details on the user interface. Users can review this information and make manual corrections or additional requests as needed. They can also easily review the entire travel schedule, ensuring that their travel plans are efficiently constructed.

[0224] (Example 1)

[0225] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0226] When planning a trip, users often find it difficult to create an optimal travel schedule that suits their needs from a vast amount of information. Furthermore, booking individual facilities and services is time-consuming and complicated, making travel preparation extremely cumbersome.

[0227] 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.

[0228] In this invention, the server includes means including an information input device, means including a data acquisition device, and means including a schedule creation device. This allows users to easily input conditions and enables the automatic generation of an optimal travel schedule and comprehensive booking processing based on those conditions.

[0229] An "information input device" is a means of providing an interface that allows users to easily input travel conditions.

[0230] A "data acquisition device" is a means of collecting and providing information on tourist destinations and accommodations based on the user's travel conditions.

[0231] A "schedule creation device" is a means of automatically creating a travel plan using a generation AI model based on acquired information.

[0232] A "reservation processing device" is a means of automatically executing reservations for affiliated tourist destinations and facilities via external communication methods, according to the generated travel plan.

[0233] A "notification device" is a means of visually presenting automatically generated travel plans and reservation information to the user.

[0234] This invention is a system that enables users to efficiently plan their trips and provides them with an optimal travel experience. This system is implemented primarily through various means, including servers, terminals, and users.

[0235] First, the user enters their travel details into the terminal. The terminal provides a particularly user-friendly interface, allowing users to easily input their destination, travel dates, budget, interests, and other information. The software used is an input assistance tool based on advanced UI design.

[0236] Next, the server uses an information input device to collect information on partner tourist facilities and accommodations based on the conditions entered by the user, using a data acquisition device. Data collection is carried out via the internet or internal company APIs. Here, the server uses state-of-the-art information update technology to obtain the latest tourist information and facility availability.

[0237] Furthermore, the server utilizes a generative AI model to analyze the collected information and automatically generate travel schedules based on the user's interests. The generative AI model used integrates historical data with real-time information and creates schedules using optimization algorithms. An example of a prompt message is, "Please suggest a travel schedule that emphasizes cultural experiences within the budget."

[0238] Next, the server utilizes the reservation processing unit to automatically execute reservations with partner facilities via external communication methods, based on the generated schedule. This process eliminates the need for users to visit multiple reservation sites, enabling centralized reservation management.

[0239] Ultimately, the device visually presents the automatically generated travel schedule and booking information to the user via a notification device. This allows the user to grasp the entire travel plan at a glance and adjust the schedule as needed.

[0240] This invention significantly reduces the time and effort users spend creating complex travel plans, resulting in a more satisfying travel experience.

[0241] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0242] Step 1:

[0243] The user enters their travel conditions into the terminal. This includes destination, travel dates, budget, interests, and other details. The terminal provides a user-friendly interface to reduce the effort required for input. The user's conditions are then digitized and used for subsequent processing. The input data is sent to the server as a request.

[0244] Step 2:

[0245] The server receives data entered by the user and uses a data acquisition device to collect information on tourist destinations and accommodations from external databases and the internet. This information collection efficiently obtains current availability and the latest tourist information via APIs. The acquired data is then used for analysis by an AI model in the next step.

[0246] Step 3:

[0247] The server uses a generative AI model to automatically generate a travel schedule tailored to the user's interests based on the collected information. The prompt used is, "Please select the main tourist attractions at your destination, prioritizing cultural experiences." The AI ​​model analyzes the input data and outputs candidate travel plans best suited to the user. As a result, an AI-adjusted schedule is created.

[0248] Step 4:

[0249] The server uses the generated travel plan schedule to automatically execute reservations at partner facilities via external communication methods using a reservation processing unit. Specifically, it accesses the reservation API of each facility, inputs the necessary reservation information, and obtains a reservation confirmation. This eliminates the need for users to make individual reservations.

[0250] Step 5:

[0251] The terminal receives the generated schedule and reservation information sent from the server and displays it to the user. This display allows the user to see the overall picture of the trip and make changes to the schedule on the terminal if necessary. The user can then make final confirmations based on the displayed information and prepare for the trip.

[0252] (Application Example 1)

[0253] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0254] Planning a trip can be burdensome for users, as it requires organizing a lot of information. Furthermore, the time-consuming process of individual bookings and information searches hinders efficient travel planning. There is a growing need to provide users with a more intuitive interface through voice control.

[0255] 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.

[0256] In this invention, the server includes recognition means for receiving travel conditions from the user by voice, data collection means for searching and acquiring information on tourist and accommodation resources via communication means based on the collected travel conditions of the user, and schedule generation means for automatically generating and ordering a travel itinerary using a generation AI model based on the acquired information. This enables efficient and intuitive travel planning through voice control.

[0257] "Recognition means" refers to a technological device that receives travel conditions from the user as voice data and converts that voice data into text data.

[0258] "Communication means" refers to network connection devices used to acquire information on tourism and accommodation resources from external databases for the purpose of data collection.

[0259] A "schedule generation method" is a processor that uses a generation AI model based on acquired information to automatically generate a travel itinerary and determine the optimal order.

[0260] A "display means" is a device that notifies the user of automatically generated travel itineraries and reservation information via voice output or screen display.

[0261] The system for implementing the present invention is configured as a voice-controlled travel planning assistant. The server collects travel conditions as input data from the user through speech recognition technology. Specifically, it analyzes the user's voice information using the Google Speech-to-Text API and converts the travel conditions into text format.

[0262] This text data is transmitted via communication to a data collection module on the server. This module searches external databases related to tourism and accommodation resources via the internet and collects the latest relevant information.

[0263] Next, the server uses a generative AI model based on the acquired information to create a travel itinerary that reflects the user's interests. This generative AI model employs OpenAI's GPT model, among others, which enables the automatic construction of the itinerary schedule. For example, if the user inputs the prompt, "I want to visit tourist spots with my family next weekend," the AI ​​model will consider popular tourist destinations and generate an optimal order of visits and timetable.

[0264] The generated travel itinerary and booking information are notified to the user's device via visual display and audio output. Google Text-to-Speech technology is used to provide information as audio or display it on the screen. Users can review this information and take further action using voice commands.

[0265] For example, if you use a prompt like, "We want to take a day trip with four people this weekend and visit some tourist attractions," the system will select appropriate spots and automatically generate a travel plan. This process allows users to efficiently prepare for their trip.

[0266] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0267] Step 1:

[0268] The user inputs their travel preferences via voice. A speech recognition module uses the Google Speech-to-Text API to convert this input voice into text data. The output is text data indicating the user's travel conditions. Specifically, a microphone device is used to collect the user's speech.

[0269] Step 2:

[0270] The user sends text data to the server. The server uses this data to search external databases of tourist and accommodation resources via communication. The input is the user's text data, used as a search query for the external database. The output is tourist and accommodation resource information as search results. Specifically, data is exchanged between the server and the database via an internet connection.

[0271] Step 3:

[0272] The server processes the acquired tourist resource information and accommodation resource information, inputs it into a generating AI model, and generates a travel itinerary. The inputs are tourist resource information, accommodation resource information, and user interest information. Using a generating AI model (such as OpenAI's GPT model), it outputs a travel itinerary including places to visit and a time schedule. Specifically, it supplies data to the model, performs processing, and automatically generates the optimal travel plan.

[0273] Step 4:

[0274] The server provides the generated travel itinerary and booking information to the terminal. The output is travel itinerary information displayed both audibly and visually. Specifically, it is provided as audio using Google Text-to-Speech, and the travel itinerary is visually displayed to the user using the display.

[0275] Step 5:

[0276] The user reviews the travel plan and makes modifications as needed. Details can be adjusted using voice commands or touch controls. The output is the final travel plan. Specifically, the user sends feedback and modification instructions to the server via their device.

[0277] 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.

[0278] This invention provides a novel system that recognizes a user's emotions and optimizes travel plans based on them. First, when a user inputs travel conditions, the terminal acquires text or voice data using an input interface. At this stage, an emotion engine is incorporated and analyzes the user's current emotional state from their writing and tone of voice. For example, if the user inputs "excited," the system recognizes a positive emotion.

[0279] Next, the server accesses a database of partner tourist attractions and accommodations, including the user's emotional data, to collect available information. The emotional engine uses the collected emotional data to generate a travel schedule best suited to the user's experience. In this process, if the user's emotions are negative, the AI ​​model adjusts to prioritize relaxing tourist destinations and activities.

[0280] The server provides a flexible plan along with the generated travel schedule, including options that respond to changes in the user's emotions. For example, if the user is feeling stressed, it might recommend visiting natural tourist spots or relaxing hot springs.

[0281] Subsequently, the server utilizes an emotion engine to automatically confirm reservations for suggested destinations and accommodations via an external interface. These reservations are made considering the user's emotional state, taking into account the time and location that aligns with their mood.

[0282] Finally, the device displays the generated travel schedule and booking information in a warm, user-friendly interface that responds to the user's emotions. This allows the user to feel confident about the entire travel plan and begin a satisfying trip.

[0283] For example, assume that the user plans a special relaxation trip on the weekend. The emotion engine recognizes that the user is a bit tired. Therefore, the AI proposes a stay at a quiet resort, generates a schedule incorporating yoga and spa experiences, and executes the related reservations. The schedule displayed on the terminal is confirmed as a plan to provide the user with relaxation.

