system

Abstract

We provide the system. [Solution] A means for receiving user input data, A means for sending a request to a generative artificial intelligence based on the user's input data, A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data 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 character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, when planning a trip or going out, users are required to make an appropriate plan based on information such as their preferences, budget, destination, etc. However, many users are not good at effectively combining these pieces of information and creating an optimal going-out plan in a short time. Also, in existing systems, there are many uniform plan proposals, and it is difficult to fully meet the individual needs of users. Therefore, there is a need for a system that automatically proposes an optimal plan based on the individual preferences and conditions of users.

Means for Solving the Problems

[0005] The present invention provides a system that receives user input data, sends a request to a generative artificial intelligence based on that data, receives a response from the generative artificial intelligence, and sends the response data to the user's terminal. Specifically, the system includes means for the user to input preferences, budget, and location; means for generating a request to the generative artificial intelligence based on that input data; means for receiving a response from the generative artificial intelligence; and means for displaying the response data to the user. This allows the user to easily obtain an optimal outing plan tailored to their individual needs.

[0006] "User input data" refers to information such as preferences, budget, and places to visit that users provide to create travel or outing plans.

[0007] "Generative artificial intelligence" refers to an artificial intelligence system that uses natural language processing technology to automatically generate text and suggestions based on user input.

[0008] A "request" refers to instructions or inquiries sent to a generative artificial intelligence system based on user input data.

[0009] "Response data" refers to the text data of information and suggestions returned by generative artificial intelligence.

[0010] A "user terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0011] A "prompt" is a set of instructions given to a generative artificial intelligence system to generate a response based on specific input data. [Brief explanation of the drawing]

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

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

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

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

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

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

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

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

[0020] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0033] This invention provides a system that automatically suggests an optimal outing plan based on the user's individual preferences and conditions. This system has the function of receiving user input data, sending a request to a generative artificial intelligence based on that data, receiving a response from the generative artificial intelligence, and providing the response data to the user's terminal.

[0034] System Overview

[0035] This system generates an optimal outing plan based on user input regarding preferences, budget, and location. A specific implementation is described below.

[0036] User input

[0037] First, the user accesses the web interface using their device (smartphone or PC). Then, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0038] Server-side processing

[0039] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[0040] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[0041] Responses and processing of generative artificial intelligence

[0042] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0043] Display on the user's terminal

[0044] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[0045] Specific examples

[0046] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," a generative AI might generate a plan like the following:

[0047] Outing plans:

[0048] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0049] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0050] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0051] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0052] budget:

[0053] Transportation expenses: 3000 yen

[0054] Food and drinks: 3000 yen

[0055] Admission fee and other charges: 3000 yen

[0056] Other contingency funds: 1000 yen

[0057] It can be confirmed that such detailed outing plans are provided to perfectly match the user's budget and preferences.

[0058] The above is one embodiment of the present invention. This system allows users to easily obtain a travel plan that is best suited to them, significantly reducing the time and effort required when planning a trip.

[0059] The following describes the processing flow.

[0060] Step 1:

[0061] The user accesses their device and enters information about their preferences, budget, and location via a web interface.

[0062] Step 2:

[0063] The terminal converts the entered information into JSON format and sends it to the server as an HTTP POST request.

[0064] Step 3:

[0065] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes information about the user's preferences, budget, and location.

[0066] Step 4:

[0067] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the system to generate the optimal outing plan based on the information entered by the user.

[0068] Step 5:

[0069] The server sends a request to the generative artificial intelligence API.

[0070] Step 6:

[0071] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[0072] Step 7:

[0073] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[0074] Step 8:

[0075] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[0076] Step 9:

[0077] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[0078] (Example 1)

[0079] 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."

[0080] Traditional travel planning systems lacked the ability to automatically suggest optimal travel plans based on individual user preferences and conditions. This meant users had to gather information and plan their trips themselves, which was time-consuming and cumbersome.

[0081] 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.

[0082] In this invention, the server includes means for converting user input data into JSON format and sending it to the server; means for the server to generate a prompt message for a generative artificial intelligence based on the user input data and send a request; and means for receiving a response from the generative artificial intelligence, converting the response data into JSON format, and sending it to the user terminal. This makes it possible for the user to easily obtain the optimal travel plan that suits their preferences and conditions.

[0083] "User input data" refers to information about user preferences, budget, and destinations entered by the user through their device.

[0084] "JSON format" is an abbreviation for JavaScript® Object Notation, and is a standard format for organizing and exchanging data in text format.

