system

Abstract

We provide the system. [Solution] A means for receiving tourist information entered by the user, Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information, Means for transmitting the generated sightseeing plan to the user terminal, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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] There are the following three problems faced by conventional tourists visiting Japan. First, although the stay time of tourists visiting Japan is limited, they get lost due to lack of local knowledge and waste time. Second, it is difficult to reorganize a plan according to the budget and time only with the information in the guidebook, which is very troublesome. Third, since it takes courage to ask locals for directions, there is a need to collect information by oneself as much as possible. The purpose of the present invention is to solve these problems so that tourists visiting Japan can enjoy sightseeing efficiently.

Means for Solving the Problems

[0005] This invention provides a tourism support system for tourists visiting Japan. The system includes means for receiving tourism information entered by a user, means for calling a generative AI model that generates an optimal tourism plan based on the tourism information, and means for transmitting the generated tourism plan to a user terminal. This enables the automatic generation of efficient and optimal tourism plans, improving the user's tourism experience. The tourism information includes places to visit, budget, available time, and the user's areas of interest, and the generative AI model has means for calculating the optimal tourism route by referring to a database of tourist spots and restaurants. As a result, users can easily obtain a tourism plan that is best suited to them, significantly reducing time lost during sightseeing and the stress of gathering information.

[0006] "Means for receiving user-entered tourist information" refers to a function that allows users to send and receive information such as tourist destinations, budget, available time, and areas of interest entered by users from their smartphones or other devices to a server.

[0007] A "generative AI model that generates optimal sightseeing plans" refers to artificial intelligence that automatically calculates and generates the optimal sightseeing route and schedule based on sightseeing information entered by the user, referencing a database of tourist spots and restaurants.

[0008] "Means for sending sightseeing plans to user terminals" refers to communication and data transmission functions that send the generated sightseeing plans from the server to the user's smartphone or other terminal for display.

[0009] "Tourism information" refers to information entered by the user regarding places to visit, budget, available time, and areas of interest.

[0010] A "tourist spot and restaurant database" refers to a database containing information and data about tourist destinations and restaurants, which is referenced by the AI ​​model when creating the optimal travel plan.

[0011] An "optimal sightseeing route" refers to a route calculated to allow users to visit tourist spots efficiently and effectively, based on the conditions they specify. [Brief explanation of the drawing]

[0012] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying out the Invention

[0013] 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.

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

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

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

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

[0018] In the following embodiments, the 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).

[0019] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0020] [First Embodiment]

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

[0022] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0023] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0024] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0025] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0026] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0027] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0029] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0030] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0031] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0032] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0033] This invention is a tourism support system for tourists visiting Japan. This system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and then transmits that plan to the user's terminal.

[0034] System Configuration

[0035] This system consists of the following main components:

[0036] 1. User Device

[0037] 2. Server

[0038] 3. Generative AI Model

[0039] System operation

[0040] User terminal operation

[0041] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is collected on the user's device and sent to the server.

[0042] Server operation

[0043] The server receives tourist information entered from the user's terminal. The received data is passed to a generating AI model, which then starts processing to create the optimal tourist plan. The server uses this tourist data to call the generating AI model and refer to a database of tourist spots and restaurants.

[0044] How generative AI models work

[0045] The AI ​​model uses user data received from the server to reference a database of tourist spots and restaurants. The AI ​​model calculates the optimal sightseeing route and selects places and facilities to visit. This generates an optimal sightseeing plan tailored to the user's preferences. This plan includes the order of visits, total cost, and estimated time required.

[0046] Sending from server to user terminal

[0047] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0048] Displaying the plan on the user's device

[0049] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0050] Specific example

[0051] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server.

[0052] The server receives this information and requests the generating AI model to create the optimal sightseeing plan. The generating AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these locations, and sends the plan, including the optimal route, back to the server.

[0053] The server sends this plan to the user's terminal, and it is displayed on Mr. Tanaka's terminal. Mr. Tanaka can then enjoy sightseeing efficiently by following this plan.

[0054] The system according to the present invention helps tourists efficiently tour tourist destinations, reducing time loss and the stress of gathering information. Furthermore, by accumulating tourism data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[0055] The following describes the processing flow.

[0056] Step 1:

[0057] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. This entered data is collected within the app.

[0058] Step 2:

[0059] The terminal sends the data entered by the user to the server. During this process, the data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[0060] Step 3:

[0061] The server receives the data sent from the terminal, verifies the validity of the data format, and then passes it on to the generating AI model.

[0062] Step 4:

[0063] The server invokes a generating AI model, passing the user's travel information as input data. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[0064] Step 5:

[0065] The AI ​​model generates an optimal travel plan based on the user's criteria. For example, the plan may include a list of sightseeing spots to visit, the order in which to visit them, estimated time required, and total cost.

[0066] Step 6:

[0067] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[0068] Step 7:

[0069] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[0070] Step 8:

[0071] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can then review this information and begin sightseeing according to the suggested plan.

[0072] Through the steps described above, the system of the present invention can provide support for tourists visiting Japan to efficiently enjoy sightseeing.

[0073] (Example 1)

[0074] 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."

[0075] Conventional tourism support systems have struggled to efficiently process user-inputted tourism information and provide optimal travel plans. Furthermore, insufficient data formatting and validation during plan generation have resulted in a poor user experience.

[0076] 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.

[0077] In this invention, the server includes means for receiving tourist information entered by a user, means for validating and formatting the tourist information to pass it to a generating AI model, means for calling a generating AI model that generates an optimal tourist plan based on the tourist information, means for converting the generated tourist plan into an appropriate data format and transmitting it to a user terminal, and means for the user terminal to analyze the tourist plan received and display it on a user interface. This makes it possible to process the information entered by the user efficiently and accurately and provide an optimal tourist plan.

[0078] "Means for receiving user-entered tourist information" refers to functions or devices that allow a server to receive information such as places to visit, budget, available time, and areas of interest, which are entered by the user through their terminal.

[0079] "Methods for validating and formatting data to pass tourism information to a generating AI model" refers to functions or devices that check whether the format and values ​​of the tourism information entered by the user are appropriate, and convert them into a format that the generating AI model can understand.

[0080] "Means for calling a generative AI model that generates an optimal sightseeing plan" refers to a function or device that executes a generative AI model that generates an optimal sightseeing plan according to the user's conditions by referring to a database of tourist spots and restaurants based on the input sightseeing information.

[0081] "Means for converting generated sightseeing plans into an appropriate data format and transmitting them to the user terminal" refers to a function or device for converting sightseeing plans generated by a generation AI model into a data format that the user terminal can understand and transmitting it to the user terminal.

[0082] "Means for analyzing a sightseeing plan received by a user terminal and displaying it on the user interface" refers to a function or device that receives and analyzes sightseeing plan data transmitted from a server on a user terminal and visually displays its contents to the user.

[0083] Modes for carrying out the invention

[0084] This invention is a tourism support system for tourists visiting Japan, and consists of the following main components.

[0085] 1. User Device

[0086] 2. Server

[0087] 3. Generative AI Model

[0088] System operation

[0089] User terminal operation

[0090] The user first opens the application using a device such as a smartphone or tablet to access the system. On the application's user interface, they enter the tourist destination they wish to visit, their budget, available time, and areas of interest. For example, the following input might be made:

[0091] Places I want to visit: Tokyo Skytree

[0092] Budget: 10,000 yen

[0093] Available time: 8 hours

[0094] Interests: History

[0095] The terminal retrieves this input data, stores it temporarily, and then sends it to the server.

[0096] Server operation

[0097] The server receives tourist information sent from the user's terminal and performs data validation and formatting. Specifically, it checks the data format and fills in any missing information. Next, the server generates a prompt message to request the AI ​​model to generate a tourist plan. An example of a prompt message is as follows:

[0098] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0099] The generated prompt text is sent to the AI ​​model, and the creation of the sightseeing plan begins.

[0100] How generative AI models work

[0101] The AI ​​model generates an optimal sightseeing plan based on user data received from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in an appropriate data format, such as JSON.

[0102] Sending from server to user terminal

[0103] The server receives the generated sightseeing plan and sends it to the user's terminal. The sightseeing plan is formatted as needed, converted back to JSON format, and sent again. For example, the following JSON data is sent:

[0104] json

[0105] {

[0106] "Plan": [

[0107] {

[0108] "Tourist attraction": "Tokyo Skytree",

[0109] "Estimated time": "2 hours"

[0110] "Cost": 3000

[0111] },

[0112] {

[0113] "Tourist destination": "Senso-ji Temple",

[0114] "Estimated time": "2 hours"

[0115] "Cost": 2000

[0116] },

[0117] {

[0118] "Tourist destination": "Ueno Park",

[0119] "Estimated time": "3 hours"

[0120] "Cost": 500

[0121] }

[0122] ],

[0123] "Total time": "7 hours"

[0124] Total cost: 5500

[0125] }

[0126] Displaying the plan on the user's device

[0127] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0128] This invention enables efficient and accurate processing of input tourism information and provides optimal tourism plans. Furthermore, by accumulating tourism data, even more accurate recommendations can be made when generating future tourism plans.

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

[0130] Processing steps

[0131] Step 1:

[0132] Users enter tourist information.

[0133] Users use their devices (such as smartphones or tablets) to open a dedicated application and enter tourist information (places they want to visit, budget, available time, areas of interest). For example, they might enter the following:

[0134] Places I want to visit: Tokyo Skytree

[0135] Budget: 10,000 yen

[0136] Available time: 8 hours

[0137] Interests: History

[0138] The entered data will be temporarily stored on the device.

[0139] Step 2:

[0140] The device sends tourist information to the server.

[0141] The terminal sends the tourist information entered by the user to the server. Specifically, it sends data to the server via an HTTP POST request using a REST API. The input data is sent in JSON format. For example, the following JSON data is sent:

[0142] json

[0143] {

[0144] "Tourist attraction": "Tokyo Skytree",

[0145] "Budget": 10000,

[0146] "time": 8,

[0147] "Interest": "History"

[0148] }

[0149] Step 3:

[0150] The server receives the data and performs validation and formatting.

[0151] The server receives tourist information sent from the terminal. After receiving the data, it validates (checks the format and values) and formats it. For example, it checks if the visited locations are appropriate and returns error messages if necessary. The formatted data is then ready to be passed to the generating AI model.

[0152] Step 4:

[0153] The server generates a prompt message and sends it to the AI ​​model.

[0154] The server generates prompts to request the AI ​​model to create a travel plan based on the formatted tourist information. An example of a prompt is as follows:

[0155] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0156] Send this prompt message to the AI ​​model that generates the data.

[0157] Step 5:

[0158] A generative AI model generates tourist plans.

[0159] The AI ​​model generates an optimal sightseeing plan based on prompts sent from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in JSON format. For example, the following JSON data is generated:

[0160] json

[0161] {

[0162] "Plan": [

[0163] {

[0164] "Tourist attraction": "Tokyo Skytree",

[0165] "Estimated time": "2 hours"

[0166] "Cost": 3000

[0167] },

[0168] {

[0169] "Tourist destination": "Senso-ji Temple",

[0170] "Estimated time": "2 hours"

[0171] "Cost": 2000

[0172] },

[0173] {

[0174] "Tourist destination": "Ueno Park",

[0175] "Estimated time": "3 hours"

[0176] "Cost": 500

[0177] }

[0178] ],

[0179] "Total time": "7 hours"

[0180] Total cost: 5500

[0181] }

[0182] Step 6:

[0183] The server sends the generated sightseeing plan to the user's terminal.

[0184] The server receives the travel plan returned from the generated AI model, converts it into an appropriate data format (such as JSON), and sends it to the user's terminal. In some cases, it may further format the data before sending it.

[0185] Step 7:

[0186] The user's terminal analyzes and displays the sightseeing plan.

[0187] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on the displayed plan, the user can proceed with their sightseeing efficiently and effectively. The displayed information includes the names of the tourist attractions, the estimated time required, the cost, and the order of visits.

[0188] (Application Example 1)

[0189] 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."

[0190] The current tourism support system focuses on providing information on tourist spots and restaurants, but it lacks detailed information such as the optimal order of visits, the time required, and the total cost of visiting physical establishments. This makes it difficult for tourists to enjoy sightseeing efficiently and effectively. Furthermore, there is no way to obtain and display detailed information about physical establishments in real time, so tourists tend to spend a lot of time making decisions on-site. This leads to problems such as wasted time and budget.

[0191] 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.

[0192] In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generative AI model that generates an optimal tourist plan based on the tourist information, means for transmitting the generated tourist plan to the user terminal, means for calculating the order of visits to physical stores, the time required, and the total cost for the tourist plan, and means for obtaining detailed information of the physical stores and displaying it on the user terminal. This allows the user to efficiently visit physical stores and enjoy sightseeing to the fullest while reducing wasted time and budget.

[0193] "Means for receiving user-entered tourist information" refers to a function that sends data such as tourist destination information, budget, available time, and areas of interest entered by the user using a terminal to a server.

[0194] The "means for calling the generative AI model" refer to a function that activates a generative AI model to calculate and generate the optimal sightseeing plan based on the sightseeing information provided by the user.

[0195] "Means for sending sightseeing plans to user terminals" refers to a function that converts the optimal sightseeing plan created by the generative AI model into an appropriate data format and transfers it to the user's terminal.

[0196] "A means of calculating the order of visits to physical stores, the time required, and the total cost for a sightseeing plan" refers to a function that identifies the physical stores that a user should visit within a sightseeing plan, and calculates the order of visits to those facilities, the time required to visit each facility, and the overall budget.

[0197] "Means for obtaining and displaying detailed information about physical stores on the user's device" refers to a function that obtains detailed information (address, business hours, menu, etc.) about each physical store that the user plans to visit in real time and displays it on the user's device.

[0198] This invention is a system that provides optimal sightseeing plans for tourists. Based on the sightseeing information entered by the user, it generates a sightseeing plan using an AI model and transmits that plan to the user's terminal. This invention also provides detailed information about the physical stores that the user plans to visit, aiming to improve the efficiency and satisfaction of sightseeing.

[0199] System Configuration

[0200] This system consists of the following main components:

[0201] 1. User-side device: A device (such as a smartphone or tablet) used by the user to input tourist information and send it to the server.

[0202] 2. Server: A central system that receives tourist information and generates optimal tourist plans using a generated AI model.

[0203] 3. Generative AI Model: A machine learning model for generating travel plans. It references a database of tourist spots and restaurants to calculate the most suitable travel route based on the user's criteria.

[0204] 4. Tourism Database: A database containing detailed information (address, opening hours, cost, etc.) about various tourist spots, restaurants, and physical stores.

[0205] System operation

[0206] User terminal operation

[0207] Users open the application using a smartphone or other device and enter travel information. This travel information includes places they want to visit, their budget, available time, and areas of interest. This data is collected on the user's device and sent to the server.

[0208] Server operation

[0209] The server receives tourist information sent from the user's terminal. Based on the received tourist information, it calls a generation AI model and starts the process of generating the optimal tourist plan. The server refers to a database of tourist spots, restaurants, and physical stores to calculate the optimal tourist plan based on the user's requests.

[0210] How generative AI models work

[0211] The generating AI model uses user data received from the server to reference databases of tourist spots, restaurants, and physical stores. The AI ​​model calculates the specified visit order, duration, total cost, etc. It also retrieves detailed information about physical stores (address, opening hours, cost, menu, etc.) and includes this in the sightseeing plan.

[0212] Sending from server to user terminal

[0213] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0214] Displaying the plan on the user's device

[0215] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. This allows users to proceed with their sightseeing efficiently and effectively, and to check detailed information about physical stores in real time.

[0216] Specific example

[0217] As a concrete example, consider the case of tourist A visiting tourist destination B. Tourist A uses a smartphone application to input "Tourist Destination B" as the place to visit, a budget of "15,000 yen," available time of "5 hours," and interests of "Dining and Shopping." Based on this, the user's device sends tourist information to the server. The server receives this information and uses a generating AI model to create a tourist plan consisting of "Restaurant X," "Cafe Y," and "Shopping Mall Z." This plan includes the order of visits for each location, the time required, the total cost, and detailed information about the actual establishments (address, opening hours, cost, menu, etc.). This tourist plan is sent to the user's device, allowing tourist A to enjoy sightseeing efficiently.

[0218] Example of a prompt

[0219] Example of tourist A entering tourist information:

[0220] Place to visit: Tourist spot B, Budget: 15,000 yen, Available time: 5 hours, Interests: Dining and shopping

[0221] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0222] Step 1: Enter tourist information using the user terminal.

[0223] Users use a smartphone application to input travel information such as the tourist destinations they want to visit, their budget, available time, and areas of interest. This becomes the input data, and the device sends this data to the server.

[0224] Step 2: Receiving tourist information from the server

[0225] The server receives tourist information sent from the user's terminal. Here, the tourist information is temporarily stored and prepared for later use in calling the generated AI model. The received data is converted into an internal data structure.

[0226] Step 3: Generating tourist plans using a generative AI model

[0227] The server calls a generating AI model based on the received user data. The generating AI model refers to a database of tourist spots and restaurants to calculate the optimal visiting order, duration, and total cost. It also retrieves detailed information about physical establishments and includes it in the sightseeing plan. The data generated at this stage is the sightseeing plan data.

[0228] Step 4: Converting the sightseeing plan data

[0229] The server converts the tourist plans obtained from the generated AI model into an appropriate data format such as JSON. This makes it easier for the user's device to receive.

[0230] Step 5: Sending data from the server to the user terminal

[0231] The server sends the converted tourist plan data to the user's terminal. The HTTP protocol or other appropriate communication methods are used for transmission.

[0232] Step 6: User terminal receives and displays the plan

[0233] The user terminal receives the sightseeing plan sent from the server. The received data is analyzed and displayed on the user interface. The user can then plan their sightseeing based on this information.

[0234] Specific actions for each step:

[0235] Step 1 Input: User-entered tourist information data (places to visit, budget, available time, areas of interest)

[0236] Output: Tourism information data sent to the server

[0237] Step 2 Input: Tourist information data sent from the user terminal.

