system

Abstract

We provide the system. [Solution] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities, A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants, A means for generating and presenting an optimal travel plan to the user based on the acquired data, After the aforementioned travel plan has been reviewed and modified by the user, a means for making online reservations for accommodation and transportation is provided. A means of sending a final itinerary to the user in order to provide them with a confirmed travel plan, 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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a conventional travel planning system, users had to separately check information such as travel schedules, budgets, regions, and activities, and make various reservations manually. For this reason, it took a great deal of time and effort to create a travel plan, and there was a possibility of reservation mistakes and overlooking information. Furthermore, it was difficult to flexibly change the plan based on the user's desires, and it was difficult to provide an ideal travel experience. The present invention aims to solve these problems and provide a system that automatically and efficiently generates a travel plan and consistently makes reservations up to the reservation stage.

Means for Solving the Problems

[0005] The present invention is a system that includes means for receiving information from a user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; and means for sending a final itinerary to the user to provide them with the confirmed travel plan. This allows the user to obtain an ideal travel plan without hassle and complete reservations automatically. Furthermore, since the plan can be flexibly modified according to the user's requests, the quality of the travel experience can be improved.

[0006] A "user" refers to an individual or group that uses a travel plan generation system to plan and book a trip.

[0007] "Terminal" refers to an electronic device used by a user to access the travel plan generation system, and includes devices such as smartphones, personal computers, and tablets.

[0008] A "server" refers to a central computer system that receives user input information and processes such as generating travel plans, querying databases, and making online reservations.

[0009] A "database" refers to an information management system that stores information on accommodations, tourist destinations, transportation, restaurants, etc., and provides the necessary data in response to queries from the server.

[0010] A "travel plan" refers to a schedule and activity plan that includes specific travel dates, places to visit, accommodations, and dining options, based on the user's input information.

[0011] A "schedule generation algorithm" refers to a series of calculation steps for automatically generating the optimal travel plan based on the user's preferences and constraints.

[0012] "Online booking" refers to the process of automatically making reservations for accommodations, transportation, and other services via the internet.

[0013] An "action plan" refers to a guide that presents the details of a finalized travel plan in list or schedule format for the user to refer to during their trip.

[0014] A "revision request" refers to a request that a user submits to the system, in which they input any changes or adjustments they wish to make to the presented travel plan.

[0015] The above are the definitions of the important words. [Brief explanation of the drawing]

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

[0017] 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.

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

[0033] As shown in Figure 2, in the data processing device 12, 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.

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

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

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

[0037] This invention relates to a travel plan generation system that allows users to easily create an ideal travel plan and even automatically make reservations. The system operates as follows:

[0038] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server.

[0039] The server queries the database based on the information received from the user and retrieves data on relevant accommodations, tourist attractions, transportation options, and restaurants. This aggregates information on the server that can serve as a travel option tailored to the user's preferences.

[0040] Next, the server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan. This travel plan includes sightseeing destinations, accommodations, transportation, and dining options, and is designed to meet the user's requirements. The generated travel plan is sent to the terminal and presented to the user.

[0041] The user reviews the proposed travel plan and enters any necessary modification requests. For example, they might want to add more time on a specific day or include additional places to visit. The device then sends the modification requests to the server.

[0042] The server regenerates the travel plan based on the user's revision requests. This time, the initial plan and the user's revision requests are integrated to generate an optimized new travel plan. The regenerated plan is sent to the terminal again for the user to review.

[0043] After the user reviews and approves the final plan, the server sequentially executes online reservations for accommodation and transportation. The server uses a reservation API to automatically make the necessary reservations. Once the reservations are complete, the user is notified and provided with the confirmed travel plan.

[0044] Finally, the server creates an itinerary based on the finalized travel plan and sends it to the device. This itinerary provides a detailed guide for the user to refer to during their trip.

[0045] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. The generated plan might include visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0046] Thus, the present invention aims to streamline the user's travel planning and booking process and provide an ideal travel experience.

[0047] The following describes the processing flow.

[0048] Step 1:

[0049] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The information entered by the user is formatted on the device and sent to the server as appropriate data packets.

[0050] Step 2:

[0051] The server receives information sent by the user and first parses it. Based on the results of the parsing, the server generates a query to the database. This query retrieves information such as accommodations, tourist attractions, transportation options, and restaurants from the database.

[0052] Step 3:

[0053] The database receives queries from the server and returns relevant information (accommodations, tourist attractions, transportation, restaurants, etc.). Based on the retrieved information, the server executes a schedule generation algorithm to generate the optimal travel plan that meets the user's requirements.

[0054] Step 4:

[0055] The server sends the generated travel plan to the terminal and presents it to the user. The user reviews the travel plan through the terminal. If the user is satisfied, they proceed to the next step; however, if they have any requests for revisions, they enter those requests.

[0056] Step 5:

[0057] When a user enters and submits a revision request, the device sends that information to the server. The server receives the revision request, runs the schedule generation algorithm again, and generates a new travel plan that reflects the revisions.

[0058] Step 6:

[0059] The server sends the regenerated travel plan to the device and presents it to the user again. The user reviews the plan again, and if they agree, they proceed to the next step. If they are dissatisfied, they enter their revision requests again and return to step 5.

[0060] Step 7:

[0061] Once the user finally approves the travel plan, the server executes online reservations for accommodation and transportation. It automatically makes the necessary reservations via a reservation API and monitors the reservation status in real time.

[0062] Step 8:

[0063] The server compiles information on completed reservations and notifies the user. Furthermore, it creates an itinerary based on the confirmed travel plan and sends it to the device.

[0064] Step 9:

[0065] Users receive an itinerary via their device and perform a final check before their trip. The itinerary includes a detailed schedule and booking information, which users use to plan their trip.

[0066] The above describes the specific processing steps in the present invention, which streamline the user's travel planning and booking process.

[0067] (Example 1)

[0068] 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."

[0069] Conventional travel planning and booking systems have the problem of being time-consuming and laborious, as users have to gather a lot of information themselves and make reservations individually. Furthermore, if the generated travel plan does not perfectly match the user's wishes, regeneration and modification are cumbersome, making efficient travel planning difficult. The present invention aims to solve these problems and provide a system that allows users to create an ideal travel plan without effort and complete reservations automatically.

[0070] 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.

[0071] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan using a schedule generation algorithm based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for integrating the user's modification requests using a generation AI model and regenerating an optimized travel plan again; and means for transmitting a final itinerary to provide the user with the confirmed travel plan. This enables the user to generate an ideal travel plan and complete reservations automatically without performing complex operations.

[0072] A "user" refers to an individual or group that uses the system to create travel plans and make reservations.

[0073] "Travel itinerary" refers to the period from the day the user starts their trip until the day it ends.

[0074] "Budget" refers to the maximum amount of money a user can spend on a trip.

[0075] "Region" refers to the place or area that the user wants to travel to.

[0076] "Desired activities" refer to the specific activities and experiences that the user wants to have during their trip.

[0077] "Means of receiving information" refers to an interface for receiving and inputting detailed travel information from users.

[0078] "Means of querying a database" refers to methods and systems for searching for data on suitable accommodations, tourist attractions, transportation options, and restaurants based on information provided by the user.

[0079] "Accommodation facilities" refer to places where users stay during their travels, such as hotels and inns.

[0080] A "tourist destination" refers to a place or landmark that a user would like to visit during their travels.

[0081] "Transportation" refers to the means of transport that users use to get around during their trip, such as trains, buses, and airplanes.

[0082] "Restaurants" refers to places where users eat during their trip.

[0083] A "schedule generation algorithm" refers to the calculation procedure used to create the optimal travel plan based on information entered by the user and data obtained from a database.

[0084] A "generative AI model" refers to a software model that utilizes machine learning and artificial intelligence technologies to automatically create a travel plan that best suits the user's preferences.

[0085] "Means of executing online reservations" refers to systems that automatically book accommodations and transportation on behalf of users.

[0086] An "action plan" refers to a detailed schedule outlining what a user will do and when during their trip.

[0087] "Optimization" refers to adjusting travel plans to best meet the user's needs and requirements.

[0088] A "revision request" refers to a user's request to change or add to a proposed travel plan.

[0089] "Regeneration" refers to the process of recreating a travel plan based on user requests for modifications.

[0090] This invention is a travel plan generation system aimed at enabling users to easily create ideal travel plans and automatically handle bookings. A detailed explanation of how to implement this system is provided below.

[0091] First, the user uses a device (for example, a PC or smartphone) to input their travel itinerary, budget, desired destination, and preferred activities. This input data is converted into a specific format by the device and sent to the server as JSON data, for example.

[0092] Next, the server queries the database based on the user information it has received. A database management system such as MySQL® or PostgreSQL is used to retrieve information about accommodations, tourist attractions, transportation, and restaurants from the database. The retrieved data includes a list of accommodations and tourist attractions that meet the user's criteria.

[0093] The server then generates a travel plan using a schedule generation algorithm. This algorithm utilizes generative AI models such as TENSORFLOW® and PyTorch. This generates an optimal schedule that takes into account the user's desired travel dates, budget, region, and activities to the greatest extent possible.

[0094] The generated travel plan is sent to the device and presented to the user. The user reviews this plan and enters any necessary revision requests. For example, if the user wants to change the place to visit on day 2, the revision request is sent from the device to the server. The server uses the AI ​​model again to integrate this revision request and generates a new, optimized travel plan. This regenerated plan is also sent to the device for the user to review again.

[0095] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. This reservation process utilizes the APIs of various services (e.g., Expedia and Airbnb APIs). This eliminates the need for the user to make individual reservations themselves.

[0096] Furthermore, an action plan is generated based on the finalized travel plan and sent to the device. This action plan includes details of places to visit, times, and modes of transportation, allowing the user to comfortably plan their trip based on it.

[0097] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. For example, a plan might be generated that includes visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0098] An example of a prompt sentence to input into a generating AI model is: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings. Please suggest a recommended travel plan."

[0099] As described above, this system aims to streamline users' travel planning and booking processes, and to provide them with an ideal travel experience.

[0100] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0101] Step 1:

[0102] Users use their devices to enter information about their travel itinerary, budget, region, and desired activities.

[0103] Input: Travel dates, budget, region, desired activities

[0104] As a concrete example, the user opens a travel plan creation application and enters into the input form, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. I want to see historical buildings."

[0105] Step 2:

[0106] The terminal converts the entered information into JSON format and sends it to the server.

[0107] Input: Travel information entered by the user

[0108] Output: Data in JSON format

[0109] Specifically, the device generates JSON data such as "{ "Dates": "August 1st - August 7th", "Budget": 100000, "Region": "Kyoto", "Activity": "Historical building sightseeing"}" and sends it to the server using an HTTP POST request.

[0110] Step 3:

[0111] The server queries the database based on the received data.

[0112] Input: User information in JSON format

[0113] Output: Information on accommodations, tourist attractions, transportation, and restaurants.

[0114] Specifically, the server executes an SQL query like "SELECT FROM hotels WHERE location='Kyoto' AND price <= 100000" to retrieve data on accommodations. It similarly queries the database for tourist attractions, transportation options, and restaurants.

[0115] Step 4:

[0116] The server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan.

[0117] Input: Information on accommodations, tourist attractions, transportation, and restaurants.

[0118] Output: Travel plan

[0119] In terms of specific operation, the server uses generative AI models such as TensorFlow to generate an optimal itinerary that aligns with the user's preferences. This itinerary includes a detailed schedule such as "August 1st: Arrive at Kyoto Station → Visit Kinkaku-ji Temple → Visit Ginkaku-ji Temple → Lunch at a Japanese restaurant."

[0120] Step 5:

[0121] The server sends the generated travel plan to the terminal.

[0122] Input: Generated travel plan

[0123] Output: Presentation of travel plan

[0124] Specifically, the server converts the generated travel plan into JSON format and sends it to the terminal as an HTTP response.

[0125] Step 6:

[0126] The user reviews the presented travel plan and enters any revision requests as needed.

[0127] Input: Travel plan

[0128] Output: Correction requests (if necessary)

[0129] In terms of specific actions, the user enters a modification request, such as "I want to change the place I'll visit on the second day," on the plan confirmation screen.

[0130] Step 7:

[0131] The device sends the correction request to the server.

[0132] Input: Correction Request

[0133] Output: Revised travel plan

[0134] Specifically, the terminal converts the correction request into JSON format and sends it to the server.

[0135] Step 8:

[0136] The server receives the correction request and generates an optimized travel plan again using the AI ​​model.

[0137] Input: Correction Request

[0138] Output: Regenerated travel plan

[0139] Specifically, the server integrates the initial travel plan with the requested revisions and then uses the generative AI model again to generate a new plan.

[0140] Step 9:

[0141] The user reviews and approves the final travel plan.

[0142] Input: Regenerated travel plan

[0143] Output: Final Approval

[0144] Specifically, the user reviews the regenerated travel plan on their device and presses the approve button.

[0145] Step 10:

[0146] The server makes online reservations for accommodations and transportation based on the final approved travel plan.

[0147] Input: Final approved travel plan

[0148] Output: Reservation confirmation

[0149] Specifically, the server uses an API to automatically book accommodations and transportation, and retrieves booking confirmation information.

[0150] Step 11:

[0151] Based on the confirmed travel plan and reservation information, an itinerary is created and sent to the device.

[0152] Input: Final travel plans and booking confirmation information

[0153] Output: Action plan

[0154] Specifically, the server integrates the schedule and reservation information, converts the action plan into JSON format, and sends it to the terminal.

[0155] In this way, users can create their ideal travel plan with minimal effort and have bookings completed automatically.

[0156] (Application Example 1)

[0157] 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."

[0158] Traditional travel planning systems struggled to automatically generate optimal travel plans and handle bookings based on user input such as itinerary, budget, region, and desired activities. Furthermore, creating flexible travel plans that incorporated user preferences often required significant effort and time, hindering a positive user experience. Additionally, the process of regenerating optimized plans when users modified their existing ones was cumbersome, highlighting the lack of sufficient automation.

[0159] 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.

[0160] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; and means for generating an optimal travel plan using a generation AI model based on the obtained data and presenting it to the user. This enables the user to easily create an ideal travel plan and efficiently make reservations. Furthermore, prompt messages can be generated based on user requests for modifications, and the travel plan can be regenerated, enabling the provision of flexible travel plans.

[0161] A "user" is someone who creates a travel plan by entering information about their travel dates, budget, region, and desired activities.

[0162] A "travel plan" is a proposed itinerary generated based on the travel dates, budget, region, and desired activities set by the user.

[0163] A "generative AI model" is an artificial intelligence computational model used to automatically optimize and generate travel plans.

[0164] A "database" is a storage device that stores information about accommodations, tourist destinations, transportation, and restaurants.

[0165] A "schedule generation algorithm" is a computational method for generating the optimal travel plan using user input information and database information.

[0166] A "prompt" is a document-formatted instruction given to a generative AI model to generate a travel plan.

[0167] An "API" is an application programming interface used by servers to automatically execute online reservations for accommodations and transportation.

[0168] "Online booking" refers to the process of making reservations for accommodations and transportation via the internet.

[0169] An "action plan sheet" is a table that contains specific instructions for the user to refer to during their trip, based on a finalized travel plan.

[0170] This invention is a system for users to create travel plans and make reservations automatically. Specific embodiments are described below.

[0171] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server. The hardware used is mainly smartphones and smart glasses, and the software utilizes JavaScript® and React.js as front-end technologies.

[0172] The server queries the database based on the received user information to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants. The database used is PostgreSQL. Next, an AI model (e.g., GPT-3®) is used to generate an optimal travel plan based on the retrieved data. The generated plan is sent to the terminal and presented to the user. The server uses a server-side framework such as Django for this process.

[0173] For example, if a user enters "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," the server will retrieve suitable accommodations, tourist attractions, transportation options, and restaurants from its database and generate the optimal plan.

[0174] When a user reviews a proposed travel plan and enters further modification requests, the AI ​​model generates prompts based on those requests and then creates an optimal plan again. For example, if a user requests to "add Ginkaku-ji Temple after visiting Kinkaku-ji Temple," the new prompt will be changed to "After visiting Kinkaku-ji Temple, I would also like to visit Ginkaku-ji Temple." This allows for flexible regeneration of travel plans.

[0175] Based on the confirmed travel plan, the server automatically makes online reservations for accommodations and transportation via API. Once the reservations are complete, the user is notified of the confirmed travel plan, and a final itinerary is generated. This itinerary provides a detailed travel plan that the user can refer to during their trip.

[0176] Thus, this invention aims to streamline the user's travel planning and booking process, and to provide an ideal travel experience.

[0177] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0178] Step 1:

[0179] The user enters information about their travel itinerary, budget, region, and desired activities into the device.

[0180] The input information includes departure date, return date, budget, desired destination, and specific activities. This information is converted to JSON format on the device and sent to the server.

[0181] Step 2:

[0182] The server analyzes the received user information and queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[0183] Input: User's travel information (e.g., dates, budget, region, activities)

[0184] Data processing: Query the PostgreSQL database using SQL to retrieve relevant information.

[0185] Output: Data on applicable accommodations, tourist attractions, transportation, and restaurants.

[0186] Step 3:

[0187] The server generates an optimal travel plan using an AI model (e.g., GPT-3) based on the acquired data, and presents it to the user.

[0188] Input: Candidate data retrieved from the database

[0189] Data processing: Input prompts into a generative AI model to generate travel plans.

[0190] Output: Draft travel plan generated

[0191] Step 4:

[0192] The user reviews the presented travel plan and enters any necessary modification requests into the terminal.

[0193] Input: Generated travel plan and user modification requests

[0194] Output: Information including correction requests

[0195] Step 5:

[0196] The server generates a prompt message based on the correction request and then uses the generation AI model again to generate a new travel plan.

[0197] Input: Correction Request

[0198] Data processing: Generate new prompt messages based on the requested modifications.

[0199] Data processing: Re-input data into the generative AI model to obtain a regenerated travel plan.

[0200] Output: Regenerated travel plan

[0201] Step 6:

[0202] After the user reviews and approves the final plan, the server automatically makes online reservations for accommodation and transportation via API.

[0203] Input: Final travel plan

[0204] Data processing: Execute online reservations via API

[0205] Output: Information confirming the reservation has been completed.

[0206] Step 7:

[0207] Based on the finalized travel plan, the server generates a detailed itinerary and sends it to the user's device. This provides the user with a specific guide to refer to during their trip.

[0208] Input: Confirmed travel plan

[0209] Data processing: Create an action plan based on the travel plan.

[0210] Output: Action Plan

[0211] 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.

[0212] This invention combines a travel plan generation system with an emotion engine, aiming to automatically optimize travel plans based on the user's emotional information. The system consists of a terminal, server, database, and emotion engine. Furthermore, the system is designed to automate travel plan generation and booking, thereby improving the user experience.