[0284] This system supports the preparation for the trip in a more user-friendly manner by providing a personalized experience based on the user's emotions.

[0285] The processing flow will be described below.

[0286] Step 1:

[0287] The user starts planning a trip and enters trip conditions such as the destination, schedule, budget, interests, etc. The terminal collects this input information and further uses the emotion engine to analyze the current emotional state from the user's input content and voice. For example, if the user enters something like "want to have an enjoyable trip", it is recognized as a positive emotion.

[0288] Step 2:

[0289] The terminal sends the entered trip conditions and the analyzed emotion data to the server. The server searches the databases of the partnered tourist facilities and accommodation facilities based on the received information and obtains the information that matches the conditions. The emotion data here affects the search algorithm and preferentially selects a place that is enjoyable or relaxing according to the user's current mood.

[0290] Step 3:

[0291] The server uses a generative AI model to generate a travel schedule based on acquired facility information and emotional data. In this process, the AI ​​model optimizes destinations based on the user's emotions and incorporates activities and experiences tailored to their emotional state. If the user is feeling stressed, it suggests relaxation programs such as healing spots, fitness classes, or yoga.

[0292] Step 4:

[0293] The server processes bookings according to the generated travel schedule. If the emotion engine determines that adjustments to bookings are needed for specific times or locations, bookings that meet those conditions are automatically made through an external interface. For example, a spa booking might be scheduled for the evening to provide a relaxing environment.

[0294] Step 5:

[0295] The server compiles the final travel schedule and completed booking information and sends it to the terminal. It may also provide additional advice and supplementary information based on emotional responses, suggesting them to the user.

[0296] Step 6:

[0297] The device uses notification displays to provide a warm and welcoming experience, employing designs and language tailored to the user's emotional state, guiding them to review their travel plans. By viewing the displayed schedule, users can prepare for departure with a sense of calm and renewed anticipation for their trip.

[0298] In this way, the entire system is designed to optimize planning around the user's emotions, resulting in a more fulfilling travel experience.

[0299] (Example 2)

[0300] Next, Example 2 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".

[0301] When planning a trip, there is a problem that sufficient information provision and schedule creation considering the influence of the user's emotions on the travel experience are not carried out, and it is difficult to create an optimal travel plan for the user. In the conventional system, planning reflecting emotions is not performed, and it is difficult to improve the user's satisfaction.

[0302] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0303] In this invention, the server includes a data collection means, an emotion analysis means, and an information acquisition means. Thereby, automatic generation of a travel schedule considering the user's emotions becomes possible.

[0304] The "data collection means" is a device or software that receives travel conditions from a user and records the information in digital form.

[0305] The "emotion analysis means" is a system that specifies an emotional state using natural language processing and speech recognition technology based on data collected from a user.

[0306] [[ID=二十四]]The "information acquisition means" is a device or program that searches for and acquires information on tourist facilities and accommodation facilities from an external database based on the analyzed emotion data.

[0307] The "schedule generation means" is a device or software that performs a process of automatically creating a travel schedule using a generation AI model based on the acquired information and emotion data.

[0308] The "reservation processing means" is a system that automatically executes reservations for tourist facilities and accommodation facilities via an external connection means based on the generated travel schedule.

[0309] A "notification display means" is a device or software that visually displays automatically generated travel schedules and reservation information in a manner that takes into consideration the user's feelings.

[0310] To implement this invention, it is necessary to construct a system that integrates emotion recognition and travel planning optimization. This system generates an optimal travel schedule and automatically makes reservations based on the user's travel conditions and emotional state. The system configuration and the technologies used are described in detail below.

[0311] At the heart of the system is a terminal for collecting data and analyzing emotions. Users input travel details through the terminal, which are captured as text or audio data. This data is sent to software that functions as an emotion analysis tool, where natural language processing techniques are used to analyze emotional states. Audio data is converted to text by dedicated speech recognition software.

[0312] The acquired sentiment data and travel condition data are processed by the server. The server retrieves appropriate tourist facilities and accommodation information from an external database via an information acquisition mechanism. SQL queries are used in this process to efficiently extract the necessary information.

[0313] The server then utilizes a schedule generation mechanism to automatically create a travel schedule using a generating AI model. Based on the prompt text, the AI ​​model generates an optimized plan from the collected information and analyzed sentiment data. In this plan, active activities are appropriately selected for positive emotions, and relaxing activities are appropriately selected for negative emotions.

[0314] For example, when a user plans a special trip seeking relaxation, the emotion engine recognizes that the user is fatigued. In this case, the AI ​​suggests a schedule that includes a stay at a quiet resort and yoga and spa experiences, and arranges the bookings. A specific example of a prompt might be, "The user is seeking relaxation. Please plan a trip that includes yoga and spa treatments in a quiet location to help them recover from fatigue."

[0315] Finally, the device uses notification display methods to show travel schedules and booking information in a way that is sensitive to the user's emotions. The user interface employs a warm design, aiming to make the overall travel experience more satisfying. This system design allows users to enjoy an emotionally-based, personalized travel experience.

[0316] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0317] Step 1:

[0318] The user enters travel requirements into the terminal. Input can be done as text or voice data. In the case of voice input, the terminal uses speech recognition software to convert the voice to text. The entered data is sent to the server by a data collection system.

[0319] Step 2:

[0320] The terminal sends the input data to the sentiment analysis device. The sentiment analysis device uses natural language processing technology to analyze the user's emotional state from the text or converted audio data. The output of this analysis is data indicating the user's emotional state, and may be labeled, for example, as "positive" or "negative."

[0321] Step 3:

[0322] The server receives the emotional data obtained through analysis and uses information acquisition tools to retrieve information on suitable tourist destinations and accommodations from an external database. Here, SQL queries are used to identify candidates based on emotional state and travel conditions. The output is a list of relevant facilities and tourist destinations.

[0323] Step 4:

[0324] The server utilizes a schedule generation mechanism to input prompt messages into the AI ​​model. These prompt messages might take the form of, for example, "The user is seeking relaxation; please plan a trip that includes yoga and spa treatments in a quiet location." Based on this, the AI ​​model automatically generates an optimal travel schedule using the input facility information and sentiment data. The schedule includes the order of visits and specific activities.

[0325] Step 5:

[0326] The server automatically makes reservations for tourist attractions and facilities via external connections, using a reservation processing mechanism according to the generated travel schedule. An API is used, and reservations are confirmed and completed in real time. As a result, reservation information that matches the schedule is output.

[0327] Step 6:

[0328] The device uses notification display methods to show the user their travel schedule and booking information. The display design is thoughtfully tailored to the user's emotional state and is designed to be visually pleasing. This display allows the user to review the entire plan and proceed with travel preparations.

[0329] (Application Example 2)

[0330] 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 as the "terminal".

[0331] In modern times, travel planning has become complex due to the wide range of options and vast amounts of information available. Furthermore, it is difficult to automatically create and flexibly adapt travel plans optimized to the individual emotions and interests of travelers. Conventional systems often provide uniform plans without adequately considering travelers' emotions and individual needs, resulting in outcomes that do not maximize traveler satisfaction. This invention aims to solve these problems and provide travelers with individually optimized travel planning.

[0332] 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.

[0333] In this invention, the server includes information gathering means for receiving travel conditions from users, data gathering means for searching and obtaining information on tourist facilities and accommodations based on the collected travel conditions and emotional state of the users, schedule generation means for automatically generating a travel schedule using a generation AI model based on the acquired information and emotional data, reservation processing means for automatically executing reservations for tourist facilities and accommodations in conjunction with current information and environmental data, and notification display means for displaying the automatically generated travel schedule and reservation information in an interface that takes into account the user's emotions. This makes it possible to provide personalized travel plans based on the traveler's emotions and interests, thereby increasing the flexibility and satisfaction of the planning.

[0334] "Information gathering means" refers to input devices and software used to obtain travel conditions and emotional states from users.

[0335] "Data collection means" refers to devices or processes that collect information on tourist facilities and accommodations from a database based on acquired travel conditions and emotional states.

[0336] A "generative AI model" refers to artificial intelligence technology that analyzes acquired data and automatically creates an appropriate travel schedule.

[0337] "Schedule generation method" refers to the process of automatically creating an optimal schedule based on the user's travel purpose and emotions using a generation AI model.

[0338] "Reservation processing means" refers to devices or programs that automatically make reservations for tourist facilities and accommodations based on a generated travel schedule, taking into account current events and environmental data.

[0339] "Notification display means" refers to a method of displaying generated travel schedules and reservation information on the device in a way that takes the user's feelings into consideration.

[0340] "Emotional state" refers to information that indicates a user's psychological condition or mood, and is data obtained through voice, text, etc.

[0341] This invention is a system that generates travel plans based on the user's emotional state. This system primarily runs on devices such as smartphones and is supported by algorithms on a cloud server. The device acquires travel conditions, voice, and text data from the user. Smartphone hardware such as microphones and cameras are used for information gathering, and sentiment analysis tools such as the Google Cloud Natural Language API are employed for natural language processing.