[0238] Output: Tourism information data converted to an internal data structure.

[0239] Step 3 Input: Converted tourist information data

[0240] Output: Tourism plan data generated by the AI ​​model (order of visits, duration, total cost, detailed information)

[0241] Input for Step 4: Tourism plan data obtained from the generated AI model.

[0242] Output: Tourist plan data converted to a data format suitable for the user's terminal (e.g., JSON).

[0243] Step 5 Input: Converted tourist plan data

[0244] Output: Tourist plan data sent to the user terminal

[0245] Step 6 Input: Tourist plan data sent from the server

[0246] Output: Analyzed tourist plan data displayed in the user interface

[0247] 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.

[0248] This invention combines a tourism support system for inbound tourists with an emotion engine that recognizes user emotions, thereby providing each user with an optimal tourism plan and realizing a more satisfying tourism experience. The system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and sends that plan to the user's terminal. Furthermore, by incorporating an emotion engine, it has the function of recognizing the user's emotions and adjusting the tourism plan in real time.

[0249] System Configuration

[0250] This system consists of the following components:

[0251] 1. User Device

[0252] 2. Server

[0253] 3. Generative AI Model

[0254] 4. Emotion Engine

[0255] System operation

[0256] User terminal operation

[0257] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is acquired on the user's device and sent to the server. In addition, the user's voice and facial expressions are captured using the camera and microphone, and this data is also sent to the emotion engine.

[0258] Server operation

[0259] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[0260] How generative AI models work

[0261] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user appears to be enjoying themselves, the plan might be adjusted to allow a little more time at the next spot; conversely, if the user appears tired, the next spot might be changed to a more relaxing location.

[0262] Sending from server to user terminal

[0263] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0264] Displaying the plan on the user's device

[0265] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[0266] Specific example

[0267] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server. In addition, Mr. Tanaka's voice and facial expressions are captured by the camera and microphone, and that data is also sent to the server.

[0268] The server receives this information and requests the generative AI model to create the optimal sightseeing plan. The generative AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these places, and sends the plan, including the optimal route, back to the server. At the same time, the emotion engine analyzes Mr. Tanaka's emotions and adjusts the sightseeing plan in real time.

[0269] The server sends this plan to the user's terminal, where it is displayed. Following this plan, Mr. Tanaka can efficiently enjoy sightseeing. Furthermore, based on the emotional data Mr. Tanaka displays during his sightseeing, the plan is adjusted as needed to optimize his sightseeing experience.

[0270] The system according to the present invention helps tourists efficiently tour tourist destinations and provides users with an optimal tourist experience by utilizing emotional data. Furthermore, by accumulating tourist data and emotional data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[0271] The following describes the processing flow.

[0272] Step 1:

[0273] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. Additionally, the smartphone's camera and microphone are used to capture emotional data such as voice and facial expressions. This input data and emotional data are collected within the app.

[0274] Step 2:

[0275] The terminal sends the data input by the user and the emotion data to the server. The data is encoded in an appropriate format such as JSON and sent using an HTTP POST request.

[0276] Step 3:

[0277] The server receives the data sent from the terminal. After verifying the validity of the received tourism information and emotion data, it performs the process of passing these data to the generation AI model and the emotion engine.

[0278] Step 4:

[0279] The server calls the generation AI model and passes the user's tourism information as input data. Furthermore, based on the emotion data of the user sensed by the emotion engine, the generation AI model is provided with additional data. The generation AI model refers to the databases of tourist spots and restaurants and calculates the optimal tourism route and schedule.

[0280] Step 5:

[0281] The generation AI model generates an optimal tourism plan based on the user's conditions and emotion data. For example, a tourism plan including a list of tourist spots to visit, the order of visits, the estimated time required, and the total cost is generated. Based on the emotion data, adjustments are made such as continuing as is if the user is enjoying themselves, or adding relaxing spots if the user is tired.

[0282] Step 6:

[0283] The generation AI model returns the optimal tourism plan it generated to the server. The server receives this plan and converts the format of the data as necessary.

[0284] Step 7:

[0285] The server sends the generated travel plan to the user terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[0286] Step 8:

[0287] The terminal analyzes the travel plan received from the server and displays it on the user interface. The user checks this information and starts traveling according to the proposed plan. Also, emotional data during the trip is sent in real time, and the travel plan may be adjusted accordingly. For example, if the user has a high satisfaction level at the current spot, adjustments such as shortening the travel time to the next spot or extending the stay time at the current location may be made.

[0288] Through the above steps, the system of the present invention can not only provide support for foreign tourists visiting Japan to enjoy their trips efficiently, but also provide an optimal experience in real time based on emotional data.

[0289] (Example 2)

[0290] Next, Example 2 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart device 14 is referred to as the "terminal".

[0291] The conventional tourism support system has a problem that it cannot fully reflect the preferences and physical conditions of individual users because it provides a travel plan only based on the information input by the user. Therefore, in order to improve the user's satisfaction, it is required to recognize the user's emotions and physical conditions in real time and provide a travel plan accordingly.

[0292] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0293] In this invention, the server includes means for receiving tourist information entered by the user, means for capturing the user's voice and facial expression data, means for transmitting the received tourist information and the captured voice and facial expression data to the server, means for the server to verify the integrity of the data transmitted from the user terminal, means for transmitting the verified data to a generating AI model, means for the generating AI model to calculate the optimal tourist route by referring to a database of tourist spots and restaurants, means for an emotion engine to analyze the user's emotional data and adjust the tourist plan in real time, means for transmitting the generated tourist plan to the user terminal, and means for the user terminal to display the received tourist plan. This makes it possible to provide a customized tourist plan that is tailored to the user's emotions and physical condition.

[0294] "Means for receiving user-entered tourism information" refers to a means for users to input tourism information such as places to visit, budget, available time, and areas of interest into a terminal and send that information to a server.

[0295] "Means for capturing user voice and facial expression data" refers to means of acquiring user voice and facial expression data using the camera and microphone on the user's terminal.

[0296] "Means for transmitting received tourist information and captured audio and facial expression data to the server" refers to a means of encrypting the tourist information and audio / facial expression data acquired by the terminal and securely transmitting it to the server.

[0297] "Means by which the server verifies the integrity of data sent from the user terminal" refers to the means by which the server verifies the format and content of the received data and confirms whether it is in the correct format.

[0298] "Means for sending data whose consistency has been verified to the generating AI model" refers to the means by which the server sends data whose consistency has been verified to the generating AI model.

[0299] "A method by which a generative AI model calculates the optimal sightseeing route by referring to a database of tourist spots and restaurants" refers to a method by which a generative AI model uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule based on the input sightseeing information.

[0300] "A means by which an emotion engine analyzes user emotional data and adjusts the sightseeing plan in real time" refers to a method in which an emotion engine analyzes the user's emotions from voice and facial expression data and adjusts the sightseeing plan in real time based on that analysis.

[0301] "Means for sending the generated sightseeing plan to the user terminal" refers to the means by which the server converts the sightseeing plan obtained from the generated AI model into an appropriate format and sends it to the user terminal.

[0302] "Means for displaying a sightseeing plan received by a user terminal" refers to means by which a user terminal analyzes a sightseeing plan received from a server and displays it to the user through a user interface.

[0303] This invention is a tourism support system for tourists visiting Japan. By combining it with an emotion engine that recognizes the user's emotions, it provides an optimal tourism plan for each individual user, thereby realizing a more satisfying tourism experience. The system is configured as follows:

[0304] 1. User Device

[0305] First, the user opens the application using a device such as a smartphone or tablet. The user then enters travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is saved on the user's device and then sent to the server. In addition, the user's voice and facial expression data are captured through the device's camera and microphone and also sent to the emotion engine.

[0306] 2. Server

[0307] The server receives the tourism information and emotion data sent from the user terminal. It checks the integrity of the received data and prepares to pass it to the generative AI model. The server sends the data with confirmed integrity to the generative AI model, where it calculates the optimal tourism route.

[0308] 3. Generative AI Model

[0309] Based on the user's tourism information and emotion data received from the server, the generative AI model refers to the databases of tourist spots and restaurants to calculate the optimal tourism route and schedule. At this time, the user's emotion data is also taken into account to adjust the plan.

[0310] 4. Emotion Engine

[0311] The emotion engine analyzes the user's voice and facial expression data and estimates the user's emotional state in real time. This emotion data is provided to the generative AI model and used to adjust the tourism plan. For example, if the user is enjoying themselves, the staying time is extended, and conversely, if the user is tired, spots where they can relax are added for adjustment.

[0312] Specific operation examples

[0313] Consider the scenario where Mr. Tanaka visits Tokyo for a one-day tour. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as the budget, "8 hours" as the available time, and "history" as his interest. This information is sent to the server, and at the same time, Mr. Tanaka's facial expressions and voice are captured by the camera and microphone of the terminal.

[0314] The server receives this data, verifies its integrity, and then sends it to the generating AI model. The generating AI model creates a sightseeing plan that includes places like "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park," and adjusts the plan based on the data from the emotion engine. The generated sightseeing plan is sent to Tanaka's smartphone via the server, and Tanaka enjoys sightseeing according to this plan.

[0315] Example of a prompt

[0316] "I'm planning a one-day sightseeing trip in Tokyo. My desired destination is Tokyo Skytree, my budget is 10,000 yen, I have 8 hours available, and my interest is history. Please suggest the best sightseeing plan. Also, please consider that the plan may be adjusted based on my emotional data during the trip."

[0317] This system makes it possible to provide customized sightseeing plans tailored to the user's emotional state, thereby increasing user satisfaction.

[0318] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0319] System program processing flow

[0320] Step 1:

[0321] Users open the application using a device such as a smartphone or tablet. They enter travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This entered travel information is temporarily stored on the user's device.

[0322] Input: User-entered tourist information (places to visit, budget, available time, areas of interest)

[0323] Output: Tourist information temporarily stored on the user's terminal.

[0324] Step 2:

[0325] The user's device uses its camera and microphone to capture the user's voice and facial expression data. This data is then input into the emotion engine.

[0326] Input: User voice data, facial expression data

[0327] Output: Audio data and facial expression data captured by the device.

[0328] Step 3:

[0329] The user's terminal sends tourist information, voice, and facial expression data to the server. This data is encrypted and transmitted securely.

[0330] Input: Tourist information, audio data, facial expression data (data stored on the user's device)

[0331] Output: Tourist information, audio data, and facial expression data sent to the server.

[0332] Step 4:

[0333] The server receives data sent from the user's terminal and verifies its integrity. If the data is invalid, it returns an error message.

[0334] Input: Tourist information, audio data, and facial expression data sent from the user's terminal.

[0335] Output: Data whose integrity has been verified, error message (if invalid)

[0336] Step 5:

[0337] The server sends the verified data to the generating AI model. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule.

[0338] Input: Authenticated tourist information and sentiment data.

[0339] Output: Data sent to the generating AI model, generated tourist plan

[0340] Step 6:

[0341] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state. This emotional data is provided to a generative AI model and used to adjust the sightseeing plan.

[0342] Input: User voice data, facial expression data

[0343] Output: Estimated user emotional state, emotional data

[0344] Step 7:

[0345] The generative AI model adjusts the sightseeing plan in real time based on emotional data obtained from the emotion engine. If the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxing spots are added.

[0346] Input: Initial tourist plan generated by a generative AI model, emotional data from an emotional engine.

[0347] Output: Customized sightseeing plan

[0348] Step 8:

[0349] The generated sightseeing plan is sent back to the server, which converts this data into an appropriate format such as JSON.

[0350] Input: Generated sightseeing plan

[0351] Output: Tourist plan converted to JSON format

[0352] Step 9:

[0353] The server sends the generated sightseeing plan to the user's terminal. The user's terminal receives this plan and displays it through the user interface. The user's terminal continues to capture the user's voice and facial expression data during sightseeing, and the plan is adjusted in real time.

[0354] Input: Tourist plan in JSON format

[0355] Output: Tourist plan displayed on the user's terminal

[0356] Step 10:

[0357] Users proceed with their sightseeing according to the displayed tour plan. If sentiment data is updated during the tour, the system adjusts the plan in real time and notifies the user.

[0358] Input: Sentiment data updated in real time

[0359] Output: Notification of updated adjusted sightseeing plan

[0360] These steps enable the system to provide the optimal sightseeing plan based on the user's input information and emotional state, thereby increasing user satisfaction.

[0361] (Application Example 2)

[0362] 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".

[0363] Conventional tourism support systems generate optimal sightseeing plans based solely on pre-entered information from users. However, this approach fails to reflect the user's real-time emotional state, making it difficult to address fatigue or disappointment experienced during sightseeing in real time. This can potentially degrade the quality of the user's sightseeing experience. To solve this problem, a system is needed that utilizes real-time emotional data from users to dynamically adjust sightseeing plans.

[0364] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generation AI model that generates an optimal tourist plan based on the tourist information and user emotion data acquired in real time, means for transmitting the generated tourist plan to the user terminal, and an emotion engine that analyzes the user emotion data and adjusts the tourist plan. This makes it possible to dynamically adjust the tourist plan to reflect the user's real-time emotional state.

[0365] "User-entered tourism information" refers to information entered by users regarding their own tourism preferences and conditions, specifically including places to visit, budget, available time, and areas of interest.

[0366] "Real-time user emotion data" refers to emotional data acquired in real time from the user's facial expressions, voice tone, and other factors.

[0367] An "optimal sightseeing plan" is a plan designed to provide an efficient and highly satisfying sightseeing experience, based on user input information and emotional data.

[0368] A "generative AI model" is an artificial intelligence model that automatically generates sightseeing plans based on input data, and has the function of calculating the optimal route by referring to a database of tourist spots and restaurants.

[0369] A "user terminal" refers to a device used by a user, and includes smartphones, in-vehicle displays, and other similar devices.

[0370] The "emotion engine" is an engine that analyzes users' real-time emotional data and adjusts sightseeing plans based on that data.

[0371] A "database of tourist spots and restaurants" is a database containing information about tourist destinations and restaurants, which is referenced by the generating AI model to calculate the optimal tourist route.

[0372] To deliver an "exceptional and authentic travel experience," this system enables dynamic plan adjustments and optimizations that reflect user emotions in real time.

[0373] This invention relates to a tourism support system that operates within an autonomous vehicle. This system improves the quality of the tourism experience by generating and dynamically adjusting an optimal tourism plan based on tourism information entered by the user and user emotion data acquired in real time.

[0374] System components

[0375] This system consists of the following components:

[0376] 1. User Device: This includes smartphones and the displays of autonomous vehicles.

[0377] 2. Server: Performs data processing and generates and manages tourist plans.

[0378] 3. Generative AI Model: Generates optimal sightseeing plans based on user input information and sentiment data.

[0379] 4. Emotion Engine: Analyzes the user's real-time emotional data and dynamically adjusts the sightseeing plan based on that data.

[0380] System operation

[0381] User terminal operation

[0382] First, the user opens the application using the display inside the autonomous vehicle or on their smartphone and enters the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is acquired by the user's device and sent to the server. In addition, the user's voice and facial expressions are captured by the camera and microphone, and this emotion data is also sent to the server.

[0383] Server operation

[0384] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[0385] How generative AI models work

[0386] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants, calculating the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user is enjoying themselves, the time spent at the next spot will be extended; conversely, if the user is tired, the location will be changed to a more relaxing one.

[0387] Sending from server to user terminal

[0388] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0389] Displaying the plan on the user's device

[0390] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[0391] Specific example

[0392] 1. For example, a user gets into an autonomous vehicle and inputs information about tourist destinations and interests. Based on emotion data obtained from the camera and microphone, the system suggests the optimal sightseeing plan for the places the user wants to visit.

[0393] 2. The user enters "Tokyo Skytree" as the place they want to visit, "10,000 yen" as their budget, "8 hours" as the available time, and "history" as their interest. The system then suggests a sightseeing route that includes Tokyo Skytree, Senso-ji Temple, and Ueno Park. If the emotion engine determines that the user is enjoying the sightseeing, it adjusts the time spent at the next spot to increase.

[0394] Example of a prompt

[0395] Generate a sightseeing plan based on the user's entered travel information (Place to visit: Tokyo Skytree, Budget: 10,000 yen, Available time: 8 hours, Interests: History). Also, adjust the plan by taking into account the user's real-time sentiment data. For example, if the user is enjoying themselves, extend the time spent at the next spot; if they are tired, suggest a place to relax.

[0396] This allows the system to dynamically adjust sightseeing plans to reflect the user's real-time emotional state.

[0397] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0398] Step 1:

[0399] Users input tourist information using a display in the autonomous vehicle or their smartphone. This information includes places to visit, budget, available time, and areas of interest, and this data is acquired on the user's device.

[0400] Input: Visit location, budget, available time, areas of interest

[0401] Output: Tourism preference data

[0402] Step 2:

[0403] The user terminal captures the user's voice and facial expressions using a camera and microphone, acquiring this data in real time. This allows for the acquisition of user emotion data.

[0404] Input: Voice data, facial expression data

[0405] Output: User sentiment data

[0406] Step 3:

[0407] The user terminal sends tourism preference data and sentiment data to the server. The server checks the format of the received data and verifies its validity.

[0408] Input: Tourism preference data, sentiment data

[0409] Output: Formatted user data

[0410] Step 4:

[0411] The server passes the formatted user data to a generating AI model and requests it to create a travel plan. The generating AI model refers to a database of tourist spots and restaurants and calculates the optimal travel route and schedule.

[0412] Input: Formatted user data

[0413] Output: Initial sightseeing plan

[0414] Step 5:

[0415] The generative AI model adjusts the initial sightseeing plan based on emotion data retrieved from the server. If the user is enjoying themselves, it extends the length of their stay; if they are tired, it adds relaxing spots.

[0416] Input: Initial sightseeing plan, sentiment data

[0417] Output: Optimized sightseeing plan

[0418] Step 6:

[0419] The server converts the optimized sightseeing plan into an appropriate format, such as JSON, and sends it to the user's terminal.