[0213] First, the user enters information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device receives the user's input and sends it to a server. Simultaneously, an emotion engine collects and analyzes emotional data from the user's tone of voice, facial expressions, text input, etc. This allows the user's current emotional state to be understood in real time.

[0214] The server receives the transmitted information and sentiment data and generates queries that take the user's emotional state into account. For example, if the user is feeling stressed, the system will adjust its recommendations to prioritize relaxing tourist destinations and activities. Using these queries, the server searches the database to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants.

[0215] Based on the acquired data, the server executes a schedule generation algorithm to generate a travel plan optimized for the user's emotional state. The generated plan is sent to the terminal and presented to the user.

[0216] The user reviews the presented travel plan and, if they have any complaints or suggestions for improvement, enters revision requests. The emotion engine analyzes the user's emotions at this point as well, recognizing, for example, that the user is feeling anxious about a particular part of the plan. The device then sends the revision requests and emotion data to the server.

[0217] The server runs the schedule generation algorithm again, generating a new travel plan that reflects the sentiment data and requested modifications. This new travel plan is sent to the terminal again and presented to the user. This process is repeated until the user is satisfied with the final plan.

[0218] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. All necessary reservations are completed via the reservation API, and the server notifies the user of the reservation completion information and creates an itinerary based on the confirmed travel plan. This itinerary is then sent to the user's device and provided to them.

[0219] As a concrete example, consider a scenario where a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice. In this case, the server prioritizes including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan is generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server automatically makes reservations for accommodation and Shinkansen tickets, and a detailed itinerary is provided to the device.

[0220] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans that better suit individual needs.

[0221] The following describes the processing flow.

[0222] Step 1:

[0223] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device formats the entered information and sends it to the server as data packets.

[0224] Step 2:

[0225] Simultaneously, the device activates its emotion engine and collects emotional data from the user's voice, facial expressions, and input. This emotional data is then analyzed, allowing the user's current emotional state to be understood in real time.

[0226] Step 3:

[0227] The server receives travel information and emotional data from the user and uses this information to generate queries for the database. For example, if a user is experiencing stress, the server will prioritize selecting relaxing tourist destinations and activities.

[0228] Step 4:

[0229] The server sends the generated query to the database and retrieves data on relevant accommodations, tourist attractions, transportation, and restaurants. The database returns the relevant data to the server according to the query.

[0230] Step 5:

[0231] The server executes a schedule generation algorithm based on the acquired data, generating a travel plan optimized for the user's emotional state. The generated travel plan is sent to the terminal and presented to the user.

[0232] Step 6:

[0233] Users review their travel plans through their devices. If they have any complaints or suggestions for improvement regarding specific dates or destinations, they input their requests for revisions into their devices. The emotion engine continues to analyze the user's emotions throughout this process, detecting changes in their feelings towards specific points.

[0234] Step 7:

[0235] The device sends the user's revision requests and sentiment data to the server. The server runs the schedule generation algorithm again and generates a new travel plan that reflects the revision requests and sentiment data.

[0236] Step 8:

[0237] The server sends the new travel plan to the device and presents it to the user again. This revision and confirmation process is repeated until the user is satisfied with the final plan.

[0238] Step 9:

[0239] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. It uses a reservation API to make the necessary reservations and compiles all the completed reservation information.

[0240] Step 10:

[0241] The server notifies the user of the booking confirmation and creates a detailed itinerary based on the confirmed travel plan. This itinerary is sent to the user's device, and the user performs a final check before traveling.

[0242] In this way, this system, which incorporates an emotion engine, can significantly improve the user experience by automatically generating optimal travel plans based on the user's emotional information and efficiently handling the booking process.

[0243] (Example 2)

[0244] 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".

[0245] Conventional travel plan generation systems generate plans based on basic user information, but they do not take into account the user's emotional state, making it difficult to provide travel plans that truly satisfy the user. Furthermore, when modifying a plan after it has been generated, it is difficult to adequately reflect the user's emotions and wishes, resulting in a poor user experience. In addition, the booking process was not fully automated, requiring users to make reservations manually, which reduced convenience. This invention aims to solve these problems and provide optimal travel plans based on the user's emotions.

[0246] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for transmitting the received information to the server; means including an emotion engine for collecting and analyzing the user's emotion data; means for generating queries based on the received information and the analyzed emotion data, querying a database, and obtaining data on relevant accommodations, tourist attractions, transportation, and restaurants; means for executing a schedule generation algorithm based on the obtained data to generate an optimal travel plan and present it to the user; means for generating a new travel plan after the user has confirmed and modified the travel plan, reflecting the modification requests and emotion data; means for executing online reservations for accommodations and transportation based on the final travel plan; and means for transmitting a final itinerary to the user to provide them with the confirmed travel plan. This makes it possible to analyze the user's emotion data in real time and provide an optimal travel plan that reflects it. Furthermore, the automation of the reservation procedure reduces the effort required from the user and improves convenience.

[0247] A "user" is an individual or group that uses the travel plan generation system to create a travel plan.

[0248] "Travel itinerary" refers to information that indicates the range of dates within which a user plans their trip.

[0249] "Budget" refers to the amount of money a user plans to spend on their trip.

[0250] "Region" refers to information that indicates the place the user wishes to travel to.

[0251] "Desired activities" refers to information about specific activities or experiences that the user wants to do during their trip.

[0252] A "device" refers to an electronic device (e.g., smartphone, tablet, or personal computer) that a user uses to input travel information and to review and modify their travel plan.

[0253] A "server" is a computer system that receives and processes information from users and generates and provides travel plans.

[0254] "Emotional data" refers to data about a user's emotional state, collected from the tone of their voice, facial expressions, text input, and other sources.

[0255] An "emotion engine" is software or a system used to collect and analyze user emotional data.

[0256] A "query" is a search instruction generated from a database to retrieve specific information.

[0257] A "database" is an information management system that stores information necessary for generating travel plans, such as accommodations, tourist destinations, transportation options, and restaurants.

[0258] A "schedule generation algorithm" refers to the mathematical methods and calculation procedures used to calculate and generate the optimal travel plan based on acquired data.

[0259] "Online booking" refers to the automated process of making reservations for accommodations and transportation via the internet.

[0260] An "action plan" is a document created based on a finalized travel plan, outlining the detailed schedule that the user should follow during their trip.

[0261] This invention relates to a system that automatically optimizes travel plans based on user sentiment information. This system consists of a terminal, a server, a database, and a sentiment engine. Specific embodiments are described below.

[0262] First, users enter information about their travel dates, budget, region, and desired activities through a smartphone app or website. The app or website used consists of a frontend using React or Vue.js and a backend using Node.js or Django. For example, a user might enter a prompt like this: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings."

[0263] The device sends the information entered by the user to the server. Simultaneously, an emotion engine (e.g., Microsoft® Azure® Emotion API or IBM Watson® Tone Analyzer) collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. This allows the system to understand the user's current emotional state.

[0264] The server integrates received user information and emotional data to generate queries tailored to the user's emotional state. For example, if a user is experiencing high stress levels, the server will prioritize recommending relaxing tourist destinations. Using these queries, the server searches databases such as MongoDB or MySQL to retrieve data on relevant accommodations, tourist destinations, transportation options, and restaurants.

[0265] Based on the acquired data, the server executes a schedule generation algorithm. For example, it uses Python's Scikit-learn or TensorFlow to generate the optimal travel plan. The generated plan is sent to the terminal and presented to the user.

[0266] When a user reviews a presented travel plan and enters requests for revisions, the emotion engine analyzes the user's emotions at this point and sends the emotion data and revision requests to the server. The server then runs the schedule generation algorithm again to generate a new travel plan that reflects the revision requests and emotion data. This process is repeated until the user is satisfied with the final plan.

[0267] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. The necessary reservations are completed via a booking API (e.g., Booking.com API or Google® Travel API), and the server notifies the user of the reservation completion information. Then, based on the confirmed travel plan, an itinerary is created and sent to the user's device.

[0268] Thus, by utilizing user emotional data, the present invention can provide travel plans that better suit individual needs and significantly improve the user experience. Furthermore, the automation of booking procedures reduces user effort and improves convenience.

[0269] As described above, the present invention realizes the optimization of travel plans based on user emotional data.

[0270] The flow of the specific process in Example 2 will be described with reference to FIG. 13.

[0271] Step 1:

[0272] Input of user information

[0273] The user inputs information regarding the travel schedule, budget, region, and desired activities through a smartphone application or a website. For example, the user inputs a prompt sentence such as "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. The main means of transportation is the bullet train, and I want to see historical buildings." This is the input data.

[0274] Specific operation:

[0275] The user fills in the necessary information in the input form and presses the "Send" button.

[0276] Input:

[0277] Information on the travel schedule, budget, region, and desired activities input by the user.

[0278] Output:

[0279] The user's travel plan request data.

[0280] Step 2:

[0281] Transmission of user information

[0282] The terminal transmits the information input by the user to the server. HTTPS is used as the transmission protocol.

[0283] Specific operation:

[0284] When the user presses the "Send" button, the terminal transmits the input data to the server through HTTPS communication.

[0285] Input:

[0286] User's travel plan request data.

[0287] Output:

[0288] User information sent to the server.

[0289] Step 3:

[0290] Collection and analysis of emotion data

[0291] The emotion engine collects and analyzes emotion data in real time from the tone of the user's voice, expressions, and text input. The Microsoft Azure Emotion API or the IBM Watson Tone Analyzer is used for the emotion engine.

[0292] Specific operations:

[0293] Collect data from the microphone, camera, and keyboard input installed on the terminal and pass it to the emotion engine. The emotion engine analyzes these data.

[0294] Input:

[0295] Tone of voice, expression, and text input data obtained from the terminal.

[0296] Output:

[0297] Analyzed user emotion data.

[0298] Step 4:

[0299] Query generation and database query

[0300] The server generates a query based on the user's input information and the analyzed emotion data and queries the database. This obtains data on optimal accommodation facilities, tourist attractions, transportation means, and restaurants.

[0301] Specific operations:

[0302] The server integrates user information and sentiment data, and generates a query that prioritizes tourist destinations where users can relax when they are feeling high stress. The generated query is sent to the database to obtain appropriate data.

[0303] Input:

[0304] User information and analyzed sentiment data.

[0305] Output:

[0306] Data on accommodation facilities, tourist destinations, transportation means, and restaurants obtained from the database.

[0307] Step 5:

[0308] Execute the schedule generation algorithm

[0309] Based on the obtained data, the server executes a schedule generation algorithm (e.g., an algorithm using TensorFlow) to generate an optimal travel plan.

[0310] Specific operations:

[0311] The server inputs the obtained data into the schedule generation algorithm to calculate an optimal schedule. The generated plan is sent to the terminal.

[0312] Input:

[0313] Necessary data obtained from the database.

[0314] Output:

[0315] The generated travel plan.

[0316] Step 6:

[0317] Presentation and modification of travel plans

[0318] The terminal presents the generated travel plan to the user. The user reviews the plan and enters any desired modifications. At this point, the emotion engine continues to collect and analyze the user's emotional data and sends it to the server.

[0319] Specific actions:

[0320] The device displays the travel plan on its screen, and when the user enters any requested modifications, the device sends them to the server.

[0321] input:

[0322] Generated travel plans and user sentiment data.

[0323] output:

[0324] Data with requested corrections and sentiment data.

[0325] Step 7:

[0326] Generating a readjustment plan

[0327] Based on the requested changes and sentiment data, the server runs the schedule generation algorithm again to generate a new travel plan. This process is repeated until the user is satisfied.

[0328] Specific actions:

[0329] The server inputs the requested correction data and sentiment data into an algorithm, calculates and generates a new plan, and sends the generated new plan to the terminal.

[0330] input:

[0331] Data requested for correction and user sentiment data.

[0332] output:

[0333] A new travel plan.

[0334] Step 8:

[0335] Final plan confirmation and booking

[0336] Once the user approves the final travel plan, the server automatically makes online reservations for accommodation and transportation. Reservation APIs (e.g., Booking.com API, Google Travel API) are used for booking.

[0337] Specific actions:

[0338] The server sends the final plan information to the reservation API and completes the necessary reservation.

[0339] input:

[0340] The final travel plan.

[0341] output:

[0342] Reservation confirmation information.

[0343] Step 9:

[0344] Action plan provided

[0345] The server creates an itinerary based on the final travel plan and sends it to the user's device. The user then reviews the itinerary through their device.

[0346] Specific actions:

[0347] The server generates an action plan and sends it to the terminal. The user checks it on the terminal.

[0348] input:

[0349] Final travel plan.

[0350] output:

[0351] Action plan.

[0352] The above outlines the specific processing steps of the travel plan generation system.

[0353] (Application Example 2)

[0354] 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".

[0355] Conventional travel plan generation systems provided optimal travel plans based on the travel dates, budget, region, and desired activities specified by the user. However, because they could not take into account the user's emotional state, the plans often did not necessarily satisfy the user. As a result, users may experience stress and dissatisfaction, potentially impairing the overall user experience of the travel plan. Therefore, the present invention aims to provide a system that utilizes the user's emotional information to automatically generate the travel plan that will satisfy the user the most.

[0356] 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.

[0357] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for transmitting a final itinerary to the user to provide them with the confirmed travel plan; means for collecting and analyzing the user's emotional data using an emotional engine; and means for optimizing the travel plan based on the emotional data. This makes it possible to provide a travel plan optimized for the user's emotional state, thereby improving the user experience.

[0358] A "user" is an individual or group that uses the travel plan generation system.

[0359] "Travel itinerary" refers to the range of dates the user wishes to travel.

[0360] "Budget" refers to the total amount of money a user plans to spend on their trip.

[0361] A "region" is a geographical location that a user wishes to visit.

[0362] "Desired activities" refer to the activities and events that the user would like to participate in during their trip.

[0363] A "database" is a system that stores information on accommodations, tourist attractions, transportation, restaurants, and more.

[0364] An "emotion engine" is a configuration of software and hardware used to collect and analyze user emotional data.

[0365] "Emotional data" refers to information about a user's emotional state obtained from their tone of voice, facial expressions, text input, etc.

[0366] A "travel plan" is a specific itinerary generated based on the user's wishes and emotional state.

[0367] An "action plan" is a detailed schedule created based on a finalized travel plan.

[0368] "Online booking" refers to the process of automatically making reservations for accommodations and transportation via the internet.

[0369] A "schedule generation algorithm" is a set of calculations that analyzes user data to generate the optimal travel plan.

[0370] A "request for revision" is input information in which a user requests changes or improvements to the travel plan presented.

[0371] This invention relates to a system that automatically optimizes travel plans based on a user's emotional information. This system consists of a terminal, a server, a database, and an emotional engine.

[0372] First, users enter information about their travel dates, budget, region, and desired activities into a dedicated app or website on their device. An example of a specific prompt message is: "Please enter the duration of your trip, budget, and desired destinations and activities. We will also analyze your emotional state to suggest the best travel plan for you. For example, if you are feeling stressed, we will prioritize including places where you can relax."

[0373] When a user enters information, the terminal sends that information to the server. Simultaneously, the emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc. The emotion engine identifies the emotional state in real time, for example, using OpenCV or other emotion analysis software.

[0374] The server receives the user's information and emotional data analyzed by the emotion engine. Based on this data, the server runs a schedule generation algorithm to generate queries optimized for the user's emotional state. For example, if the user is seeking relaxation, relaxing tourist destinations and activities will be prioritized in the plan.

[0375] The server uses the generated query to look up data on the database for relevant accommodations, tourist attractions, transportation, and restaurants. Based on this retrieved data, the server generates an optimal travel plan and sends it to the terminal.

[0376] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal. The emotion engine also re-analyzes the user's emotions at this point, identifying any areas of anxiety. The revision requests and emotion data are sent back to the server, which then runs the schedule generation algorithm again to generate a new plan that reflects the emotion data and revision requests.

[0377] If the user is ultimately satisfied with the travel plan, the server automatically makes online reservations for accommodation and transportation. It utilizes a reservation API to complete the necessary booking procedures and notifies the user of the booking confirmation. Then, it creates an itinerary based on the confirmed travel plan and sends it to the user's device for their use.

[0378] For example, if a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice, the server will prioritize including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan will be generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server will automatically make reservations for accommodation and Shinkansen tickets, and a detailed itinerary will be provided to the device.

[0379] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans tailored to individual needs.

[0380] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0381] Step 1:

[0382] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website.

[0383] Input: User information (travel itinerary, budget, region, desired activities)

[0384] Output: Sends input information to the terminal.

[0385] Step 2:

[0386] The terminal sends the entered information to the server.

[0387] Input: User information

[0388] Output: Information sent to the server

[0389] Step 3:

[0390] The emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc.

[0391] Input: User voice, facial expressions, text input

[0392] Output: Sentiment data

[0393] Specific operation: Use OpenCV and other sentiment analysis software to identify emotional states in real time.

[0394] Step 4:

[0395] The server receives the user's information and sentiment data that was sent.

[0396] Input: User information, sentiment data

[0397] Output: Data used to generate queries

[0398] Step 5:

[0399] The server executes a schedule generation algorithm based on the user information and sentiment data it receives, and generates the optimal query.

[0400] Input: User information, sentiment data

[0401] Output: Optimized query

[0402] Specific behavior: If the user is looking for relaxation, the query will include relaxing tourist destinations and activities.

[0403] Step 6:

[0404] The server queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[0405] Input: Optimized query

[0406] Output: Accommodation, tourist attractions, transportation, and restaurant data

[0407] Step 7:

[0408] The server generates an optimal travel plan based on the data it acquires and sends it to the device.

[0409] Input: Data on accommodations, tourist attractions, transportation, and restaurants.

[0410] Output: Optimal travel plan

[0411] Step 8:

[0412] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal.

[0413] Input: Feedback on travel plans

[0414] Output: Correction Request

[0415] Step 9:

[0416] The device sends correction requests and sentiment data to the server.

[0417] Input: Correction requests, sentiment data

[0418] Output: Send correction requests and sentiment data to the server.

[0419] Step 10:

[0420] The server runs the schedule generation algorithm again and generates a new plan that reflects the sentiment data and revision requests.

[0421] Input: Correction requests, sentiment data

[0422] Output: New travel plan

[0423] Specific action: If the user requests further relaxation, more relaxing options will be included in the revised plan.

[0424] Step 11:

[0425] If the user is satisfied with the final travel plan, the server will make online reservations for accommodation and transportation.

[0426] Input: Final travel plan

[0427] Output: Reservation confirmation information

[0428] Specific operation: Executes booking procedures for accommodations and transportation via the booking API.

[0429] Step 12:

[0430] The server creates an action plan based on the confirmed travel plan and sends it to the terminal.