[0342] Data collected by the device is sent to a cloud server via the internet. The server searches for and retrieves information on tourist facilities and accommodations based on the user's emotional state and travel conditions. Data retrieval is managed by a database system on Amazon Web Services (AWS), and the generated AI model utilizes machine learning frameworks such as TensorFlow and PyTorch to automatically generate travel schedules.

[0343] The schedule generation system analyzes collected information and emotional data to create a travel plan that includes the most suitable destinations and activities for the user. The generated schedule provides flexible planning that can accommodate future changes in emotions. It also takes current events and environmental data into consideration to proceed with the optimal schedule and booking process.

[0344] For example, if a user enters "I'm looking for a new experience," the system recognizes this feeling as a positive sense of adventure and suggests art exhibitions or new restaurants in the city. Reservations are automatically made with the relevant facilities, and the results are displayed on the terminal with an interface that takes the user's feelings into consideration.

[0345] An example of a prompt to input into the generating AI model is: "The user wants to have a new experience this weekend. Analyze their emotions and suggest the best travel plan for them. Please include information on local events in the plan and handle the arrangements."

[0346] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0347] Step 1:

[0348] The device collects travel conditions and emotional states from the user. Voice and text are used as input, and this data is analyzed for emotion and text using the Google Cloud Natural Language API, with the results obtained as output. This analysis identifies the user's current emotional state.

[0349] Step 2:

[0350] The data analyzed on the terminal is sent to the server via the internet. The server searches for information on tourist facilities and accommodations in a database on AWS based on the received emotional data and travel conditions. It collects data that matches the entered travel conditions and emotional state and provides the results as output.

[0351] Step 3:

[0352] The server uses the acquired information to automatically generate travel schedules using a generative AI model. It utilizes tourist facility data, accommodation data, and sentiment analysis results as inputs, performs schedule calculations based on these, and outputs an optimized schedule.

[0353] Step 4:

[0354] The server processes bookings based on the generated travel schedule, taking into account current events and environmental data. Bookings are automatically executed via an external interface, thereby providing a travel experience tailored to the user. The booking results are returned to the user as output.

[0355] Step 5:

[0356] The device receives schedule and reservation information from the server. This data is displayed through a user-friendly interface. The final output is a customized travel plan provided to the user.

[0357] 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.

[0358] 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.

[0359] 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.

[0360] [Third Embodiment]

[0361] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0362] 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.

[0363] 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).

[0364] 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.

[0365] 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.

[0366] 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).

[0367] 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.

[0368] 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.

[0369] 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.

[0370] 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.

[0371] 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.

[0372] 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".

[0373] This invention is a system for efficiently planning travel and providing users with the optimal travel experience. This system is implemented using multiple means. First, the user inputs their travel conditions into a terminal. These conditions include destination, travel dates, budget, interests, etc. The input interface is designed to process this data quickly.

[0374] Next, the server searches a database of affiliated tourist facilities and accommodations based on the travel conditions entered by the user, and also collects relevant information from the internet. What is important here is that this information collection is carried out efficiently and comprehensively, and that the latest tourist information and availability can be obtained.

[0375] Subsequently, the server automatically generates a travel schedule, or "travel itinerary," based on the user's interests, using the collected information via a generative AI model. This AI model considers multiple variables to select the most suitable destinations and optimize the itinerary for the user. For example, for a user interested in history and culture, it generates a schedule incorporating temples and museums selected as destinations.

[0376] Next, the server automatically executes reservations with partner facilities using an external interface based on the generated bookmark. This eliminates the need for users to individually manage multiple reservation sites, allowing for efficient, one-stop reservation completion.

[0377] Finally, the device displays the automatically generated travel schedule and booking information to the user. This allows the user to see the entire plan at a glance and make manual adjustments if necessary.

[0378] As an example, consider a scenario where a user plans a four-day trip to Kyoto. The user inputs the conditions: "cultural experience," "budget of 150,000 yen," and "two people." The server selects historical and cultural sites worth visiting and creates a travel schedule, such as "Kiyomizu-dera Temple and Kinkaku-ji Temple" on day one and "Arashiyama and Fushimi Inari Taisha Shrine" on day two, and automatically makes reservations for the accompanying accommodations. The terminal displays the generated schedule, allowing the user to check the details and ensure a satisfying trip.

[0379] Thus, this invention utilizes advanced data processing and AI technology to create a system that significantly reduces the effort required from users while providing a highly satisfying travel experience.

[0380] The following describes the processing flow.

[0381] Step 1:

[0382] The user enters travel conditions such as destination, itinerary, budget, and interests into the terminal's input interface. The terminal formats the entered data and generates a request to send to the server.

[0383] Step 2:

[0384] The server searches a database of affiliated tourist facilities and accommodations based on the travel conditions received from the user, and retrieves information on available facilities that match the conditions. At the same time, it also obtains the latest tourist events and review ratings by collecting relevant information from the internet using a crawler.

[0385] Step 3:

[0386] The server uses an AI model generated based on collected facility information and user input conditions to create a travel schedule optimized for the user. In this process, the AI ​​model determines the priority of destinations based on the user's interests and proposes a schedule that considers efficient travel routes.

[0387] Step 4:

[0388] Based on the generated travel schedule, the server sends booking requests via API to partner facilities and service providers, automatically executing the necessary reservations for accommodations and activities. The server confirms the success of the booking and records this fact.

[0389] Step 5:

[0390] The server compiles all reservation statuses and generated bookmarks, and creates a package that notifies the user. This information includes details of the reservations made and is sent to the terminal.

[0391] Step 6:

[0392] The device displays the notified travel schedule and booking details on the user interface. Users can review this information and make manual corrections or additional requests as needed. They can also easily review the entire travel schedule, ensuring that their travel plans are efficiently constructed.

[0393] (Example 1)

[0394] 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."

[0395] When planning a trip, users often find it difficult to create an optimal travel schedule that suits their needs from a vast amount of information. Furthermore, booking individual facilities and services is time-consuming and complicated, making travel preparation extremely cumbersome.

[0396] 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.

[0397] In this invention, the server includes means including an information input device, means including a data acquisition device, and means including a schedule creation device. This allows users to easily input conditions and enables the automatic generation of an optimal travel schedule and comprehensive booking processing based on those conditions.

[0398] An "information input device" is a means of providing an interface that allows users to easily input travel conditions.

[0399] A "data acquisition device" is a means of collecting and providing information on tourist destinations and accommodations based on the user's travel conditions.

[0400] A "schedule creation device" is a means of automatically creating a travel plan using a generation AI model based on acquired information.

[0401] A "reservation processing device" is a means of automatically executing reservations for affiliated tourist destinations and facilities via external communication methods, according to the generated travel plan.

[0402] A "notification device" is a means of visually presenting automatically generated travel plans and reservation information to the user.

[0403] This invention is a system that enables users to efficiently plan their trips and provides them with an optimal travel experience. This system is implemented primarily through various means, including servers, terminals, and users.

[0404] First, the user enters their travel details into the terminal. The terminal provides a particularly user-friendly interface, allowing users to easily input their destination, travel dates, budget, interests, and other information. The software used is an input assistance tool based on advanced UI design.

[0405] Next, the server uses an information input device to collect information on partner tourist facilities and accommodations based on the conditions entered by the user, using a data acquisition device. Data collection is carried out via the internet or internal company APIs. Here, the server uses state-of-the-art information update technology to obtain the latest tourist information and facility availability.

[0406] Furthermore, the server utilizes a generative AI model to analyze the collected information and automatically generate travel schedules based on the user's interests. The generative AI model used integrates historical data with real-time information and creates schedules using optimization algorithms. An example of a prompt message is, "Please suggest a travel schedule that emphasizes cultural experiences within the budget."

[0407] Next, the server utilizes the reservation processing unit to automatically execute reservations with partner facilities via external communication methods, based on the generated schedule. This process eliminates the need for users to visit multiple reservation sites, enabling centralized reservation management.

[0408] Ultimately, the device visually presents the automatically generated travel schedule and booking information to the user via a notification device. This allows the user to grasp the entire travel plan at a glance and adjust the schedule as needed.

[0409] This invention significantly reduces the time and effort users spend creating complex travel plans, resulting in a more satisfying travel experience.

[0410] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0411] Step 1:

[0412] The user enters their travel conditions into the terminal. This includes destination, travel dates, budget, interests, and other details. The terminal provides a user-friendly interface to reduce the effort required for input. The user's conditions are then digitized and used for subsequent processing. The input data is sent to the server as a request.

[0413] Step 2:

[0414] The server receives data entered by the user and uses a data acquisition device to collect information on tourist destinations and accommodations from external databases and the internet. This information collection efficiently obtains current availability and the latest tourist information via APIs. The acquired data is then used for analysis by an AI model in the next step.

[0415] Step 3:

[0416] The server uses a generative AI model to automatically generate a travel schedule tailored to the user's interests based on the collected information. The prompt used is, "Please select the main tourist attractions at your destination, prioritizing cultural experiences." The AI ​​model analyzes the input data and outputs candidate travel plans best suited to the user. As a result, an AI-adjusted schedule is created.

[0417] Step 4:

[0418] The server uses the generated travel plan schedule to automatically execute reservations at partner facilities via external communication methods using a reservation processing unit. Specifically, it accesses the reservation API of each facility, inputs the necessary reservation information, and obtains a reservation confirmation. This eliminates the need for users to make individual reservations.