[0420] Input: Optimized sightseeing plan

[0421] Output: Format-converted sightseeing plan

[0422] Step 7:

[0423] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can review the suggested plan and begin sightseeing accordingly. During sightseeing, emotion data is continuously collected via camera and microphone, and the plan is updated as needed.

[0424] Input: Formatted sightseeing plan

[0425] Output: Displayed sightseeing plan

[0426] 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.

[0427] 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.

[0428] 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.

[0429] [Second Embodiment]

[0430] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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).

[0436] 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.

[0437] 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.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] 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".

[0442] This invention is a tourism support system for tourists visiting Japan. This system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and then transmits that plan to the user's terminal.

[0443] System Configuration

[0444] This system consists of the following main components:

[0445] 1. User Device

[0446] 2. Server

[0447] 3. Generative AI Model

[0448] System operation

[0449] User terminal operation

[0450] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is collected on the user's device and sent to the server.

[0451] Server operation

[0452] The server receives tourist information entered from the user's terminal. The received data is passed to a generating AI model, which then starts processing to create the optimal tourist plan. The server uses this tourist data to call the generating AI model and refer to a database of tourist spots and restaurants.

[0453] How generative AI models work

[0454] The AI ​​model uses user data received from the server to reference a database of tourist spots and restaurants. The AI ​​model calculates the optimal sightseeing route and selects places and facilities to visit. This generates an optimal sightseeing plan tailored to the user's preferences. This plan includes the order of visits, total cost, and estimated time required.

[0455] Sending from server to user terminal

[0456] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0457] Displaying the plan on the user's device

[0458] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0459] Specific example

[0460] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server.

[0461] The server receives this information and requests the generating AI model to create the optimal sightseeing plan. The generating AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these locations, and sends the plan, including the optimal route, back to the server.

[0462] The server sends this plan to the user's terminal, and it is displayed on Mr. Tanaka's terminal. Mr. Tanaka can then enjoy sightseeing efficiently by following this plan.

[0463] The system according to the present invention helps tourists efficiently tour tourist destinations, reducing time loss and the stress of gathering information. Furthermore, by accumulating tourism data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[0464] The following describes the processing flow.

[0465] Step 1:

[0466] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. This entered data is collected within the app.

[0467] Step 2:

[0468] The terminal sends the data entered by the user to the server. During this process, the data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[0469] Step 3:

[0470] The server receives the data sent from the terminal, verifies the validity of the data format, and then passes it on to the generating AI model.

[0471] Step 4:

[0472] The server invokes a generating AI model, passing the user's travel information as input data. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[0473] Step 5:

[0474] The AI ​​model generates an optimal travel plan based on the user's criteria. For example, the plan may include a list of sightseeing spots to visit, the order in which to visit them, estimated time required, and total cost.

[0475] Step 6:

[0476] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[0477] Step 7:

[0478] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[0479] Step 8:

[0480] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can then review this information and begin sightseeing according to the suggested plan.

[0481] Through the steps described above, the system of the present invention can provide support for tourists visiting Japan to efficiently enjoy sightseeing.

[0482] (Example 1)

[0483] 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."

[0484] Conventional tourism support systems have struggled to efficiently process user-inputted tourism information and provide optimal travel plans. Furthermore, insufficient data formatting and validation during plan generation have resulted in a poor user experience.

[0485] 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.

[0486] In this invention, the server includes means for receiving tourist information entered by a user, means for validating and formatting the tourist information to pass it to a generating AI model, means for calling a generating AI model that generates an optimal tourist plan based on the tourist information, means for converting the generated tourist plan into an appropriate data format and transmitting it to a user terminal, and means for the user terminal to analyze the tourist plan received and display it on a user interface. This makes it possible to process the information entered by the user efficiently and accurately and provide an optimal tourist plan.

[0487] "Means for receiving user-entered tourist information" refers to functions or devices that allow a server to receive information such as places to visit, budget, available time, and areas of interest, which are entered by the user through their terminal.

[0488] "Methods for validating and formatting data to pass tourism information to a generating AI model" refers to functions or devices that check whether the format and values ​​of the tourism information entered by the user are appropriate, and convert them into a format that the generating AI model can understand.

[0489] "Means for calling a generative AI model that generates an optimal sightseeing plan" refers to a function or device that executes a generative AI model that generates an optimal sightseeing plan according to the user's conditions by referring to a database of tourist spots and restaurants based on the input sightseeing information.

[0490] "Means for converting generated sightseeing plans into an appropriate data format and transmitting them to the user terminal" refers to a function or device for converting sightseeing plans generated by a generation AI model into a data format that the user terminal can understand and transmitting it to the user terminal.

[0491] "Means for analyzing a sightseeing plan received by a user terminal and displaying it on the user interface" refers to a function or device that receives and analyzes sightseeing plan data transmitted from a server on a user terminal and visually displays its contents to the user.

[0492] Modes for carrying out the invention

[0493] This invention is a tourism support system for tourists visiting Japan, and consists of the following main components.

[0494] 1. User Device

[0495] 2. Server

[0496] 3. Generative AI Model

[0497] System operation

[0498] User terminal operation

[0499] The user first opens the application using a device such as a smartphone or tablet to access the system. On the application's user interface, they enter the tourist destination they wish to visit, their budget, available time, and areas of interest. For example, the following input might be made:

[0500] Places I want to visit: Tokyo Skytree

[0501] Budget: 10,000 yen

[0502] Available time: 8 hours

[0503] Interests: History

[0504] The terminal retrieves this input data, stores it temporarily, and then sends it to the server.

[0505] Server operation

[0506] The server receives tourist information sent from the user's terminal and performs data validation and formatting. Specifically, it checks the data format and fills in any missing information. Next, the server generates a prompt message to request the AI ​​model to generate a tourist plan. An example of a prompt message is as follows:

[0507] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0508] The generated prompt text is sent to the AI ​​model, and the creation of the sightseeing plan begins.

[0509] How generative AI models work

[0510] The AI ​​model generates an optimal sightseeing plan based on user data received from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in an appropriate data format, such as JSON.

[0511] Sending from server to user terminal

[0512] The server receives the generated sightseeing plan and sends it to the user's terminal. The sightseeing plan is formatted as needed, converted back to JSON format, and sent again. For example, the following JSON data is sent:

[0513] json

[0514] {

[0515] "Plan": [

[0516] {

[0517] "Tourist attraction": "Tokyo Skytree",

[0518] "Estimated time": "2 hours"

[0519] "Cost": 3000

[0520] },

[0521] {

[0522] "Tourist destination": "Senso-ji Temple",

[0523] "Estimated time": "2 hours"

[0524] "Cost": 2000

[0525] },

[0526] {

[0527] "Tourist destination": "Ueno Park",

[0528] "Estimated time": "3 hours"

[0529] "Cost": 500

[0530] }

[0531] ],

[0532] "Total time": "7 hours"

[0533] Total cost: 5500

[0534] }

[0535] Displaying the plan on the user's device

[0536] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0537] This invention enables efficient and accurate processing of input tourism information and provides optimal tourism plans. Furthermore, by accumulating tourism data, even more accurate recommendations can be made when generating future tourism plans.

[0538] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0539] Processing steps

[0540] Step 1:

[0541] Users enter tourist information.

[0542] Users use their devices (such as smartphones or tablets) to open a dedicated application and enter tourist information (places they want to visit, budget, available time, areas of interest). For example, they might enter the following:

[0543] Places I want to visit: Tokyo Skytree

[0544] Budget: 10,000 yen

[0545] Available time: 8 hours

[0546] Interests: History

[0547] The entered data will be temporarily stored on the device.

[0548] Step 2:

[0549] The device sends tourist information to the server.

[0550] The terminal sends the tourist information entered by the user to the server. Specifically, it sends data to the server via an HTTP POST request using a REST API. The input data is sent in JSON format. For example, the following JSON data is sent:

[0551] json

[0552] {

[0553] "Tourist attraction": "Tokyo Skytree",

[0554] "Budget": 10000,

[0555] "time": 8,

[0556] "Interest": "History"

[0557] }

[0558] Step 3:

[0559] The server receives the data and performs validation and formatting.

[0560] The server receives tourist information sent from the terminal. After receiving the data, it validates (checks the format and values) and formats it. For example, it checks if the visited locations are appropriate and returns error messages if necessary. The formatted data is then ready to be passed to the generating AI model.

[0561] Step 4:

[0562] The server generates a prompt message and sends it to the AI ​​model.

[0563] The server generates prompts to request the AI ​​model to create a travel plan based on the formatted tourist information. An example of a prompt is as follows:

[0564] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0565] Send this prompt message to the AI ​​model that generates the data.

[0566] Step 5:

[0567] A generative AI model generates tourist plans.

[0568] The AI ​​model generates an optimal sightseeing plan based on prompts sent from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in JSON format. For example, the following JSON data is generated:

[0569] json

[0570] {

[0571] "Plan": [

[0572] {

[0573] "Tourist attraction": "Tokyo Skytree",

[0574] "Estimated time": "2 hours"

[0575] "Cost": 3000

[0576] },

[0577] {

[0578] "Tourist destination": "Senso-ji Temple",

[0579] "Estimated time": "2 hours"

[0580] "Cost": 2000

[0581] },

[0582] {

[0583] "Tourist destination": "Ueno Park",

[0584] "Estimated time": "3 hours"

[0585] "Cost": 500

[0586] }

[0587] ],

[0588] "Total time": "7 hours"

[0589] Total cost: 5500

[0590] }

[0591] Step 6:

[0592] The server sends the generated sightseeing plan to the user's terminal.

[0593] The server receives the travel plan returned from the generated AI model, converts it into an appropriate data format (such as JSON), and sends it to the user's terminal. In some cases, it may further format the data before sending it.

[0594] Step 7:

[0595] The user's terminal analyzes and displays the sightseeing plan.

[0596] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on the displayed plan, the user can proceed with their sightseeing efficiently and effectively. The displayed information includes the names of the tourist attractions, the estimated time required, the cost, and the order of visits.

[0597] (Application Example 1)

[0598] 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."

[0599] The current tourism support system focuses on providing information on tourist spots and restaurants, but it lacks detailed information such as the optimal order of visits, the time required, and the total cost of visiting physical establishments. This makes it difficult for tourists to enjoy sightseeing efficiently and effectively. Furthermore, there is no way to obtain and display detailed information about physical establishments in real time, so tourists tend to spend a lot of time making decisions on-site. This leads to problems such as wasted time and budget.

[0600] 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.

[0601] In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generative AI model that generates an optimal tourist plan based on the tourist information, means for transmitting the generated tourist plan to the user terminal, means for calculating the order of visits to physical stores, the time required, and the total cost for the tourist plan, and means for obtaining detailed information of the physical stores and displaying it on the user terminal. This allows the user to efficiently visit physical stores and enjoy sightseeing to the fullest while reducing wasted time and budget.

[0602] "Means for receiving user-entered tourist information" refers to a function that sends data such as tourist destination information, budget, available time, and areas of interest entered by the user using a terminal to a server.

[0603] The "means for calling the generative AI model" refer to a function that activates a generative AI model to calculate and generate the optimal sightseeing plan based on the sightseeing information provided by the user.

[0604] "Means for sending sightseeing plans to user terminals" refers to a function that converts the optimal sightseeing plan created by the generative AI model into an appropriate data format and transfers it to the user's terminal.

[0605] "A means of calculating the order of visits to physical stores, the time required, and the total cost for a sightseeing plan" refers to a function that identifies the physical stores that a user should visit within a sightseeing plan, and calculates the order of visits to those facilities, the time required to visit each facility, and the overall budget.

[0606] "Means for obtaining and displaying detailed information about physical stores on the user's device" refers to a function that obtains detailed information (address, business hours, menu, etc.) about each physical store that the user plans to visit in real time and displays it on the user's device.

[0607] This invention is a system that provides optimal sightseeing plans for tourists. Based on the sightseeing information entered by the user, it generates a sightseeing plan using an AI model and transmits that plan to the user's terminal. This invention also provides detailed information about the physical stores that the user plans to visit, aiming to improve the efficiency and satisfaction of sightseeing.

[0608] System Configuration

[0609] This system consists of the following main components:

[0610] 1. User-side device: A device (such as a smartphone or tablet) used by the user to input tourist information and send it to the server.

[0611] 2. Server: A central system that receives tourist information and generates optimal tourist plans using a generated AI model.

[0612] 3. Generative AI Model: A machine learning model for generating travel plans. It references a database of tourist spots and restaurants to calculate the most suitable travel route based on the user's criteria.

[0613] 4. Tourism Database: A database containing detailed information (address, opening hours, cost, etc.) about various tourist spots, restaurants, and physical stores.

[0614] System operation

[0615] User terminal operation

[0616] Users open the application using a smartphone or other device and enter travel information. This travel information includes places they want to visit, their budget, available time, and areas of interest. This data is collected on the user's device and sent to the server.

[0617] Server operation

[0618] The server receives tourist information sent from the user's terminal. Based on the received tourist information, it calls a generation AI model and starts the process of generating the optimal tourist plan. The server refers to a database of tourist spots, restaurants, and physical stores to calculate the optimal tourist plan based on the user's requests.

[0619] How generative AI models work

[0620] The generating AI model uses user data received from the server to reference databases of tourist spots, restaurants, and physical stores. The AI ​​model calculates the specified visit order, duration, total cost, etc. It also retrieves detailed information about physical stores (address, opening hours, cost, menu, etc.) and includes this in the sightseeing plan.

[0621] Sending from server to user terminal

[0622] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0623] Displaying the plan on the user's device

[0624] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. This allows users to proceed with their sightseeing efficiently and effectively, and to check detailed information about physical stores in real time.

[0625] Specific example

[0626] As a concrete example, consider the case of tourist A visiting tourist destination B. Tourist A uses a smartphone application to input "Tourist Destination B" as the place to visit, a budget of "15,000 yen," available time of "5 hours," and interests of "Dining and Shopping." Based on this, the user's device sends tourist information to the server. The server receives this information and uses a generating AI model to create a tourist plan consisting of "Restaurant X," "Cafe Y," and "Shopping Mall Z." This plan includes the order of visits for each location, the time required, the total cost, and detailed information about the actual establishments (address, opening hours, cost, menu, etc.). This tourist plan is sent to the user's device, allowing tourist A to enjoy sightseeing efficiently.

[0627] Example of a prompt

[0628] Example of tourist A entering tourist information:

[0629] Place to visit: Tourist spot B, Budget: 15,000 yen, Available time: 5 hours, Interests: Dining and shopping

[0630] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0631] Step 1: Enter tourist information using the user terminal.

[0632] Users use a smartphone application to input travel information such as the tourist destinations they want to visit, their budget, available time, and areas of interest. This becomes the input data, and the device sends this data to the server.

[0633] Step 2: Receiving tourist information from the server

[0634] The server receives tourist information sent from the user's terminal. Here, the tourist information is temporarily stored and prepared for later use in calling the generated AI model. The received data is converted into an internal data structure.

[0635] Step 3: Generating tourist plans using a generative AI model

[0636] The server calls a generating AI model based on the received user data. The generating AI model refers to a database of tourist spots and restaurants to calculate the optimal visiting order, duration, and total cost. It also retrieves detailed information about physical establishments and includes it in the sightseeing plan. The data generated at this stage is the sightseeing plan data.

[0637] Step 4: Converting the sightseeing plan data

[0638] The server converts the tourist plans obtained from the generated AI model into an appropriate data format such as JSON. This makes it easier for the user's device to receive.

[0639] Step 5: Sending data from the server to the user terminal

[0640] The server sends the converted tourist plan data to the user's terminal. The HTTP protocol or other appropriate communication methods are used for transmission.

[0641] Step 6: User terminal receives and displays the plan

[0642] The user terminal receives the sightseeing plan sent from the server. The received data is analyzed and displayed on the user interface. The user can then plan their sightseeing based on this information.

[0643] Specific actions for each step:

[0644] Step 1 Input: User-entered tourist information data (places to visit, budget, available time, areas of interest)

[0645] Output: Tourism information data sent to the server

[0646] Step 2 Input: Tourist information data sent from the user terminal.

[0647] Output: Tourism information data converted to an internal data structure.

[0648] Step 3 Input: Converted tourist information data

[0649] Output: Tourism plan data generated by the AI ​​model (order of visits, duration, total cost, detailed information)

[0650] Input for Step 4: Tourism plan data obtained from the generated AI model.

[0651] Output: Tourist plan data converted to a data format suitable for the user's terminal (e.g., JSON).

[0652] Step 5 Input: Converted tourist plan data

[0653] Output: Tourist plan data sent to the user terminal

[0654] Step 6 Input: Tourist plan data sent from the server

[0655] Output: Analyzed tourist plan data displayed in the user interface

[0656] 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.

[0657] This invention combines a tourism support system for inbound tourists with an emotion engine that recognizes user emotions, thereby providing each user with an optimal tourism plan and realizing a more satisfying tourism experience. The system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and sends that plan to the user's terminal. Furthermore, by incorporating an emotion engine, it has the function of recognizing the user's emotions and adjusting the tourism plan in real time.

[0658] System Configuration

[0659] This system consists of the following components:

[0660] 1. User Device

[0661] 2. Server

[0662] 3. Generative AI Model

[0663] 4. Emotion Engine

[0664] System operation

[0665] User terminal operation

[0666] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is acquired on the user's device and sent to the server. In addition, the user's voice and facial expressions are captured using the camera and microphone, and this data is also sent to the emotion engine.

[0667] Server operation

[0668] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[0669] How generative AI models work

[0670] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user appears to be enjoying themselves, the plan might be adjusted to allow a little more time at the next spot; conversely, if the user appears tired, the next spot might be changed to a more relaxing location.

[0671] Sending from server to user terminal

[0672] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0673] Displaying the plan on the user's device

[0674] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[0675] Specific example

[0676] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server. In addition, Mr. Tanaka's voice and facial expressions are captured by the camera and microphone, and that data is also sent to the server.

[0677] The server receives this information and requests the generative AI model to create the optimal sightseeing plan. The generative AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these places, and sends the plan, including the optimal route, back to the server. At the same time, the emotion engine analyzes Mr. Tanaka's emotions and adjusts the sightseeing plan in real time.