[0431] Input: Booking confirmation information, confirmed travel plan

[0432] Output: Action Plan

[0433] Specific actions: Generate an action plan and provide it to the user to guide them through their trip.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] [Second Embodiment]

[0438] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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".

[0450] This invention relates to a travel plan generation system that allows users to easily create an ideal travel plan and even automatically make reservations. The system operates as follows:

[0451] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server.

[0452] The server queries the database based on the information received from the user and retrieves data on relevant accommodations, tourist attractions, transportation options, and restaurants. This aggregates information on the server that can serve as a travel option tailored to the user's preferences.

[0453] Next, the server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan. This travel plan includes sightseeing destinations, accommodations, transportation, and dining options, and is designed to meet the user's requirements. The generated travel plan is sent to the terminal and presented to the user.

[0454] The user reviews the proposed travel plan and enters any necessary modification requests. For example, they might want to add more time on a specific day or include additional places to visit. The device then sends the modification requests to the server.

[0455] The server regenerates the travel plan based on the user's revision requests. This time, the initial plan and the user's revision requests are integrated to generate an optimized new travel plan. The regenerated plan is sent to the terminal again for the user to review.

[0456] After the user reviews and approves the final plan, the server sequentially executes online reservations for accommodation and transportation. The server uses a reservation API to automatically make the necessary reservations. Once the reservations are complete, the user is notified and provided with the confirmed travel plan.

[0457] Finally, the server creates an itinerary based on the finalized travel plan and sends it to the device. This itinerary provides a detailed guide for the user to refer to during their trip.

[0458] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. The generated plan might include visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0459] Thus, the present invention aims to streamline the user's travel planning and booking process and provide an ideal travel experience.

[0460] The following describes the processing flow.

[0461] Step 1:

[0462] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The information entered by the user is formatted on the device and sent to the server as appropriate data packets.

[0463] Step 2:

[0464] The server receives information sent by the user and first parses it. Based on the results of the parsing, the server generates a query to the database. This query retrieves information such as accommodations, tourist attractions, transportation options, and restaurants from the database.

[0465] Step 3:

[0466] The database receives queries from the server and returns relevant information (accommodations, tourist attractions, transportation, restaurants, etc.). Based on the retrieved information, the server executes a schedule generation algorithm to generate the optimal travel plan that meets the user's requirements.

[0467] Step 4:

[0468] The server sends the generated travel plan to the terminal and presents it to the user. The user reviews the travel plan through the terminal. If the user is satisfied, they proceed to the next step; however, if they have any requests for revisions, they enter those requests.

[0469] Step 5:

[0470] When a user enters and submits a revision request, the device sends that information to the server. The server receives the revision request, runs the schedule generation algorithm again, and generates a new travel plan that reflects the revisions.

[0471] Step 6:

[0472] The server sends the regenerated travel plan to the device and presents it to the user again. The user reviews the plan again, and if they agree, they proceed to the next step. If they are dissatisfied, they enter their revision requests again and return to step 5.

[0473] Step 7:

[0474] Once the user finally approves the travel plan, the server executes online reservations for accommodation and transportation. It automatically makes the necessary reservations via a reservation API and monitors the reservation status in real time.

[0475] Step 8:

[0476] The server compiles information on completed reservations and notifies the user. Furthermore, it creates an itinerary based on the confirmed travel plan and sends it to the device.

[0477] Step 9:

[0478] Users receive an itinerary via their device and perform a final check before their trip. The itinerary includes a detailed schedule and booking information, which users use to plan their trip.

[0479] The above describes the specific processing steps in the present invention, which streamline the user's travel planning and booking process.

[0480] (Example 1)

[0481] 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".

[0482] Conventional travel planning and booking systems have the problem of being time-consuming and laborious, as users have to gather a lot of information themselves and make reservations individually. Furthermore, if the generated travel plan does not perfectly match the user's wishes, regeneration and modification are cumbersome, making efficient travel planning difficult. The present invention aims to solve these problems and provide a system that allows users to create an ideal travel plan without effort and complete reservations automatically.

[0483] 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.

[0484] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan using a schedule generation algorithm based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for integrating the user's modification requests using a generation AI model and regenerating an optimized travel plan again; and means for transmitting a final itinerary to provide the user with the confirmed travel plan. This enables the user to generate an ideal travel plan and complete reservations automatically without performing complex operations.

[0485] A "user" refers to an individual or group that uses the system to create travel plans and make reservations.

[0486] "Travel itinerary" refers to the period from the day the user starts their trip until the day it ends.

[0487] "Budget" refers to the maximum amount of money a user can spend on a trip.

[0488] "Region" refers to the place or area that the user wants to travel to.

[0489] "Desired activities" refer to the specific activities and experiences that the user wants to have during their trip.

[0490] "Means of receiving information" refers to an interface for receiving and inputting detailed travel information from users.

[0491] "Means of querying a database" refers to methods and systems for searching for data on suitable accommodations, tourist attractions, transportation options, and restaurants based on information provided by the user.

[0492] "Accommodation facilities" refer to places where users stay during their travels, such as hotels and inns.

[0493] A "tourist destination" refers to a place or landmark that a user would like to visit during their travels.

[0494] "Transportation" refers to the means of transport that users use to get around during their trip, such as trains, buses, and airplanes.

[0495] "Restaurants" refers to places where users eat during their trip.

[0496] A "schedule generation algorithm" refers to the calculation procedure used to create the optimal travel plan based on information entered by the user and data obtained from a database.

[0497] A "generative AI model" refers to a software model that utilizes machine learning and artificial intelligence technologies to automatically create a travel plan that best suits the user's preferences.

[0498] "Means of executing online reservations" refers to systems that automatically book accommodations and transportation on behalf of users.

[0499] An "action plan" refers to a detailed schedule outlining what a user will do and when during their trip.

[0500] "Optimization" refers to adjusting travel plans to best meet the user's needs and requirements.

[0501] A "revision request" refers to a user's request to change or add to a proposed travel plan.

[0502] "Regeneration" refers to the process of recreating a travel plan based on user requests for modifications.

[0503] This invention is a travel plan generation system aimed at enabling users to easily create ideal travel plans and automatically handle bookings. A detailed explanation of how to implement this system is provided below.

[0504] First, the user uses a device (for example, a PC or smartphone) to input their travel itinerary, budget, desired destination, and preferred activities. This input data is converted into a specific format by the device and sent to the server as JSON data, for example.

[0505] Next, the server queries the database based on the user information it received. A database management system such as MySQL or PostgreSQL is used to retrieve information about accommodations, tourist attractions, transportation, and restaurants from the database. The retrieved data includes a list of accommodations and tourist attractions that meet the user's criteria.

[0506] The server then generates a travel plan using a schedule generation algorithm. This algorithm utilizes generative AI models such as TensorFlow or PyTorch. This generates an optimal schedule that takes into account the user's desired travel dates, budget, region, and activities to the greatest extent possible.

[0507] The generated travel plan is sent to the device and presented to the user. The user reviews this plan and enters any necessary revision requests. For example, if the user wants to change the place to visit on day 2, the revision request is sent from the device to the server. The server uses the AI ​​model again to integrate this revision request and generates a new, optimized travel plan. This regenerated plan is also sent to the device for the user to review again.

[0508] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. This reservation process utilizes the APIs of various services (e.g., Expedia and Airbnb APIs). This eliminates the need for the user to make individual reservations themselves.

[0509] Furthermore, an action plan is generated based on the finalized travel plan and sent to the device. This action plan includes details of places to visit, times, and modes of transportation, allowing the user to comfortably plan their trip based on it.

[0510] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. For example, a plan might be generated that includes visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0511] An example of a prompt sentence to input into a generating AI model is: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings. Please suggest a recommended travel plan."

[0512] As described above, this system aims to streamline users' travel planning and booking processes, and to provide them with an ideal travel experience.

[0513] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0514] Step 1:

[0515] Users use their devices to enter information about their travel itinerary, budget, region, and desired activities.

[0516] Input: Travel dates, budget, region, desired activities

[0517] As a concrete example, the user opens a travel plan creation application and enters into the input form, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. I want to see historical buildings."

[0518] Step 2:

[0519] The terminal converts the entered information into JSON format and sends it to the server.

[0520] Input: Travel information entered by the user

[0521] Output: Data in JSON format

[0522] Specifically, the device generates JSON data such as "{ "Dates": "August 1st - August 7th", "Budget": 100000, "Region": "Kyoto", "Activity": "Historical building sightseeing"}" and sends it to the server using an HTTP POST request.

[0523] Step 3:

[0524] The server queries the database based on the received data.

[0525] Input: User information in JSON format

[0526] Output: Information on accommodations, tourist attractions, transportation, and restaurants.

[0527] Specifically, the server executes an SQL query like "SELECT FROM hotels WHERE location='Kyoto' AND price <= 100000" to retrieve data on accommodations. It similarly queries the database for tourist attractions, transportation options, and restaurants.

[0528] Step 4:

[0529] The server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan.

[0530] Input: Information on accommodations, tourist attractions, transportation, and restaurants.

[0531] Output: Travel plan

[0532] In terms of specific operation, the server uses generative AI models such as TensorFlow to generate an optimal itinerary that aligns with the user's preferences. This itinerary includes a detailed schedule such as "August 1st: Arrive at Kyoto Station → Visit Kinkaku-ji Temple → Visit Ginkaku-ji Temple → Lunch at a Japanese restaurant."

[0533] Step 5:

[0534] The server sends the generated travel plan to the terminal.

[0535] Input: Generated travel plan

[0536] Output: Presentation of travel plan

[0537] Specifically, the server converts the generated travel plan into JSON format and sends it to the terminal as an HTTP response.

[0538] Step 6:

[0539] The user reviews the presented travel plan and enters any revision requests as needed.

[0540] Input: Travel plan

[0541] Output: Correction requests (if necessary)

[0542] In terms of specific actions, the user enters a modification request, such as "I want to change the place I'll visit on the second day," on the plan confirmation screen.

[0543] Step 7:

[0544] The device sends the correction request to the server.

[0545] Input: Correction Request

[0546] Output: Revised travel plan

[0547] Specifically, the terminal converts the correction request into JSON format and sends it to the server.

[0548] Step 8:

[0549] The server receives the correction request and generates an optimized travel plan again using the AI ​​model.

[0550] Input: Correction Request

[0551] Output: Regenerated travel plan

[0552] Specifically, the server integrates the initial travel plan with the requested revisions and then uses the generative AI model again to generate a new plan.

[0553] Step 9:

[0554] The user reviews and approves the final travel plan.

[0555] Input: Regenerated travel plan

[0556] Output: Final Approval

[0557] Specifically, the user reviews the regenerated travel plan on their device and presses the approve button.

[0558] Step 10:

[0559] The server makes online reservations for accommodations and transportation based on the final approved travel plan.

[0560] Input: Final approved travel plan

[0561] Output: Reservation confirmation

[0562] Specifically, the server uses an API to automatically book accommodations and transportation, and retrieves booking confirmation information.

[0563] Step 11:

[0564] Based on the confirmed travel plan and reservation information, an itinerary is created and sent to the device.

[0565] Input: Final travel plans and booking confirmation information

[0566] Output: Action plan

[0567] Specifically, the server integrates the schedule and reservation information, converts the action plan into JSON format, and sends it to the terminal.

[0568] In this way, users can create their ideal travel plan with minimal effort and have bookings completed automatically.

[0569] (Application Example 1)

[0570] 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."

[0571] Traditional travel planning systems struggled to automatically generate optimal travel plans and handle bookings based on user input such as itinerary, budget, region, and desired activities. Furthermore, creating flexible travel plans that incorporated user preferences often required significant effort and time, hindering a positive user experience. Additionally, the process of regenerating optimized plans when users modified their existing ones was cumbersome, highlighting the lack of sufficient automation.

[0572] 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.

[0573] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; and means for generating an optimal travel plan using a generation AI model based on the obtained data and presenting it to the user. This enables the user to easily create an ideal travel plan and efficiently make reservations. Furthermore, prompt messages can be generated based on user requests for modifications, and the travel plan can be regenerated, enabling the provision of flexible travel plans.

[0574] A "user" is someone who creates a travel plan by entering information about their travel dates, budget, region, and desired activities.

[0575] A "travel plan" is a proposed itinerary generated based on the travel dates, budget, region, and desired activities set by the user.

[0576] A "generative AI model" is an artificial intelligence computational model used to automatically optimize and generate travel plans.

[0577] A "database" is a storage device that stores information about accommodations, tourist destinations, transportation, and restaurants.

[0578] A "schedule generation algorithm" is a computational method for generating the optimal travel plan using user input information and database information.

[0579] A "prompt" is a document-formatted instruction given to a generative AI model to generate a travel plan.

[0580] An "API" is an application programming interface used by servers to automatically execute online reservations for accommodations and transportation.

[0581] "Online booking" refers to the process of making reservations for accommodations and transportation via the internet.

[0582] An "action plan sheet" is a table that contains specific instructions for the user to refer to during their trip, based on a finalized travel plan.

[0583] This invention is a system for users to create travel plans and make reservations automatically. Specific embodiments are described below.

[0584] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server. The hardware used is mainly smartphones and smart glasses, and the software utilizes JavaScript and React.js as front-end technologies.

[0585] The server queries the database based on the received user information to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants. The database used is PostgreSQL. Next, an AI model (e.g., GPT-3) is used to generate an optimal travel plan based on the retrieved data. The generated plan is sent to the terminal and presented to the user. The server uses a server-side framework such as Django for this process.

[0586] For example, if a user enters "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," the server will retrieve suitable accommodations, tourist attractions, transportation options, and restaurants from its database and generate the optimal plan.

[0587] When a user reviews a proposed travel plan and enters further modification requests, the AI ​​model generates prompts based on those requests and then creates an optimal plan again. For example, if a user requests to "add Ginkaku-ji Temple after visiting Kinkaku-ji Temple," the new prompt will be changed to "After visiting Kinkaku-ji Temple, I would also like to visit Ginkaku-ji Temple." This allows for flexible regeneration of travel plans.

[0588] Based on the confirmed travel plan, the server automatically makes online reservations for accommodations and transportation via API. Once the reservations are complete, the user is notified of the confirmed travel plan, and a final itinerary is generated. This itinerary provides a detailed travel plan that the user can refer to during their trip.

[0589] Thus, this invention aims to streamline the user's travel planning and booking process, and to provide an ideal travel experience.

[0590] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0591] Step 1:

[0592] The user enters information about their travel itinerary, budget, region, and desired activities into the device.

[0593] The input information includes departure date, return date, budget, desired destination, and specific activities. This information is converted to JSON format on the device and sent to the server.

[0594] Step 2:

[0595] The server analyzes the received user information and queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[0596] Input: User's travel information (e.g., dates, budget, region, activities)

[0597] Data processing: Query the PostgreSQL database using SQL to retrieve relevant information.

[0598] Output: Data on applicable accommodations, tourist attractions, transportation, and restaurants.

[0599] Step 3:

[0600] The server generates an optimal travel plan using an AI model (e.g., GPT-3) based on the acquired data, and presents it to the user.

[0601] Input: Candidate data retrieved from the database

[0602] Data processing: Input prompts into a generative AI model to generate travel plans.

[0603] Output: Draft travel plan generated

[0604] Step 4:

[0605] The user reviews the presented travel plan and enters any necessary modification requests into the terminal.

[0606] Input: Generated travel plan and user modification requests

[0607] Output: Information including correction requests

[0608] Step 5:

[0609] The server generates a prompt message based on the correction request and then uses the generation AI model again to generate a new travel plan.

[0610] Input: Correction Request

[0611] Data processing: Generate new prompt messages based on the requested modifications.

[0612] Data processing: Re-input data into the generative AI model to obtain a regenerated travel plan.

[0613] Output: Regenerated travel plan

[0614] Step 6:

[0615] After the user reviews and approves the final plan, the server automatically makes online reservations for accommodation and transportation via API.

[0616] Input: Final travel plan

[0617] Data processing: Execute online reservations via API

[0618] Output: Information confirming the reservation has been completed.

[0619] Step 7:

[0620] Based on the finalized travel plan, the server generates a detailed itinerary and sends it to the user's device. This provides the user with a specific guide to refer to during their trip.

[0621] Input: Confirmed travel plan

[0622] Data processing: Create an action plan based on the travel plan.

[0623] Output: Action Plan

[0624] 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.

[0625] This invention combines a travel plan generation system with an emotion engine, aiming to automatically optimize travel plans based on the user's emotional information. The system consists of a terminal, server, database, and emotion engine. Furthermore, the system is designed to automate travel plan generation and booking, thereby improving the user experience.

[0626] First, the user enters information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device receives the user's input and sends it to a server. Simultaneously, an emotion engine collects and analyzes emotional data from the user's tone of voice, facial expressions, text input, etc. This allows the user's current emotional state to be understood in real time.

[0627] The server receives the transmitted information and sentiment data and generates queries that take the user's emotional state into account. For example, if the user is feeling stressed, the system will adjust its recommendations to prioritize relaxing tourist destinations and activities. Using these queries, the server searches the database to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants.

[0628] Based on the acquired data, the server executes a schedule generation algorithm to generate a travel plan optimized for the user's emotional state. The generated plan is sent to the terminal and presented to the user.

[0629] The user reviews the presented travel plan and, if they have any complaints or suggestions for improvement, enters revision requests. The emotion engine analyzes the user's emotions at this point as well, recognizing, for example, that the user is feeling anxious about a particular part of the plan. The device then sends the revision requests and emotion data to the server.

[0630] The server runs the schedule generation algorithm again, generating a new travel plan that reflects the sentiment data and requested modifications. This new travel plan is sent to the terminal again and presented to the user. This process is repeated until the user is satisfied with the final plan.

[0631] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. All necessary reservations are completed via the reservation API, and the server notifies the user of the reservation completion information and creates an itinerary based on the confirmed travel plan. This itinerary is then sent to the user's device and provided to them.

[0632] As a concrete example, consider a scenario where a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice. In this case, the server prioritizes including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan is generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server automatically makes reservations for accommodation and Shinkansen tickets, and a detailed itinerary is provided to the device.

[0633] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans that better suit individual needs.

[0634] The following describes the processing flow.

[0635] Step 1:

[0636] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device formats the entered information and sends it to the server as data packets.

[0637] Step 2:

[0638] Simultaneously, the device activates its emotion engine and collects emotional data from the user's voice, facial expressions, and input. This emotional data is then analyzed, allowing the user's current emotional state to be understood in real time.

[0639] Step 3:

[0640] The server receives travel information and emotional data from the user and uses this information to generate queries for the database. For example, if a user is experiencing stress, the server will prioritize selecting relaxing tourist destinations and activities.

[0641] Step 4:

[0642] The server sends the generated query to the database and retrieves data on relevant accommodations, tourist attractions, transportation, and restaurants. The database returns the relevant data to the server according to the query.