[0419] Step 5:

[0420] The terminal receives the generated schedule and reservation information sent from the server and displays it to the user. This display allows the user to see the overall picture of the trip and make changes to the schedule on the terminal if necessary. The user can then make final confirmations based on the displayed information and prepare for the trip.

[0421] (Application Example 1)

[0422] 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."

[0423] Planning a trip can be burdensome for users, as it requires organizing a lot of information. Furthermore, the time-consuming process of individual bookings and information searches hinders efficient travel planning. There is a growing need to provide users with a more intuitive interface through voice control.

[0424] 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.

[0425] In this invention, the server includes recognition means for receiving travel conditions from the user by voice, data collection means for searching and acquiring information on tourist and accommodation resources via communication means based on the collected travel conditions of the user, and schedule generation means for automatically generating and ordering a travel itinerary using a generation AI model based on the acquired information. This enables efficient and intuitive travel planning through voice control.

[0426] "Recognition means" refers to a technological device that receives travel conditions from the user as voice data and converts that voice data into text data.

[0427] "Communication means" refers to network connection devices used to acquire information on tourism and accommodation resources from external databases for the purpose of data collection.

[0428] A "schedule generation method" is a processor that uses a generation AI model based on acquired information to automatically generate a travel itinerary and determine the optimal order.

[0429] A "display means" is a device that notifies the user of automatically generated travel itineraries and reservation information via voice output or screen display.

[0430] The system for implementing the present invention is configured as a voice-controlled travel planning assistant. The server collects travel conditions as input data from the user through speech recognition technology. Specifically, it analyzes the user's voice information using the Google Speech-to-Text API and converts the travel conditions into text format.

[0431] This text data is transmitted via communication to a data collection module on the server. This module searches external databases related to tourism and accommodation resources via the internet and collects the latest relevant information.

[0432] Next, the server uses a generative AI model based on the acquired information to create a travel itinerary that reflects the user's interests. This generative AI model employs OpenAI's GPT model, among others, which enables the automatic construction of the itinerary schedule. For example, if the user inputs the prompt, "I want to visit tourist spots with my family next weekend," the AI ​​model will consider popular tourist destinations and generate an optimal order of visits and timetable.

[0433] The generated travel itinerary and booking information are notified to the user's device via visual display and audio output. Google Text-to-Speech technology is used to provide information as audio or display it on the screen. Users can review this information and take further action using voice commands.

[0434] For example, if you use a prompt like, "We want to take a day trip with four people this weekend and visit some tourist attractions," the system will select appropriate spots and automatically generate a travel plan. This process allows users to efficiently prepare for their trip.

[0435] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0436] Step 1:

[0437] The user inputs their travel preferences via voice. A speech recognition module uses the Google Speech-to-Text API to convert this input voice into text data. The output is text data indicating the user's travel conditions. Specifically, a microphone device is used to collect the user's speech.

[0438] Step 2:

[0439] The user sends text data to the server. The server uses this data to search external databases of tourist and accommodation resources via communication. The input is the user's text data, used as a search query for the external database. The output is tourist and accommodation resource information as search results. Specifically, data is exchanged between the server and the database via an internet connection.

[0440] Step 3:

[0441] The server processes the acquired tourist resource information and accommodation resource information, inputs it into a generating AI model, and generates a travel itinerary. The inputs are tourist resource information, accommodation resource information, and user interest information. Using a generating AI model (such as OpenAI's GPT model), it outputs a travel itinerary including places to visit and a time schedule. Specifically, it supplies data to the model, performs processing, and automatically generates the optimal travel plan.

[0442] Step 4:

[0443] The server provides the generated travel itinerary and booking information to the terminal. The output is travel itinerary information displayed both audibly and visually. Specifically, it is provided as audio using Google Text-to-Speech, and the travel itinerary is visually displayed to the user using the display.

[0444] Step 5:

[0445] The user reviews the travel plan and makes modifications as needed. Details can be adjusted using voice commands or touch controls. The output is the final travel plan. Specifically, the user sends feedback and modification instructions to the server via their device.

[0446] 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.

[0447] This invention provides a novel system that recognizes a user's emotions and optimizes travel plans based on them. First, when a user inputs travel conditions, the terminal acquires text or voice data using an input interface. At this stage, an emotion engine is incorporated and analyzes the user's current emotional state from their writing and tone of voice. For example, if the user inputs "excited," the system recognizes a positive emotion.

[0448] Next, the server accesses a database of partner tourist attractions and accommodations, including the user's emotional data, to collect available information. The emotional engine uses the collected emotional data to generate a travel schedule best suited to the user's experience. In this process, if the user's emotions are negative, the AI ​​model adjusts to prioritize relaxing tourist destinations and activities.

[0449] The server provides a flexible plan along with the generated travel schedule, including options that respond to changes in the user's emotions. For example, if the user is feeling stressed, it might recommend visiting natural tourist spots or relaxing hot springs.

[0450] Subsequently, the server utilizes an emotion engine to automatically confirm reservations for suggested destinations and accommodations via an external interface. These reservations are made considering the user's emotional state, taking into account the time and location that aligns with their mood.

[0451] Finally, the device displays the generated travel schedule and booking information in a warm, user-friendly interface that responds to the user's emotions. This allows the user to feel confident about the entire travel plan and begin a satisfying trip.

[0452] For example, suppose a user plans a special relaxation trip for the weekend. The emotion engine recognizes that the user is a little tired, and therefore the AI ​​suggests a stay at a quiet resort, generates a schedule incorporating yoga and spa experiences, and makes the relevant reservations. The schedule displayed on the device is then confirmed as a plan that will provide the user with peace of mind.

[0453] This system provides a personalized experience based on the user's emotions, supporting travel preparations in a more user-centric way.

[0454] The following describes the processing flow.

[0455] Step 1:

[0456] The user begins planning a trip, entering travel conditions such as destination, dates, budget, and interests. The device collects this information and uses an emotion engine to analyze the user's current emotional state from their input and voice. For example, if the user enters something like "I want to have a fun trip," it is recognized as a positive emotion.

[0457] Step 2:

[0458] The terminal sends the entered travel conditions and analyzed sentiment data to the server. Based on the received information, the server searches a database of partner tourist facilities and accommodations and retrieves information that matches the conditions. The sentiment data here influences the search algorithm, prioritizing the selection of fun or relaxing places that match the user's current mood.

[0459] Step 3:

[0460] The server uses a generative AI model to generate a travel schedule based on acquired facility information and emotional data. In this process, the AI ​​model optimizes destinations based on the user's emotions and incorporates activities and experiences tailored to their emotional state. If the user is feeling stressed, it suggests relaxation programs such as healing spots, fitness classes, or yoga.

[0461] Step 4:

[0462] The server processes bookings according to the generated travel schedule. If the emotion engine determines that adjustments to bookings are needed for specific times or locations, bookings that meet those conditions are automatically made through an external interface. For example, a spa booking might be scheduled for the evening to provide a relaxing environment.

[0463] Step 5:

[0464] The server compiles the final travel schedule and completed booking information and sends it to the terminal. It may also provide additional advice and supplementary information based on emotional responses, suggesting them to the user.

[0465] Step 6:

[0466] The device uses notification displays to provide a warm and welcoming experience, employing designs and language tailored to the user's emotional state, guiding them to review their travel plans. By viewing the displayed schedule, users can prepare for departure with a sense of calm and renewed anticipation for their trip.

[0467] In this way, the entire system is designed to optimize planning around the user's emotions, resulting in a more fulfilling travel experience.

[0468] (Example 2)

[0469] 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."

[0470] When planning a trip, there is a challenge in creating optimal travel plans for users because information and schedules are not adequately provided that take into account the impact of users' emotions on the travel experience. Conventional systems do not reflect emotions in planning, making it difficult to increase user satisfaction.

[0471] 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.

[0472] In this invention, the server includes data collection means, emotion analysis means, and information acquisition means. This makes it possible to automatically generate a travel schedule that takes the user's emotions into consideration.

[0473] "Data collection means" refers to a device or software that receives travel conditions from users and records that information in digital format.

[0474] An "emotion analysis system" is a system that identifies emotional states using natural language processing and speech recognition technologies based on data collected from users.

[0475] "Information acquisition means" refers to a device or program that retrieves information about tourist facilities and accommodations from an external database based on analyzed sentiment data.

[0476] A "schedule generation method" is a device or software that performs the process of automatically creating a travel schedule using a generation AI model based on acquired information and sentiment data.

[0477] A "reservation processing system" is a system that automatically executes reservations for tourist facilities and accommodations based on a generated travel schedule, via an external connection.

[0478] A "notification display means" is a device or software that visually displays automatically generated travel schedules and reservation information in a manner that takes into consideration the user's feelings.

[0479] To implement this invention, it is necessary to construct a system that integrates emotion recognition and travel planning optimization. This system generates an optimal travel schedule and automatically makes reservations based on the user's travel conditions and emotional state. The system configuration and the technologies used are described in detail below.

[0480] At the heart of the system is a terminal for collecting data and analyzing emotions. Users input travel details through the terminal, which are captured as text or audio data. This data is sent to software that functions as an emotion analysis tool, where natural language processing techniques are used to analyze emotional states. Audio data is converted to text by dedicated speech recognition software.