[0085] A "server" is a computer system that receives requests sent from a user's terminal, sends prompt messages to a generative artificial intelligence system, and returns the response to the user's terminal.

[0086] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal travel plan based on given data.

[0087] A "prompt statement" is a document containing questions or instructions used when making a specific request to a generative artificial intelligence system.

[0088] An "HTTP POST request" is one of the HTTP methods used to send data from a client to a server.

[0089] A "user terminal" refers to a device such as a computer or smartphone that is operated by the user.

[0090] "Response data" refers to travel plan information generated by generative artificial intelligence, and is data sent from the server to the user's terminal.

[0091] A "user interface" refers to the screen display and operating methods that allow a user to input information or confirm received data through a device.

[0092] This invention is a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. A specific embodiment of this system is described below.

[0093] System Overview

[0094] This system allows users to input information about their preferences, budget, and location using their own devices (smartphones or PCs). Based on this information, a generative artificial intelligence system generates and provides the user with an optimal outing plan.

[0095] User input

[0096] First, the user accesses the web interface using their device. There, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0097] Server-side processing

[0098] The server receives an HTTP POST request sent from the terminal. The request contains user preferences, budget, and location information in JSON format. The server parses this JSON data and extracts the necessary information. Based on this information, it generates a request for the generative artificial intelligence.

[0099] The request content creates a prompt message based on the user's input information and includes that information. For example, it generates a prompt message like the following:

[0100] Please generate the optimal outing plan based on the user's input information. The information required is as follows:

[0101] Preferences: I like nature.

[0102] Hobbies: Hiking

[0103] Budget: 10,000 yen

[0104] Location: Hakone

[0105] The server sends this prompt message to the generative artificial intelligence API.

[0106] Responses and processing of generative artificial intelligence

[0107] Generative artificial intelligence generates the optimal outing plan based on requests received from the server. This generated plan is in text format and is returned to the server. For example, the following plan may be generated:

[0108] Outing plans:

[0109] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0110] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0111] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0112] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0113] budget:

[0114] Transportation expenses: 3000 yen

[0115] Food and drinks: 3000 yen

[0116] Admission fee and other charges: 3000 yen

[0117] Other contingency funds: 1000 yen

[0118] The server converts this response back into JSON format and sends it to the user's terminal as an HTTP response.

[0119] Display on the user's terminal

[0120] The user terminal receives JSON data sent back from the server, parses the data, and displays it on the user interface. The user can then review this displayed outing plan and create a detailed travel plan.

[0121] The system of this invention allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip.

[0122] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0123] Step 1:

[0124] The user accesses the web interface using their device and enters information about their preferences, budget, and location into a form. Specifically, they might enter information such as "I like nature," "Hiking is my hobby," "My budget is 10,000 yen," and "Hakone." This entered data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[0125] Input: User preferences, budget, and location information

[0126] Output: Data in JSON format

[0127] Step 2:

[0128] The server receives an HTTP POST request sent from the user's terminal. The request contains the user's input data in JSON format. The server parses this JSON data and extracts information about the user's preferences, budget, and location.

[0129] Input: User input data in JSON format

[0130] Output: Information about user preferences, budget, and location.

[0131] Step 3:

[0132] The server generates prompt messages for the generative artificial intelligence based on the extracted data. Specifically, it creates prompt messages like the following: "Please generate the optimal outing plan based on the user's input information. The information is as follows: - Preferences: Likes nature - Hobbies: Hiking - Budget: 10,000 yen - Location: Hakone."

[0133] Input: User preferences, budget, and location information

[0134] Output: Prompt message

[0135] Step 4:

[0136] The server sends the generated prompt message to the generative artificial intelligence API. The prompt message is sent as a specific HTTP request using the POST method, instructing the AI ​​model to generate the optimal plan.

[0137] Input: Prompt message

[0138] Output: HTTP request

[0139] Step 5:

[0140] The generative artificial intelligence generates the optimal outing plan based on prompt messages sent from the server. The generated plan is returned to the server in text format.

[0141] Input: HTTP request (prompt text)

[0142] Output: Text-formatted response

[0143] Step 6:

[0144] The server receives the text-based response from the generative artificial intelligence and converts it back into JSON format. For example, it converts the response text: "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway. 2. After hiking, relax in a hot spring..." into JSON format.

[0145] Input: Text-formatted response

[0146] Output: Data in JSON format

[0147] Step 7:

[0148] The server sends the converted JSON data to the user's terminal as an HTTP response.

[0149] Input: Data in JSON format

[0150] Output: HTTP response

[0151] Step 8:

[0152] The user terminal receives JSON data sent from the server, parses that data, and displays it on the user interface. Specifically, it parses the JSON data to display the outing plan in an easy-to-understand visual format.