[0643] Step 5:

[0644] The server executes a schedule generation algorithm based on the acquired data, generating a travel plan optimized for the user's emotional state. The generated travel plan is sent to the terminal and presented to the user.

[0645] Step 6:

[0646] Users review their travel plans through their devices. If they have any complaints or suggestions for improvement regarding specific dates or destinations, they input their requests for revisions into their devices. The emotion engine continues to analyze the user's emotions throughout this process, detecting changes in their feelings towards specific points.

[0647] Step 7:

[0648] The device sends the user's revision requests and sentiment data to the server. The server runs the schedule generation algorithm again and generates a new travel plan that reflects the revision requests and sentiment data.

[0649] Step 8:

[0650] The server sends the new travel plan to the device and presents it to the user again. This revision and confirmation process is repeated until the user is satisfied with the final plan.

[0651] Step 9:

[0652] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. It uses a reservation API to make the necessary reservations and compiles all the completed reservation information.

[0653] Step 10:

[0654] The server notifies the user of the booking confirmation and creates a detailed itinerary based on the confirmed travel plan. This itinerary is sent to the user's device, and the user performs a final check before traveling.

[0655] In this way, this system, which incorporates an emotion engine, can significantly improve the user experience by automatically generating optimal travel plans based on the user's emotional information and efficiently handling the booking process.

[0656] (Example 2)

[0657] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0658] Conventional travel plan generation systems generate plans based on basic user information, but they do not take into account the user's emotional state, making it difficult to provide travel plans that truly satisfy the user. Furthermore, when modifying a plan after it has been generated, it is difficult to adequately reflect the user's emotions and wishes, resulting in a poor user experience. In addition, the booking process was not fully automated, requiring users to make reservations manually, which reduced convenience. This invention aims to solve these problems and provide optimal travel plans based on the user's emotions.

[0659] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for transmitting the received information to the server; means including an emotion engine for collecting and analyzing the user's emotion data; means for generating queries based on the received information and the analyzed emotion data, querying a database, and obtaining data on relevant accommodations, tourist attractions, transportation, and restaurants; means for executing a schedule generation algorithm based on the obtained data to generate an optimal travel plan and present it to the user; means for generating a new travel plan after the user has confirmed and modified the travel plan, reflecting the modification requests and emotion data; means for executing online reservations for accommodations and transportation based on the final travel plan; and means for transmitting a final itinerary to the user to provide them with the confirmed travel plan. This makes it possible to analyze the user's emotion data in real time and provide an optimal travel plan that reflects it. Furthermore, the automation of the reservation procedure reduces the effort required from the user and improves convenience.

[0660] A "user" is an individual or group that uses the travel plan generation system to create a travel plan.

[0661] "Travel itinerary" refers to information that indicates the range of dates within which a user plans their trip.

[0662] "Budget" refers to the amount of money a user plans to spend on their trip.

[0663] "Region" refers to information that indicates the place the user wishes to travel to.

[0664] "Desired activities" refers to information about specific activities or experiences that the user wants to do during their trip.

[0665] A "device" refers to an electronic device (e.g., smartphone, tablet, or personal computer) that a user uses to input travel information and to review and modify their travel plan.

[0666] A "server" is a computer system that receives and processes information from users and generates and provides travel plans.

[0667] "Emotional data" refers to data about a user's emotional state, collected from the tone of their voice, facial expressions, text input, and other sources.

[0668] An "emotion engine" is software or a system used to collect and analyze user emotional data.

[0669] A "query" is a search instruction generated from a database to retrieve specific information.

[0670] A "database" is an information management system that stores information necessary for generating travel plans, such as accommodations, tourist destinations, transportation options, and restaurants.

[0671] A "schedule generation algorithm" refers to the mathematical methods and calculation procedures used to calculate and generate the optimal travel plan based on acquired data.

[0672] "Online booking" refers to the automated process of making reservations for accommodations and transportation via the internet.

[0673] An "action plan" is a document created based on a finalized travel plan, outlining the detailed schedule that the user should follow during their trip.

[0674] This invention relates to a system that automatically optimizes travel plans based on user sentiment information. This system consists of a terminal, a server, a database, and a sentiment engine. Specific embodiments are described below.

[0675] First, users enter information about their travel dates, budget, region, and desired activities through a smartphone app or website. The app or website used consists of a frontend using React or Vue.js and a backend using Node.js or Django. For example, a user might enter a prompt like this: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings."

[0676] The device sends the information entered by the user to the server. Simultaneously, an emotion engine (e.g., Microsoft Azure Emotion API or IBM Watson Tone Analyzer) collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. This allows the system to understand the user's current emotional state.

[0677] The server integrates received user information and emotional data to generate queries tailored to the user's emotional state. For example, if a user is experiencing high stress levels, the server will prioritize recommending relaxing tourist destinations. Using these queries, the server searches databases such as MongoDB or MySQL to retrieve data on relevant accommodations, tourist destinations, transportation options, and restaurants.

[0678] Based on the acquired data, the server executes a schedule generation algorithm. For example, it uses Python's Scikit-learn or TensorFlow to generate the optimal travel plan. The generated plan is sent to the terminal and presented to the user.

[0679] When a user reviews a presented travel plan and enters requests for revisions, the emotion engine analyzes the user's emotions at this point and sends the emotion data and revision requests to the server. The server then runs the schedule generation algorithm again to generate a new travel plan that reflects the revision requests and emotion data. This process is repeated until the user is satisfied with the final plan.

[0680] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. The necessary reservations are completed via a booking API (e.g., Booking.com API or Google Travel API), and the server notifies the user of the reservation confirmation. Then, based on the confirmed travel plan, an itinerary is created and sent to the user's device.

[0681] Thus, by utilizing user emotional data, the present invention can provide travel plans that better suit individual needs and significantly improve the user experience. Furthermore, the automation of booking procedures reduces user effort and improves convenience.

[0682] As described above, the present invention realizes the optimization of travel plans based on user emotional data.

[0683] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0684] Step 1:

[0685] Entering user information

[0686] Users input information about their travel dates, budget, region, and desired activities through a smartphone app or website. For example, a user might enter a prompt message such as, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." This is the input data.

[0687] Specific actions:

[0688] The user fills in the required information in the input form and presses the "Submit" button.

[0689] input:

[0690] Information entered by the user, including travel itinerary, budget, region, and desired activities.

[0691] output:

[0692] User travel plan request data.

[0693] Step 2:

[0694] Send user information

[0695] The terminal sends the information entered by the user to the server. HTTPS is used as the transmission protocol.

[0696] Specific actions:

[0697] When the user presses the "Send" button, the device sends the input data to the server via HTTPS communication.

[0698] input:

[0699] User travel plan request data.

[0700] output:

[0701] User information sent to the server.

[0702] Step 3:

[0703] Collection and analysis of emotional data

[0704] The emotion engine collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. The emotion engine utilizes Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[0705] Specific actions:

[0706] The device collects data from its built-in microphone, camera, and keyboard input, and passes it to the emotion engine. The emotion engine then analyzes this data.

[0707] input:

[0708] Voice tone, facial expressions, and text input data acquired from the device.

[0709] output:

[0710] Analyzed user sentiment data.

[0711] Step 4:

[0712] Query generation and database queries

[0713] The server generates queries based on user input and analyzed sentiment data, and queries the database. This retrieves data on optimal accommodations, tourist attractions, transportation, and restaurants.

[0714] Specific actions:

[0715] The server integrates user information and emotional data, and generates queries that prioritize relaxing tourist destinations if the user is experiencing high levels of stress. The generated queries are then sent to the database to retrieve the appropriate data.

[0716] input:

[0717] User information and analyzed sentiment data.

[0718] output:

[0719] Data on accommodations, tourist attractions, transportation, and restaurants obtained from a database.

[0720] Step 5:

[0721] Execute schedule generation algorithm

[0722] Based on the acquired data, the server executes a schedule generation algorithm (e.g., an algorithm using TensorFlow) to generate the optimal travel plan.

[0723] Specific actions:

[0724] The server inputs the acquired data into a schedule generation algorithm to calculate the optimal schedule. The generated plan is then sent to the terminal.

[0725] input:

[0726] The necessary data retrieved from the database.

[0727] output:

[0728] A generated travel plan.

[0729] Step 6:

[0730] Presentation and modification of travel plans

[0731] The terminal presents the generated travel plan to the user. The user reviews the plan and enters any desired modifications. At this point, the emotion engine continues to collect and analyze the user's emotional data and sends it to the server.

[0732] Specific actions:

[0733] The device displays the travel plan on its screen, and when the user enters any requested modifications, the device sends them to the server.

[0734] input:

[0735] Generated travel plans and user sentiment data.

[0736] output:

[0737] Data with requested corrections and sentiment data.

[0738] Step 7:

[0739] Generating a readjustment plan

[0740] Based on the requested changes and sentiment data, the server runs the schedule generation algorithm again to generate a new travel plan. This process is repeated until the user is satisfied.

[0741] Specific actions:

[0742] The server inputs the requested correction data and sentiment data into an algorithm, calculates and generates a new plan, and sends the generated new plan to the terminal.

[0743] input:

[0744] Data requested for correction and user sentiment data.

[0745] output:

[0746] A new travel plan.

[0747] Step 8:

[0748] Final plan confirmation and booking

[0749] Once the user approves the final travel plan, the server automatically makes online reservations for accommodation and transportation. Reservation APIs (e.g., Booking.com API, Google Travel API) are used for booking.

[0750] Specific actions:

[0751] The server sends the final plan information to the reservation API and completes the necessary reservation.

[0752] input:

[0753] The final travel plan.

[0754] output:

[0755] Reservation confirmation information.

[0756] Step 9:

[0757] Action plan provided

[0758] The server creates an itinerary based on the final travel plan and sends it to the user's device. The user then reviews the itinerary through their device.

[0759] Specific actions:

[0760] The server generates an action plan and sends it to the terminal. The user checks it on the terminal.

[0761] input:

[0762] Final travel plan.

[0763] output:

[0764] Action plan.

[0765] The above outlines the specific processing steps of the travel plan generation system.

[0766] (Application Example 2)

[0767] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0768] Conventional travel plan generation systems provided optimal travel plans based on the travel dates, budget, region, and desired activities specified by the user. However, because they could not take into account the user's emotional state, the plans often did not necessarily satisfy the user. As a result, users may experience stress and dissatisfaction, potentially impairing the overall user experience of the travel plan. Therefore, the present invention aims to provide a system that utilizes the user's emotional information to automatically generate the travel plan that will satisfy the user the most.

[0769] 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.

[0770] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for transmitting a final itinerary to the user to provide them with the confirmed travel plan; means for collecting and analyzing the user's emotional data using an emotional engine; and means for optimizing the travel plan based on the emotional data. This makes it possible to provide a travel plan optimized for the user's emotional state, thereby improving the user experience.

[0771] A "user" is an individual or group that uses the travel plan generation system.

[0772] "Travel itinerary" refers to the range of dates the user wishes to travel.

[0773] "Budget" refers to the total amount of money a user plans to spend on their trip.

[0774] A "region" is a geographical location that a user wishes to visit.

[0775] "Desired activities" refer to the activities and events that the user would like to participate in during their trip.

[0776] A "database" is a system that stores information on accommodations, tourist attractions, transportation, restaurants, and more.

[0777] An "emotion engine" is a configuration of software and hardware used to collect and analyze user emotional data.

[0778] "Emotional data" refers to information about a user's emotional state obtained from their tone of voice, facial expressions, text input, etc.

[0779] A "travel plan" is a specific itinerary generated based on the user's wishes and emotional state.

[0780] An "action plan" is a detailed schedule created based on a finalized travel plan.

[0781] "Online booking" refers to the process of automatically making reservations for accommodations and transportation via the internet.

[0782] A "schedule generation algorithm" is a set of calculations that analyzes user data to generate the optimal travel plan.

[0783] A "request for revision" is input information in which a user requests changes or improvements to the travel plan presented.

[0784] This invention relates to a system that automatically optimizes travel plans based on a user's emotional information. This system consists of a terminal, a server, a database, and an emotional engine.

[0785] First, users enter information about their travel dates, budget, region, and desired activities into a dedicated app or website on their device. An example of a specific prompt message is: "Please enter the duration of your trip, budget, and desired destinations and activities. We will also analyze your emotional state to suggest the best travel plan for you. For example, if you are feeling stressed, we will prioritize including places where you can relax."

[0786] When a user enters information, the terminal sends that information to the server. Simultaneously, the emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc. The emotion engine identifies the emotional state in real time, for example, using OpenCV or other emotion analysis software.

[0787] The server receives the user's information and emotional data analyzed by the emotion engine. Based on this data, the server runs a schedule generation algorithm to generate queries optimized for the user's emotional state. For example, if the user is seeking relaxation, relaxing tourist destinations and activities will be prioritized in the plan.

[0788] The server uses the generated query to look up data on the database for relevant accommodations, tourist attractions, transportation, and restaurants. Based on this retrieved data, the server generates an optimal travel plan and sends it to the terminal.

[0789] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal. The emotion engine also re-analyzes the user's emotions at this point, identifying any areas of anxiety. The revision requests and emotion data are sent back to the server, which then runs the schedule generation algorithm again to generate a new plan that reflects the emotion data and revision requests.

[0790] If the user is ultimately satisfied with the travel plan, the server automatically makes online reservations for accommodation and transportation. It utilizes a reservation API to complete the necessary booking procedures and notifies the user of the booking confirmation. Then, it creates an itinerary based on the confirmed travel plan and sends it to the user's device for their use.

[0791] For example, if a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice, the server will prioritize including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan will be generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server will automatically make reservations for accommodation and Shinkansen tickets, and a detailed itinerary will be provided to the device.

[0792] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans tailored to individual needs.

[0793] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0794] Step 1:

[0795] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website.

[0796] Input: User information (travel itinerary, budget, region, desired activities)

[0797] Output: Sends input information to the terminal.

[0798] Step 2:

[0799] The terminal sends the entered information to the server.

[0800] Input: User information

[0801] Output: Information sent to the server

[0802] Step 3:

[0803] The emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc.

[0804] Input: User voice, facial expressions, text input

[0805] Output: Sentiment data

[0806] Specific operation: Use OpenCV and other sentiment analysis software to identify emotional states in real time.

[0807] Step 4:

[0808] The server receives the user's information and sentiment data that was sent.

[0809] Input: User information, sentiment data

[0810] Output: Data used to generate queries

[0811] Step 5:

[0812] The server executes a schedule generation algorithm based on the user information and sentiment data it receives, and generates the optimal query.

[0813] Input: User information, sentiment data

[0814] Output: Optimized query

[0815] Specific behavior: If the user is looking for relaxation, the query will include relaxing tourist destinations and activities.

[0816] Step 6:

[0817] The server queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[0818] Input: Optimized query

[0819] Output: Accommodation, tourist attractions, transportation, and restaurant data

[0820] Step 7:

[0821] The server generates an optimal travel plan based on the data it acquires and sends it to the device.

[0822] Input: Data on accommodations, tourist attractions, transportation, and restaurants.

[0823] Output: Optimal travel plan

[0824] Step 8:

[0825] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal.

[0826] Input: Feedback on travel plans

[0827] Output: Correction Request

[0828] Step 9:

[0829] The device sends correction requests and sentiment data to the server.

[0830] Input: Correction requests, sentiment data

[0831] Output: Send correction requests and sentiment data to the server.

[0832] Step 10:

[0833] The server runs the schedule generation algorithm again and generates a new plan that reflects the sentiment data and revision requests.

[0834] Input: Correction requests, sentiment data

[0835] Output: New travel plan

[0836] Specific action: If the user requests further relaxation, more relaxing options will be included in the revised plan.

[0837] Step 11:

[0838] If the user is satisfied with the final travel plan, the server will make online reservations for accommodation and transportation.

[0839] Input: Final travel plan

[0840] Output: Reservation confirmation information

[0841] Specific operation: Executes booking procedures for accommodations and transportation via the booking API.

[0842] Step 12:

[0843] The server creates an action plan based on the confirmed travel plan and sends it to the terminal.

[0844] Input: Booking confirmation information, confirmed travel plan

[0845] Output: Action Plan

[0846] Specific actions: Generate an action plan and provide it to the user to guide them through their trip.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] [Third Embodiment]

[0851] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0852] 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.

[0853] 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).

[0854] 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.

[0855] 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.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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".

[0863] This invention relates to a travel plan generation system that allows users to easily create an ideal travel plan and even automatically make reservations. The system operates as follows:

[0864] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server.

[0865] The server queries the database based on the information received from the user and retrieves data on relevant accommodations, tourist attractions, transportation options, and restaurants. This aggregates information on the server that can serve as a travel option tailored to the user's preferences.

[0866] Next, the server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan. This travel plan includes sightseeing destinations, accommodations, transportation, and dining options, and is designed to meet the user's requirements. The generated travel plan is sent to the terminal and presented to the user.

[0867] The user reviews the proposed travel plan and enters any necessary modification requests. For example, they might want to add more time on a specific day or include additional places to visit. The device then sends the modification requests to the server.

[0868] The server regenerates the travel plan based on the user's revision requests. This time, the initial plan and the user's revision requests are integrated to generate an optimized new travel plan. The regenerated plan is sent to the terminal again for the user to review.

[0869] After the user reviews and approves the final plan, the server sequentially executes online reservations for accommodation and transportation. The server uses a reservation API to automatically make the necessary reservations. Once the reservations are complete, the user is notified and provided with the confirmed travel plan.

[0870] Finally, the server creates an itinerary based on the finalized travel plan and sends it to the device. This itinerary provides a detailed guide for the user to refer to during their trip.

[0871] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. The generated plan might include visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0872] Thus, the present invention aims to streamline the user's travel planning and booking process and provide an ideal travel experience.

[0873] The following describes the processing flow.

[0874] Step 1:

[0875] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The information entered by the user is formatted on the device and sent to the server as appropriate data packets.

[0876] Step 2:

[0877] The server receives information sent by the user and first parses it. Based on the results of the parsing, the server generates a query to the database. This query retrieves information such as accommodations, tourist attractions, transportation options, and restaurants from the database.

[0878] Step 3:

[0879] The database receives queries from the server and returns relevant information (accommodations, tourist attractions, transportation, restaurants, etc.). Based on the retrieved information, the server executes a schedule generation algorithm to generate the optimal travel plan that meets the user's requirements.

[0880] Step 4:

[0881] The server sends the generated travel plan to the terminal and presents it to the user. The user reviews the travel plan through the terminal. If the user is satisfied, they proceed to the next step; however, if they have any requests for revisions, they enter those requests.

[0882] Step 5:

[0883] When a user enters and submits a revision request, the device sends that information to the server. The server receives the revision request, runs the schedule generation algorithm again, and generates a new travel plan that reflects the revisions.