[0481] The acquired sentiment data and travel condition data are processed by the server. The server retrieves appropriate tourist facilities and accommodation information from an external database via an information acquisition mechanism. SQL queries are used in this process to efficiently extract the necessary information.

[0482] The server then utilizes a schedule generation mechanism to automatically create a travel schedule using a generating AI model. Based on the prompt text, the AI ​​model generates an optimized plan from the collected information and analyzed sentiment data. In this plan, active activities are appropriately selected for positive emotions, and relaxing activities are appropriately selected for negative emotions.

[0483] For example, when a user plans a special trip seeking relaxation, the emotion engine recognizes that the user is fatigued. In this case, the AI ​​suggests a schedule that includes a stay at a quiet resort and yoga and spa experiences, and arranges the bookings. A specific example of a prompt might be, "The user is seeking relaxation. Please plan a trip that includes yoga and spa treatments in a quiet location to help them recover from fatigue."

[0484] Finally, the device uses notification display methods to show travel schedules and booking information in a way that is sensitive to the user's emotions. The user interface employs a warm design, aiming to make the overall travel experience more satisfying. This system design allows users to enjoy an emotionally-based, personalized travel experience.

[0485] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0486] Step 1:

[0487] The user enters travel requirements into the terminal. Input can be done as text or voice data. In the case of voice input, the terminal uses speech recognition software to convert the voice to text. The entered data is sent to the server by a data collection system.

[0488] Step 2:

[0489] The terminal sends the input data to the sentiment analysis device. The sentiment analysis device uses natural language processing technology to analyze the user's emotional state from the text or converted audio data. The output of this analysis is data indicating the user's emotional state, and may be labeled, for example, as "positive" or "negative."

[0490] Step 3:

[0491] The server receives the emotional data obtained through analysis and uses information acquisition tools to retrieve information on suitable tourist destinations and accommodations from an external database. Here, SQL queries are used to identify candidates based on emotional state and travel conditions. The output is a list of relevant facilities and tourist destinations.

[0492] Step 4:

[0493] The server utilizes a schedule generation mechanism to input prompt messages into the AI ​​model. These prompt messages might take the form of, for example, "The user is seeking relaxation; please plan a trip that includes yoga and spa treatments in a quiet location." Based on this, the AI ​​model automatically generates an optimal travel schedule using the input facility information and sentiment data. The schedule includes the order of visits and specific activities.

[0494] Step 5:

[0495] The server automatically makes reservations for tourist attractions and facilities via external connections, using a reservation processing mechanism according to the generated travel schedule. An API is used, and reservations are confirmed and completed in real time. As a result, reservation information that matches the schedule is output.

[0496] Step 6:

[0497] The device uses notification display methods to show the user their travel schedule and booking information. The display design is thoughtfully tailored to the user's emotional state and is designed to be visually pleasing. This display allows the user to review the entire plan and proceed with travel preparations.

[0498] (Application Example 2)

[0499] 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."

[0500] In modern times, travel planning has become complex due to the wide range of options and vast amounts of information available. Furthermore, it is difficult to automatically create and flexibly adapt travel plans optimized to the individual emotions and interests of travelers. Conventional systems often provide uniform plans without adequately considering travelers' emotions and individual needs, resulting in outcomes that do not maximize traveler satisfaction. This invention aims to solve these problems and provide travelers with individually optimized travel planning.

[0501] 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.

[0502] In this invention, the server includes information gathering means for receiving travel conditions from users, data gathering means for searching and obtaining information on tourist facilities and accommodations based on the collected travel conditions and emotional state of the users, schedule generation means for automatically generating a travel schedule using a generation AI model based on the acquired information and emotional data, reservation processing means for automatically executing reservations for tourist facilities and accommodations in conjunction with current information and environmental data, and notification display means for displaying the automatically generated travel schedule and reservation information in an interface that takes into account the user's emotions. This makes it possible to provide personalized travel plans based on the traveler's emotions and interests, thereby increasing the flexibility and satisfaction of the planning.

[0503] "Information gathering means" refers to input devices and software used to obtain travel conditions and emotional states from users.

[0504] "Data collection means" refers to devices or processes that collect information on tourist facilities and accommodations from a database based on acquired travel conditions and emotional states.

[0505] A "generative AI model" refers to artificial intelligence technology that analyzes acquired data and automatically creates an appropriate travel schedule.

[0506] "Schedule generation method" refers to the process of automatically creating an optimal schedule based on the user's travel purpose and emotions using a generation AI model.

[0507] "Reservation processing means" refers to devices or programs that automatically make reservations for tourist facilities and accommodations based on a generated travel schedule, taking into account current events and environmental data.

[0508] "Notification display means" refers to a method of displaying generated travel schedules and reservation information on the device in a way that takes the user's feelings into consideration.

[0509] "Emotional state" refers to information that indicates a user's psychological condition or mood, and is data obtained through voice, text, etc.

[0510] This invention is a system that generates travel plans based on the user's emotional state. This system primarily runs on devices such as smartphones and is supported by algorithms on a cloud server. The device acquires travel conditions, voice, and text data from the user. Smartphone hardware such as microphones and cameras are used for information gathering, and sentiment analysis tools such as the Google Cloud Natural Language API are employed for natural language processing.

[0511] Data collected by the device is sent to a cloud server via the internet. The server searches for and retrieves information on tourist facilities and accommodations based on the user's emotional state and travel conditions. Data retrieval is managed by a database system on Amazon Web Services (AWS), and the generated AI model utilizes machine learning frameworks such as TensorFlow and PyTorch to automatically generate travel schedules.

[0512] The schedule generation system analyzes collected information and emotional data to create a travel plan that includes the most suitable destinations and activities for the user. The generated schedule provides flexible planning that can accommodate future changes in emotions. It also takes current events and environmental data into consideration to proceed with the optimal schedule and booking process.

[0513] For example, if a user enters "I'm looking for a new experience," the system recognizes this feeling as a positive sense of adventure and suggests art exhibitions or new restaurants in the city. Reservations are automatically made with the relevant facilities, and the results are displayed on the terminal with an interface that takes the user's feelings into consideration.

[0514] An example of a prompt to input into the generating AI model is: "The user wants to have a new experience this weekend. Analyze their emotions and suggest the best travel plan for them. Please include information on local events in the plan and handle the arrangements."

[0515] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0516] Step 1:

[0517] The device collects travel conditions and emotional states from the user. Voice and text are used as input, and this data is analyzed for emotion and text using the Google Cloud Natural Language API, with the results obtained as output. This analysis identifies the user's current emotional state.

[0518] Step 2:

[0519] The data analyzed on the terminal is sent to the server via the internet. The server searches for information on tourist facilities and accommodations in a database on AWS based on the received emotional data and travel conditions. It collects data that matches the entered travel conditions and emotional state and provides the results as output.

[0520] Step 3:

[0521] The server uses the acquired information to automatically generate travel schedules using a generative AI model. It utilizes tourist facility data, accommodation data, and sentiment analysis results as inputs, performs schedule calculations based on these, and outputs an optimized schedule.

[0522] Step 4:

[0523] The server processes bookings based on the generated travel schedule, taking into account current events and environmental data. Bookings are automatically executed via an external interface, thereby providing a travel experience tailored to the user. The booking results are returned to the user as output.

[0524] Step 5:

[0525] The device receives schedule and reservation information from the server. This data is displayed through a user-friendly interface. The final output is a customized travel plan provided to the user.

[0526] 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.

[0527] 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.

[0528] 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.

[0529] [Fourth Embodiment]

[0530] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0531] 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.

[0532] 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).

[0533] 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.

[0534] 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.

[0535] 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).

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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.

[0540] 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.

[0541] 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.

[0542] 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".

[0543] This invention is a system for efficiently planning travel and providing users with the optimal travel experience. This system is implemented using multiple means. First, the user inputs their travel conditions into a terminal. These conditions include destination, travel dates, budget, interests, etc. The input interface is designed to process this data quickly.

[0544] Next, the server searches a database of affiliated tourist facilities and accommodations based on the travel conditions entered by the user, and also collects relevant information from the internet. What is important here is that this information collection is carried out efficiently and comprehensively, and that the latest tourist information and availability can be obtained.

[0545] Subsequently, the server automatically generates a travel schedule, or "travel itinerary," based on the user's interests, using the collected information via a generative AI model. This AI model considers multiple variables to select the most suitable destinations and optimize the itinerary for the user. For example, for a user interested in history and culture, it generates a schedule incorporating temples and museums selected as destinations.

[0546] Next, the server automatically executes reservations with partner facilities using an external interface based on the generated bookmark. This eliminates the need for users to individually manage multiple reservation sites, allowing for efficient, one-stop reservation completion.

[0547] Finally, the device displays the automatically generated travel schedule and booking information to the user. This allows the user to see the entire plan at a glance and make manual adjustments if necessary.

[0548] As an example, consider a scenario where a user plans a four-day trip to Kyoto. The user inputs the conditions: "cultural experience," "budget of 150,000 yen," and "two people." The server selects historical and cultural sites worth visiting and creates a travel schedule, such as "Kiyomizu-dera Temple and Kinkaku-ji Temple" on day one and "Arashiyama and Fushimi Inari Taisha Shrine" on day two, and automatically makes reservations for the accompanying accommodations. The terminal displays the generated schedule, allowing the user to check the details and ensure a satisfying trip.