[0678] The server sends this plan to the user's terminal, where it is displayed. Following this plan, Mr. Tanaka can efficiently enjoy sightseeing. Furthermore, based on the emotional data Mr. Tanaka displays during his sightseeing, the plan is adjusted as needed to optimize his sightseeing experience.

[0679] The system according to the present invention helps tourists efficiently tour tourist destinations and provides users with an optimal tourist experience by utilizing emotional data. Furthermore, by accumulating tourist data and emotional data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[0680] The following describes the processing flow.

[0681] Step 1:

[0682] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. Additionally, the smartphone's camera and microphone are used to capture emotional data such as voice and facial expressions. This input data and emotional data are collected within the app.

[0683] Step 2:

[0684] The device sends user-entered data and sentiment data to the server. The data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[0685] Step 3:

[0686] The server receives data sent from the terminal. After verifying the validity of the received tourist information and sentiment data, it processes this data and passes it to the generative AI model and sentiment engine.

[0687] Step 4:

[0688] The server invokes the generative AI model, passing the user's travel information as input data. Furthermore, the emotion engine provides additional data to the generative AI model based on the user's perceived emotions. The generative AI model then refers to a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[0689] Step 5:

[0690] The generative AI model generates an optimal travel plan based on the user's conditions and emotional data. For example, the plan may include a list of sightseeing spots to visit, the order of visits, estimated time required, and total cost. Based on emotional data, adjustments are made, such as continuing as planned if the user is enjoying themselves, or adding relaxing spots if they are tired.

[0691] Step 6:

[0692] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[0693] Step 7:

[0694] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[0695] Step 8:

[0696] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user reviews this information and begins sightseeing according to the suggested plan. In addition, emotional data during sightseeing is transmitted in real time, and the sightseeing plan may be adjusted accordingly. For example, if the user is highly satisfied at the current spot, adjustments may be made to shorten the travel time to the next spot or extend the time spent at that location.

[0697] Through the steps described above, the system of the present invention can not only provide support for tourists visiting Japan to efficiently enjoy sightseeing, but also provide an optimal experience in real time based on emotional data.

[0698] (Example 2)

[0699] 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".

[0700] Conventional tourism support systems provide travel plans based solely on information entered by the user, which has the problem of not adequately reflecting the individual user's preferences and physical condition. Therefore, in order to increase user satisfaction, it is necessary to recognize the user's emotions and physical condition in real time and provide a travel plan that is tailored to them.

[0701] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0702] In this invention, the server includes means for receiving tourist information entered by the user, means for capturing the user's voice and facial expression data, means for transmitting the received tourist information and the captured voice and facial expression data to the server, means for the server to verify the integrity of the data transmitted from the user terminal, means for transmitting the verified data to a generating AI model, means for the generating AI model to calculate the optimal tourist route by referring to a database of tourist spots and restaurants, means for an emotion engine to analyze the user's emotional data and adjust the tourist plan in real time, means for transmitting the generated tourist plan to the user terminal, and means for the user terminal to display the received tourist plan. This makes it possible to provide a customized tourist plan that is tailored to the user's emotions and physical condition.

[0703] "Means for receiving user-entered tourism information" refers to a means for users to input tourism information such as places to visit, budget, available time, and areas of interest into a terminal and send that information to a server.

[0704] "Means for capturing user voice and facial expression data" refers to means of acquiring user voice and facial expression data using the camera and microphone on the user's terminal.

[0705] "Means for transmitting received tourist information and captured audio and facial expression data to the server" refers to a means of encrypting the tourist information and audio / facial expression data acquired by the terminal and securely transmitting it to the server.

[0706] "Means by which the server verifies the integrity of data sent from the user terminal" refers to the means by which the server verifies the format and content of the received data and confirms whether it is in the correct format.

[0707] "Means for sending data whose consistency has been verified to the generating AI model" refers to the means by which the server sends data whose consistency has been verified to the generating AI model.

[0708] "A method by which a generative AI model calculates the optimal sightseeing route by referring to a database of tourist spots and restaurants" refers to a method by which a generative AI model uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule based on the input sightseeing information.

[0709] "A means by which an emotion engine analyzes user emotional data and adjusts the sightseeing plan in real time" refers to a method in which an emotion engine analyzes the user's emotions from voice and facial expression data and adjusts the sightseeing plan in real time based on that analysis.

[0710] "Means for sending the generated sightseeing plan to the user terminal" refers to the means by which the server converts the sightseeing plan obtained from the generated AI model into an appropriate format and sends it to the user terminal.

[0711] "Means for displaying a sightseeing plan received by a user terminal" refers to means by which a user terminal analyzes a sightseeing plan received from a server and displays it to the user through a user interface.

[0712] This invention is a tourism support system for tourists visiting Japan. By combining it with an emotion engine that recognizes the user's emotions, it provides an optimal tourism plan for each individual user, thereby realizing a more satisfying tourism experience. The system is configured as follows:

[0713] 1. User Device

[0714] First, the user opens the application using a device such as a smartphone or tablet. The user then enters travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is saved on the user's device and then sent to the server. In addition, the user's voice and facial expression data are captured through the device's camera and microphone and also sent to the emotion engine.

[0715] 2. Server

[0716] The server receives tourist information and sentiment data sent from the user's terminal. It verifies the integrity of the received data and prepares it for transmission to the generative AI model. The server sends the verified data to the generative AI model, from which it calculates the optimal tourist route.

[0717] 3. Generative AI Model

[0718] The generative AI model calculates the optimal sightseeing route and schedule by referencing a database of tourist spots and restaurants based on the user's travel information and sentiment data received from the server. The plan is adjusted in this process, taking the user's sentiment data into consideration.

[0719] 4. Emotion Engine

[0720] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state in real time. This emotional data is provided to a generative AI model, which is used to adjust the sightseeing plan. For example, if the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxation spots are added.

[0721] Specific examples of operation

[0722] The scenario involves Ms. Tanaka visiting Tokyo for a day of sightseeing. Ms. Tanaka opens the app and enters "Tokyo Skytree" as the place she wants to visit, "10,000 yen" as her budget, "8 hours" as the available time, and "history" as her interest. This information is sent to the server, and at the same time, Ms. Tanaka's facial expressions and voice are captured using the device's camera and microphone.

[0723] The server receives this data, verifies its integrity, and then sends it to the generating AI model. The generating AI model creates a sightseeing plan that includes places like "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park," and adjusts the plan based on the data from the emotion engine. The generated sightseeing plan is sent to Tanaka's smartphone via the server, and Tanaka enjoys sightseeing according to this plan.

[0724] Example of a prompt

[0725] "I'm planning a one-day sightseeing trip in Tokyo. My desired destination is Tokyo Skytree, my budget is 10,000 yen, I have 8 hours available, and my interest is history. Please suggest the best sightseeing plan. Also, please consider that the plan may be adjusted based on my emotional data during the trip."

[0726] This system makes it possible to provide customized sightseeing plans tailored to the user's emotional state, thereby increasing user satisfaction.

[0727] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0728] System program processing flow

[0729] Step 1:

[0730] Users open the application using a device such as a smartphone or tablet. They enter travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This entered travel information is temporarily stored on the user's device.

[0731] Input: User-entered tourist information (places to visit, budget, available time, areas of interest)

[0732] Output: Tourist information temporarily stored on the user's terminal.

[0733] Step 2:

[0734] The user's device uses its camera and microphone to capture the user's voice and facial expression data. This data is then input into the emotion engine.

[0735] Input: User voice data, facial expression data

[0736] Output: Audio data and facial expression data captured by the device.

[0737] Step 3:

[0738] The user's terminal sends tourist information, voice, and facial expression data to the server. This data is encrypted and transmitted securely.

[0739] Input: Tourist information, audio data, facial expression data (data stored on the user's device)

[0740] Output: Tourist information, audio data, and facial expression data sent to the server.

[0741] Step 4:

[0742] The server receives data sent from the user's terminal and verifies its integrity. If the data is invalid, it returns an error message.

[0743] Input: Tourist information, audio data, and facial expression data sent from the user's terminal.

[0744] Output: Data whose integrity has been verified, error message (if invalid)

[0745] Step 5:

[0746] The server sends the verified data to the generating AI model. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule.

[0747] Input: Authenticated tourist information and sentiment data.

[0748] Output: Data sent to the generating AI model, generated tourist plan

[0749] Step 6:

[0750] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state. This emotional data is provided to a generative AI model and used to adjust the sightseeing plan.

[0751] Input: User voice data, facial expression data

[0752] Output: Estimated user emotional state, emotional data

[0753] Step 7:

[0754] The generative AI model adjusts the sightseeing plan in real time based on emotional data obtained from the emotion engine. If the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxing spots are added.

[0755] Input: Initial tourist plan generated by a generative AI model, emotional data from an emotional engine.

[0756] Output: Customized sightseeing plan

[0757] Step 8:

[0758] The generated sightseeing plan is sent back to the server, which converts this data into an appropriate format such as JSON.

[0759] Input: Generated sightseeing plan

[0760] Output: Tourist plan converted to JSON format

[0761] Step 9:

[0762] The server sends the generated sightseeing plan to the user's terminal. The user's terminal receives this plan and displays it through the user interface. The user's terminal continues to capture the user's voice and facial expression data during sightseeing, and the plan is adjusted in real time.

[0763] Input: Tourist plan in JSON format

[0764] Output: Tourist plan displayed on the user's terminal

[0765] Step 10:

[0766] Users proceed with their sightseeing according to the displayed tour plan. If sentiment data is updated during the tour, the system adjusts the plan in real time and notifies the user.

[0767] Input: Sentiment data updated in real time

[0768] Output: Notification of updated adjusted sightseeing plan

[0769] These steps enable the system to provide the optimal sightseeing plan based on the user's input information and emotional state, thereby increasing user satisfaction.

[0770] (Application Example 2)

[0771] 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."

[0772] Conventional tourism support systems generate optimal sightseeing plans based solely on pre-entered information from users. However, this approach fails to reflect the user's real-time emotional state, making it difficult to address fatigue or disappointment experienced during sightseeing in real time. This can potentially degrade the quality of the user's sightseeing experience. To solve this problem, a system is needed that utilizes real-time emotional data from users to dynamically adjust sightseeing plans.

[0773] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generation AI model that generates an optimal tourist plan based on the tourist information and user emotion data acquired in real time, means for transmitting the generated tourist plan to the user terminal, and an emotion engine that analyzes the user emotion data and adjusts the tourist plan. This makes it possible to dynamically adjust the tourist plan to reflect the user's real-time emotional state.

[0774] "User-entered tourism information" refers to information entered by users regarding their own tourism preferences and conditions, specifically including places to visit, budget, available time, and areas of interest.

[0775] "Real-time user emotion data" refers to emotional data acquired in real time from the user's facial expressions, voice tone, and other factors.

[0776] An "optimal sightseeing plan" is a plan designed to provide an efficient and highly satisfying sightseeing experience, based on user input information and emotional data.

[0777] A "generative AI model" is an artificial intelligence model that automatically generates sightseeing plans based on input data, and has the function of calculating the optimal route by referring to a database of tourist spots and restaurants.

[0778] A "user terminal" refers to a device used by a user, and includes smartphones, in-vehicle displays, and other similar devices.

[0779] The "emotion engine" is an engine that analyzes users' real-time emotional data and adjusts sightseeing plans based on that data.

[0780] A "database of tourist spots and restaurants" is a database containing information about tourist destinations and restaurants, which is referenced by the generating AI model to calculate the optimal tourist route.

[0781] To deliver an "exceptional and authentic travel experience," this system enables dynamic plan adjustments and optimizations that reflect user emotions in real time.

[0782] This invention relates to a tourism support system that operates within an autonomous vehicle. This system improves the quality of the tourism experience by generating and dynamically adjusting an optimal tourism plan based on tourism information entered by the user and user emotion data acquired in real time.

[0783] System components

[0784] This system consists of the following components:

[0785] 1. User Device: This includes smartphones and the displays of autonomous vehicles.

[0786] 2. Server: Performs data processing and generates and manages tourist plans.

[0787] 3. Generative AI Model: Generates optimal sightseeing plans based on user input information and sentiment data.

[0788] 4. Emotion Engine: Analyzes the user's real-time emotional data and dynamically adjusts the sightseeing plan based on that data.

[0789] System operation

[0790] User terminal operation

[0791] First, the user opens the application using the display inside the autonomous vehicle or on their smartphone and enters the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is acquired by the user's device and sent to the server. In addition, the user's voice and facial expressions are captured by the camera and microphone, and this emotion data is also sent to the server.

[0792] Server operation

[0793] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[0794] How generative AI models work

[0795] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants, calculating the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user is enjoying themselves, the time spent at the next spot will be extended; conversely, if the user is tired, the location will be changed to a more relaxing one.

[0796] Sending from server to user terminal

[0797] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0798] Displaying the plan on the user's device

[0799] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[0800] Specific example

[0801] 1. For example, a user gets into an autonomous vehicle and inputs information about tourist destinations and interests. Based on emotion data obtained from the camera and microphone, the system suggests the optimal sightseeing plan for the places the user wants to visit.

[0802] 2. The user enters "Tokyo Skytree" as the place they want to visit, "10,000 yen" as their budget, "8 hours" as the available time, and "history" as their interest. The system then suggests a sightseeing route that includes Tokyo Skytree, Senso-ji Temple, and Ueno Park. If the emotion engine determines that the user is enjoying the sightseeing, it adjusts the time spent at the next spot to increase.

[0803] Example of a prompt

[0804] Generate a sightseeing plan based on the user's entered travel information (Place to visit: Tokyo Skytree, Budget: 10,000 yen, Available time: 8 hours, Interests: History). Also, adjust the plan by taking into account the user's real-time sentiment data. For example, if the user is enjoying themselves, extend the time spent at the next spot; if they are tired, suggest a place to relax.

[0805] This allows the system to dynamically adjust sightseeing plans to reflect the user's real-time emotional state.

[0806] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0807] Step 1:

[0808] Users input tourist information using a display in the autonomous vehicle or their smartphone. This information includes places to visit, budget, available time, and areas of interest, and this data is acquired on the user's device.

[0809] Input: Visit location, budget, available time, areas of interest

[0810] Output: Tourism preference data

[0811] Step 2:

[0812] The user terminal captures the user's voice and facial expressions using a camera and microphone, acquiring this data in real time. This allows for the acquisition of user emotion data.

[0813] Input: Voice data, facial expression data

[0814] Output: User sentiment data

[0815] Step 3:

[0816] The user terminal sends tourism preference data and sentiment data to the server. The server checks the format of the received data and verifies its validity.

[0817] Input: Tourism preference data, sentiment data

[0818] Output: Formatted user data

[0819] Step 4:

[0820] The server passes the formatted user data to a generating AI model and requests it to create a travel plan. The generating AI model refers to a database of tourist spots and restaurants and calculates the optimal travel route and schedule.

[0821] Input: Formatted user data

[0822] Output: Initial sightseeing plan

[0823] Step 5:

[0824] The generative AI model adjusts the initial sightseeing plan based on emotion data retrieved from the server. If the user is enjoying themselves, it extends the length of their stay; if they are tired, it adds relaxing spots.

[0825] Input: Initial sightseeing plan, sentiment data

[0826] Output: Optimized sightseeing plan

[0827] Step 6:

[0828] The server converts the optimized sightseeing plan into an appropriate format, such as JSON, and sends it to the user's terminal.

[0829] Input: Optimized sightseeing plan

[0830] Output: Format-converted sightseeing plan

[0831] Step 7:

[0832] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can review the suggested plan and begin sightseeing accordingly. During sightseeing, emotion data is continuously collected via camera and microphone, and the plan is updated as needed.

[0833] Input: Formatted sightseeing plan

[0834] Output: Displayed sightseeing plan

[0835] 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.

[0836] 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.

[0837] 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.

[0838] [Third Embodiment]

[0839] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0840] 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.

[0841] 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).

[0842] 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.

[0843] 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.

[0844] 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).

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] 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.

[0850] 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".

[0851] This invention is a tourism support system for tourists visiting Japan. This system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and then transmits that plan to the user's terminal.

[0852] System Configuration

[0853] This system consists of the following main components:

[0854] 1. User Device

[0855] 2. Server

[0856] 3. Generative AI Model

[0857] System operation

[0858] User terminal operation

[0859] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is collected on the user's device and sent to the server.

[0860] Server operation

[0861] The server receives tourist information entered from the user's terminal. The received data is passed to a generating AI model, which then starts processing to create the optimal tourist plan. The server uses this tourist data to call the generating AI model and refer to a database of tourist spots and restaurants.

[0862] How generative AI models work

[0863] The AI ​​model uses user data received from the server to reference a database of tourist spots and restaurants. The AI ​​model calculates the optimal sightseeing route and selects places and facilities to visit. This generates an optimal sightseeing plan tailored to the user's preferences. This plan includes the order of visits, total cost, and estimated time required.

[0864] Sending from server to user terminal

[0865] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[0866] Displaying the plan on the user's device

[0867] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0868] Specific example

[0869] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server.

[0870] The server receives this information and requests the generating AI model to create the optimal sightseeing plan. The generating AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these locations, and sends the plan, including the optimal route, back to the server.

[0871] The server sends this plan to the user's terminal, and it is displayed on Mr. Tanaka's terminal. Mr. Tanaka can then enjoy sightseeing efficiently by following this plan.

[0872] The system according to the present invention helps tourists efficiently tour tourist destinations, reducing time loss and the stress of gathering information. Furthermore, by accumulating tourism data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[0873] The following describes the processing flow.

[0874] Step 1:

[0875] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. This entered data is collected within the app.

[0876] Step 2:

[0877] The terminal sends the data entered by the user to the server. During this process, the data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[0878] Step 3:

[0879] The server receives the data sent from the terminal, verifies the validity of the data format, and then passes it on to the generating AI model.