[0884] Step 6:

[0885] The server sends the regenerated travel plan to the device and presents it to the user again. The user reviews the plan again, and if they agree, they proceed to the next step. If they are dissatisfied, they enter their revision requests again and return to step 5.

[0886] Step 7:

[0887] Once the user finally approves the travel plan, the server executes online reservations for accommodation and transportation. It automatically makes the necessary reservations via a reservation API and monitors the reservation status in real time.

[0888] Step 8:

[0889] The server compiles information on completed reservations and notifies the user. Furthermore, it creates an itinerary based on the confirmed travel plan and sends it to the device.

[0890] Step 9:

[0891] Users receive an itinerary via their device and perform a final check before their trip. The itinerary includes a detailed schedule and booking information, which users use to plan their trip.

[0892] The above describes the specific processing steps in the present invention, which streamline the user's travel planning and booking process.

[0893] (Example 1)

[0894] 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."

[0895] Conventional travel planning and booking systems have the problem of being time-consuming and laborious, as users have to gather a lot of information themselves and make reservations individually. Furthermore, if the generated travel plan does not perfectly match the user's wishes, regeneration and modification are cumbersome, making efficient travel planning difficult. The present invention aims to solve these problems and provide a system that allows users to create an ideal travel plan without effort and complete reservations automatically.

[0896] 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.

[0897] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan using a schedule generation algorithm based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for integrating the user's modification requests using a generation AI model and regenerating an optimized travel plan again; and means for transmitting a final itinerary to provide the user with the confirmed travel plan. This enables the user to generate an ideal travel plan and complete reservations automatically without performing complex operations.

[0898] A "user" refers to an individual or group that uses the system to create travel plans and make reservations.

[0899] "Travel itinerary" refers to the period from the day the user starts their trip until the day it ends.

[0900] "Budget" refers to the maximum amount of money a user can spend on a trip.

[0901] "Region" refers to the place or area that the user wants to travel to.

[0902] "Desired activities" refer to the specific activities and experiences that the user wants to have during their trip.

[0903] "Means of receiving information" refers to an interface for receiving and inputting detailed travel information from users.

[0904] "Means of querying a database" refers to methods and systems for searching for data on suitable accommodations, tourist attractions, transportation options, and restaurants based on information provided by the user.

[0905] "Accommodation facilities" refer to places where users stay during their travels, such as hotels and inns.

[0906] A "tourist destination" refers to a place or landmark that a user would like to visit during their travels.

[0907] "Transportation" refers to the means of transport that users use to get around during their trip, such as trains, buses, and airplanes.

[0908] "Restaurants" refers to places where users eat during their trip.

[0909] A "schedule generation algorithm" refers to the calculation procedure used to create the optimal travel plan based on information entered by the user and data obtained from a database.

[0910] A "generative AI model" refers to a software model that utilizes machine learning and artificial intelligence technologies to automatically create a travel plan that best suits the user's preferences.

[0911] "Means of executing online reservations" refers to systems that automatically book accommodations and transportation on behalf of users.

[0912] An "action plan" refers to a detailed schedule outlining what a user will do and when during their trip.

[0913] "Optimization" refers to adjusting travel plans to best meet the user's needs and requirements.

[0914] A "revision request" refers to a user's request to change or add to a proposed travel plan.

[0915] "Regeneration" refers to the process of recreating a travel plan based on user requests for modifications.

[0916] This invention is a travel plan generation system aimed at enabling users to easily create ideal travel plans and automatically handle bookings. A detailed explanation of how to implement this system is provided below.

[0917] First, the user uses a device (for example, a PC or smartphone) to input their travel itinerary, budget, desired destination, and preferred activities. This input data is converted into a specific format by the device and sent to the server as JSON data, for example.

[0918] Next, the server queries the database based on the user information it received. A database management system such as MySQL or PostgreSQL is used to retrieve information about accommodations, tourist attractions, transportation, and restaurants from the database. The retrieved data includes a list of accommodations and tourist attractions that meet the user's criteria.

[0919] The server then generates a travel plan using a schedule generation algorithm. This algorithm utilizes generative AI models such as TensorFlow or PyTorch. This generates an optimal schedule that takes into account the user's desired travel dates, budget, region, and activities to the greatest extent possible.

[0920] The generated travel plan is sent to the device and presented to the user. The user reviews this plan and enters any necessary revision requests. For example, if the user wants to change the place to visit on day 2, the revision request is sent from the device to the server. The server uses the AI ​​model again to integrate this revision request and generates a new, optimized travel plan. This regenerated plan is also sent to the device for the user to review again.

[0921] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. This reservation process utilizes the APIs of various services (e.g., Expedia and Airbnb APIs). This eliminates the need for the user to make individual reservations themselves.

[0922] Furthermore, an action plan is generated based on the finalized travel plan and sent to the device. This action plan includes details of places to visit, times, and modes of transportation, allowing the user to comfortably plan their trip based on it.

[0923] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. For example, a plan might be generated that includes visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[0924] An example of a prompt sentence to input into a generating AI model is: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings. Please suggest a recommended travel plan."

[0925] As described above, this system aims to streamline users' travel planning and booking processes, and to provide them with an ideal travel experience.

[0926] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0927] Step 1:

[0928] Users use their devices to enter information about their travel itinerary, budget, region, and desired activities.

[0929] Input: Travel dates, budget, region, desired activities

[0930] As a concrete example, the user opens a travel plan creation application and enters into the input form, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. I want to see historical buildings."

[0931] Step 2:

[0932] The terminal converts the entered information into JSON format and sends it to the server.

[0933] Input: Travel information entered by the user

[0934] Output: Data in JSON format

[0935] Specifically, the device generates JSON data such as "{ "Dates": "August 1st - August 7th", "Budget": 100000, "Region": "Kyoto", "Activity": "Historical building sightseeing"}" and sends it to the server using an HTTP POST request.

[0936] Step 3:

[0937] The server queries the database based on the received data.

[0938] Input: User information in JSON format

[0939] Output: Information on accommodations, tourist attractions, transportation, and restaurants.

[0940] Specifically, the server executes an SQL query like "SELECT FROM hotels WHERE location='Kyoto' AND price <= 100000" to retrieve data on accommodations. It similarly queries the database for tourist attractions, transportation options, and restaurants.

[0941] Step 4:

[0942] The server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan.

[0943] Input: Information on accommodations, tourist attractions, transportation, and restaurants.

[0944] Output: Travel plan

[0945] In terms of specific operation, the server uses generative AI models such as TensorFlow to generate an optimal itinerary that aligns with the user's preferences. This itinerary includes a detailed schedule such as "August 1st: Arrive at Kyoto Station → Visit Kinkaku-ji Temple → Visit Ginkaku-ji Temple → Lunch at a Japanese restaurant."

[0946] Step 5:

[0947] The server sends the generated travel plan to the terminal.

[0948] Input: Generated travel plan

[0949] Output: Presentation of travel plan

[0950] Specifically, the server converts the generated travel plan into JSON format and sends it to the terminal as an HTTP response.

[0951] Step 6:

[0952] The user reviews the presented travel plan and enters any revision requests as needed.

[0953] Input: Travel plan

[0954] Output: Correction requests (if necessary)

[0955] In terms of specific actions, the user enters a modification request, such as "I want to change the place I'll visit on the second day," on the plan confirmation screen.

[0956] Step 7:

[0957] The device sends the correction request to the server.

[0958] Input: Correction Request

[0959] Output: Revised travel plan

[0960] Specifically, the terminal converts the correction request into JSON format and sends it to the server.

[0961] Step 8:

[0962] The server receives the correction request and generates an optimized travel plan again using the AI ​​model.

[0963] Input: Correction Request

[0964] Output: Regenerated travel plan

[0965] Specifically, the server integrates the initial travel plan with the requested revisions and then uses the generative AI model again to generate a new plan.

[0966] Step 9:

[0967] The user reviews and approves the final travel plan.

[0968] Input: Regenerated travel plan

[0969] Output: Final Approval

[0970] Specifically, the user reviews the regenerated travel plan on their device and presses the approve button.

[0971] Step 10:

[0972] The server makes online reservations for accommodations and transportation based on the final approved travel plan.

[0973] Input: Final approved travel plan

[0974] Output: Reservation confirmation

[0975] Specifically, the server uses an API to automatically book accommodations and transportation, and retrieves booking confirmation information.

[0976] Step 11:

[0977] Based on the confirmed travel plan and reservation information, an itinerary is created and sent to the device.

[0978] Input: Final travel plans and booking confirmation information

[0979] Output: Action plan

[0980] Specifically, the server integrates the schedule and reservation information, converts the action plan into JSON format, and sends it to the terminal.

[0981] In this way, users can create their ideal travel plan with minimal effort and have bookings completed automatically.

[0982] (Application Example 1)

[0983] 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."

[0984] Traditional travel planning systems struggled to automatically generate optimal travel plans and handle bookings based on user input such as itinerary, budget, region, and desired activities. Furthermore, creating flexible travel plans that incorporated user preferences often required significant effort and time, hindering a positive user experience. Additionally, the process of regenerating optimized plans when users modified their existing ones was cumbersome, highlighting the lack of sufficient automation.

[0985] 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.

[0986] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; and means for generating an optimal travel plan using a generation AI model based on the obtained data and presenting it to the user. This enables the user to easily create an ideal travel plan and efficiently make reservations. Furthermore, prompt messages can be generated based on user requests for modifications, and the travel plan can be regenerated, enabling the provision of flexible travel plans.

[0987] A "user" is someone who creates a travel plan by entering information about their travel dates, budget, region, and desired activities.

[0988] A "travel plan" is a proposed itinerary generated based on the travel dates, budget, region, and desired activities set by the user.

[0989] A "generative AI model" is an artificial intelligence computational model used to automatically optimize and generate travel plans.

[0990] A "database" is a storage device that stores information about accommodations, tourist destinations, transportation, and restaurants.

[0991] A "schedule generation algorithm" is a computational method for generating the optimal travel plan using user input information and database information.

[0992] A "prompt" is a document-formatted instruction given to a generative AI model to generate a travel plan.

[0993] An "API" is an application programming interface used by servers to automatically execute online reservations for accommodations and transportation.

[0994] "Online booking" refers to the process of making reservations for accommodations and transportation via the internet.

[0995] An "action plan sheet" is a table that contains specific instructions for the user to refer to during their trip, based on a finalized travel plan.

[0996] This invention is a system for users to create travel plans and make reservations automatically. Specific embodiments are described below.

[0997] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server. The hardware used is mainly smartphones and smart glasses, and the software utilizes JavaScript and React.js as front-end technologies.

[0998] The server queries the database based on the received user information to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants. The database used is PostgreSQL. Next, an AI model (e.g., GPT-3) is used to generate an optimal travel plan based on the retrieved data. The generated plan is sent to the terminal and presented to the user. The server uses a server-side framework such as Django for this process.

[0999] For example, if a user enters "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," the server will retrieve suitable accommodations, tourist attractions, transportation options, and restaurants from its database and generate the optimal plan.

[1000] When a user reviews a proposed travel plan and enters further modification requests, the AI ​​model generates prompts based on those requests and then creates an optimal plan again. For example, if a user requests to "add Ginkaku-ji Temple after visiting Kinkaku-ji Temple," the new prompt will be changed to "After visiting Kinkaku-ji Temple, I would also like to visit Ginkaku-ji Temple." This allows for flexible regeneration of travel plans.

[1001] Based on the confirmed travel plan, the server automatically makes online reservations for accommodations and transportation via API. Once the reservations are complete, the user is notified of the confirmed travel plan, and a final itinerary is generated. This itinerary provides a detailed travel plan that the user can refer to during their trip.

[1002] Thus, this invention aims to streamline the user's travel planning and booking process, and to provide an ideal travel experience.

[1003] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1004] Step 1:

[1005] The user enters information about their travel itinerary, budget, region, and desired activities into the device.

[1006] The input information includes departure date, return date, budget, desired destination, and specific activities. This information is converted to JSON format on the device and sent to the server.

[1007] Step 2:

[1008] The server analyzes the received user information and queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[1009] Input: User's travel information (e.g., dates, budget, region, activities)

[1010] Data processing: Query the PostgreSQL database using SQL to retrieve relevant information.

[1011] Output: Data on applicable accommodations, tourist attractions, transportation, and restaurants.

[1012] Step 3:

[1013] The server generates an optimal travel plan using an AI model (e.g., GPT-3) based on the acquired data, and presents it to the user.

[1014] Input: Candidate data retrieved from the database

[1015] Data processing: Input prompts into a generative AI model to generate travel plans.

[1016] Output: Draft travel plan generated

[1017] Step 4:

[1018] The user reviews the presented travel plan and enters any necessary modification requests into the terminal.

[1019] Input: Generated travel plan and user modification requests

[1020] Output: Information including correction requests

[1021] Step 5:

[1022] The server generates a prompt message based on the correction request and then uses the generation AI model again to generate a new travel plan.

[1023] Input: Correction Request

[1024] Data processing: Generate new prompt messages based on the requested modifications.

[1025] Data processing: Re-input data into the generative AI model to obtain a regenerated travel plan.

[1026] Output: Regenerated travel plan

[1027] Step 6:

[1028] After the user reviews and approves the final plan, the server automatically makes online reservations for accommodation and transportation via API.

[1029] Input: Final travel plan

[1030] Data processing: Execute online reservations via API

[1031] Output: Information confirming the reservation has been completed.

[1032] Step 7:

[1033] Based on the finalized travel plan, the server generates a detailed itinerary and sends it to the user's device. This provides the user with a specific guide to refer to during their trip.

[1034] Input: Confirmed travel plan

[1035] Data processing: Create an action plan based on the travel plan.

[1036] Output: Action Plan

[1037] 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.

[1038] This invention combines a travel plan generation system with an emotion engine, aiming to automatically optimize travel plans based on the user's emotional information. The system consists of a terminal, server, database, and emotion engine. Furthermore, the system is designed to automate travel plan generation and booking, thereby improving the user experience.

[1039] First, the user enters information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device receives the user's input and sends it to a server. Simultaneously, an emotion engine collects and analyzes emotional data from the user's tone of voice, facial expressions, text input, etc. This allows the user's current emotional state to be understood in real time.

[1040] The server receives the transmitted information and sentiment data and generates queries that take the user's emotional state into account. For example, if the user is feeling stressed, the system will adjust its recommendations to prioritize relaxing tourist destinations and activities. Using these queries, the server searches the database to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants.

[1041] Based on the acquired data, the server executes a schedule generation algorithm to generate a travel plan optimized for the user's emotional state. The generated plan is sent to the terminal and presented to the user.

[1042] The user reviews the presented travel plan and, if they have any complaints or suggestions for improvement, enters revision requests. The emotion engine analyzes the user's emotions at this point as well, recognizing, for example, that the user is feeling anxious about a particular part of the plan. The device then sends the revision requests and emotion data to the server.

[1043] The server runs the schedule generation algorithm again, generating a new travel plan that reflects the sentiment data and requested modifications. This new travel plan is sent to the terminal again and presented to the user. This process is repeated until the user is satisfied with the final plan.

[1044] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. All necessary reservations are completed via the reservation API, and the server notifies the user of the reservation completion information and creates an itinerary based on the confirmed travel plan. This itinerary is then sent to the user's device and provided to them.

[1045] As a concrete example, consider a scenario where a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice. In this case, the server prioritizes including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan is generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server automatically makes reservations for accommodation and Shinkansen tickets, and a detailed itinerary is provided to the device.

[1046] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans that better suit individual needs.

[1047] The following describes the processing flow.

[1048] Step 1:

[1049] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device formats the entered information and sends it to the server as data packets.

[1050] Step 2:

[1051] Simultaneously, the device activates its emotion engine and collects emotional data from the user's voice, facial expressions, and input. This emotional data is then analyzed, allowing the user's current emotional state to be understood in real time.

[1052] Step 3:

[1053] The server receives travel information and emotional data from the user and uses this information to generate queries for the database. For example, if a user is experiencing stress, the server will prioritize selecting relaxing tourist destinations and activities.

[1054] Step 4:

[1055] The server sends the generated query to the database and retrieves data on relevant accommodations, tourist attractions, transportation, and restaurants. The database returns the relevant data to the server according to the query.

[1056] Step 5:

[1057] The server executes a schedule generation algorithm based on the acquired data, generating a travel plan optimized for the user's emotional state. The generated travel plan is sent to the terminal and presented to the user.

[1058] Step 6:

[1059] Users review their travel plans through their devices. If they have any complaints or suggestions for improvement regarding specific dates or destinations, they input their requests for revisions into their devices. The emotion engine continues to analyze the user's emotions throughout this process, detecting changes in their feelings towards specific points.

[1060] Step 7:

[1061] The device sends the user's revision requests and sentiment data to the server. The server runs the schedule generation algorithm again and generates a new travel plan that reflects the revision requests and sentiment data.

[1062] Step 8:

[1063] The server sends the new travel plan to the device and presents it to the user again. This revision and confirmation process is repeated until the user is satisfied with the final plan.

[1064] Step 9:

[1065] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. It uses a reservation API to make the necessary reservations and compiles all the completed reservation information.

[1066] Step 10:

[1067] The server notifies the user of the booking confirmation and creates a detailed itinerary based on the confirmed travel plan. This itinerary is sent to the user's device, and the user performs a final check before traveling.

[1068] In this way, this system, which incorporates an emotion engine, can significantly improve the user experience by automatically generating optimal travel plans based on the user's emotional information and efficiently handling the booking process.

[1069] (Example 2)

[1070] 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."

[1071] Conventional travel plan generation systems generate plans based on basic user information, but they do not take into account the user's emotional state, making it difficult to provide travel plans that truly satisfy the user. Furthermore, when modifying a plan after it has been generated, it is difficult to adequately reflect the user's emotions and wishes, resulting in a poor user experience. In addition, the booking process was not fully automated, requiring users to make reservations manually, which reduced convenience. This invention aims to solve these problems and provide optimal travel plans based on the user's emotions.

[1072] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for transmitting the received information to the server; means including an emotion engine for collecting and analyzing the user's emotion data; means for generating queries based on the received information and the analyzed emotion data, querying a database, and obtaining data on relevant accommodations, tourist attractions, transportation, and restaurants; means for executing a schedule generation algorithm based on the obtained data to generate an optimal travel plan and present it to the user; means for generating a new travel plan after the user has confirmed and modified the travel plan, reflecting the modification requests and emotion data; means for executing online reservations for accommodations and transportation based on the final travel plan; and means for transmitting a final itinerary to the user to provide them with the confirmed travel plan. This makes it possible to analyze the user's emotion data in real time and provide an optimal travel plan that reflects it. Furthermore, the automation of the reservation procedure reduces the effort required from the user and improves convenience.