[0153] Input: HTTP response (JSON data)

[0154] Output: Outing plan displayed in the user interface

[0155] (Application Example 1)

[0156] 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."

[0157] To address the problem of users having difficulty easily finding the optimal plan based on their preferences and circumstances, there is a need for a system that automatically analyzes this information and suggests appropriate outing plans. Furthermore, a method for effectively utilizing generative artificial intelligence is required to make this possible.

[0158] 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.

[0159] In this invention, the server includes means for receiving user input data, means for sending a request to a generative artificial intelligence based on the user input data, means for receiving a response from the generative artificial intelligence and sending the response data to the user terminal, means for generating a prompt containing information about a content generation service based on the user input data, and means for generating and displaying an outing plan based on the prompt. This makes it possible to automatically generate and provide the user with an optimal outing plan based on the user's preferences and conditions.

[0160] "User input data" refers to information that users provide to the system, such as their individual preferences, budget, and location.

[0161] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal plan based on user input data, and produces responses to specific tasks.

[0162] "Means of sending requests" refers to the part of the system that uses user input data to send requests to a generative artificial intelligence.

[0163] "Means for transmitting response data to the user terminal" refers to the part of the system that has the function of transmitting response data obtained from generative artificial intelligence to the user's device.

[0164] A "content generation service" refers to an online service that automatically generates travel plans and other information based on user input data.

[0165] A "prompt" refers to text data containing detailed instructions about the user's preferences and conditions, used when sending a request to a generative artificial intelligence system.

[0166] An "outing plan" refers to a specific travel or event schedule or suggestion tailored to the user's preferences and requirements.

[0167] This invention provides a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. The system is configured as follows:

[0168] System Overview

[0169] The system has the function of receiving user input data, sending requests to a generative artificial intelligence system based on that data, and providing the response to the user's terminal. Specifically, it generates an optimal plan using information about the user's preferences, budget, and location.

[0170] User input

[0171] Users access the interface using their own devices (smartphones or computers). Users enter their preferences (e.g., they like nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0172] Server-side processing

[0173] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[0174] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[0175] Responses and processing of generative artificial intelligence

[0176] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0177] Display on the user's terminal

[0178] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[0179] Hardware and software to be used

[0180] Hardware: Smartphones, personal computers

[0181] software:

[0182] Python: Main logic of the program

[0183] requests: A library for sending API requests.

[0184] JSON: Data Format

[0185] Specific examples

[0186] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," the generative artificial intelligence will generate a plan like the following.

[0187] Outing plans

[0188] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0189] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0190] 3. In the afternoon, visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0191] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0192] Examples of prompts for generative AI models

[0193] "I love nature, hiking is my hobby, my budget is 10,000 yen, and the location is Hakone."

[0194] This allows users to easily find outing plans that suit their preferences and circumstances.

[0195] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0196] Step 1:

[0197] Users access the interface using their own devices (smartphones or computers) and display the data entry screen.

[0198] Input: User preferences (e.g., likes nature), budget (e.g., 10,000 yen), destination (e.g., Hakone)

[0199] Output: Input data in JSON format

[0200] Specific operation: When the user enters information into each form field and presses the "Submit" button, the device converts the entered data into JSON format and sends it to the server as an HTTP POST request.

[0201] Step 2:

[0202] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body.

[0203] Input: HTTP POST request

[0204] Output: User input data in JSON format

[0205] Specific operation: The server reads JSON data from the request body, which includes information about the user's preferences, budget, and location.

[0206] Step 3:

[0207] The server generates requests for the generative artificial intelligence based on the user's input data.

[0208] Input: User input data in JSON format

[0209] Output: Request (prompt) for generative artificial intelligence

[0210] Specific operation: The server extracts user input data and generates a prompt message based on it. This prompt message includes information about the user's preferences, budget, and location.

[0211] Step 4:

[0212] The server sends a request to the generative artificial intelligence API based on the generated prompt message.

[0213] Input: Request (prompt) for generative artificial intelligence

[0214] Output: Response data from generative artificial intelligence

[0215] Specific operation: The server issues an HTTP POST request to the generative artificial intelligence API endpoint and sends a prompt message.

[0216] Step 5:

[0217] The generative artificial intelligence generates the optimal outing plan based on the request received from the server and responds to the server.

[0218] Input: Request (prompt) for generative artificial intelligence

[0219] Output: Optimal outing plan (text format)

[0220] Specific operation: The generative artificial intelligence analyzes the prompt text, generates the most suitable outing plan based on the user's conditions, and sends it back to the server.