[0880] Step 4:

[0881] The server invokes a generating AI model, passing the user's travel information as input data. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[0882] Step 5:

[0883] The AI ​​model generates an optimal travel plan based on the user's criteria. For example, the plan may include a list of sightseeing spots to visit, the order in which to visit them, estimated time required, and total cost.

[0884] Step 6:

[0885] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[0886] Step 7:

[0887] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[0888] Step 8:

[0889] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can then review this information and begin sightseeing according to the suggested plan.

[0890] Through the steps described above, the system of the present invention can provide support for tourists visiting Japan to efficiently enjoy sightseeing.

[0891] (Example 1)

[0892] 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."

[0893] Conventional tourism support systems have struggled to efficiently process user-inputted tourism information and provide optimal travel plans. Furthermore, insufficient data formatting and validation during plan generation have resulted in a poor user experience.

[0894] 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.

[0895] In this invention, the server includes means for receiving tourist information entered by a user, means for validating and formatting the tourist information to pass it to a generating AI model, means for calling a generating AI model that generates an optimal tourist plan based on the tourist information, means for converting the generated tourist plan into an appropriate data format and transmitting it to a user terminal, and means for the user terminal to analyze the tourist plan received and display it on a user interface. This makes it possible to process the information entered by the user efficiently and accurately and provide an optimal tourist plan.

[0896] "Means for receiving user-entered tourist information" refers to functions or devices that allow a server to receive information such as places to visit, budget, available time, and areas of interest, which are entered by the user through their terminal.

[0897] "Methods for validating and formatting data to pass tourism information to a generating AI model" refers to functions or devices that check whether the format and values ​​of the tourism information entered by the user are appropriate, and convert them into a format that the generating AI model can understand.

[0898] "Means for calling a generative AI model that generates an optimal sightseeing plan" refers to a function or device that executes a generative AI model that generates an optimal sightseeing plan according to the user's conditions by referring to a database of tourist spots and restaurants based on the input sightseeing information.

[0899] "Means for converting generated sightseeing plans into an appropriate data format and transmitting them to the user terminal" refers to a function or device for converting sightseeing plans generated by a generation AI model into a data format that the user terminal can understand and transmitting it to the user terminal.

[0900] "Means for analyzing a sightseeing plan received by a user terminal and displaying it on the user interface" refers to a function or device that receives and analyzes sightseeing plan data transmitted from a server on a user terminal and visually displays its contents to the user.

[0901] Modes for carrying out the invention

[0902] This invention is a tourism support system for tourists visiting Japan, and consists of the following main components.

[0903] 1. User Device

[0904] 2. Server

[0905] 3. Generative AI Model

[0906] System operation

[0907] User terminal operation

[0908] The user first opens the application using a device such as a smartphone or tablet to access the system. On the application's user interface, they enter the tourist destination they wish to visit, their budget, available time, and areas of interest. For example, the following input might be made:

[0909] Places I want to visit: Tokyo Skytree

[0910] Budget: 10,000 yen

[0911] Available time: 8 hours

[0912] Interests: History

[0913] The terminal retrieves this input data, stores it temporarily, and then sends it to the server.

[0914] Server operation

[0915] The server receives tourist information sent from the user's terminal and performs data validation and formatting. Specifically, it checks the data format and fills in any missing information. Next, the server generates a prompt message to request the AI ​​model to generate a tourist plan. An example of a prompt message is as follows:

[0916] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0917] The generated prompt text is sent to the AI ​​model, and the creation of the sightseeing plan begins.

[0918] How generative AI models work

[0919] The AI ​​model generates an optimal sightseeing plan based on user data received from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in an appropriate data format, such as JSON.

[0920] Sending from server to user terminal

[0921] The server receives the generated sightseeing plan and sends it to the user's terminal. The sightseeing plan is formatted as needed, converted back to JSON format, and sent again. For example, the following JSON data is sent:

[0922] json

[0923] {

[0924] "Plan": [

[0925] {

[0926] "Tourist attraction": "Tokyo Skytree",

[0927] "Estimated time": "2 hours"

[0928] "Cost": 3000

[0929] },

[0930] {

[0931] "Tourist destination": "Senso-ji Temple",

[0932] "Estimated time": "2 hours"

[0933] "Cost": 2000

[0934] },

[0935] {

[0936] "Tourist destination": "Ueno Park",

[0937] "Estimated time": "3 hours"

[0938] "Cost": 500

[0939] }

[0940] ],

[0941] "Total time": "7 hours"

[0942] Total cost: 5500

[0943] }

[0944] Displaying the plan on the user's device

[0945] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[0946] This invention enables efficient and accurate processing of input tourism information and provides optimal tourism plans. Furthermore, by accumulating tourism data, even more accurate recommendations can be made when generating future tourism plans.

[0947] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0948] Processing steps

[0949] Step 1:

[0950] Users enter tourist information.

[0951] Users use their devices (such as smartphones or tablets) to open a dedicated application and enter tourist information (places they want to visit, budget, available time, areas of interest). For example, they might enter the following:

[0952] Places I want to visit: Tokyo Skytree

[0953] Budget: 10,000 yen

[0954] Available time: 8 hours

[0955] Interests: History

[0956] The entered data will be temporarily stored on the device.

[0957] Step 2:

[0958] The device sends tourist information to the server.

[0959] The terminal sends the tourist information entered by the user to the server. Specifically, it sends data to the server via an HTTP POST request using a REST API. The input data is sent in JSON format. For example, the following JSON data is sent:

[0960] json

[0961] {

[0962] "Tourist attraction": "Tokyo Skytree",

[0963] "Budget": 10000,

[0964] "time": 8,

[0965] "Interest": "History"

[0966] }

[0967] Step 3:

[0968] The server receives the data and performs validation and formatting.

[0969] The server receives tourist information sent from the terminal. After receiving the data, it validates (checks the format and values) and formats it. For example, it checks if the visited locations are appropriate and returns error messages if necessary. The formatted data is then ready to be passed to the generating AI model.

[0970] Step 4:

[0971] The server generates a prompt message and sends it to the AI ​​model.

[0972] The server generates prompts to request the AI ​​model to create a travel plan based on the formatted tourist information. An example of a prompt is as follows:

[0973] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[0974] Send this prompt message to the AI ​​model that generates the data.

[0975] Step 5:

[0976] A generative AI model generates tourist plans.

[0977] The AI ​​model generates an optimal sightseeing plan based on prompts sent from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in JSON format. For example, the following JSON data is generated:

[0978] json

[0979] {

[0980] "Plan": [

[0981] {

[0982] "Tourist attraction": "Tokyo Skytree",

[0983] "Estimated time": "2 hours"

[0984] "Cost": 3000

[0985] },

[0986] {

[0987] "Tourist destination": "Senso-ji Temple",

[0988] "Estimated time": "2 hours"

[0989] "Cost": 2000

[0990] },

[0991] {

[0992] "Tourist destination": "Ueno Park",

[0993] "Estimated time": "3 hours"

[0994] "Cost": 500

[0995] }

[0996] ],

[0997] "Total time": "7 hours"

[0998] Total cost: 5500

[0999] }

[1000] Step 6:

[1001] The server sends the generated sightseeing plan to the user's terminal.

[1002] The server receives the travel plan returned from the generated AI model, converts it into an appropriate data format (such as JSON), and sends it to the user's terminal. In some cases, it may further format the data before sending it.

[1003] Step 7:

[1004] The user's terminal analyzes and displays the sightseeing plan.

[1005] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on the displayed plan, the user can proceed with their sightseeing efficiently and effectively. The displayed information includes the names of the tourist attractions, the estimated time required, the cost, and the order of visits.

[1006] (Application Example 1)

[1007] 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."

[1008] The current tourism support system focuses on providing information on tourist spots and restaurants, but it lacks detailed information such as the optimal order of visits, the time required, and the total cost of visiting physical establishments. This makes it difficult for tourists to enjoy sightseeing efficiently and effectively. Furthermore, there is no way to obtain and display detailed information about physical establishments in real time, so tourists tend to spend a lot of time making decisions on-site. This leads to problems such as wasted time and budget.

[1009] 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.

[1010] In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generative AI model that generates an optimal tourist plan based on the tourist information, means for transmitting the generated tourist plan to the user terminal, means for calculating the order of visits to physical stores, the time required, and the total cost for the tourist plan, and means for obtaining detailed information of the physical stores and displaying it on the user terminal. This allows the user to efficiently visit physical stores and enjoy sightseeing to the fullest while reducing wasted time and budget.

[1011] "Means for receiving user-entered tourist information" refers to a function that sends data such as tourist destination information, budget, available time, and areas of interest entered by the user using a terminal to a server.

[1012] The "means for calling the generative AI model" refer to a function that activates a generative AI model to calculate and generate the optimal sightseeing plan based on the sightseeing information provided by the user.

[1013] "Means for sending sightseeing plans to user terminals" refers to a function that converts the optimal sightseeing plan created by the generative AI model into an appropriate data format and transfers it to the user's terminal.

[1014] "A means of calculating the order of visits to physical stores, the time required, and the total cost for a sightseeing plan" refers to a function that identifies the physical stores that a user should visit within a sightseeing plan, and calculates the order of visits to those facilities, the time required to visit each facility, and the overall budget.

[1015] "Means for obtaining and displaying detailed information about physical stores on the user's device" refers to a function that obtains detailed information (address, business hours, menu, etc.) about each physical store that the user plans to visit in real time and displays it on the user's device.

[1016] This invention is a system that provides optimal sightseeing plans for tourists. Based on the sightseeing information entered by the user, it generates a sightseeing plan using an AI model and transmits that plan to the user's terminal. This invention also provides detailed information about the physical stores that the user plans to visit, aiming to improve the efficiency and satisfaction of sightseeing.

[1017] System Configuration

[1018] This system consists of the following main components:

[1019] 1. User-side device: A device (such as a smartphone or tablet) used by the user to input tourist information and send it to the server.

[1020] 2. Server: A central system that receives tourist information and generates optimal tourist plans using a generated AI model.

[1021] 3. Generative AI Model: A machine learning model for generating travel plans. It references a database of tourist spots and restaurants to calculate the most suitable travel route based on the user's criteria.

[1022] 4. Tourism Database: A database containing detailed information (address, opening hours, cost, etc.) about various tourist spots, restaurants, and physical stores.

[1023] System operation

[1024] User terminal operation

[1025] Users open the application using a smartphone or other device and enter travel information. This travel information includes places they want to visit, their budget, available time, and areas of interest. This data is collected on the user's device and sent to the server.

[1026] Server operation

[1027] The server receives tourist information sent from the user's terminal. Based on the received tourist information, it calls a generation AI model and starts the process of generating the optimal tourist plan. The server refers to a database of tourist spots, restaurants, and physical stores to calculate the optimal tourist plan based on the user's requests.

[1028] How generative AI models work

[1029] The generating AI model uses user data received from the server to reference databases of tourist spots, restaurants, and physical stores. The AI ​​model calculates the specified visit order, duration, total cost, etc. It also retrieves detailed information about physical stores (address, opening hours, cost, menu, etc.) and includes this in the sightseeing plan.

[1030] Sending from server to user terminal

[1031] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1032] Displaying the plan on the user's device

[1033] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. This allows users to proceed with their sightseeing efficiently and effectively, and to check detailed information about physical stores in real time.

[1034] Specific example

[1035] As a concrete example, consider the case of tourist A visiting tourist destination B. Tourist A uses a smartphone application to input "Tourist Destination B" as the place to visit, a budget of "15,000 yen," available time of "5 hours," and interests of "Dining and Shopping." Based on this, the user's device sends tourist information to the server. The server receives this information and uses a generating AI model to create a tourist plan consisting of "Restaurant X," "Cafe Y," and "Shopping Mall Z." This plan includes the order of visits for each location, the time required, the total cost, and detailed information about the actual establishments (address, opening hours, cost, menu, etc.). This tourist plan is sent to the user's device, allowing tourist A to enjoy sightseeing efficiently.

[1036] Example of a prompt

[1037] Example of tourist A entering tourist information:

[1038] Place to visit: Tourist spot B, Budget: 15,000 yen, Available time: 5 hours, Interests: Dining and shopping

[1039] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1040] Step 1: Enter tourist information using the user terminal.

[1041] Users use a smartphone application to input travel information such as the tourist destinations they want to visit, their budget, available time, and areas of interest. This becomes the input data, and the device sends this data to the server.

[1042] Step 2: Receiving tourist information from the server

[1043] The server receives tourist information sent from the user's terminal. Here, the tourist information is temporarily stored and prepared for later use in calling the generated AI model. The received data is converted into an internal data structure.

[1044] Step 3: Generating tourist plans using a generative AI model

[1045] The server calls a generating AI model based on the received user data. The generating AI model refers to a database of tourist spots and restaurants to calculate the optimal visiting order, duration, and total cost. It also retrieves detailed information about physical establishments and includes it in the sightseeing plan. The data generated at this stage is the sightseeing plan data.

[1046] Step 4: Converting the sightseeing plan data

[1047] The server converts the tourist plans obtained from the generated AI model into an appropriate data format such as JSON. This makes it easier for the user's device to receive.

[1048] Step 5: Sending data from the server to the user terminal

[1049] The server sends the converted tourist plan data to the user's terminal. The HTTP protocol or other appropriate communication methods are used for transmission.

[1050] Step 6: User terminal receives and displays the plan

[1051] The user terminal receives the sightseeing plan sent from the server. The received data is analyzed and displayed on the user interface. The user can then plan their sightseeing based on this information.

[1052] Specific actions for each step:

[1053] Step 1 Input: User-entered tourist information data (places to visit, budget, available time, areas of interest)

[1054] Output: Tourism information data sent to the server

[1055] Step 2 Input: Tourist information data sent from the user terminal.

[1056] Output: Tourism information data converted to an internal data structure.

[1057] Step 3 Input: Converted tourist information data

[1058] Output: Tourism plan data generated by the AI ​​model (order of visits, duration, total cost, detailed information)

[1059] Input for Step 4: Tourism plan data obtained from the generated AI model.

[1060] Output: Tourist plan data converted to a data format suitable for the user's terminal (e.g., JSON).

[1061] Step 5 Input: Converted tourist plan data

[1062] Output: Tourist plan data sent to the user terminal

[1063] Step 6 Input: Tourist plan data sent from the server

[1064] Output: Analyzed tourist plan data displayed in the user interface

[1065] 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.

[1066] This invention combines a tourism support system for inbound tourists with an emotion engine that recognizes user emotions, thereby providing each user with an optimal tourism plan and realizing a more satisfying tourism experience. The system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and sends that plan to the user's terminal. Furthermore, by incorporating an emotion engine, it has the function of recognizing the user's emotions and adjusting the tourism plan in real time.

[1067] System Configuration

[1068] This system consists of the following components:

[1069] 1. User Device

[1070] 2. Server

[1071] 3. Generative AI Model

[1072] 4. Emotion Engine

[1073] System operation

[1074] User terminal operation

[1075] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is acquired on the user's device and sent to the server. In addition, the user's voice and facial expressions are captured using the camera and microphone, and this data is also sent to the emotion engine.

[1076] Server operation

[1077] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[1078] How generative AI models work

[1079] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user appears to be enjoying themselves, the plan might be adjusted to allow a little more time at the next spot; conversely, if the user appears tired, the next spot might be changed to a more relaxing location.

[1080] Sending from server to user terminal

[1081] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1082] Displaying the plan on the user's device

[1083] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[1084] Specific example

[1085] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server. In addition, Mr. Tanaka's voice and facial expressions are captured by the camera and microphone, and that data is also sent to the server.

[1086] The server receives this information and requests the generative AI model to create the optimal sightseeing plan. The generative AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these places, and sends the plan, including the optimal route, back to the server. At the same time, the emotion engine analyzes Mr. Tanaka's emotions and adjusts the sightseeing plan in real time.

[1087] The server sends this plan to the user's terminal, where it is displayed. Following this plan, Mr. Tanaka can efficiently enjoy sightseeing. Furthermore, based on the emotional data Mr. Tanaka displays during his sightseeing, the plan is adjusted as needed to optimize his sightseeing experience.

[1088] The system according to the present invention helps tourists efficiently tour tourist destinations and provides users with an optimal tourist experience by utilizing emotional data. Furthermore, by accumulating tourist data and emotional data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[1089] The following describes the processing flow.

[1090] Step 1:

[1091] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. Additionally, the smartphone's camera and microphone are used to capture emotional data such as voice and facial expressions. This input data and emotional data are collected within the app.

[1092] Step 2:

[1093] The device sends user-entered data and sentiment data to the server. The data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[1094] Step 3:

[1095] The server receives data sent from the terminal. After verifying the validity of the received tourist information and sentiment data, it processes this data and passes it to the generative AI model and sentiment engine.

[1096] Step 4:

[1097] The server invokes the generative AI model, passing the user's travel information as input data. Furthermore, the emotion engine provides additional data to the generative AI model based on the user's perceived emotions. The generative AI model then refers to a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[1098] Step 5:

[1099] The generative AI model generates an optimal travel plan based on the user's conditions and emotional data. For example, the plan may include a list of sightseeing spots to visit, the order of visits, estimated time required, and total cost. Based on emotional data, adjustments are made, such as continuing as planned if the user is enjoying themselves, or adding relaxing spots if they are tired.

[1100] Step 6:

[1101] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[1102] Step 7:

[1103] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[1104] Step 8:

[1105] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user reviews this information and begins sightseeing according to the suggested plan. In addition, emotional data during sightseeing is transmitted in real time, and the sightseeing plan may be adjusted accordingly. For example, if the user is highly satisfied at the current spot, adjustments may be made to shorten the travel time to the next spot or extend the time spent at that location.

[1106] Through the steps described above, the system of the present invention can not only provide support for tourists visiting Japan to efficiently enjoy sightseeing, but also provide an optimal experience in real time based on emotional data.

[1107] (Example 2)

[1108] 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."

[1109] Conventional tourism support systems provide travel plans based solely on information entered by the user, which has the problem of not adequately reflecting the individual user's preferences and physical condition. Therefore, in order to increase user satisfaction, it is necessary to recognize the user's emotions and physical condition in real time and provide a travel plan that is tailored to them.