[1073] A "user" is an individual or group that uses the travel plan generation system to create a travel plan.

[1074] "Travel itinerary" refers to information that indicates the range of dates within which a user plans their trip.

[1075] "Budget" refers to the amount of money a user plans to spend on their trip.

[1076] "Region" refers to information that indicates the place the user wishes to travel to.

[1077] "Desired activities" refers to information about specific activities or experiences that the user wants to do during their trip.

[1078] A "device" refers to an electronic device (e.g., smartphone, tablet, or personal computer) that a user uses to input travel information and to review and modify their travel plan.

[1079] A "server" is a computer system that receives and processes information from users and generates and provides travel plans.

[1080] "Emotional data" refers to data about a user's emotional state, collected from the tone of their voice, facial expressions, text input, and other sources.

[1081] An "emotion engine" is software or a system used to collect and analyze user emotional data.

[1082] A "query" is a search instruction generated from a database to retrieve specific information.

[1083] A "database" is an information management system that stores information necessary for generating travel plans, such as accommodations, tourist destinations, transportation options, and restaurants.

[1084] A "schedule generation algorithm" refers to the mathematical methods and calculation procedures used to calculate and generate the optimal travel plan based on acquired data.

[1085] "Online booking" refers to the automated process of making reservations for accommodations and transportation via the internet.

[1086] An "action plan" is a document created based on a finalized travel plan, outlining the detailed schedule that the user should follow during their trip.

[1087] This invention relates to a system that automatically optimizes travel plans based on user sentiment information. This system consists of a terminal, a server, a database, and a sentiment engine. Specific embodiments are described below.

[1088] First, users enter information about their travel dates, budget, region, and desired activities through a smartphone app or website. The app or website used consists of a frontend using React or Vue.js and a backend using Node.js or Django. For example, a user might enter a prompt like this: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings."

[1089] The device sends the information entered by the user to the server. Simultaneously, an emotion engine (e.g., Microsoft Azure Emotion API or IBM Watson Tone Analyzer) collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. This allows the system to understand the user's current emotional state.

[1090] The server integrates received user information and emotional data to generate queries tailored to the user's emotional state. For example, if a user is experiencing high stress levels, the server will prioritize recommending relaxing tourist destinations. Using these queries, the server searches databases such as MongoDB or MySQL to retrieve data on relevant accommodations, tourist destinations, transportation options, and restaurants.

[1091] Based on the acquired data, the server executes a schedule generation algorithm. For example, it uses Python's Scikit-learn or TensorFlow to generate the optimal travel plan. The generated plan is sent to the terminal and presented to the user.

[1092] When a user reviews a presented travel plan and enters requests for revisions, the emotion engine analyzes the user's emotions at this point and sends the emotion data and revision requests to the server. The server then runs the schedule generation algorithm again to generate a new travel plan that reflects the revision requests and emotion data. This process is repeated until the user is satisfied with the final plan.

[1093] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. The necessary reservations are completed via a booking API (e.g., Booking.com API or Google Travel API), and the server notifies the user of the reservation confirmation. Then, based on the confirmed travel plan, an itinerary is created and sent to the user's device.

[1094] Thus, by utilizing user emotional data, the present invention can provide travel plans that better suit individual needs and significantly improve the user experience. Furthermore, the automation of booking procedures reduces user effort and improves convenience.

[1095] As described above, the present invention realizes the optimization of travel plans based on user emotional data.

[1096] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1097] Step 1:

[1098] Entering user information

[1099] Users input information about their travel dates, budget, region, and desired activities through a smartphone app or website. For example, a user might enter a prompt message such as, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." This is the input data.

[1100] Specific actions:

[1101] The user fills in the required information in the input form and presses the "Submit" button.

[1102] input:

[1103] Information entered by the user, including travel itinerary, budget, region, and desired activities.

[1104] output:

[1105] User travel plan request data.

[1106] Step 2:

[1107] Send user information

[1108] The terminal sends the information entered by the user to the server. HTTPS is used as the transmission protocol.

[1109] Specific actions:

[1110] When the user presses the "Send" button, the device sends the input data to the server via HTTPS communication.

[1111] input:

[1112] User travel plan request data.

[1113] output:

[1114] User information sent to the server.

[1115] Step 3:

[1116] Collection and analysis of emotional data

[1117] The emotion engine collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. The emotion engine utilizes Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1118] Specific actions:

[1119] The device collects data from its built-in microphone, camera, and keyboard input, and passes it to the emotion engine. The emotion engine then analyzes this data.

[1120] input:

[1121] Voice tone, facial expressions, and text input data acquired from the device.

[1122] output:

[1123] Analyzed user sentiment data.

[1124] Step 4:

[1125] Query generation and database queries

[1126] The server generates queries based on user input and analyzed sentiment data, and queries the database. This retrieves data on optimal accommodations, tourist attractions, transportation, and restaurants.

[1127] Specific actions:

[1128] The server integrates user information and emotional data, and generates queries that prioritize relaxing tourist destinations if the user is experiencing high levels of stress. The generated queries are then sent to the database to retrieve the appropriate data.

[1129] input:

[1130] User information and analyzed sentiment data.

[1131] output:

[1132] Data on accommodations, tourist attractions, transportation, and restaurants obtained from a database.

[1133] Step 5:

[1134] Execute schedule generation algorithm

[1135] Based on the acquired data, the server executes a schedule generation algorithm (e.g., an algorithm using TensorFlow) to generate the optimal travel plan.

[1136] Specific actions:

[1137] The server inputs the acquired data into a schedule generation algorithm to calculate the optimal schedule. The generated plan is then sent to the terminal.

[1138] input:

[1139] The necessary data retrieved from the database.

[1140] output:

[1141] A generated travel plan.

[1142] Step 6:

[1143] Presentation and modification of travel plans

[1144] The terminal presents the generated travel plan to the user. The user reviews the plan and enters any desired modifications. At this point, the emotion engine continues to collect and analyze the user's emotional data and sends it to the server.

[1145] Specific actions:

[1146] The device displays the travel plan on its screen, and when the user enters any requested modifications, the device sends them to the server.

[1147] input:

[1148] Generated travel plans and user sentiment data.

[1149] output:

[1150] Data with requested corrections and sentiment data.

[1151] Step 7:

[1152] Generating a readjustment plan

[1153] Based on the requested changes and sentiment data, the server runs the schedule generation algorithm again to generate a new travel plan. This process is repeated until the user is satisfied.

[1154] Specific actions:

[1155] The server inputs the requested correction data and sentiment data into an algorithm, calculates and generates a new plan, and sends the generated new plan to the terminal.

[1156] input:

[1157] Data requested for correction and user sentiment data.

[1158] output:

[1159] A new travel plan.

[1160] Step 8:

[1161] Final plan confirmation and booking

[1162] Once the user approves the final travel plan, the server automatically makes online reservations for accommodation and transportation. Reservation APIs (e.g., Booking.com API, Google Travel API) are used for booking.

[1163] Specific actions:

[1164] The server sends the final plan information to the reservation API and completes the necessary reservation.

[1165] input:

[1166] The final travel plan.

[1167] output:

[1168] Reservation confirmation information.

[1169] Step 9:

[1170] Action plan provided

[1171] The server creates an itinerary based on the final travel plan and sends it to the user's device. The user then reviews the itinerary through their device.

[1172] Specific actions:

[1173] The server generates an action plan and sends it to the terminal. The user checks it on the terminal.

[1174] input:

[1175] Final travel plan.

[1176] output:

[1177] Action plan.

[1178] The above outlines the specific processing steps of the travel plan generation system.

[1179] (Application Example 2)

[1180] 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."

[1181] Conventional travel plan generation systems provided optimal travel plans based on the travel dates, budget, region, and desired activities specified by the user. However, because they could not take into account the user's emotional state, the plans often did not necessarily satisfy the user. As a result, users may experience stress and dissatisfaction, potentially impairing the overall user experience of the travel plan. Therefore, the present invention aims to provide a system that utilizes the user's emotional information to automatically generate the travel plan that will satisfy the user the most.

[1182] 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.

[1183] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for transmitting a final itinerary to the user to provide them with the confirmed travel plan; means for collecting and analyzing the user's emotional data using an emotional engine; and means for optimizing the travel plan based on the emotional data. This makes it possible to provide a travel plan optimized for the user's emotional state, thereby improving the user experience.

[1184] A "user" is an individual or group that uses the travel plan generation system.

[1185] "Travel itinerary" refers to the range of dates the user wishes to travel.

[1186] "Budget" refers to the total amount of money a user plans to spend on their trip.

[1187] A "region" is a geographical location that a user wishes to visit.

[1188] "Desired activities" refer to the activities and events that the user would like to participate in during their trip.

[1189] A "database" is a system that stores information on accommodations, tourist attractions, transportation, restaurants, and more.

[1190] An "emotion engine" is a configuration of software and hardware used to collect and analyze user emotional data.

[1191] "Emotional data" refers to information about a user's emotional state obtained from their tone of voice, facial expressions, text input, etc.

[1192] A "travel plan" is a specific itinerary generated based on the user's wishes and emotional state.

[1193] An "action plan" is a detailed schedule created based on a finalized travel plan.

[1194] "Online booking" refers to the process of automatically making reservations for accommodations and transportation via the internet.

[1195] A "schedule generation algorithm" is a set of calculations that analyzes user data to generate the optimal travel plan.

[1196] A "request for revision" is input information in which a user requests changes or improvements to the travel plan presented.

[1197] This invention relates to a system that automatically optimizes travel plans based on a user's emotional information. This system consists of a terminal, a server, a database, and an emotional engine.

[1198] First, users enter information about their travel dates, budget, region, and desired activities into a dedicated app or website on their device. An example of a specific prompt message is: "Please enter the duration of your trip, budget, and desired destinations and activities. We will also analyze your emotional state to suggest the best travel plan for you. For example, if you are feeling stressed, we will prioritize including places where you can relax."

[1199] When a user enters information, the terminal sends that information to the server. Simultaneously, the emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc. The emotion engine identifies the emotional state in real time, for example, using OpenCV or other emotion analysis software.

[1200] The server receives the user's information and emotional data analyzed by the emotion engine. Based on this data, the server runs a schedule generation algorithm to generate queries optimized for the user's emotional state. For example, if the user is seeking relaxation, relaxing tourist destinations and activities will be prioritized in the plan.

[1201] The server uses the generated query to look up data on the database for relevant accommodations, tourist attractions, transportation, and restaurants. Based on this retrieved data, the server generates an optimal travel plan and sends it to the terminal.

[1202] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal. The emotion engine also re-analyzes the user's emotions at this point, identifying any areas of anxiety. The revision requests and emotion data are sent back to the server, which then runs the schedule generation algorithm again to generate a new plan that reflects the emotion data and revision requests.

[1203] If the user is ultimately satisfied with the travel plan, the server automatically makes online reservations for accommodation and transportation. It utilizes a reservation API to complete the necessary booking procedures and notifies the user of the booking confirmation. Then, it creates an itinerary based on the confirmed travel plan and sends it to the user's device for their use.

[1204] For example, if a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice, the server will prioritize including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan will be generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server will automatically make reservations for accommodation and Shinkansen tickets, and a detailed itinerary will be provided to the device.

[1205] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans tailored to individual needs.

[1206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1207] Step 1:

[1208] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website.

[1209] Input: User information (travel itinerary, budget, region, desired activities)

[1210] Output: Sends input information to the terminal.

[1211] Step 2:

[1212] The terminal sends the entered information to the server.

[1213] Input: User information

[1214] Output: Information sent to the server

[1215] Step 3:

[1216] The emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc.

[1217] Input: User voice, facial expressions, text input

[1218] Output: Sentiment data

[1219] Specific operation: Use OpenCV and other sentiment analysis software to identify emotional states in real time.

[1220] Step 4:

[1221] The server receives the user's information and sentiment data that was sent.

[1222] Input: User information, sentiment data

[1223] Output: Data used to generate queries

[1224] Step 5:

[1225] The server executes a schedule generation algorithm based on the user information and sentiment data it receives, and generates the optimal query.

[1226] Input: User information, sentiment data

[1227] Output: Optimized query

[1228] Specific behavior: If the user is looking for relaxation, the query will include relaxing tourist destinations and activities.

[1229] Step 6:

[1230] The server queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[1231] Input: Optimized query

[1232] Output: Accommodation, tourist attractions, transportation, and restaurant data

[1233] Step 7:

[1234] The server generates an optimal travel plan based on the data it acquires and sends it to the device.

[1235] Input: Data on accommodations, tourist attractions, transportation, and restaurants.

[1236] Output: Optimal travel plan

[1237] Step 8:

[1238] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal.

[1239] Input: Feedback on travel plans

[1240] Output: Correction Request

[1241] Step 9:

[1242] The device sends correction requests and sentiment data to the server.

[1243] Input: Correction requests, sentiment data

[1244] Output: Send correction requests and sentiment data to the server.

[1245] Step 10:

[1246] The server runs the schedule generation algorithm again and generates a new plan that reflects the sentiment data and revision requests.

[1247] Input: Correction requests, sentiment data

[1248] Output: New travel plan

[1249] Specific action: If the user requests further relaxation, more relaxing options will be included in the revised plan.

[1250] Step 11:

[1251] If the user is satisfied with the final travel plan, the server will make online reservations for accommodation and transportation.

[1252] Input: Final travel plan

[1253] Output: Reservation confirmation information

[1254] Specific operation: Executes booking procedures for accommodations and transportation via the booking API.

[1255] Step 12:

[1256] The server creates an action plan based on the confirmed travel plan and sends it to the terminal.

[1257] Input: Booking confirmation information, confirmed travel plan

[1258] Output: Action Plan

[1259] Specific actions: Generate an action plan and provide it to the user to guide them through their trip.

[1260] 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.

[1261] 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.

[1262] 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.

[1263] [Fourth Embodiment]

[1264] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1265] 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.

[1266] 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).

[1267] 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.

[1268] 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.

[1269] 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).

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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.

[1276] 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".

[1277] This invention relates to a travel plan generation system that allows users to easily create an ideal travel plan and even automatically make reservations. The system operates as follows:

[1278] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server.

[1279] The server queries the database based on the information received from the user and retrieves data on relevant accommodations, tourist attractions, transportation options, and restaurants. This aggregates information on the server that can serve as a travel option tailored to the user's preferences.

[1280] Next, the server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan. This travel plan includes sightseeing destinations, accommodations, transportation, and dining options, and is designed to meet the user's requirements. The generated travel plan is sent to the terminal and presented to the user.

[1281] The user reviews the proposed travel plan and enters any necessary modification requests. For example, they might want to add more time on a specific day or include additional places to visit. The device then sends the modification requests to the server.

[1282] The server regenerates the travel plan based on the user's revision requests. This time, the initial plan and the user's revision requests are integrated to generate an optimized new travel plan. The regenerated plan is sent to the terminal again for the user to review.

[1283] After the user reviews and approves the final plan, the server sequentially executes online reservations for accommodation and transportation. The server uses a reservation API to automatically make the necessary reservations. Once the reservations are complete, the user is notified and provided with the confirmed travel plan.

[1284] Finally, the server creates an itinerary based on the finalized travel plan and sends it to the device. This itinerary provides a detailed guide for the user to refer to during their trip.

[1285] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. The generated plan might include visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[1286] Thus, the present invention aims to streamline the user's travel planning and booking process and provide an ideal travel experience.

[1287] The following describes the processing flow.

[1288] Step 1:

[1289] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The information entered by the user is formatted on the device and sent to the server as appropriate data packets.

[1290] Step 2:

[1291] The server receives information sent by the user and first parses it. Based on the results of the parsing, the server generates a query to the database. This query retrieves information such as accommodations, tourist attractions, transportation options, and restaurants from the database.

[1292] Step 3:

[1293] The database receives queries from the server and returns relevant information (accommodations, tourist attractions, transportation, restaurants, etc.). Based on the retrieved information, the server executes a schedule generation algorithm to generate the optimal travel plan that meets the user's requirements.

[1294] Step 4:

[1295] The server sends the generated travel plan to the terminal and presents it to the user. The user reviews the travel plan through the terminal. If the user is satisfied, they proceed to the next step; however, if they have any requests for revisions, they enter those requests.

[1296] Step 5:

[1297] When a user enters and submits a revision request, the device sends that information to the server. The server receives the revision request, runs the schedule generation algorithm again, and generates a new travel plan that reflects the revisions.

[1298] Step 6:

[1299] The server sends the regenerated travel plan to the device and presents it to the user again. The user reviews the plan again, and if they agree, they proceed to the next step. If they are dissatisfied, they enter their revision requests again and return to step 5.

[1300] Step 7:

[1301] Once the user finally approves the travel plan, the server executes online reservations for accommodation and transportation. It automatically makes the necessary reservations via a reservation API and monitors the reservation status in real time.

[1302] Step 8:

[1303] The server compiles information on completed reservations and notifies the user. Furthermore, it creates an itinerary based on the confirmed travel plan and sends it to the device.

[1304] Step 9:

[1305] Users receive an itinerary via their device and perform a final check before their trip. The itinerary includes a detailed schedule and booking information, which users use to plan their trip.

[1306] The above describes the specific processing steps in the present invention, which streamline the user's travel planning and booking process.

[1307] (Example 1)

[1308] 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".

[1309] Conventional travel planning and booking systems have the problem of being time-consuming and laborious, as users have to gather a lot of information themselves and make reservations individually. Furthermore, if the generated travel plan does not perfectly match the user's wishes, regeneration and modification are cumbersome, making efficient travel planning difficult. The present invention aims to solve these problems and provide a system that allows users to create an ideal travel plan without effort and complete reservations automatically.

[1310] 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.

[1311] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan using a schedule generation algorithm based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for integrating the user's modification requests using a generation AI model and regenerating an optimized travel plan again; and means for transmitting a final itinerary to provide the user with the confirmed travel plan. This enables the user to generate an ideal travel plan and complete reservations automatically without performing complex operations.

[1312] A "user" refers to an individual or group that uses the system to create travel plans and make reservations.

[1313] "Travel itinerary" refers to the period from the day the user starts their trip until the day it ends.

[1314] "Budget" refers to the maximum amount of money a user can spend on a trip.

[1315] "Region" refers to the place or area that the user wants to travel to.

[1316] "Desired activities" refer to the specific activities and experiences that the user wants to have during their trip.

[1317] "Means of receiving information" refers to an interface for receiving and inputting detailed travel information from users.

[1318] "Means of querying a database" refers to methods and systems for searching for data on suitable accommodations, tourist attractions, transportation options, and restaurants based on information provided by the user.

[1319] "Accommodation facilities" refer to places where users stay during their travels, such as hotels and inns.

[1320] A "tourist destination" refers to a place or landmark that a user would like to visit during their travels.