[0549] Thus, this invention utilizes advanced data processing and AI technology to create a system that significantly reduces the effort required from users while providing a highly satisfying travel experience.

[0550] The following describes the processing flow.

[0551] Step 1:

[0552] The user enters travel conditions such as destination, itinerary, budget, and interests into the terminal's input interface. The terminal formats the entered data and generates a request to send to the server.

[0553] Step 2:

[0554] The server searches a database of affiliated tourist facilities and accommodations based on the travel conditions received from the user, and retrieves information on available facilities that match the conditions. At the same time, it also obtains the latest tourist events and review ratings by collecting relevant information from the internet using a crawler.

[0555] Step 3:

[0556] The server uses an AI model generated based on collected facility information and user input conditions to create a travel schedule optimized for the user. In this process, the AI ​​model determines the priority of destinations based on the user's interests and proposes a schedule that considers efficient travel routes.

[0557] Step 4:

[0558] Based on the generated travel schedule, the server sends booking requests via API to partner facilities and service providers, automatically executing the necessary reservations for accommodations and activities. The server confirms the success of the booking and records this fact.

[0559] Step 5:

[0560] The server compiles all reservation statuses and generated bookmarks, and creates a package that notifies the user. This information includes details of the reservations made and is sent to the terminal.

[0561] Step 6:

[0562] The device displays the notified travel schedule and booking details on the user interface. Users can review this information and make manual corrections or additional requests as needed. They can also easily review the entire travel schedule, ensuring that their travel plans are efficiently constructed.

[0563] (Example 1)

[0564] 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".

[0565] When planning a trip, users often find it difficult to create an optimal travel schedule that suits their needs from a vast amount of information. Furthermore, booking individual facilities and services is time-consuming and complicated, making travel preparation extremely cumbersome.

[0566] 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.

[0567] In this invention, the server includes means including an information input device, means including a data acquisition device, and means including a schedule creation device. This allows users to easily input conditions and enables the automatic generation of an optimal travel schedule and comprehensive booking processing based on those conditions.

[0568] An "information input device" is a means of providing an interface that allows users to easily input travel conditions.

[0569] A "data acquisition device" is a means of collecting and providing information on tourist destinations and accommodations based on the user's travel conditions.

[0570] A "schedule creation device" is a means of automatically creating a travel plan using a generation AI model based on acquired information.

[0571] A "reservation processing device" is a means of automatically executing reservations for affiliated tourist destinations and facilities via external communication methods, according to the generated travel plan.

[0572] A "notification device" is a means of visually presenting automatically generated travel plans and reservation information to the user.

[0573] This invention is a system that enables users to efficiently plan their trips and provides them with an optimal travel experience. This system is implemented primarily through various means, including servers, terminals, and users.

[0574] First, the user enters their travel details into the terminal. The terminal provides a particularly user-friendly interface, allowing users to easily input their destination, travel dates, budget, interests, and other information. The software used is an input assistance tool based on advanced UI design.

[0575] Next, the server uses an information input device to collect information on partner tourist facilities and accommodations based on the conditions entered by the user, using a data acquisition device. Data collection is carried out via the internet or internal company APIs. Here, the server uses state-of-the-art information update technology to obtain the latest tourist information and facility availability.

[0576] Furthermore, the server utilizes a generative AI model to analyze the collected information and automatically generate travel schedules based on the user's interests. The generative AI model used integrates historical data with real-time information and creates schedules using optimization algorithms. An example of a prompt message is, "Please suggest a travel schedule that emphasizes cultural experiences within the budget."

[0577] Next, the server utilizes the reservation processing unit to automatically execute reservations with partner facilities via external communication methods, based on the generated schedule. This process eliminates the need for users to visit multiple reservation sites, enabling centralized reservation management.

[0578] Ultimately, the device visually presents the automatically generated travel schedule and booking information to the user via a notification device. This allows the user to grasp the entire travel plan at a glance and adjust the schedule as needed.

[0579] This invention significantly reduces the time and effort users spend creating complex travel plans, resulting in a more satisfying travel experience.

[0580] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0581] Step 1:

[0582] The user enters their travel conditions into the terminal. This includes destination, travel dates, budget, interests, and other details. The terminal provides a user-friendly interface to reduce the effort required for input. The user's conditions are then digitized and used for subsequent processing. The input data is sent to the server as a request.

[0583] Step 2:

[0584] The server receives data entered by the user and uses a data acquisition device to collect information on tourist destinations and accommodations from external databases and the internet. This information collection efficiently obtains current availability and the latest tourist information via APIs. The acquired data is then used for analysis by an AI model in the next step.

[0585] Step 3:

[0586] The server uses a generative AI model to automatically generate a travel schedule tailored to the user's interests based on the collected information. The prompt used is, "Please select the main tourist attractions at your destination, prioritizing cultural experiences." The AI ​​model analyzes the input data and outputs candidate travel plans best suited to the user. As a result, an AI-adjusted schedule is created.

[0587] Step 4:

[0588] The server uses the generated travel plan schedule to automatically execute reservations at partner facilities via external communication methods using a reservation processing unit. Specifically, it accesses the reservation API of each facility, inputs the necessary reservation information, and obtains a reservation confirmation. This eliminates the need for users to make individual reservations.

[0589] Step 5:

[0590] The terminal receives the generated schedule and reservation information sent from the server and displays it to the user. This display allows the user to see the overall picture of the trip and make changes to the schedule on the terminal if necessary. The user can then make final confirmations based on the displayed information and prepare for the trip.

[0591] (Application Example 1)

[0592] 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".

[0593] Planning a trip can be burdensome for users, as it requires organizing a lot of information. Furthermore, the time-consuming process of individual bookings and information searches hinders efficient travel planning. There is a growing need to provide users with a more intuitive interface through voice control.

[0594] 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.

[0595] In this invention, the server includes recognition means for receiving travel conditions from the user by voice, data collection means for searching and acquiring information on tourist and accommodation resources via communication means based on the collected travel conditions of the user, and schedule generation means for automatically generating and ordering a travel itinerary using a generation AI model based on the acquired information. This enables efficient and intuitive travel planning through voice control.

[0596] "Recognition means" refers to a technological device that receives travel conditions from the user as voice data and converts that voice data into text data.

[0597] "Communication means" refers to network connection devices used to acquire information on tourism and accommodation resources from external databases for the purpose of data collection.

[0598] A "schedule generation method" is a processor that uses a generation AI model based on acquired information to automatically generate a travel itinerary and determine the optimal order.

[0599] A "display means" is a device that notifies the user of automatically generated travel itineraries and reservation information via voice output or screen display.

[0600] The system for implementing the present invention is configured as a voice-controlled travel planning assistant. The server collects travel conditions as input data from the user through speech recognition technology. Specifically, it analyzes the user's voice information using the Google Speech-to-Text API and converts the travel conditions into text format.

[0601] This text data is transmitted via communication to a data collection module on the server. This module searches external databases related to tourism and accommodation resources via the internet and collects the latest relevant information.

[0602] Next, the server uses a generative AI model based on the acquired information to create a travel itinerary that reflects the user's interests. This generative AI model employs OpenAI's GPT model, among others, which enables the automatic construction of the itinerary schedule. For example, if the user inputs the prompt, "I want to visit tourist spots with my family next weekend," the AI ​​model will consider popular tourist destinations and generate an optimal order of visits and timetable.

[0603] The generated travel itinerary and booking information are notified to the user's device via visual display and audio output. Google Text-to-Speech technology is used to provide information as audio or display it on the screen. Users can review this information and take further action using voice commands.

[0604] For example, if you use a prompt like, "We want to take a day trip with four people this weekend and visit some tourist attractions," the system will select appropriate spots and automatically generate a travel plan. This process allows users to efficiently prepare for their trip.

[0605] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0606] Step 1:

[0607] The user inputs their travel preferences via voice. A speech recognition module uses the Google Speech-to-Text API to convert this input voice into text data. The output is text data indicating the user's travel conditions. Specifically, a microphone device is used to collect the user's speech.

[0608] Step 2:

[0609] The user sends text data to the server. The server uses this data to search external databases of tourist and accommodation resources via communication. The input is the user's text data, used as a search query for the external database. The output is tourist and accommodation resource information as search results. Specifically, data is exchanged between the server and the database via an internet connection.

[0610] Step 3:

[0611] The server processes the acquired tourist resource information and accommodation resource information, inputs it into a generating AI model, and generates a travel itinerary. The inputs are tourist resource information, accommodation resource information, and user interest information. Using a generating AI model (such as OpenAI's GPT model), it outputs a travel itinerary including places to visit and a time schedule. Specifically, it supplies data to the model, performs processing, and automatically generates the optimal travel plan.

[0612] Step 4:

[0613] The server provides the generated travel itinerary and booking information to the terminal. The output is travel itinerary information displayed both audibly and visually. Specifically, it is provided as audio using Google Text-to-Speech, and the travel itinerary is visually displayed to the user using the display.

[0614] Step 5:

[0615] The user reviews the travel plan and makes modifications as needed. Details can be adjusted using voice commands or touch controls. The output is the final travel plan. Specifically, the user sends feedback and modification instructions to the server via their device.