[1110] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1111] In this invention, the server includes means for receiving tourist information entered by the user, means for capturing the user's voice and facial expression data, means for transmitting the received tourist information and the captured voice and facial expression data to the server, means for the server to verify the integrity of the data transmitted from the user terminal, means for transmitting the verified data to a generating AI model, means for the generating AI model to calculate the optimal tourist route by referring to a database of tourist spots and restaurants, means for an emotion engine to analyze the user's emotional data and adjust the tourist plan in real time, means for transmitting the generated tourist plan to the user terminal, and means for the user terminal to display the received tourist plan. This makes it possible to provide a customized tourist plan that is tailored to the user's emotions and physical condition.

[1112] "Means for receiving user-entered tourism information" refers to a means for users to input tourism information such as places to visit, budget, available time, and areas of interest into a terminal and send that information to a server.

[1113] "Means for capturing user voice and facial expression data" refers to means of acquiring user voice and facial expression data using the camera and microphone on the user's terminal.

[1114] "Means for transmitting received tourist information and captured audio and facial expression data to the server" refers to a means of encrypting the tourist information and audio / facial expression data acquired by the terminal and securely transmitting it to the server.

[1115] "Means by which the server verifies the integrity of data sent from the user terminal" refers to the means by which the server verifies the format and content of the received data and confirms whether it is in the correct format.

[1116] "Means for sending data whose consistency has been verified to the generating AI model" refers to the means by which the server sends data whose consistency has been verified to the generating AI model.

[1117] "A method by which a generative AI model calculates the optimal sightseeing route by referring to a database of tourist spots and restaurants" refers to a method by which a generative AI model uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule based on the input sightseeing information.

[1118] "A means by which an emotion engine analyzes user emotional data and adjusts the sightseeing plan in real time" refers to a method in which an emotion engine analyzes the user's emotions from voice and facial expression data and adjusts the sightseeing plan in real time based on that analysis.

[1119] "Means for sending the generated sightseeing plan to the user terminal" refers to the means by which the server converts the sightseeing plan obtained from the generated AI model into an appropriate format and sends it to the user terminal.

[1120] "Means for displaying a sightseeing plan received by a user terminal" refers to means by which a user terminal analyzes a sightseeing plan received from a server and displays it to the user through a user interface.

[1121] This invention is a tourism support system for tourists visiting Japan. By combining it with an emotion engine that recognizes the user's emotions, it provides an optimal tourism plan for each individual user, thereby realizing a more satisfying tourism experience. The system is configured as follows:

[1122] 1. User Device

[1123] First, the user opens the application using a device such as a smartphone or tablet. The user then enters travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is saved on the user's device and then sent to the server. In addition, the user's voice and facial expression data are captured through the device's camera and microphone and also sent to the emotion engine.

[1124] 2. Server

[1125] The server receives tourist information and sentiment data sent from the user's terminal. It verifies the integrity of the received data and prepares it for transmission to the generative AI model. The server sends the verified data to the generative AI model, from which it calculates the optimal tourist route.

[1126] 3. Generative AI Model

[1127] The generative AI model calculates the optimal sightseeing route and schedule by referencing a database of tourist spots and restaurants based on the user's travel information and sentiment data received from the server. The plan is adjusted in this process, taking the user's sentiment data into consideration.

[1128] 4. Emotion Engine

[1129] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state in real time. This emotional data is provided to a generative AI model, which is used to adjust the sightseeing plan. For example, if the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxation spots are added.

[1130] Specific examples of operation

[1131] The scenario involves Ms. Tanaka visiting Tokyo for a day of sightseeing. Ms. Tanaka opens the app and enters "Tokyo Skytree" as the place she wants to visit, "10,000 yen" as her budget, "8 hours" as the available time, and "history" as her interest. This information is sent to the server, and at the same time, Ms. Tanaka's facial expressions and voice are captured using the device's camera and microphone.

[1132] The server receives this data, verifies its integrity, and then sends it to the generating AI model. The generating AI model creates a sightseeing plan that includes places like "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park," and adjusts the plan based on the data from the emotion engine. The generated sightseeing plan is sent to Tanaka's smartphone via the server, and Tanaka enjoys sightseeing according to this plan.

[1133] Example of a prompt

[1134] "I'm planning a one-day sightseeing trip in Tokyo. My desired destination is Tokyo Skytree, my budget is 10,000 yen, I have 8 hours available, and my interest is history. Please suggest the best sightseeing plan. Also, please consider that the plan may be adjusted based on my emotional data during the trip."

[1135] This system makes it possible to provide customized sightseeing plans tailored to the user's emotional state, thereby increasing user satisfaction.

[1136] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1137] System program processing flow

[1138] Step 1:

[1139] Users open the application using a device such as a smartphone or tablet. They enter travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This entered travel information is temporarily stored on the user's device.

[1140] Input: User-entered tourist information (places to visit, budget, available time, areas of interest)

[1141] Output: Tourist information temporarily stored on the user's terminal.

[1142] Step 2:

[1143] The user's device uses its camera and microphone to capture the user's voice and facial expression data. This data is then input into the emotion engine.

[1144] Input: User voice data, facial expression data

[1145] Output: Audio data and facial expression data captured by the device.

[1146] Step 3:

[1147] The user's terminal sends tourist information, voice, and facial expression data to the server. This data is encrypted and transmitted securely.

[1148] Input: Tourist information, audio data, facial expression data (data stored on the user's device)

[1149] Output: Tourist information, audio data, and facial expression data sent to the server.

[1150] Step 4:

[1151] The server receives data sent from the user's terminal and verifies its integrity. If the data is invalid, it returns an error message.

[1152] Input: Tourist information, audio data, and facial expression data sent from the user's terminal.

[1153] Output: Data whose integrity has been verified, error message (if invalid)

[1154] Step 5:

[1155] The server sends the verified data to the generating AI model. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule.

[1156] Input: Authenticated tourist information and sentiment data.

[1157] Output: Data sent to the generating AI model, generated tourist plan

[1158] Step 6:

[1159] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state. This emotional data is provided to a generative AI model and used to adjust the sightseeing plan.

[1160] Input: User voice data, facial expression data

[1161] Output: Estimated user emotional state, emotional data

[1162] Step 7:

[1163] The generative AI model adjusts the sightseeing plan in real time based on emotional data obtained from the emotion engine. If the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxing spots are added.

[1164] Input: Initial tourist plan generated by a generative AI model, emotional data from an emotional engine.

[1165] Output: Customized sightseeing plan

[1166] Step 8:

[1167] The generated sightseeing plan is sent back to the server, which converts this data into an appropriate format such as JSON.

[1168] Input: Generated sightseeing plan

[1169] Output: Tourist plan converted to JSON format

[1170] Step 9:

[1171] The server sends the generated sightseeing plan to the user's terminal. The user's terminal receives this plan and displays it through the user interface. The user's terminal continues to capture the user's voice and facial expression data during sightseeing, and the plan is adjusted in real time.

[1172] Input: Tourist plan in JSON format

[1173] Output: Tourist plan displayed on the user's terminal

[1174] Step 10:

[1175] Users proceed with their sightseeing according to the displayed tour plan. If sentiment data is updated during the tour, the system adjusts the plan in real time and notifies the user.

[1176] Input: Sentiment data updated in real time

[1177] Output: Notification of updated adjusted sightseeing plan

[1178] These steps enable the system to provide the optimal sightseeing plan based on the user's input information and emotional state, thereby increasing user satisfaction.

[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 tourism support systems generate optimal sightseeing plans based solely on pre-entered information from users. However, this approach fails to reflect the user's real-time emotional state, making it difficult to address fatigue or disappointment experienced during sightseeing in real time. This can potentially degrade the quality of the user's sightseeing experience. To solve this problem, a system is needed that utilizes real-time emotional data from users to dynamically adjust sightseeing plans.

[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. In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generation AI model that generates an optimal tourist plan based on the tourist information and user emotion data acquired in real time, means for transmitting the generated tourist plan to the user terminal, and an emotion engine that analyzes the user emotion data and adjusts the tourist plan. This makes it possible to dynamically adjust the tourist plan to reflect the user's real-time emotional state.

[1183] "User-entered tourism information" refers to information entered by users regarding their own tourism preferences and conditions, specifically including places to visit, budget, available time, and areas of interest.

[1184] "Real-time user emotion data" refers to emotional data acquired in real time from the user's facial expressions, voice tone, and other factors.

[1185] An "optimal sightseeing plan" is a plan designed to provide an efficient and highly satisfying sightseeing experience, based on user input information and emotional data.

[1186] A "generative AI model" is an artificial intelligence model that automatically generates sightseeing plans based on input data, and has the function of calculating the optimal route by referring to a database of tourist spots and restaurants.

[1187] A "user terminal" refers to a device used by a user, and includes smartphones, in-vehicle displays, and other similar devices.

[1188] The "emotion engine" is an engine that analyzes users' real-time emotional data and adjusts sightseeing plans based on that data.

[1189] A "database of tourist spots and restaurants" is a database containing information about tourist destinations and restaurants, which is referenced by the generating AI model to calculate the optimal tourist route.

[1190] To deliver an "exceptional and authentic travel experience," this system enables dynamic plan adjustments and optimizations that reflect user emotions in real time.

[1191] This invention relates to a tourism support system that operates within an autonomous vehicle. This system improves the quality of the tourism experience by generating and dynamically adjusting an optimal tourism plan based on tourism information entered by the user and user emotion data acquired in real time.

[1192] System components

[1193] This system consists of the following components:

[1194] 1. User Device: This includes smartphones and the displays of autonomous vehicles.

[1195] 2. Server: Performs data processing and generates and manages tourist plans.

[1196] 3. Generative AI Model: Generates optimal sightseeing plans based on user input information and sentiment data.

[1197] 4. Emotion Engine: Analyzes the user's real-time emotional data and dynamically adjusts the sightseeing plan based on that data.

[1198] System operation

[1199] User terminal operation

[1200] First, the user opens the application using the display inside the autonomous vehicle or on their smartphone and enters the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is acquired by the user's device and sent to the server. In addition, the user's voice and facial expressions are captured by the camera and microphone, and this emotion data is also sent to the server.

[1201] Server operation

[1202] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[1203] How generative AI models work

[1204] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants, calculating the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user is enjoying themselves, the time spent at the next spot will be extended; conversely, if the user is tired, the location will be changed to a more relaxing one.

[1205] Sending from server to user terminal

[1206] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1207] Displaying the plan on the user's device

[1208] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[1209] Specific example

[1210] 1. For example, a user gets into an autonomous vehicle and inputs information about tourist destinations and interests. Based on emotion data obtained from the camera and microphone, the system suggests the optimal sightseeing plan for the places the user wants to visit.

[1211] 2. The user enters "Tokyo Skytree" as the place they want to visit, "10,000 yen" as their budget, "8 hours" as the available time, and "history" as their interest. The system then suggests a sightseeing route that includes Tokyo Skytree, Senso-ji Temple, and Ueno Park. If the emotion engine determines that the user is enjoying the sightseeing, it adjusts the time spent at the next spot to increase.

[1212] Example of a prompt

[1213] Generate a sightseeing plan based on the user's entered travel information (Place to visit: Tokyo Skytree, Budget: 10,000 yen, Available time: 8 hours, Interests: History). Also, adjust the plan by taking into account the user's real-time sentiment data. For example, if the user is enjoying themselves, extend the time spent at the next spot; if they are tired, suggest a place to relax.

[1214] This allows the system to dynamically adjust sightseeing plans to reflect the user's real-time emotional state.

[1215] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1216] Step 1:

[1217] Users input tourist information using a display in the autonomous vehicle or their smartphone. This information includes places to visit, budget, available time, and areas of interest, and this data is acquired on the user's device.

[1218] Input: Visit location, budget, available time, areas of interest

[1219] Output: Tourism preference data

[1220] Step 2:

[1221] The user terminal captures the user's voice and facial expressions using a camera and microphone, acquiring this data in real time. This allows for the acquisition of user emotion data.

[1222] Input: Voice data, facial expression data

[1223] Output: User sentiment data

[1224] Step 3:

[1225] The user terminal sends tourism preference data and sentiment data to the server. The server checks the format of the received data and verifies its validity.

[1226] Input: Tourism preference data, sentiment data

[1227] Output: Formatted user data

[1228] Step 4:

[1229] The server passes the formatted user data to a generating AI model and requests it to create a travel plan. The generating AI model refers to a database of tourist spots and restaurants and calculates the optimal travel route and schedule.

[1230] Input: Formatted user data

[1231] Output: Initial sightseeing plan

[1232] Step 5:

[1233] The generative AI model adjusts the initial sightseeing plan based on emotion data retrieved from the server. If the user is enjoying themselves, it extends the length of their stay; if they are tired, it adds relaxing spots.

[1234] Input: Initial sightseeing plan, sentiment data

[1235] Output: Optimized sightseeing plan

[1236] Step 6:

[1237] The server converts the optimized sightseeing plan into an appropriate format, such as JSON, and sends it to the user's terminal.

[1238] Input: Optimized sightseeing plan

[1239] Output: Format-converted sightseeing plan

[1240] Step 7:

[1241] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can review the suggested plan and begin sightseeing accordingly. During sightseeing, emotion data is continuously collected via camera and microphone, and the plan is updated as needed.

[1242] Input: Formatted sightseeing plan

[1243] Output: Displayed sightseeing plan

[1244] 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.

[1245] 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.

[1246] 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.

[1247] [Fourth Embodiment]

[1248] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1249] 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.

[1250] 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).

[1251] 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.

[1252] 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.

[1253] 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).

[1254] 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.

[1255] 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.

[1256] 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.

[1257] 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.

[1258] 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.

[1259] 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.

[1260] 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".

[1261] This invention is a tourism support system for tourists visiting Japan. This system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and then transmits that plan to the user's terminal.

[1262] System Configuration

[1263] This system consists of the following main components:

[1264] 1. User Device

[1265] 2. Server

[1266] 3. Generative AI Model

[1267] System operation

[1268] User terminal operation

[1269] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is collected on the user's device and sent to the server.

[1270] Server operation

[1271] The server receives tourist information entered from the user's terminal. The received data is passed to a generating AI model, which then starts processing to create the optimal tourist plan. The server uses this tourist data to call the generating AI model and refer to a database of tourist spots and restaurants.

[1272] How generative AI models work

[1273] The AI ​​model uses user data received from the server to reference a database of tourist spots and restaurants. The AI ​​model calculates the optimal sightseeing route and selects places and facilities to visit. This generates an optimal sightseeing plan tailored to the user's preferences. This plan includes the order of visits, total cost, and estimated time required.

[1274] Sending from server to user terminal

[1275] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1276] Displaying the plan on the user's device

[1277] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[1278] Specific example

[1279] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server.

[1280] The server receives this information and requests the generating AI model to create the optimal sightseeing plan. The generating AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these locations, and sends the plan, including the optimal route, back to the server.

[1281] The server sends this plan to the user's terminal, and it is displayed on Mr. Tanaka's terminal. Mr. Tanaka can then enjoy sightseeing efficiently by following this plan.

[1282] The system according to the present invention helps tourists efficiently tour tourist destinations, reducing time loss and the stress of gathering information. Furthermore, by accumulating tourism data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[1283] The following describes the processing flow.

[1284] Step 1:

[1285] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. This entered data is collected within the app.

[1286] Step 2:

[1287] The terminal sends the data entered by the user to the server. During this process, the data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[1288] Step 3:

[1289] The server receives the data sent from the terminal, verifies the validity of the data format, and then passes it on to the generating AI model.

[1290] Step 4:

[1291] The server invokes a generating AI model, passing the user's travel information as input data. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[1292] Step 5:

[1293] The AI ​​model generates an optimal travel plan based on the user's criteria. For example, the plan may include a list of sightseeing spots to visit, the order in which to visit them, estimated time required, and total cost.

[1294] Step 6:

[1295] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[1296] Step 7:

[1297] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[1298] Step 8:

[1299] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can then review this information and begin sightseeing according to the suggested plan.

[1300] Through the steps described above, the system of the present invention can provide support for tourists visiting Japan to efficiently enjoy sightseeing.

[1301] (Example 1)

[1302] 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".

[1303] Conventional tourism support systems have struggled to efficiently process user-inputted tourism information and provide optimal travel plans. Furthermore, insufficient data formatting and validation during plan generation have resulted in a poor user experience.

[1304] 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.

[1305] In this invention, the server includes means for receiving tourist information entered by a user, means for validating and formatting the tourist information to pass it to a generating AI model, means for calling a generating AI model that generates an optimal tourist plan based on the tourist information, means for converting the generated tourist plan into an appropriate data format and transmitting it to a user terminal, and means for the user terminal to analyze the tourist plan received and display it on a user interface. This makes it possible to process the information entered by the user efficiently and accurately and provide an optimal tourist plan.

[1306] "Means for receiving user-entered tourist information" refers to functions or devices that allow a server to receive information such as places to visit, budget, available time, and areas of interest, which are entered by the user through their terminal.

[1307] "Methods for validating and formatting data to pass tourism information to a generating AI model" refers to functions or devices that check whether the format and values ​​of the tourism information entered by the user are appropriate, and convert them into a format that the generating AI model can understand.

[1308] "Means for calling a generative AI model that generates an optimal sightseeing plan" refers to a function or device that executes a generative AI model that generates an optimal sightseeing plan according to the user's conditions by referring to a database of tourist spots and restaurants based on the input sightseeing information.

[1309] "Means for converting generated sightseeing plans into an appropriate data format and transmitting them to the user terminal" refers to a function or device for converting sightseeing plans generated by a generation AI model into a data format that the user terminal can understand and transmitting it to the user terminal.

[1310] "Means for analyzing a sightseeing plan received by a user terminal and displaying it on the user interface" refers to a function or device that receives and analyzes sightseeing plan data transmitted from a server on a user terminal and visually displays its contents to the user.

[1311] Modes for carrying out the invention

[1312] This invention is a tourism support system for tourists visiting Japan, and consists of the following main components.