[1321] "Transportation" refers to the means of transport that users use to get around during their trip, such as trains, buses, and airplanes.

[1322] "Restaurants" refers to places where users eat during their trip.

[1323] A "schedule generation algorithm" refers to the calculation procedure used to create the optimal travel plan based on information entered by the user and data obtained from a database.

[1324] A "generative AI model" refers to a software model that utilizes machine learning and artificial intelligence technologies to automatically create a travel plan that best suits the user's preferences.

[1325] "Means of executing online reservations" refers to systems that automatically book accommodations and transportation on behalf of users.

[1326] An "action plan" refers to a detailed schedule outlining what a user will do and when during their trip.

[1327] "Optimization" refers to adjusting travel plans to best meet the user's needs and requirements.

[1328] A "revision request" refers to a user's request to change or add to a proposed travel plan.

[1329] "Regeneration" refers to the process of recreating a travel plan based on user requests for modifications.

[1330] This invention is a travel plan generation system aimed at enabling users to easily create ideal travel plans and automatically handle bookings. A detailed explanation of how to implement this system is provided below.

[1331] First, the user uses a device (for example, a PC or smartphone) to input their travel itinerary, budget, desired destination, and preferred activities. This input data is converted into a specific format by the device and sent to the server as JSON data, for example.

[1332] Next, the server queries the database based on the user information it received. A database management system such as MySQL or PostgreSQL is used to retrieve information about accommodations, tourist attractions, transportation, and restaurants from the database. The retrieved data includes a list of accommodations and tourist attractions that meet the user's criteria.

[1333] The server then generates a travel plan using a schedule generation algorithm. This algorithm utilizes generative AI models such as TensorFlow or PyTorch. This generates an optimal schedule that takes into account the user's desired travel dates, budget, region, and activities to the greatest extent possible.

[1334] The generated travel plan is sent to the device and presented to the user. The user reviews this plan and enters any necessary revision requests. For example, if the user wants to change the place to visit on day 2, the revision request is sent from the device to the server. The server uses the AI ​​model again to integrate this revision request and generates a new, optimized travel plan. This regenerated plan is also sent to the device for the user to review again.

[1335] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. This reservation process utilizes the APIs of various services (e.g., Expedia and Airbnb APIs). This eliminates the need for the user to make individual reservations themselves.

[1336] Furthermore, an action plan is generated based on the finalized travel plan and sent to the device. This action plan includes details of places to visit, times, and modes of transportation, allowing the user to comfortably plan their trip based on it.

[1337] As a concrete example, consider a user who inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." Based on this information, the server retrieves candidate accommodations, tourist spots, and transportation options from its database and generates an optimal plan. For example, a plan might be generated that includes visiting Kinkaku-ji and Ginkaku-ji temples on the first day and having lunch at a nearby Japanese restaurant. If the user wants to modify part of the plan, they input a modification request, and the plan is regenerated based on that information. Finally, the server automatically makes reservations for accommodations and Shinkansen tickets according to the plan the user has finalized. Before the trip, the user receives an itinerary, which they can use to enjoy a comfortable trip.

[1338] An example of a prompt sentence to input into a generating AI model is: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings. Please suggest a recommended travel plan."

[1339] As described above, this system aims to streamline users' travel planning and booking processes, and to provide them with an ideal travel experience.

[1340] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1341] Step 1:

[1342] Users use their devices to enter information about their travel itinerary, budget, region, and desired activities.

[1343] Input: Travel dates, budget, region, desired activities

[1344] As a concrete example, the user opens a travel plan creation application and enters into the input form, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. I want to see historical buildings."

[1345] Step 2:

[1346] The terminal converts the entered information into JSON format and sends it to the server.

[1347] Input: Travel information entered by the user

[1348] Output: Data in JSON format

[1349] Specifically, the device generates JSON data such as "{ "Dates": "August 1st - August 7th", "Budget": 100000, "Region": "Kyoto", "Activity": "Historical building sightseeing"}" and sends it to the server using an HTTP POST request.

[1350] Step 3:

[1351] The server queries the database based on the received data.

[1352] Input: User information in JSON format

[1353] Output: Information on accommodations, tourist attractions, transportation, and restaurants.

[1354] Specifically, the server executes an SQL query like "SELECT FROM hotels WHERE location='Kyoto' AND price <= 100000" to retrieve data on accommodations. It similarly queries the database for tourist attractions, transportation options, and restaurants.

[1355] Step 4:

[1356] The server executes a schedule generation algorithm based on the acquired data to generate the optimal travel plan.

[1357] Input: Information on accommodations, tourist attractions, transportation, and restaurants.

[1358] Output: Travel plan

[1359] In terms of specific operation, the server uses generative AI models such as TensorFlow to generate an optimal itinerary that aligns with the user's preferences. This itinerary includes a detailed schedule such as "August 1st: Arrive at Kyoto Station → Visit Kinkaku-ji Temple → Visit Ginkaku-ji Temple → Lunch at a Japanese restaurant."

[1360] Step 5:

[1361] The server sends the generated travel plan to the terminal.

[1362] Input: Generated travel plan

[1363] Output: Presentation of travel plan

[1364] Specifically, the server converts the generated travel plan into JSON format and sends it to the terminal as an HTTP response.

[1365] Step 6:

[1366] The user reviews the presented travel plan and enters any revision requests as needed.

[1367] Input: Travel plan

[1368] Output: Correction requests (if necessary)

[1369] In terms of specific actions, the user enters a modification request, such as "I want to change the place I'll visit on the second day," on the plan confirmation screen.

[1370] Step 7:

[1371] The device sends the correction request to the server.

[1372] Input: Correction Request

[1373] Output: Revised travel plan

[1374] Specifically, the terminal converts the correction request into JSON format and sends it to the server.

[1375] Step 8:

[1376] The server receives the correction request and generates an optimized travel plan again using the AI ​​model.

[1377] Input: Correction Request

[1378] Output: Regenerated travel plan

[1379] Specifically, the server integrates the initial travel plan with the requested revisions and then uses the generative AI model again to generate a new plan.

[1380] Step 9:

[1381] The user reviews and approves the final travel plan.

[1382] Input: Regenerated travel plan

[1383] Output: Final Approval

[1384] Specifically, the user reviews the regenerated travel plan on their device and presses the approve button.

[1385] Step 10:

[1386] The server makes online reservations for accommodations and transportation based on the final approved travel plan.

[1387] Input: Final approved travel plan

[1388] Output: Reservation confirmation

[1389] Specifically, the server uses an API to automatically book accommodations and transportation, and retrieves booking confirmation information.

[1390] Step 11:

[1391] Based on the confirmed travel plan and reservation information, an itinerary is created and sent to the device.

[1392] Input: Final travel plans and booking confirmation information

[1393] Output: Action plan

[1394] Specifically, the server integrates the schedule and reservation information, converts the action plan into JSON format, and sends it to the terminal.

[1395] In this way, users can create their ideal travel plan with minimal effort and have bookings completed automatically.

[1396] (Application Example 1)

[1397] 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".

[1398] Traditional travel planning systems struggled to automatically generate optimal travel plans and handle bookings based on user input such as itinerary, budget, region, and desired activities. Furthermore, creating flexible travel plans that incorporated user preferences often required significant effort and time, hindering a positive user experience. Additionally, the process of regenerating optimized plans when users modified their existing ones was cumbersome, highlighting the lack of sufficient automation.

[1399] 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.

[1400] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; and means for generating an optimal travel plan using a generation AI model based on the obtained data and presenting it to the user. This enables the user to easily create an ideal travel plan and efficiently make reservations. Furthermore, prompt messages can be generated based on user requests for modifications, and the travel plan can be regenerated, enabling the provision of flexible travel plans.

[1401] A "user" is someone who creates a travel plan by entering information about their travel dates, budget, region, and desired activities.

[1402] A "travel plan" is a proposed itinerary generated based on the travel dates, budget, region, and desired activities set by the user.

[1403] A "generative AI model" is an artificial intelligence computational model used to automatically optimize and generate travel plans.

[1404] A "database" is a storage device that stores information about accommodations, tourist destinations, transportation, and restaurants.

[1405] A "schedule generation algorithm" is a computational method for generating the optimal travel plan using user input information and database information.

[1406] A "prompt" is a document-formatted instruction given to a generative AI model to generate a travel plan.

[1407] An "API" is an application programming interface used by servers to automatically execute online reservations for accommodations and transportation.

[1408] "Online booking" refers to the process of making reservations for accommodations and transportation via the internet.

[1409] An "action plan sheet" is a table that contains specific instructions for the user to refer to during their trip, based on a finalized travel plan.

[1410] This invention is a system for users to create travel plans and make reservations automatically. Specific embodiments are described below.

[1411] First, the user enters information about their travel itinerary, budget, region, and desired activities into the device. The device converts the entered information into a specific format and sends it to the server. The hardware used is mainly smartphones and smart glasses, and the software utilizes JavaScript and React.js as front-end technologies.

[1412] The server queries the database based on the received user information to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants. The database used is PostgreSQL. Next, an AI model (e.g., GPT-3) is used to generate an optimal travel plan based on the retrieved data. The generated plan is sent to the terminal and presented to the user. The server uses a server-side framework such as Django for this process.

[1413] For example, if a user enters "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," the server will retrieve suitable accommodations, tourist attractions, transportation options, and restaurants from its database and generate the optimal plan.

[1414] When a user reviews a proposed travel plan and enters further modification requests, the AI ​​model generates prompts based on those requests and then creates an optimal plan again. For example, if a user requests to "add Ginkaku-ji Temple after visiting Kinkaku-ji Temple," the new prompt will be changed to "After visiting Kinkaku-ji Temple, I would also like to visit Ginkaku-ji Temple." This allows for flexible regeneration of travel plans.

[1415] Based on the confirmed travel plan, the server automatically makes online reservations for accommodations and transportation via API. Once the reservations are complete, the user is notified of the confirmed travel plan, and a final itinerary is generated. This itinerary provides a detailed travel plan that the user can refer to during their trip.

[1416] Thus, this invention aims to streamline the user's travel planning and booking process, and to provide an ideal travel experience.

[1417] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1418] Step 1:

[1419] The user enters information about their travel itinerary, budget, region, and desired activities into the device.

[1420] The input information includes departure date, return date, budget, desired destination, and specific activities. This information is converted to JSON format on the device and sent to the server.

[1421] Step 2:

[1422] The server analyzes the received user information and queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[1423] Input: User's travel information (e.g., dates, budget, region, activities)

[1424] Data processing: Query the PostgreSQL database using SQL to retrieve relevant information.

[1425] Output: Data on applicable accommodations, tourist attractions, transportation, and restaurants.

[1426] Step 3:

[1427] The server generates an optimal travel plan using an AI model (e.g., GPT-3) based on the acquired data, and presents it to the user.

[1428] Input: Candidate data retrieved from the database

[1429] Data processing: Input prompts into a generative AI model to generate travel plans.

[1430] Output: Draft travel plan generated

[1431] Step 4:

[1432] The user reviews the presented travel plan and enters any necessary modification requests into the terminal.

[1433] Input: Generated travel plan and user modification requests

[1434] Output: Information including correction requests

[1435] Step 5:

[1436] The server generates a prompt message based on the correction request and then uses the generation AI model again to generate a new travel plan.

[1437] Input: Correction Request

[1438] Data processing: Generate new prompt messages based on the requested modifications.

[1439] Data processing: Re-input data into the generative AI model to obtain a regenerated travel plan.

[1440] Output: Regenerated travel plan

[1441] Step 6:

[1442] After the user reviews and approves the final plan, the server automatically makes online reservations for accommodation and transportation via API.

[1443] Input: Final travel plan

[1444] Data processing: Execute online reservations via API

[1445] Output: Information confirming the reservation has been completed.

[1446] Step 7:

[1447] Based on the finalized travel plan, the server generates a detailed itinerary and sends it to the user's device. This provides the user with a specific guide to refer to during their trip.

[1448] Input: Confirmed travel plan

[1449] Data processing: Create an action plan based on the travel plan.

[1450] Output: Action Plan

[1451] 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.

[1452] This invention combines a travel plan generation system with an emotion engine, aiming to automatically optimize travel plans based on the user's emotional information. The system consists of a terminal, server, database, and emotion engine. Furthermore, the system is designed to automate travel plan generation and booking, thereby improving the user experience.

[1453] First, the user enters information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device receives the user's input and sends it to a server. Simultaneously, an emotion engine collects and analyzes emotional data from the user's tone of voice, facial expressions, text input, etc. This allows the user's current emotional state to be understood in real time.

[1454] The server receives the transmitted information and sentiment data and generates queries that take the user's emotional state into account. For example, if the user is feeling stressed, the system will adjust its recommendations to prioritize relaxing tourist destinations and activities. Using these queries, the server searches the database to retrieve data on relevant accommodations, tourist attractions, transportation, and restaurants.

[1455] Based on the acquired data, the server executes a schedule generation algorithm to generate a travel plan optimized for the user's emotional state. The generated plan is sent to the terminal and presented to the user.

[1456] The user reviews the presented travel plan and, if they have any complaints or suggestions for improvement, enters revision requests. The emotion engine analyzes the user's emotions at this point as well, recognizing, for example, that the user is feeling anxious about a particular part of the plan. The device then sends the revision requests and emotion data to the server.

[1457] The server runs the schedule generation algorithm again, generating a new travel plan that reflects the sentiment data and requested modifications. This new travel plan is sent to the terminal again and presented to the user. This process is repeated until the user is satisfied with the final plan.

[1458] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. All necessary reservations are completed via the reservation API, and the server notifies the user of the reservation completion information and creates an itinerary based on the confirmed travel plan. This itinerary is then sent to the user's device and provided to them.

[1459] As a concrete example, consider a scenario where a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice. In this case, the server prioritizes including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan is generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server automatically makes reservations for accommodation and Shinkansen tickets, and a detailed itinerary is provided to the device.

[1460] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans that better suit individual needs.

[1461] The following describes the processing flow.

[1462] Step 1:

[1463] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website on their device. The device formats the entered information and sends it to the server as data packets.

[1464] Step 2:

[1465] Simultaneously, the device activates its emotion engine and collects emotional data from the user's voice, facial expressions, and input. This emotional data is then analyzed, allowing the user's current emotional state to be understood in real time.

[1466] Step 3:

[1467] The server receives travel information and emotional data from the user and uses this information to generate queries for the database. For example, if a user is experiencing stress, the server will prioritize selecting relaxing tourist destinations and activities.

[1468] Step 4:

[1469] The server sends the generated query to the database and retrieves data on relevant accommodations, tourist attractions, transportation, and restaurants. The database returns the relevant data to the server according to the query.

[1470] Step 5:

[1471] The server executes a schedule generation algorithm based on the acquired data, generating a travel plan optimized for the user's emotional state. The generated travel plan is sent to the terminal and presented to the user.

[1472] Step 6:

[1473] Users review their travel plans through their devices. If they have any complaints or suggestions for improvement regarding specific dates or destinations, they input their requests for revisions into their devices. The emotion engine continues to analyze the user's emotions throughout this process, detecting changes in their feelings towards specific points.

[1474] Step 7:

[1475] The device sends the user's revision requests and sentiment data to the server. The server runs the schedule generation algorithm again and generates a new travel plan that reflects the revision requests and sentiment data.

[1476] Step 8:

[1477] The server sends the new travel plan to the device and presents it to the user again. This revision and confirmation process is repeated until the user is satisfied with the final plan.

[1478] Step 9:

[1479] After the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. It uses a reservation API to make the necessary reservations and compiles all the completed reservation information.

[1480] Step 10:

[1481] The server notifies the user of the booking confirmation and creates a detailed itinerary based on the confirmed travel plan. This itinerary is sent to the user's device, and the user performs a final check before traveling.

[1482] In this way, this system, which incorporates an emotion engine, can significantly improve the user experience by automatically generating optimal travel plans based on the user's emotional information and efficiently handling the booking process.

[1483] (Example 2)

[1484] 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".

[1485] Conventional travel plan generation systems generate plans based on basic user information, but they do not take into account the user's emotional state, making it difficult to provide travel plans that truly satisfy the user. Furthermore, when modifying a plan after it has been generated, it is difficult to adequately reflect the user's emotions and wishes, resulting in a poor user experience. In addition, the booking process was not fully automated, requiring users to make reservations manually, which reduced convenience. This invention aims to solve these problems and provide optimal travel plans based on the user's emotions.

[1486] The identification processing by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for transmitting the received information to the server; means including an emotion engine for collecting and analyzing the user's emotion data; means for generating queries based on the received information and the analyzed emotion data, querying a database, and obtaining data on relevant accommodations, tourist attractions, transportation, and restaurants; means for executing a schedule generation algorithm based on the obtained data to generate an optimal travel plan and present it to the user; means for generating a new travel plan after the user has confirmed and modified the travel plan, reflecting the modification requests and emotion data; means for executing online reservations for accommodations and transportation based on the final travel plan; and means for transmitting a final itinerary to the user to provide them with the confirmed travel plan. This makes it possible to analyze the user's emotion data in real time and provide an optimal travel plan that reflects it. Furthermore, the automation of the reservation procedure reduces the effort required from the user and improves convenience.

[1487] A "user" is an individual or group that uses the travel plan generation system to create a travel plan.

[1488] "Travel itinerary" refers to information that indicates the range of dates within which a user plans their trip.

[1489] "Budget" refers to the amount of money a user plans to spend on their trip.

[1490] "Region" refers to information that indicates the place the user wishes to travel to.

[1491] "Desired activities" refers to information about specific activities or experiences that the user wants to do during their trip.

[1492] A "device" refers to an electronic device (e.g., smartphone, tablet, or personal computer) that a user uses to input travel information and to review and modify their travel plan.

[1493] A "server" is a computer system that receives and processes information from users and generates and provides travel plans.

[1494] "Emotional data" refers to data about a user's emotional state, collected from the tone of their voice, facial expressions, text input, and other sources.

[1495] An "emotion engine" is software or a system used to collect and analyze user emotional data.

[1496] A "query" is a search instruction generated from a database to retrieve specific information.

[1497] A "database" is an information management system that stores information necessary for generating travel plans, such as accommodations, tourist destinations, transportation options, and restaurants.

[1498] A "schedule generation algorithm" refers to the mathematical methods and calculation procedures used to calculate and generate the optimal travel plan based on acquired data.

[1499] "Online booking" refers to the automated process of making reservations for accommodations and transportation via the internet.

[1500] An "action plan" is a document created based on a finalized travel plan, outlining the detailed schedule that the user should follow during their trip.

[1501] This invention relates to a system that automatically optimizes travel plans based on user sentiment information. This system consists of a terminal, a server, a database, and a sentiment engine. Specific embodiments are described below.