[0221] Step 6:

[0222] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[0223] Input: Response data from a generative artificial intelligence (text format)

[0224] Output: Response data in JSON format

[0225] Specific operation: The server receives the response data sent back from the generative artificial intelligence and converts it into JSON format.

[0226] Step 7:

[0227] The server sends the converted JSON-formatted response data to the user's terminal.

[0228] Input: Response data in JSON format

[0229] Output: Sent to the user's terminal as an HTTP response

[0230] Specific operation: The server uses the converted JSON data to generate an HTTP response and sends that response to the user's terminal.

[0231] Step 8:

[0232] The user terminal parses the JSON data received from the server and displays it on the user interface.

[0233] Input: Response data in JSON format

[0234] Output: Optimal outing plan displayed in the user interface

[0235] Specific operation: The user's terminal parses the received JSON data and displays it in the user interface in the appropriate format. This allows the user to see the outing plan that best suits their preferences and conditions.

[0236] Through the processing steps described above, users can easily obtain the outing plan that best suits their preferences and circumstances.

[0237] 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.

[0238] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user's terminal.

[0239] System Overview

[0240] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[0241] User input

[0242] First, the user accesses a web interface using their device (smartphone or PC). They then enter their preferences (e.g., love nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine to collect the user's emotional data (e.g., tone of voice and facial expressions). This data is converted into JSON format by the device and sent to the server as an HTTP POST request.

[0243] Server-side processing

[0244] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Subsequently, a generative artificial intelligence generates a request based on this information.

[0245] The request instructs the system to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the generative artificial intelligence API.

[0246] Responses and processing of generative artificial intelligence

[0247] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0248] Display on the user's terminal

[0249] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[0250] Specific examples

[0251] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[0252] Outing plans:

[0253] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[0254] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0255] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[0256] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0257] budget:

[0258] Transportation expenses: 3000 yen

[0259] Food and drinks: 3000 yen

[0260] Admission fee and other charges: 3000 yen

[0261] Other contingency funds: 1000 yen

[0262] It can be seen that such detailed outing plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data.

[0263] The above is one embodiment of the present invention. This system allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip. Furthermore, by combining it with an emotion engine, plans that take the user's emotions into consideration can be provided, enabling the generation of even more satisfying plans.

[0264] The following describes the processing flow.

[0265] Step 1:

[0266] Users access their devices and enter their preferences, budget, and location information via a web interface.

[0267] Step 2:

[0268] The device uses an emotion engine to collect emotional data from the user's voice and facial expressions. For example, it uses the device's microphone and camera to analyze what emotions the user is expressing when inputting data.

[0269] Step 3:

[0270] The terminal converts the entered information and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[0271] Step 4:

[0272] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes user preferences, budget, location information, and sentiment data.

[0273] Step 5:

[0274] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the AI ​​to generate the optimal outing plan based on the user's input information and emotional data.

[0275] Step 6:

[0276] The server sends a request to the generative artificial intelligence API.

[0277] Step 7:

[0278] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[0279] Step 8:

[0280] The server receives the response data sent from the generative artificial intelligence, converts it into JSON format, and prepares to send it to the terminal.

[0281] Step 9:

[0282] The terminal receives the JSON data sent from the server, analyzes the data, and displays it on the user interface.

[0283] Step 10:

[0284] The user checks the going-out plan displayed on the terminal and makes a specific travel plan based on its content.

[0285] (Example 2)

[0286] 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".

[0287] In the conventional travel plan creation system, it was possible to provide a plan based on basic information such as the user's preferences, budget, and location, but it was difficult to create a plan considering the user's emotional state. Therefore, there is a need to automatically generate a highly satisfactory plan that takes into account the user's emotions. In addition, there is a need for a system that efficiently processes multiple pieces of information input by the user and sends an appropriate request to the generative artificial intelligence.

[0288] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0289] In this invention, the server includes means for receiving user input data, means for collecting user emotion data, means for sending requests to a generative artificial intelligence based on the user input data and emotion data, and means for receiving responses from the generative artificial intelligence and sending response data to the user terminal. This makes it possible to automatically generate an optimal travel plan that takes into account the user's preferences, budget, location, and emotion data.

[0290] "User input data" refers to data such as preferences, budget, and destinations that users provide as information necessary for generating travel plans.

[0291] "Emotional data" refers to data that indicates a user's emotional state, and is collected from sources such as voice and facial expressions.

[0292] "Generative artificial intelligence" refers to an artificial intelligence system that automatically generates optimal travel plans based on user input data and emotional data.