[1313] 1. User Device

[1314] 2. Server

[1315] 3. Generative AI Model

[1316] System operation

[1317] User terminal operation

[1318] The user first opens the application using a device such as a smartphone or tablet to access the system. On the application's user interface, they enter the tourist destination they wish to visit, their budget, available time, and areas of interest. For example, the following input might be made:

[1319] Places I want to visit: Tokyo Skytree

[1320] Budget: 10,000 yen

[1321] Available time: 8 hours

[1322] Interests: History

[1323] The terminal retrieves this input data, stores it temporarily, and then sends it to the server.

[1324] Server operation

[1325] The server receives tourist information sent from the user's terminal and performs data validation and formatting. Specifically, it checks the data format and fills in any missing information. Next, the server generates a prompt message to request the AI ​​model to generate a tourist plan. An example of a prompt message is as follows:

[1326] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[1327] The generated prompt text is sent to the AI ​​model, and the creation of the sightseeing plan begins.

[1328] How generative AI models work

[1329] The AI ​​model generates an optimal sightseeing plan based on user data received from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in an appropriate data format, such as JSON.

[1330] Sending from server to user terminal

[1331] The server receives the generated sightseeing plan and sends it to the user's terminal. The sightseeing plan is formatted as needed, converted back to JSON format, and sent again. For example, the following JSON data is sent:

[1332] json

[1333] {

[1334] "Plan": [

[1335] {

[1336] "Tourist attraction": "Tokyo Skytree",

[1337] "Estimated time": "2 hours"

[1338] "Cost": 3000

[1339] },

[1340] {

[1341] "Tourist destination": "Senso-ji Temple",

[1342] "Estimated time": "2 hours"

[1343] "Cost": 2000

[1344] },

[1345] {

[1346] "Tourist destination": "Ueno Park",

[1347] "Estimated time": "3 hours"

[1348] "Cost": 500

[1349] }

[1350] ],

[1351] "Total time": "7 hours"

[1352] Total cost: 5500

[1353] }

[1354] Displaying the plan on the user's device

[1355] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on this information, the user can proceed with their sightseeing efficiently and effectively.

[1356] This invention enables efficient and accurate processing of input tourism information and provides optimal tourism plans. Furthermore, by accumulating tourism data, even more accurate recommendations can be made when generating future tourism plans.

[1357] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1358] Processing steps

[1359] Step 1:

[1360] Users enter tourist information.

[1361] Users use their devices (such as smartphones or tablets) to open a dedicated application and enter tourist information (places they want to visit, budget, available time, areas of interest). For example, they might enter the following:

[1362] Places I want to visit: Tokyo Skytree

[1363] Budget: 10,000 yen

[1364] Available time: 8 hours

[1365] Interests: History

[1366] The entered data will be temporarily stored on the device.

[1367] Step 2:

[1368] The device sends tourist information to the server.

[1369] The terminal sends the tourist information entered by the user to the server. Specifically, it sends data to the server via an HTTP POST request using a REST API. The input data is sent in JSON format. For example, the following JSON data is sent:

[1370] json

[1371] {

[1372] "Tourist attraction": "Tokyo Skytree",

[1373] "Budget": 10000,

[1374] "time": 8,

[1375] "Interest": "History"

[1376] }

[1377] Step 3:

[1378] The server receives the data and performs validation and formatting.

[1379] The server receives tourist information sent from the terminal. After receiving the data, it validates (checks the format and values) and formats it. For example, it checks if the visited locations are appropriate and returns error messages if necessary. The formatted data is then ready to be passed to the generating AI model.

[1380] Step 4:

[1381] The server generates a prompt message and sends it to the AI ​​model.

[1382] The server generates prompts to request the AI ​​model to create a travel plan based on the formatted tourist information. An example of a prompt is as follows:

[1383] "Please create a one-day sightseeing plan for Tokyo. The destination is Tokyo Skytree, the budget is 10,000 yen, the available time is 8 hours, and the interest is history."

[1384] Send this prompt message to the AI ​​model that generates the data.

[1385] Step 5:

[1386] A generative AI model generates tourist plans.

[1387] The AI ​​model generates an optimal sightseeing plan based on prompts sent from the server, referencing a database of tourist attractions and restaurants. The generated plan includes the order of visits, estimated time, and total cost for each attraction. The generated sightseeing plan is returned to the server in JSON format. For example, the following JSON data is generated:

[1388] json

[1389] {

[1390] "Plan": [

[1391] {

[1392] "Tourist attraction": "Tokyo Skytree",

[1393] "Estimated time": "2 hours"

[1394] "Cost": 3000

[1395] },

[1396] {

[1397] "Tourist destination": "Senso-ji Temple",

[1398] "Estimated time": "2 hours"

[1399] "Cost": 2000

[1400] },

[1401] {

[1402] "Tourist destination": "Ueno Park",

[1403] "Estimated time": "3 hours"

[1404] "Cost": 500

[1405] }

[1406] ],

[1407] "Total time": "7 hours"

[1408] Total cost: 5500

[1409] }

[1410] Step 6:

[1411] The server sends the generated sightseeing plan to the user's terminal.

[1412] The server receives the travel plan returned from the generated AI model, converts it into an appropriate data format (such as JSON), and sends it to the user's terminal. In some cases, it may further format the data before sending it.

[1413] Step 7:

[1414] The user's terminal analyzes and displays the sightseeing plan.

[1415] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Based on the displayed plan, the user can proceed with their sightseeing efficiently and effectively. The displayed information includes the names of the tourist attractions, the estimated time required, the cost, and the order of visits.

[1416] (Application Example 1)

[1417] 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".

[1418] The current tourism support system focuses on providing information on tourist spots and restaurants, but it lacks detailed information such as the optimal order of visits, the time required, and the total cost of visiting physical establishments. This makes it difficult for tourists to enjoy sightseeing efficiently and effectively. Furthermore, there is no way to obtain and display detailed information about physical establishments in real time, so tourists tend to spend a lot of time making decisions on-site. This leads to problems such as wasted time and budget.

[1419] 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.

[1420] In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generative AI model that generates an optimal tourist plan based on the tourist information, means for transmitting the generated tourist plan to the user terminal, means for calculating the order of visits to physical stores, the time required, and the total cost for the tourist plan, and means for obtaining detailed information of the physical stores and displaying it on the user terminal. This allows the user to efficiently visit physical stores and enjoy sightseeing to the fullest while reducing wasted time and budget.

[1421] "Means for receiving user-entered tourist information" refers to a function that sends data such as tourist destination information, budget, available time, and areas of interest entered by the user using a terminal to a server.

[1422] The "means for calling the generative AI model" refer to a function that activates a generative AI model to calculate and generate the optimal sightseeing plan based on the sightseeing information provided by the user.

[1423] "Means for sending sightseeing plans to user terminals" refers to a function that converts the optimal sightseeing plan created by the generative AI model into an appropriate data format and transfers it to the user's terminal.

[1424] "A means of calculating the order of visits to physical stores, the time required, and the total cost for a sightseeing plan" refers to a function that identifies the physical stores that a user should visit within a sightseeing plan, and calculates the order of visits to those facilities, the time required to visit each facility, and the overall budget.

[1425] "Means for obtaining and displaying detailed information about physical stores on the user's device" refers to a function that obtains detailed information (address, business hours, menu, etc.) about each physical store that the user plans to visit in real time and displays it on the user's device.

[1426] This invention is a system that provides optimal sightseeing plans for tourists. Based on the sightseeing information entered by the user, it generates a sightseeing plan using an AI model and transmits that plan to the user's terminal. This invention also provides detailed information about the physical stores that the user plans to visit, aiming to improve the efficiency and satisfaction of sightseeing.

[1427] System Configuration

[1428] This system consists of the following main components:

[1429] 1. User-side device: A device (such as a smartphone or tablet) used by the user to input tourist information and send it to the server.

[1430] 2. Server: A central system that receives tourist information and generates optimal tourist plans using a generated AI model.

[1431] 3. Generative AI Model: A machine learning model for generating travel plans. It references a database of tourist spots and restaurants to calculate the most suitable travel route based on the user's criteria.

[1432] 4. Tourism Database: A database containing detailed information (address, opening hours, cost, etc.) about various tourist spots, restaurants, and physical stores.

[1433] System operation

[1434] User terminal operation

[1435] Users open the application using a smartphone or other device and enter travel information. This travel information includes places they want to visit, their budget, available time, and areas of interest. This data is collected on the user's device and sent to the server.

[1436] Server operation

[1437] The server receives tourist information sent from the user's terminal. Based on the received tourist information, it calls a generation AI model and starts the process of generating the optimal tourist plan. The server refers to a database of tourist spots, restaurants, and physical stores to calculate the optimal tourist plan based on the user's requests.

[1438] How generative AI models work

[1439] The generating AI model uses user data received from the server to reference databases of tourist spots, restaurants, and physical stores. The AI ​​model calculates the specified visit order, duration, total cost, etc. It also retrieves detailed information about physical stores (address, opening hours, cost, menu, etc.) and includes this in the sightseeing plan.

[1440] Sending from server to user terminal

[1441] The generated sightseeing plan is sent to the user's terminal by the server. The server converts the sightseeing plan into an appropriate data format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1442] Displaying the plan on the user's device

[1443] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. This allows users to proceed with their sightseeing efficiently and effectively, and to check detailed information about physical stores in real time.

[1444] Specific example

[1445] As a concrete example, consider the case of tourist A visiting tourist destination B. Tourist A uses a smartphone application to input "Tourist Destination B" as the place to visit, a budget of "15,000 yen," available time of "5 hours," and interests of "Dining and Shopping." Based on this, the user's device sends tourist information to the server. The server receives this information and uses a generating AI model to create a tourist plan consisting of "Restaurant X," "Cafe Y," and "Shopping Mall Z." This plan includes the order of visits for each location, the time required, the total cost, and detailed information about the actual establishments (address, opening hours, cost, menu, etc.). This tourist plan is sent to the user's device, allowing tourist A to enjoy sightseeing efficiently.

[1446] Example of a prompt

[1447] Example of tourist A entering tourist information:

[1448] Place to visit: Tourist spot B, Budget: 15,000 yen, Available time: 5 hours, Interests: Dining and shopping

[1449] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1450] Step 1: Enter tourist information using the user terminal.

[1451] Users use a smartphone application to input travel information such as the tourist destinations they want to visit, their budget, available time, and areas of interest. This becomes the input data, and the device sends this data to the server.

[1452] Step 2: Receiving tourist information from the server

[1453] The server receives tourist information sent from the user's terminal. Here, the tourist information is temporarily stored and prepared for later use in calling the generated AI model. The received data is converted into an internal data structure.

[1454] Step 3: Generating tourist plans using a generative AI model

[1455] The server calls a generating AI model based on the received user data. The generating AI model refers to a database of tourist spots and restaurants to calculate the optimal visiting order, duration, and total cost. It also retrieves detailed information about physical establishments and includes it in the sightseeing plan. The data generated at this stage is the sightseeing plan data.

[1456] Step 4: Converting the sightseeing plan data

[1457] The server converts the tourist plans obtained from the generated AI model into an appropriate data format such as JSON. This makes it easier for the user's device to receive.

[1458] Step 5: Sending data from the server to the user terminal

[1459] The server sends the converted tourist plan data to the user's terminal. The HTTP protocol or other appropriate communication methods are used for transmission.

[1460] Step 6: User terminal receives and displays the plan

[1461] The user terminal receives the sightseeing plan sent from the server. The received data is analyzed and displayed on the user interface. The user can then plan their sightseeing based on this information.

[1462] Specific actions for each step:

[1463] Step 1 Input: User-entered tourist information data (places to visit, budget, available time, areas of interest)

[1464] Output: Tourism information data sent to the server

[1465] Step 2 Input: Tourist information data sent from the user terminal.

[1466] Output: Tourism information data converted to an internal data structure.

[1467] Step 3 Input: Converted tourist information data

[1468] Output: Tourism plan data generated by the AI ​​model (order of visits, duration, total cost, detailed information)

[1469] Input for Step 4: Tourism plan data obtained from the generated AI model.

[1470] Output: Tourist plan data converted to a data format suitable for the user's terminal (e.g., JSON).

[1471] Step 5 Input: Converted tourist plan data

[1472] Output: Tourist plan data sent to the user terminal

[1473] Step 6 Input: Tourist plan data sent from the server

[1474] Output: Analyzed tourist plan data displayed in the user interface

[1475] 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.

[1476] This invention combines a tourism support system for inbound tourists with an emotion engine that recognizes user emotions, thereby providing each user with an optimal tourism plan and realizing a more satisfying tourism experience. The system receives tourism information entered by the user, automatically generates an optimal tourism plan using a generation AI model, and sends that plan to the user's terminal. Furthermore, by incorporating an emotion engine, it has the function of recognizing the user's emotions and adjusting the tourism plan in real time.

[1477] System Configuration

[1478] This system consists of the following components:

[1479] 1. User Device

[1480] 2. Server

[1481] 3. Generative AI Model

[1482] 4. Emotion Engine

[1483] System operation

[1484] User terminal operation

[1485] First, the user opens the application on a device such as a smartphone and enters the tourist destination they wish to visit, their budget, available time, and areas of interest. This input data is acquired on the user's device and sent to the server. In addition, the user's voice and facial expressions are captured using the camera and microphone, and this data is also sent to the emotion engine.

[1486] Server operation

[1487] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[1488] How generative AI models work

[1489] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user appears to be enjoying themselves, the plan might be adjusted to allow a little more time at the next spot; conversely, if the user appears tired, the next spot might be changed to a more relaxing location.

[1490] Sending from server to user terminal

[1491] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1492] Displaying the plan on the user's device

[1493] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[1494] Specific example

[1495] For example, let's say Mr. Tanaka visits Tokyo and plans a day of sightseeing. Mr. Tanaka opens the app and enters "Tokyo Skytree" as the place he wants to visit, "10,000 yen" as his budget, "8 hours" as the available time, and "history" as his interest. The user's device then sends this information to the server. In addition, Mr. Tanaka's voice and facial expressions are captured by the camera and microphone, and that data is also sent to the server.

[1496] The server receives this information and requests the generative AI model to create the optimal sightseeing plan. The generative AI model generates a sightseeing plan that includes, for example, "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park." Furthermore, it calculates the order of visits, the time required, and the total cost of these places, and sends the plan, including the optimal route, back to the server. At the same time, the emotion engine analyzes Mr. Tanaka's emotions and adjusts the sightseeing plan in real time.

[1497] The server sends this plan to the user's terminal, where it is displayed. Following this plan, Mr. Tanaka can efficiently enjoy sightseeing. Furthermore, based on the emotional data Mr. Tanaka displays during his sightseeing, the plan is adjusted as needed to optimize his sightseeing experience.

[1498] The system according to the present invention helps tourists efficiently tour tourist destinations and provides users with an optimal tourist experience by utilizing emotional data. Furthermore, by accumulating tourist data and emotional data, it becomes possible to make even more accurate recommendations when generating future tourist plans.

[1499] The following describes the processing flow.

[1500] Step 1:

[1501] The user opens the app on their smartphone and enters the tourist destinations they want to visit, their budget, available time, and areas of interest. Additionally, the smartphone's camera and microphone are used to capture emotional data such as voice and facial expressions. This input data and emotional data are collected within the app.

[1502] Step 2:

[1503] The device sends user-entered data and sentiment data to the server. The data is encoded in an appropriate format, such as JSON, and sent using an HTTP POST request.

[1504] Step 3:

[1505] The server receives data sent from the terminal. After verifying the validity of the received tourist information and sentiment data, it processes this data and passes it to the generative AI model and sentiment engine.

[1506] Step 4:

[1507] The server invokes the generative AI model, passing the user's travel information as input data. Furthermore, the emotion engine provides additional data to the generative AI model based on the user's perceived emotions. The generative AI model then refers to a database of tourist spots and restaurants to calculate the optimal travel route and schedule.

[1508] Step 5:

[1509] The generative AI model generates an optimal travel plan based on the user's conditions and emotional data. For example, the plan may include a list of sightseeing spots to visit, the order of visits, estimated time required, and total cost. Based on emotional data, adjustments are made, such as continuing as planned if the user is enjoying themselves, or adding relaxing spots if they are tired.

[1510] Step 6:

[1511] The AI ​​model generates an optimal sightseeing plan and sends it back to the server. The server receives this plan and converts the data format as needed.

[1512] Step 7:

[1513] The server sends the generated sightseeing plan to the user's terminal in an appropriate format such as JSON. It is returned to the terminal as an HTTP response.

[1514] Step 8:

[1515] The terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user reviews this information and begins sightseeing according to the suggested plan. In addition, emotional data during sightseeing is transmitted in real time, and the sightseeing plan may be adjusted accordingly. For example, if the user is highly satisfied at the current spot, adjustments may be made to shorten the travel time to the next spot or extend the time spent at that location.

[1516] Through the steps described above, the system of the present invention can not only provide support for tourists visiting Japan to efficiently enjoy sightseeing, but also provide an optimal experience in real time based on emotional data.

[1517] (Example 2)

[1518] 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".

[1519] Conventional tourism support systems provide travel plans based solely on information entered by the user, which has the problem of not adequately reflecting the individual user's preferences and physical condition. Therefore, in order to increase user satisfaction, it is necessary to recognize the user's emotions and physical condition in real time and provide a travel plan that is tailored to them.

[1520] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[1521] In this invention, the server includes means for receiving tourist information entered by the user, means for capturing the user's voice and facial expression data, means for transmitting the received tourist information and the captured voice and facial expression data to the server, means for the server to verify the integrity of the data transmitted from the user terminal, means for transmitting the verified data to a generating AI model, means for the generating AI model to calculate the optimal tourist route by referring to a database of tourist spots and restaurants, means for an emotion engine to analyze the user's emotional data and adjust the tourist plan in real time, means for transmitting the generated tourist plan to the user terminal, and means for the user terminal to display the received tourist plan. This makes it possible to provide a customized tourist plan that is tailored to the user's emotions and physical condition.

[1522] "Means for receiving user-entered tourism information" refers to a means for users to input tourism information such as places to visit, budget, available time, and areas of interest into a terminal and send that information to a server.