[0616] 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.

[0617] This invention provides a novel system that recognizes a user's emotions and optimizes travel plans based on them. First, when a user inputs travel conditions, the terminal acquires text or voice data using an input interface. At this stage, an emotion engine is incorporated and analyzes the user's current emotional state from their writing and tone of voice. For example, if the user inputs "excited," the system recognizes a positive emotion.

[0618] Next, the server accesses a database of partner tourist attractions and accommodations, including the user's emotional data, to collect available information. The emotional engine uses the collected emotional data to generate a travel schedule best suited to the user's experience. In this process, if the user's emotions are negative, the AI ​​model adjusts to prioritize relaxing tourist destinations and activities.

[0619] The server provides a flexible plan along with the generated travel schedule, including options that respond to changes in the user's emotions. For example, if the user is feeling stressed, it might recommend visiting natural tourist spots or relaxing hot springs.

[0620] Subsequently, the server utilizes an emotion engine to automatically confirm reservations for suggested destinations and accommodations via an external interface. These reservations are made considering the user's emotional state, taking into account the time and location that aligns with their mood.

[0621] Finally, the device displays the generated travel schedule and booking information in a warm, user-friendly interface that responds to the user's emotions. This allows the user to feel confident about the entire travel plan and begin a satisfying trip.

[0622] For example, suppose a user plans a special relaxation trip for the weekend. The emotion engine recognizes that the user is a little tired, and therefore the AI ​​suggests a stay at a quiet resort, generates a schedule incorporating yoga and spa experiences, and makes the relevant reservations. The schedule displayed on the device is then confirmed as a plan that will provide the user with peace of mind.

[0623] This system provides a personalized experience based on the user's emotions, supporting travel preparations in a more user-centric way.

[0624] The following describes the processing flow.

[0625] Step 1:

[0626] The user begins planning a trip, entering travel conditions such as destination, dates, budget, and interests. The device collects this information and uses an emotion engine to analyze the user's current emotional state from their input and voice. For example, if the user enters something like "I want to have a fun trip," it is recognized as a positive emotion.

[0627] Step 2:

[0628] The terminal sends the entered travel conditions and analyzed sentiment data to the server. Based on the received information, the server searches a database of partner tourist facilities and accommodations and retrieves information that matches the conditions. The sentiment data here influences the search algorithm, prioritizing the selection of fun or relaxing places that match the user's current mood.

[0629] Step 3:

[0630] The server uses a generative AI model to generate a travel schedule based on acquired facility information and emotional data. In this process, the AI ​​model optimizes destinations based on the user's emotions and incorporates activities and experiences tailored to their emotional state. If the user is feeling stressed, it suggests relaxation programs such as healing spots, fitness classes, or yoga.

[0631] Step 4:

[0632] The server processes bookings according to the generated travel schedule. If the emotion engine determines that adjustments to bookings are needed for specific times or locations, bookings that meet those conditions are automatically made through an external interface. For example, a spa booking might be scheduled for the evening to provide a relaxing environment.

[0633] Step 5:

[0634] The server compiles the final travel schedule and completed booking information and sends it to the terminal. It may also provide additional advice and supplementary information based on emotional responses, suggesting them to the user.

[0635] Step 6:

[0636] The device uses notification displays to provide a warm and welcoming experience, employing designs and language tailored to the user's emotional state, guiding them to review their travel plans. By viewing the displayed schedule, users can prepare for departure with a sense of calm and renewed anticipation for their trip.

[0637] In this way, the entire system is designed to optimize planning around the user's emotions, resulting in a more fulfilling travel experience.

[0638] (Example 2)

[0639] 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".

[0640] When planning a trip, there is a challenge in creating optimal travel plans for users because information and schedules are not adequately provided that take into account the impact of users' emotions on the travel experience. Conventional systems do not reflect emotions in planning, making it difficult to increase user satisfaction.

[0641] 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.

[0642] In this invention, the server includes data collection means, emotion analysis means, and information acquisition means. This makes it possible to automatically generate a travel schedule that takes the user's emotions into consideration.

[0643] "Data collection means" refers to a device or software that receives travel conditions from users and records that information in digital format.

[0644] An "emotion analysis system" is a system that identifies emotional states using natural language processing and speech recognition technologies based on data collected from users.

[0645] "Information acquisition means" refers to a device or program that retrieves information about tourist facilities and accommodations from an external database based on analyzed sentiment data.

[0646] A "schedule generation method" is a device or software that performs the process of automatically creating a travel schedule using a generation AI model based on acquired information and sentiment data.

[0647] A "reservation processing system" is a system that automatically executes reservations for tourist facilities and accommodations based on a generated travel schedule, via an external connection.

[0648] A "notification display means" is a device or software that visually displays automatically generated travel schedules and reservation information in a manner that takes into consideration the user's feelings.

[0649] To implement this invention, it is necessary to construct a system that integrates emotion recognition and travel planning optimization. This system generates an optimal travel schedule and automatically makes reservations based on the user's travel conditions and emotional state. The system configuration and the technologies used are described in detail below.

[0650] At the heart of the system is a terminal for collecting data and analyzing emotions. Users input travel details through the terminal, which are captured as text or audio data. This data is sent to software that functions as an emotion analysis tool, where natural language processing techniques are used to analyze emotional states. Audio data is converted to text by dedicated speech recognition software.

[0651] The acquired sentiment data and travel condition data are processed by the server. The server retrieves appropriate tourist facilities and accommodation information from an external database via an information acquisition mechanism. SQL queries are used in this process to efficiently extract the necessary information.

[0652] The server then utilizes a schedule generation mechanism to automatically create a travel schedule using a generating AI model. Based on the prompt text, the AI ​​model generates an optimized plan from the collected information and analyzed sentiment data. In this plan, active activities are appropriately selected for positive emotions, and relaxing activities are appropriately selected for negative emotions.

[0653] For example, when a user plans a special trip seeking relaxation, the emotion engine recognizes that the user is fatigued. In this case, the AI ​​suggests a schedule that includes a stay at a quiet resort and yoga and spa experiences, and arranges the bookings. A specific example of a prompt might be, "The user is seeking relaxation. Please plan a trip that includes yoga and spa treatments in a quiet location to help them recover from fatigue."

[0654] Finally, the device uses notification display methods to show travel schedules and booking information in a way that is sensitive to the user's emotions. The user interface employs a warm design, aiming to make the overall travel experience more satisfying. This system design allows users to enjoy an emotionally-based, personalized travel experience.

[0655] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0656] Step 1:

[0657] The user enters travel requirements into the terminal. Input can be done as text or voice data. In the case of voice input, the terminal uses speech recognition software to convert the voice to text. The entered data is sent to the server by a data collection system.

[0658] Step 2:

[0659] The terminal sends the input data to the sentiment analysis device. The sentiment analysis device uses natural language processing technology to analyze the user's emotional state from the text or converted audio data. The output of this analysis is data indicating the user's emotional state, and may be labeled, for example, as "positive" or "negative."

[0660] Step 3:

[0661] The server receives the emotional data obtained through analysis and uses information acquisition tools to retrieve information on suitable tourist destinations and accommodations from an external database. Here, SQL queries are used to identify candidates based on emotional state and travel conditions. The output is a list of relevant facilities and tourist destinations.

[0662] Step 4:

[0663] The server utilizes a schedule generation mechanism to input prompt messages into the AI ​​model. These prompt messages might take the form of, for example, "The user is seeking relaxation; please plan a trip that includes yoga and spa treatments in a quiet location." Based on this, the AI ​​model automatically generates an optimal travel schedule using the input facility information and sentiment data. The schedule includes the order of visits and specific activities.

[0664] Step 5:

[0665] The server automatically makes reservations for tourist attractions and facilities via external connections, using a reservation processing mechanism according to the generated travel schedule. An API is used, and reservations are confirmed and completed in real time. As a result, reservation information that matches the schedule is output.

[0666] Step 6:

[0667] The device uses notification display methods to show the user their travel schedule and booking information. The display design is thoughtfully tailored to the user's emotional state and is designed to be visually pleasing. This display allows the user to review the entire plan and proceed with travel preparations.

[0668] (Application Example 2)

[0669] 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".

[0670] In modern times, travel planning has become complex due to the wide range of options and vast amounts of information available. Furthermore, it is difficult to automatically create and flexibly adapt travel plans optimized to the individual emotions and interests of travelers. Conventional systems often provide uniform plans without adequately considering travelers' emotions and individual needs, resulting in outcomes that do not maximize traveler satisfaction. This invention aims to solve these problems and provide travelers with individually optimized travel planning.

[0671] 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.

[0672] In this invention, the server includes information gathering means for receiving travel conditions from users, data gathering means for searching and obtaining information on tourist facilities and accommodations based on the collected travel conditions and emotional state of the users, schedule generation means for automatically generating a travel schedule using a generation AI model based on the acquired information and emotional data, reservation processing means for automatically executing reservations for tourist facilities and accommodations in conjunction with current information and environmental data, and notification display means for displaying the automatically generated travel schedule and reservation information in an interface that takes into account the user's emotions. This makes it possible to provide personalized travel plans based on the traveler's emotions and interests, thereby increasing the flexibility and satisfaction of the planning.