[1502] First, users enter information about their travel dates, budget, region, and desired activities through a smartphone app or website. The app or website used consists of a frontend using React or Vue.js and a backend using Node.js or Django. For example, a user might enter a prompt like this: "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings."

[1503] The device sends the information entered by the user to the server. Simultaneously, an emotion engine (e.g., Microsoft Azure Emotion API or IBM Watson Tone Analyzer) collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. This allows the system to understand the user's current emotional state.

[1504] The server integrates received user information and emotional data to generate queries tailored to the user's emotional state. For example, if a user is experiencing high stress levels, the server will prioritize recommending relaxing tourist destinations. Using these queries, the server searches databases such as MongoDB or MySQL to retrieve data on relevant accommodations, tourist destinations, transportation options, and restaurants.

[1505] Based on the acquired data, the server executes a schedule generation algorithm. For example, it uses Python's Scikit-learn or TensorFlow to generate the optimal travel plan. The generated plan is sent to the terminal and presented to the user.

[1506] When a user reviews a presented travel plan and enters requests for revisions, the emotion engine analyzes the user's emotions at this point and sends the emotion data and revision requests to the server. The server then runs the schedule generation algorithm again to generate a new travel plan that reflects the revision requests and emotion data. This process is repeated until the user is satisfied with the final plan.

[1507] Once the user finally approves the travel plan, the server automatically makes online reservations for accommodation and transportation. The necessary reservations are completed via a booking API (e.g., Booking.com API or Google Travel API), and the server notifies the user of the reservation confirmation. Then, based on the confirmed travel plan, an itinerary is created and sent to the user's device.

[1508] Thus, by utilizing user emotional data, the present invention can provide travel plans that better suit individual needs and significantly improve the user experience. Furthermore, the automation of booking procedures reduces user effort and improves convenience.

[1509] As described above, the present invention realizes the optimization of travel plans based on user emotional data.

[1510] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1511] Step 1:

[1512] Entering user information

[1513] Users input information about their travel dates, budget, region, and desired activities through a smartphone app or website. For example, a user might enter a prompt message such as, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings." This is the input data.

[1514] Specific actions:

[1515] The user fills in the required information in the input form and presses the "Submit" button.

[1516] input:

[1517] Information entered by the user, including travel itinerary, budget, region, and desired activities.

[1518] output:

[1519] User travel plan request data.

[1520] Step 2:

[1521] Send user information

[1522] The terminal sends the information entered by the user to the server. HTTPS is used as the transmission protocol.

[1523] Specific actions:

[1524] When the user presses the "Send" button, the device sends the input data to the server via HTTPS communication.

[1525] input:

[1526] User travel plan request data.

[1527] output:

[1528] User information sent to the server.

[1529] Step 3:

[1530] Collection and analysis of emotional data

[1531] The emotion engine collects and analyzes emotional data in real time from the user's voice tone, facial expressions, and text input. The emotion engine utilizes Microsoft Azure Emotion API and IBM Watson Tone Analyzer.

[1532] Specific actions:

[1533] The device collects data from its built-in microphone, camera, and keyboard input, and passes it to the emotion engine. The emotion engine then analyzes this data.

[1534] input:

[1535] Voice tone, facial expressions, and text input data acquired from the device.

[1536] output:

[1537] Analyzed user sentiment data.

[1538] Step 4:

[1539] Query generation and database queries

[1540] The server generates queries based on user input and analyzed sentiment data, and queries the database. This retrieves data on optimal accommodations, tourist attractions, transportation, and restaurants.

[1541] Specific actions:

[1542] The server integrates user information and emotional data, and generates queries that prioritize relaxing tourist destinations if the user is experiencing high levels of stress. The generated queries are then sent to the database to retrieve the appropriate data.

[1543] input:

[1544] User information and analyzed sentiment data.

[1545] output:

[1546] Data on accommodations, tourist attractions, transportation, and restaurants obtained from a database.

[1547] Step 5:

[1548] Execute schedule generation algorithm

[1549] Based on the acquired data, the server executes a schedule generation algorithm (e.g., an algorithm using TensorFlow) to generate the optimal travel plan.

[1550] Specific actions:

[1551] The server inputs the acquired data into a schedule generation algorithm to calculate the optimal schedule. The generated plan is then sent to the terminal.

[1552] input:

[1553] The necessary data retrieved from the database.

[1554] output:

[1555] A generated travel plan.

[1556] Step 6:

[1557] Presentation and modification of travel plans

[1558] The terminal presents the generated travel plan to the user. The user reviews the plan and enters any desired modifications. At this point, the emotion engine continues to collect and analyze the user's emotional data and sends it to the server.

[1559] Specific actions:

[1560] The device displays the travel plan on its screen, and when the user enters any requested modifications, the device sends them to the server.

[1561] input:

[1562] Generated travel plans and user sentiment data.

[1563] output:

[1564] Data with requested corrections and sentiment data.

[1565] Step 7:

[1566] Generating a readjustment plan

[1567] Based on the requested changes and sentiment data, the server runs the schedule generation algorithm again to generate a new travel plan. This process is repeated until the user is satisfied.

[1568] Specific actions:

[1569] The server inputs the requested correction data and sentiment data into an algorithm, calculates and generates a new plan, and sends the generated new plan to the terminal.

[1570] input:

[1571] Data requested for correction and user sentiment data.

[1572] output:

[1573] A new travel plan.

[1574] Step 8:

[1575] Final plan confirmation and booking

[1576] Once the user approves the final travel plan, the server automatically makes online reservations for accommodation and transportation. Reservation APIs (e.g., Booking.com API, Google Travel API) are used for booking.

[1577] Specific actions:

[1578] The server sends the final plan information to the reservation API and completes the necessary reservation.

[1579] input:

[1580] The final travel plan.

[1581] output:

[1582] Reservation confirmation information.

[1583] Step 9:

[1584] Action plan provided

[1585] The server creates an itinerary based on the final travel plan and sends it to the user's device. The user then reviews the itinerary through their device.

[1586] Specific actions:

[1587] The server generates an action plan and sends it to the terminal. The user checks it on the terminal.

[1588] input:

[1589] Final travel plan.

[1590] output:

[1591] Action plan.

[1592] The above outlines the specific processing steps of the travel plan generation system.

[1593] (Application Example 2)

[1594] 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".

[1595] Conventional travel plan generation systems provided optimal travel plans based on the travel dates, budget, region, and desired activities specified by the user. However, because they could not take into account the user's emotional state, the plans often did not necessarily satisfy the user. As a result, users may experience stress and dissatisfaction, potentially impairing the overall user experience of the travel plan. Therefore, the present invention aims to provide a system that utilizes the user's emotional information to automatically generate the travel plan that will satisfy the user the most.

[1596] 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.

[1597] In this invention, the server includes means for receiving information from the user regarding travel itinerary, budget, region, and desired activities; means for querying a database based on the received information to obtain data on relevant accommodations, tourist attractions, transportation, and restaurants; means for generating an optimal travel plan based on the obtained data and presenting it to the user; means for executing online reservations for accommodations and transportation after the travel plan has been confirmed and modified by the user; means for transmitting a final itinerary to the user to provide them with the confirmed travel plan; means for collecting and analyzing the user's emotional data using an emotional engine; and means for optimizing the travel plan based on the emotional data. This makes it possible to provide a travel plan optimized for the user's emotional state, thereby improving the user experience.

[1598] A "user" is an individual or group that uses the travel plan generation system.

[1599] "Travel itinerary" refers to the range of dates the user wishes to travel.

[1600] "Budget" refers to the total amount of money a user plans to spend on their trip.

[1601] A "region" is a geographical location that a user wishes to visit.

[1602] "Desired activities" refer to the activities and events that the user would like to participate in during their trip.

[1603] A "database" is a system that stores information on accommodations, tourist attractions, transportation, restaurants, and more.

[1604] An "emotion engine" is a configuration of software and hardware used to collect and analyze user emotional data.

[1605] "Emotional data" refers to information about a user's emotional state obtained from their tone of voice, facial expressions, text input, etc.

[1606] A "travel plan" is a specific itinerary generated based on the user's wishes and emotional state.

[1607] An "action plan" is a detailed schedule created based on a finalized travel plan.

[1608] "Online booking" refers to the process of automatically making reservations for accommodations and transportation via the internet.

[1609] A "schedule generation algorithm" is a set of calculations that analyzes user data to generate the optimal travel plan.

[1610] A "request for revision" is input information in which a user requests changes or improvements to the travel plan presented.

[1611] This invention relates to a system that automatically optimizes travel plans based on a user's emotional information. This system consists of a terminal, a server, a database, and an emotional engine.

[1612] First, users enter information about their travel dates, budget, region, and desired activities into a dedicated app or website on their device. An example of a specific prompt message is: "Please enter the duration of your trip, budget, and desired destinations and activities. We will also analyze your emotional state to suggest the best travel plan for you. For example, if you are feeling stressed, we will prioritize including places where you can relax."

[1613] When a user enters information, the terminal sends that information to the server. Simultaneously, the emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc. The emotion engine identifies the emotional state in real time, for example, using OpenCV or other emotion analysis software.

[1614] The server receives the user's information and emotional data analyzed by the emotion engine. Based on this data, the server runs a schedule generation algorithm to generate queries optimized for the user's emotional state. For example, if the user is seeking relaxation, relaxing tourist destinations and activities will be prioritized in the plan.

[1615] The server uses the generated query to look up data on the database for relevant accommodations, tourist attractions, transportation, and restaurants. Based on this retrieved data, the server generates an optimal travel plan and sends it to the terminal.

[1616] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal. The emotion engine also re-analyzes the user's emotions at this point, identifying any areas of anxiety. The revision requests and emotion data are sent back to the server, which then runs the schedule generation algorithm again to generate a new plan that reflects the emotion data and revision requests.

[1617] If the user is ultimately satisfied with the travel plan, the server automatically makes online reservations for accommodation and transportation. It utilizes a reservation API to complete the necessary booking procedures and notifies the user of the booking confirmation. Then, it creates an itinerary based on the confirmed travel plan and sends it to the user's device for their use.

[1618] For example, if a user inputs, "I want to go to Kyoto from August 1st to August 7th with a budget of 100,000 yen. My main mode of transportation will be the Shinkansen (bullet train), and I want to see historical buildings," and the emotion engine detects a high stress level from the user's voice, the server will prioritize including relaxing tourist spots (for example, quiet gardens or hot spring resorts) in the plan. If the user reviews the plan and modifies some of the destinations to make them more relaxing, a new plan will be generated that reflects those requests and the emotion data. If the user is ultimately satisfied, the server will automatically make reservations for accommodation and Shinkansen tickets, and a detailed itinerary will be provided to the device.

[1619] Thus, the present invention aims to significantly improve the user experience by utilizing user emotional data to provide travel plans tailored to individual needs.

[1620] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1621] Step 1:

[1622] Users enter information about their travel itinerary, budget, region, and desired activities into a dedicated app or website.

[1623] Input: User information (travel itinerary, budget, region, desired activities)

[1624] Output: Sends input information to the terminal.

[1625] Step 2:

[1626] The terminal sends the entered information to the server.

[1627] Input: User information

[1628] Output: Information sent to the server

[1629] Step 3:

[1630] The emotion engine collects and analyzes emotional data from the user's voice tone, facial expressions, text input, etc.

[1631] Input: User voice, facial expressions, text input

[1632] Output: Sentiment data

[1633] Specific operation: Use OpenCV and other sentiment analysis software to identify emotional states in real time.

[1634] Step 4:

[1635] The server receives the user's information and sentiment data that was sent.

[1636] Input: User information, sentiment data

[1637] Output: Data used to generate queries

[1638] Step 5:

[1639] The server executes a schedule generation algorithm based on the user information and sentiment data it receives, and generates the optimal query.

[1640] Input: User information, sentiment data

[1641] Output: Optimized query

[1642] Specific behavior: If the user is looking for relaxation, the query will include relaxing tourist destinations and activities.

[1643] Step 6:

[1644] The server queries the database to retrieve data on relevant accommodations, tourist attractions, transportation options, and restaurants.

[1645] Input: Optimized query

[1646] Output: Accommodation, tourist attractions, transportation, and restaurant data

[1647] Step 7:

[1648] The server generates an optimal travel plan based on the data it acquires and sends it to the device.

[1649] Input: Data on accommodations, tourist attractions, transportation, and restaurants.

[1650] Output: Optimal travel plan

[1651] Step 8:

[1652] The user reviews the presented travel plan and enters any dissatisfaction or suggestions for improvement into the terminal.

[1653] Input: Feedback on travel plans

[1654] Output: Correction Request

[1655] Step 9:

[1656] The device sends correction requests and sentiment data to the server.

[1657] Input: Correction requests, sentiment data

[1658] Output: Send correction requests and sentiment data to the server.

[1659] Step 10:

[1660] The server runs the schedule generation algorithm again and generates a new plan that reflects the sentiment data and revision requests.

[1661] Input: Correction requests, sentiment data

[1662] Output: New travel plan

[1663] Specific action: If the user requests further relaxation, more relaxing options will be included in the revised plan.

[1664] Step 11:

[1665] If the user is satisfied with the final travel plan, the server will make online reservations for accommodation and transportation.

[1666] Input: Final travel plan

[1667] Output: Reservation confirmation information

[1668] Specific operation: Executes booking procedures for accommodations and transportation via the booking API.

[1669] Step 12:

[1670] The server creates an action plan based on the confirmed travel plan and sends it to the terminal.

[1671] Input: Booking confirmation information, confirmed travel plan

[1672] Output: Action Plan

[1673] Specific actions: Generate an action plan and provide it to the user to guide them through their trip.

[1674] 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.

[1675] 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.

[1676] 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.

[1677] 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.

[1678] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1679] 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.

[1680] 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.

[1681] 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.

[1682] 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."

[1683] 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.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] 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.

[1691] 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.

[1692] 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.

[1693] 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.

[1694] 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.

[1695] The following is further disclosed regarding the embodiments described above.

[1696] (Claim 1)

[1697] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities,

[1698] A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants,

[1699] A means for generating and presenting an optimal travel plan to the user based on the acquired data,

[1700] After the aforementioned travel plan has been reviewed and modified by the user, a means for making online reservations for accommodation and transportation is provided.

[1701] A means of sending a final itinerary to the user in order to provide them with a confirmed travel plan,

[1702] A system that includes this.

[1703] (Claim 2)

[1704] The system according to claim 1, further comprising means for analyzing the acquired data and executing a schedule generation algorithm.

[1705] (Claim 3)

[1706] The system according to claim 1, further comprising means for regenerating a travel plan based on the user's request for modification.

[1707] The above is the draft of the patent claims.

[1708] "Example 1"

[1709] (Claim 1)

[1710] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities,

[1711] A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants,

[1712] A means of generating an optimal travel plan using a schedule generation algorithm based on the acquired data and presenting it to the user,

[1713] After the aforementioned travel plan has been confirmed and modified by the user, a means for making online reservations for accommodation and transportation is provided.

[1714] A means of integrating user modification requests using a generative AI model and regenerating an optimized travel plan,

[1715] A means of sending the final itinerary to the user in order to provide them with a confirmed travel plan,

[1716] A system that includes this.

[1717] (Claim 2)

[1718] The system according to claim 1, further comprising means for analyzing the acquired data and generating a specific action schedule.

[1719] (Claim 3)

[1720] The system according to claim 1, further comprising means for generating a travel plan again based on the user's request for modification.

[1721] "Application Example 1"

[1722] (Claim 1)

[1723] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities,

[1724] A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants,

[1725] A means of generating an optimal travel plan using an AI model based on the acquired data and presenting it to the user,

[1726] After the aforementioned travel plan has been confirmed and modified by the user, a means for automatically executing online reservations for accommodations and transportation via an API,

[1727] A means of generating and sending a final itinerary to provide the user with a confirmed travel plan,

[1728] A system that includes this.

[1729] (Claim 2)

[1730] The system according to claim 1, further comprising means for analyzing the acquired data and executing a schedule generation algorithm.

[1731] (Claim 3)

[1732] The system according to claim 1, further comprising means for generating a prompt message and regenerating a travel plan based on the user's request for modification.

[1733] "Example 2 of combining an emotion engine"

[1734] (Claim 1)

[1735] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities,

[1736] A means for transmitting the received information to a server,

[1737] Means including an emotion engine for collecting and analyzing the user's emotion data,

[1738] A means for generating queries based on the received information and the analyzed sentiment data, querying a database, and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants,

[1739] A means of generating an optimal travel plan by executing a schedule generation algorithm based on the acquired data and presenting it to the user,

[1740] After the aforementioned travel plan has been reviewed and modified by the user, a means for regenerating the travel plan by reflecting the modification requests and sentiment data,

[1741] A means of making online reservations for accommodations and transportation based on the final travel plan,

[1742] A means of sending a final itinerary to the user in order to provide them with a confirmed travel plan,

[1743] A system that includes this.

[1744] (Claim 2)

[1745] The system according to claim 1, further comprising means for using an artificial intelligence model (e.g., a machine learning algorithm) to execute the schedule generation algorithm.

[1746] (Claim 3)

[1747] The system according to claim 1, further comprising means for analyzing the user's emotional data in real time and reflecting it in the generation and modification of travel plans.

[1748] The above constitutes the claims.

[1749] "Application example 2 of combining emotional engines"

[1750] (Claim 1)

[1751] A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities,

[1752] A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants,

[1753] A means for generating and presenting an optimal travel plan to the user based on the acquired data,

[1754] After the aforementioned travel plan has been reviewed and modified by the user, a means for making online reservations for accommodation and transportation is provided.

[1755] A means of sending a final itinerary to the user in order to provide them with a confirmed travel plan,

[1756] A means of collecting and analyzing user emotional data using an emotion engine,

[1757] A means for optimizing a travel plan based on the aforementioned emotional data,

[1758] A system that includes this.

[1759] (Claim 2)

[1760] The system according to claim 1, further comprising means for analyzing acquired data and executing a schedule generation algorithm.

[1761] (Claim 3)

[1762] The system according to claim 1, further comprising means for regenerating a travel plan based on user requests for modifications. [Explanation of Symbols]

[1763] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of receiving information from users regarding their travel itinerary, budget, region, and desired activities, A means of querying a database based on the information received and obtaining data on relevant accommodations, tourist destinations, transportation, and restaurants, A means for generating and presenting an optimal travel plan to the user based on the acquired data, After the aforementioned travel plan has been reviewed and modified by the user, a means for making online reservations for accommodation and transportation is provided. A means of sending a final itinerary to the user in order to provide them with a confirmed travel plan, A system that includes this.

2. The system according to claim 1, further comprising means for analyzing the acquired data and executing a schedule generation algorithm.

3. The system according to claim 1, further comprising means for generating a travel plan again based on the user's request for modification.

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