[1523] "Means for capturing user voice and facial expression data" refers to means of acquiring user voice and facial expression data using the camera and microphone on the user's terminal.

[1524] "Means for transmitting received tourist information and captured audio and facial expression data to the server" refers to a means of encrypting the tourist information and audio / facial expression data acquired by the terminal and securely transmitting it to the server.

[1525] "Means by which the server verifies the integrity of data sent from the user terminal" refers to the means by which the server verifies the format and content of the received data and confirms whether it is in the correct format.

[1526] "Means for sending data whose consistency has been verified to the generating AI model" refers to the means by which the server sends data whose consistency has been verified to the generating AI model.

[1527] "A method by which a generative AI model calculates the optimal sightseeing route by referring to a database of tourist spots and restaurants" refers to a method by which a generative AI model uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule based on the input sightseeing information.

[1528] "A means by which an emotion engine analyzes user emotional data and adjusts the sightseeing plan in real time" refers to a method in which an emotion engine analyzes the user's emotions from voice and facial expression data and adjusts the sightseeing plan in real time based on that analysis.

[1529] "Means for sending the generated sightseeing plan to the user terminal" refers to the means by which the server converts the sightseeing plan obtained from the generated AI model into an appropriate format and sends it to the user terminal.

[1530] "Means for displaying a sightseeing plan received by a user terminal" refers to means by which a user terminal analyzes a sightseeing plan received from a server and displays it to the user through a user interface.

[1531] This invention is a tourism support system for tourists visiting Japan. By combining it with an emotion engine that recognizes the user's emotions, it provides an optimal tourism plan for each individual user, thereby realizing a more satisfying tourism experience. The system is configured as follows:

[1532] 1. User Device

[1533] First, the user opens the application using a device such as a smartphone or tablet. The user then enters travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is saved on the user's device and then sent to the server. In addition, the user's voice and facial expression data are captured through the device's camera and microphone and also sent to the emotion engine.

[1534] 2. Server

[1535] The server receives tourist information and sentiment data sent from the user's terminal. It verifies the integrity of the received data and prepares it for transmission to the generative AI model. The server sends the verified data to the generative AI model, from which it calculates the optimal tourist route.

[1536] 3. Generative AI Model

[1537] The generative AI model calculates the optimal sightseeing route and schedule by referencing a database of tourist spots and restaurants based on the user's travel information and sentiment data received from the server. The plan is adjusted in this process, taking the user's sentiment data into consideration.

[1538] 4. Emotion Engine

[1539] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state in real time. This emotional data is provided to a generative AI model, which is used to adjust the sightseeing plan. For example, if the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxation spots are added.

[1540] Specific examples of operation

[1541] The scenario involves Ms. Tanaka visiting Tokyo for a day of sightseeing. Ms. Tanaka opens the app and enters "Tokyo Skytree" as the place she wants to visit, "10,000 yen" as her budget, "8 hours" as the available time, and "history" as her interest. This information is sent to the server, and at the same time, Ms. Tanaka's facial expressions and voice are captured using the device's camera and microphone.

[1542] The server receives this data, verifies its integrity, and then sends it to the generating AI model. The generating AI model creates a sightseeing plan that includes places like "Tokyo Skytree," "Senso-ji Temple," and "Ueno Park," and adjusts the plan based on the data from the emotion engine. The generated sightseeing plan is sent to Tanaka's smartphone via the server, and Tanaka enjoys sightseeing according to this plan.

[1543] Example of a prompt

[1544] "I'm planning a one-day sightseeing trip in Tokyo. My desired destination is Tokyo Skytree, my budget is 10,000 yen, I have 8 hours available, and my interest is history. Please suggest the best sightseeing plan. Also, please consider that the plan may be adjusted based on my emotional data during the trip."

[1545] This system makes it possible to provide customized sightseeing plans tailored to the user's emotional state, thereby increasing user satisfaction.

[1546] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1547] System program processing flow

[1548] Step 1:

[1549] Users open the application using a device such as a smartphone or tablet. They enter travel information such as the tourist destinations they wish to visit, their budget, available time, and areas of interest. This entered travel information is temporarily stored on the user's device.

[1550] Input: User-entered tourist information (places to visit, budget, available time, areas of interest)

[1551] Output: Tourist information temporarily stored on the user's terminal.

[1552] Step 2:

[1553] The user's device uses its camera and microphone to capture the user's voice and facial expression data. This data is then input into the emotion engine.

[1554] Input: User voice data, facial expression data

[1555] Output: Audio data and facial expression data captured by the device.

[1556] Step 3:

[1557] The user's terminal sends tourist information, voice, and facial expression data to the server. This data is encrypted and transmitted securely.

[1558] Input: Tourist information, audio data, facial expression data (data stored on the user's device)

[1559] Output: Tourist information, audio data, and facial expression data sent to the server.

[1560] Step 4:

[1561] The server receives data sent from the user's terminal and verifies its integrity. If the data is invalid, it returns an error message.

[1562] Input: Tourist information, audio data, and facial expression data sent from the user's terminal.

[1563] Output: Data whose integrity has been verified, error message (if invalid)

[1564] Step 5:

[1565] The server sends the verified data to the generating AI model. The generating AI model then uses a database of tourist spots and restaurants to calculate the optimal sightseeing route and schedule.

[1566] Input: Authenticated tourist information and sentiment data.

[1567] Output: Data sent to the generating AI model, generated tourist plan

[1568] Step 6:

[1569] The emotion engine analyzes the user's voice and facial expression data to estimate the user's emotional state. This emotional data is provided to a generative AI model and used to adjust the sightseeing plan.

[1570] Input: User voice data, facial expression data

[1571] Output: Estimated user emotional state, emotional data

[1572] Step 7:

[1573] The generative AI model adjusts the sightseeing plan in real time based on emotional data obtained from the emotion engine. If the user is enjoying themselves, the length of their stay is extended; conversely, if they are tired, relaxing spots are added.

[1574] Input: Initial tourist plan generated by a generative AI model, emotional data from an emotional engine.

[1575] Output: Customized sightseeing plan

[1576] Step 8:

[1577] The generated sightseeing plan is sent back to the server, which converts this data into an appropriate format such as JSON.

[1578] Input: Generated sightseeing plan

[1579] Output: Tourist plan converted to JSON format

[1580] Step 9:

[1581] The server sends the generated sightseeing plan to the user's terminal. The user's terminal receives this plan and displays it through the user interface. The user's terminal continues to capture the user's voice and facial expression data during sightseeing, and the plan is adjusted in real time.

[1582] Input: Tourist plan in JSON format

[1583] Output: Tourist plan displayed on the user's terminal

[1584] Step 10:

[1585] Users proceed with their sightseeing according to the displayed tour plan. If sentiment data is updated during the tour, the system adjusts the plan in real time and notifies the user.

[1586] Input: Sentiment data updated in real time

[1587] Output: Notification of updated adjusted sightseeing plan

[1588] These steps enable the system to provide the optimal sightseeing plan based on the user's input information and emotional state, thereby increasing user satisfaction.

[1589] (Application Example 2)

[1590] 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".

[1591] Conventional tourism support systems generate optimal sightseeing plans based solely on pre-entered information from users. However, this approach fails to reflect the user's real-time emotional state, making it difficult to address fatigue or disappointment experienced during sightseeing in real time. This can potentially degrade the quality of the user's sightseeing experience. To solve this problem, a system is needed that utilizes real-time emotional data from users to dynamically adjust sightseeing plans.

[1592] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving tourist information entered by the user, means for calling a generation AI model that generates an optimal tourist plan based on the tourist information and user emotion data acquired in real time, means for transmitting the generated tourist plan to the user terminal, and an emotion engine that analyzes the user emotion data and adjusts the tourist plan. This makes it possible to dynamically adjust the tourist plan to reflect the user's real-time emotional state.

[1593] "User-entered tourism information" refers to information entered by users regarding their own tourism preferences and conditions, specifically including places to visit, budget, available time, and areas of interest.

[1594] "Real-time user emotion data" refers to emotional data acquired in real time from the user's facial expressions, voice tone, and other factors.

[1595] An "optimal sightseeing plan" is a plan designed to provide an efficient and highly satisfying sightseeing experience, based on user input information and emotional data.

[1596] A "generative AI model" is an artificial intelligence model that automatically generates sightseeing plans based on input data, and has the function of calculating the optimal route by referring to a database of tourist spots and restaurants.

[1597] A "user terminal" refers to a device used by a user, and includes smartphones, in-vehicle displays, and other similar devices.

[1598] The "emotion engine" is an engine that analyzes users' real-time emotional data and adjusts sightseeing plans based on that data.

[1599] A "database of tourist spots and restaurants" is a database containing information about tourist destinations and restaurants, which is referenced by the generating AI model to calculate the optimal tourist route.

[1600] To deliver an "exceptional and authentic travel experience," this system enables dynamic plan adjustments and optimizations that reflect user emotions in real time.

[1601] This invention relates to a tourism support system that operates within an autonomous vehicle. This system improves the quality of the tourism experience by generating and dynamically adjusting an optimal tourism plan based on tourism information entered by the user and user emotion data acquired in real time.

[1602] System components

[1603] This system consists of the following components:

[1604] 1. User Device: This includes smartphones and the displays of autonomous vehicles.

[1605] 2. Server: Performs data processing and generates and manages tourist plans.

[1606] 3. Generative AI Model: Generates optimal sightseeing plans based on user input information and sentiment data.

[1607] 4. Emotion Engine: Analyzes the user's real-time emotional data and dynamically adjusts the sightseeing plan based on that data.

[1608] System operation

[1609] User terminal operation

[1610] First, the user opens the application using the display inside the autonomous vehicle or on their smartphone and enters the tourist destinations they wish to visit, their budget, available time, and areas of interest. This input data is acquired by the user's device and sent to the server. In addition, the user's voice and facial expressions are captured by the camera and microphone, and this emotion data is also sent to the server.

[1611] Server operation

[1612] The server receives data sent from the user's terminal, verifies the validity of the data format, and then passes it on to the generating AI model. In addition, the user's emotional data perceived by the emotion engine is also provided to the generating AI model.

[1613] How generative AI models work

[1614] The generative AI model uses user data received from the server to reference a database of tourist spots and restaurants, calculating the optimal sightseeing route and schedule. Furthermore, it adjusts the plan by taking into account user emotion data provided by the emotion engine. For example, if the user is enjoying themselves, the time spent at the next spot will be extended; conversely, if the user is tired, the location will be changed to a more relaxing one.

[1615] Sending from server to user terminal

[1616] The generated sightseeing plan is sent to the user's terminal by the server. The server converts this plan into an appropriate format, such as JSON, and sends it to the user's terminal. This information is received and displayed on the user's terminal.

[1617] Displaying the plan on the user's device

[1618] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. Furthermore, the plan may be updated in real time based on the user's sentiment data, and this information is immediately communicated to the user. The user can then review this information and begin sightseeing according to the suggested plan.

[1619] Specific example

[1620] 1. For example, a user gets into an autonomous vehicle and inputs information about tourist destinations and interests. Based on emotion data obtained from the camera and microphone, the system suggests the optimal sightseeing plan for the places the user wants to visit.

[1621] 2. The user enters "Tokyo Skytree" as the place they want to visit, "10,000 yen" as their budget, "8 hours" as the available time, and "history" as their interest. The system then suggests a sightseeing route that includes Tokyo Skytree, Senso-ji Temple, and Ueno Park. If the emotion engine determines that the user is enjoying the sightseeing, it adjusts the time spent at the next spot to increase.

[1622] Example of a prompt

[1623] Generate a sightseeing plan based on the user's entered travel information (Place to visit: Tokyo Skytree, Budget: 10,000 yen, Available time: 8 hours, Interests: History). Also, adjust the plan by taking into account the user's real-time sentiment data. For example, if the user is enjoying themselves, extend the time spent at the next spot; if they are tired, suggest a place to relax.

[1624] This allows the system to dynamically adjust sightseeing plans to reflect the user's real-time emotional state.

[1625] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1626] Step 1:

[1627] Users input tourist information using a display in the autonomous vehicle or their smartphone. This information includes places to visit, budget, available time, and areas of interest, and this data is acquired on the user's device.

[1628] Input: Visit location, budget, available time, areas of interest

[1629] Output: Tourism preference data

[1630] Step 2:

[1631] The user terminal captures the user's voice and facial expressions using a camera and microphone, acquiring this data in real time. This allows for the acquisition of user emotion data.

[1632] Input: Voice data, facial expression data

[1633] Output: User sentiment data

[1634] Step 3:

[1635] The user terminal sends tourism preference data and sentiment data to the server. The server checks the format of the received data and verifies its validity.

[1636] Input: Tourism preference data, sentiment data

[1637] Output: Formatted user data

[1638] Step 4:

[1639] The server passes the formatted user data to a generating AI model and requests it to create a travel plan. The generating AI model refers to a database of tourist spots and restaurants and calculates the optimal travel route and schedule.

[1640] Input: Formatted user data

[1641] Output: Initial sightseeing plan

[1642] Step 5:

[1643] The generative AI model adjusts the initial sightseeing plan based on emotion data retrieved from the server. If the user is enjoying themselves, it extends the length of their stay; if they are tired, it adds relaxing spots.

[1644] Input: Initial sightseeing plan, sentiment data

[1645] Output: Optimized sightseeing plan

[1646] Step 6:

[1647] The server converts the optimized sightseeing plan into an appropriate format, such as JSON, and sends it to the user's terminal.

[1648] Input: Optimized sightseeing plan

[1649] Output: Format-converted sightseeing plan

[1650] Step 7:

[1651] The user terminal analyzes the sightseeing plan received from the server and displays it on the user interface. The user can review the suggested plan and begin sightseeing accordingly. During sightseeing, emotion data is continuously collected via camera and microphone, and the plan is updated as needed.

[1652] Input: Formatted sightseeing plan

[1653] Output: Displayed sightseeing plan

[1654] 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.

[1655] 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.

[1656] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1657] 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.

[1658] 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.

[1659] 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.

[1660] 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.

[1661] 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.

[1662] 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."

[1663] 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.

[1664] 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.

[1665] 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.

[1666] 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.

[1667] 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.

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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.

[1675] The following is further disclosed regarding the embodiments described above.

[1676] (Claim 1)

[1677] A means of receiving tourist information entered by the user,

[1678] Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information,

[1679] Means for transmitting the generated sightseeing plan to the user terminal,

[1680] A system that includes this.

[1681] (Claim 2)

[1682] The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

[1683] (Claim 3)

[1684] The system according to claim 1, wherein the generating AI model has means for calculating an optimal tourist route by referring to a database of tourist spots and restaurants.

[1685] "Example 1"

[1686] (Claim 1)

[1687] A means of receiving tourist information entered by the user,

[1688] A means for validating and formatting the aforementioned tourism information in order to pass it to the AI ​​model for generating it,

[1689] Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information,

[1690] A means for converting the generated sightseeing plan into an appropriate data format and transmitting it to the user terminal,

[1691] The means for analyzing the sightseeing plan received by the user terminal and displaying it on the user interface,

[1692] A system that includes this.

[1693] (Claim 2)

[1694] The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

[1695] (Claim 3)

[1696] The system according to claim 1, wherein the generating AI model has means for calculating an optimal tourist route by referring to a database of tourist spots and restaurants.

[1697] "Application Example 1"

[1698] (Claim 1)

[1699] A means of receiving tourist information entered by the user,

[1700] Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information,

[1701] Means for transmitting the generated sightseeing plan to the user terminal,

[1702] A means for calculating the order of visits to physical stores, the time required, and the total cost for the aforementioned sightseeing plan,

[1703] A means for obtaining detailed information about the aforementioned physical store and displaying it on the user terminal,

[1704] A system that includes this.

[1705] (Claim 2)

[1706] The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

[1707] (Claim 3)

[1708] The system according to claim 1, wherein the generating AI model has means for calculating an optimal tourist route by referring to a database of tourist spots and restaurants.

[1709] "Example 2 of combining an emotion engine"

[1710] (Claim 1)

[1711] A means of receiving tourist information entered by the user,

[1712] A means for capturing user voice and facial expression data,

[1713] A means for transmitting received tourist information and captured audio and facial expression data to a server,

[1714] A means for the server to verify the integrity of data sent from the user terminal,

[1715] A means of sending data whose consistency has been verified to a generating AI model,

[1716] A method for generating AI models to calculate the optimal tourist route by referring to a database of tourist spots and restaurants,

[1717] The emotion engine analyzes user emotion data and adjusts the travel plan in real time,

[1718] A means for sending the generated sightseeing plan to the user's terminal,

[1719] A means for displaying the tourist plan received by the user terminal,

[1720] A system that includes this.

[1721] (Claim 2)

[1722] The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

[1723] (Claim 3)

[1724] The system according to claim 1, wherein the generating AI model has means for adjusting the sightseeing plan while taking into account the user's emotional data.

[1725] "Application example 2 when combining with an emotional engine"

[1726] (Claim 1)

[1727] A means of receiving tourist information entered by the user,

[1728] Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information and user sentiment data acquired in real time,

[1729] Means for transmitting the generated sightseeing plan to the user terminal,

[1730] A means including an emotion engine that analyzes user emotion data and adjusts the travel plan,

[1731] A system that includes this.

[1732] (Claim 2)

[1733] The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

[1734] (Claim 3)

[1735] The system according to claim 1, wherein the generating AI model has means for calculating an optimal tourist route by referring to a database of tourist spots and restaurants, and for adjusting the tourist plan in real time based on the data of the emotion engine. [Explanation of Symbols]

[1736] 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 tourist information entered by the user, Means for calling a generative AI model that generates an optimal sightseeing plan based on the aforementioned sightseeing information, Means for transmitting the generated sightseeing plan to the user terminal, A system that includes this.

2. The system according to claim 1, wherein the tourist information includes places to visit, budget, available time, and areas of interest to the user.

3. The system according to claim 1, wherein the generating AI model has means for calculating an optimal tourist route by referring to a database of tourist spots and restaurants.

Images