[0673] "Information gathering means" refers to input devices and software used to obtain travel conditions and emotional states from users.

[0674] "Data collection means" refers to devices or processes that collect information on tourist facilities and accommodations from a database based on acquired travel conditions and emotional states.

[0675] A "generative AI model" refers to artificial intelligence technology that analyzes acquired data and automatically creates an appropriate travel schedule.

[0676] "Schedule generation method" refers to the process of automatically creating an optimal schedule based on the user's travel purpose and emotions using a generation AI model.

[0677] "Reservation processing means" refers to devices or programs that automatically make reservations for tourist facilities and accommodations based on a generated travel schedule, taking into account current events and environmental data.

[0678] "Notification display means" refers to a method of displaying generated travel schedules and reservation information on the device in a way that takes the user's feelings into consideration.

[0679] "Emotional state" refers to information that indicates a user's psychological condition or mood, and is data obtained through voice, text, etc.

[0680] This invention is a system that generates travel plans based on the user's emotional state. This system primarily runs on devices such as smartphones and is supported by algorithms on a cloud server. The device acquires travel conditions, voice, and text data from the user. Smartphone hardware such as microphones and cameras are used for information gathering, and sentiment analysis tools such as the Google Cloud Natural Language API are employed for natural language processing.

[0681] Data collected by the device is sent to a cloud server via the internet. The server searches for and retrieves information on tourist facilities and accommodations based on the user's emotional state and travel conditions. Data retrieval is managed by a database system on Amazon Web Services (AWS), and the generated AI model utilizes machine learning frameworks such as TensorFlow and PyTorch to automatically generate travel schedules.

[0682] The schedule generation system analyzes collected information and emotional data to create a travel plan that includes the most suitable destinations and activities for the user. The generated schedule provides flexible planning that can accommodate future changes in emotions. It also takes current events and environmental data into consideration to proceed with the optimal schedule and booking process.

[0683] For example, if a user enters "I'm looking for a new experience," the system recognizes this feeling as a positive sense of adventure and suggests art exhibitions or new restaurants in the city. Reservations are automatically made with the relevant facilities, and the results are displayed on the terminal with an interface that takes the user's feelings into consideration.

[0684] An example of a prompt to input into the generating AI model is: "The user wants to have a new experience this weekend. Analyze their emotions and suggest the best travel plan for them. Please include information on local events in the plan and handle the arrangements."

[0685] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0686] Step 1:

[0687] The device collects travel conditions and emotional states from the user. Voice and text are used as input, and this data is analyzed for emotion and text using the Google Cloud Natural Language API, with the results obtained as output. This analysis identifies the user's current emotional state.

[0688] Step 2:

[0689] The data analyzed on the terminal is sent to the server via the internet. The server searches for information on tourist facilities and accommodations in a database on AWS based on the received emotional data and travel conditions. It collects data that matches the entered travel conditions and emotional state and provides the results as output.

[0690] Step 3:

[0691] The server uses the acquired information to automatically generate travel schedules using a generative AI model. It utilizes tourist facility data, accommodation data, and sentiment analysis results as inputs, performs schedule calculations based on these, and outputs an optimized schedule.

[0692] Step 4:

[0693] The server processes bookings based on the generated travel schedule, taking into account current events and environmental data. Bookings are automatically executed via an external interface, thereby providing a travel experience tailored to the user. The booking results are returned to the user as output.

[0694] Step 5:

[0695] The device receives schedule and reservation information from the server. This data is displayed through a user-friendly interface. The final output is a customized travel plan provided to the user.

[0696] 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.

[0697] 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.

[0698] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0699] 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.

[0700] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0701] 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.

[0702] 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.

[0703] 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.

[0704] 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."

[0705] 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.

[0706] 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.

[0707] 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.

[0708] 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.

[0709] 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.

[0710] 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.

[0711] 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.

[0712] 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.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] The following is further disclosed regarding the embodiments described above.

[0718] (Claim 1)

[0719] A means of collecting information to accept travel conditions from users,

[0720] A data collection method for searching and obtaining information on tourist facilities and accommodations based on the travel conditions of collected users,

[0721] A schedule generation method that automatically generates a travel schedule using an AI model based on acquired information,

[0722] A reservation processing means that automatically executes reservations for tourist facilities and accommodations according to the generated travel schedule,

[0723] A notification display means for displaying automatically generated travel schedules and reservation information to the user,

[0724] A system that includes this.

[0725] (Claim 2)

[0726] The system according to claim 1, wherein the reservation processing means makes reservations to affiliated facilities via an external interface.

[0727] (Claim 3)

[0728] The system according to claim 1, wherein the schedule generation means determines the priority of destinations based on the user's interests and constructs the order of visits using an optimization algorithm.

[0729] "Example 1"

[0730] (Claim 1)

[0731] A means including an information input device for receiving travel conditions from users,

[0732] Means including a data acquisition device for searching for and obtaining information on tourist destinations and accommodation facilities based on the travel conditions of the collected users,

[0733] A means including a schedule creation device that automatically generates a travel plan using an AI model based on acquired information,

[0734] A means including a reservation processing device that automatically executes reservations for tourist destinations and accommodations according to an automatically generated travel plan,

[0735] Means including a notification device for displaying automatically generated travel plans and reservation information to the user,

[0736] A system that includes this.

[0737] (Claim 2)

[0738] The system according to claim 1, wherein the reservation processing device makes reservations to affiliated facilities via external communication means.

[0739] (Claim 3)

[0740] The system according to claim 1, wherein the scheduling device determines the priority of destinations to visit based on the user's interests and preferences, and determines the order of visits using an optimization method.

[0741] "Application Example 1"

[0742] (Claim 1)

[0743] A recognition means for receiving travel conditions from users via voice,

[0744] A data collection means for searching and obtaining information on tourist resources and accommodation resources via communication means based on the travel conditions of collected users,

[0745] A schedule generation method that automatically generates and sequences travel itineraries using an AI model based on acquired information,

[0746] A means for automatically making reservations for tourist attractions and accommodations according to the generated travel itinerary,

[0747] A display means that notifies the user of automatically generated travel itinerary and reservation information through voice output and visual display,

[0748] A system that includes this.

[0749] (Claim 2)

[0750] The system according to claim 1, wherein the recognition means and the display means are connected to an internal processing unit and are operable by voice control.

[0751] (Claim 3)

[0752] The system according to claim 1, wherein the schedule generation means prioritizes destinations based on the user's interests and utilizes a dynamic scheduling algorithm for execution.

[0753] "Example 2 of combining an emotion engine"

[0754] (Claim 1)

[0755] A means of collecting data to accept travel conditions from users,

[0756] A means for analyzing the emotions of users based on collected data,

[0757] A means of acquiring information for collecting and obtaining information on tourist facilities and accommodations based on analyzed sentiment data,

[0758] A schedule generation method that automatically generates a travel schedule using an AI model based on acquired information and sentiment data,

[0759] A reservation processing means that automatically executes reservations for tourist facilities and accommodations according to the generated travel schedule,

[0760] A notification display means for displaying automatically generated travel schedules and reservation information in a manner that is considerate of the user's feelings,

[0761] A system that includes this.

[0762] (Claim 2)

[0763] The system according to claim 1, wherein the reservation processing means makes reservations to affiliated facilities via an external connection means.

[0764] (Claim 3)

[0765] The system according to claim 1, wherein the schedule generation means determines the priority of destinations to visit based on the user's emotional state and constructs the order of visits using an optimization method.

[0766] "Application example 2 when combining with an emotional engine"

[0767] (Claim 1)

[0768] A means of collecting information to accept travel conditions from users,

[0769] A data collection method for searching and obtaining information on tourist facilities and accommodations based on the travel conditions and emotional state of collected users,

[0770] A schedule generation method that automatically generates a travel schedule using an AI model based on acquired information and sentiment data,

[0771] A reservation processing means that automatically executes reservations for tourist facilities and accommodations in accordance with the generated travel schedule, in conjunction with current events information and environmental data.

[0772] A notification display means for displaying automatically generated travel schedules and reservation information in an interface that takes into consideration the user's feelings,

[0773] A system that includes this.

[0774] (Claim 2)

[0775] The system according to claim 1, wherein the reservation processing means makes reservations to affiliated facilities via an external interface, taking into account time slots determined based on emotional data.

[0776] (Claim 3)

[0777] The system according to claim 1, wherein the schedule generation means determines the priority of destinations based on the user's interests and emotional state, and constructs the order of visits using an optimization algorithm, thereby providing a flexible schedule that responds to changes in emotions. [Explanation of Symbols]

[0778] 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 recognition means for receiving travel conditions from users via voice, A data collection means for searching and obtaining information on tourist resources and accommodation resources via communication means based on the travel conditions of collected users, A schedule generation means that automatically generates and sequences a travel itinerary using an AI model based on acquired information, A means for automatically making reservations for tourist attractions and accommodations according to the generated travel itinerary, A display means that notifies the user of automatically generated travel itinerary and reservation information through voice output and visual display, A system that includes this.

2. The system according to claim 1, wherein the recognition means and the display means are connected to an internal processing unit and are operable by voice control.

3. The system according to claim 1, wherein the schedule generation means prioritizes destinations based on the user's interests and utilizes a dynamic scheduling algorithm for execution.

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