[0293] The "means of sending requests" refer to a mechanism for instructing a generative artificial intelligence to generate the optimal plan based on user input data and emotional data.

[0294] "Response data" refers to data about travel plans provided by generative artificial intelligence, which is transmitted to the user's terminal via a server.

[0295] A "user terminal" is an electronic device used by a user to access the system and view travel plans.

[0296] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system receives user input data and emotion data, sends a request to a generative artificial intelligence system based on this data, and provides the generated plan to the user's terminal. A specific embodiment of this system is described below.

[0297] System Overview

[0298] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[0299] User input

[0300] First, the user accesses a web interface using their device (smartphone or PC). Here, the user enters their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine (e.g., general emotion recognition software) to collect the user's emotional data (e.g., tone of voice and facial expressions). This collected data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0301] Server-side processing

[0302] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Based on this information, the server generates a request to the generative artificial intelligence. This request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server then sends this request to the generative artificial intelligence's API.

[0303] Responses and processing of generative artificial intelligence

[0304] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is sent back to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0305] Display on User Terminal

[0306] The user terminal receives the JSON data sent back from the server, analyzes the data, and displays it on the user interface. In this way, the user can view the outing plan that best suits their preferences, conditions, and even emotions.

[0307] Specific Example

[0308] For example, if the user enters "likes nature, hiking is a hobby, budget is 10,000 yen, location is Hakone", and the emotion engine determines that the user seems to be enjoying themselves, the generative AI may generate a plan like the following:

[0309] Outing Plan:

[0310] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking course on the old street. There are rest facilities and cafes along the way for the user to enjoy.

[0311] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0312] 3. In the afternoon, visit art museums and nature parks in Hakone. As a plan that emphasizes relaxation from the emotion data, visit the Hakone Glass Forest Museum and foot bath cafes.

[0313] 4. In the evening, relax while watching the sunset around Lake Ashi, and return to Hakone-Yumoto Station by free shuttle bus.

[0314] Budget:

[0315] Transportation fee: 3,000 yen

[0316] Food and drinks: 3,000 yen

[0317] Admission fee and others: 3,000 yen

[0318] Other contingency funds: 1000 yen

[0319] Examples of prompts for generative artificial intelligence

[0320] Use prompts like the following to generate outing plans based on user preferences, budget, location, and sentiment data:

[0321] User preference: Loves nature

[0322] User's hobby: Hiking

[0323] Budget: 10,000 yen

[0324] Location: Hakone

[0325] Emotional data: Looks like they're having fun.

[0326] Based on this information, please generate the optimal outing plan.

[0327] Such detailed travel plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data. This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining this with an emotional engine, plans that take the user's emotions into consideration can be provided, resulting in the generation of even more satisfying travel plans.

[0328] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0329] Step 1:

[0330] The user accesses a web interface and enters information about their preferences, budget, and location.

[0331] Specific actions:

[0332] The user opens a browser and accesses the system's web interface.

[0333] The user enters their preferences (e.g., likes nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into an input form.

[0334] Input: Data about the user's preferences, budget, and location.

[0335] Output: Data on user preferences, budget, and location.

[0336] Step 2:

[0337] The device activates an emotion engine and collects emotional data from the user's voice tone and facial expressions.

[0338] Specific actions:

[0339] Once the user completes their input, the emotion engine built into the device will activate.

[0340] The device analyzes the user's voice tone and facial expressions in real time and collects emotional data (e.g., sounds happy, sounds sad).

[0341] Input: User's voice and facial expression data.

[0342] Output: Sentiment data.

[0343] Step 3:

[0344] The device converts the user's input data and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[0345] Specific actions:

[0346] The device then compiles the user's preferences, budget, location information, and sentiment data that were collected earlier.

[0347] Convert this information into JSON format (e.g., {"like":"Nature","budget":10000,"location":"Hakone","emotion":"Looks fun"}).

[0348] The device sends this JSON data to the server as an HTTP POST request.

[0349] Input: User preferences, budget, location information, and sentiment data.

[0350] Output: JSON data sent to the server.

[0351] Step 4:

[0352] The server receives an HTTP POST request sent from the terminal and extracts the JSON data from it.

[0353] Specific actions:

[0354] The server receives an HTTP POST request.

[0355] The server extracts JSON data from the request body.

[0356] Input: JSON data sent from the terminal.

[0357] Output: Extracted user preferences, budget, location, and sentiment data.

[0358] Step 5:

[0359] The server generates a request to the generative artificial intelligence based on the extracted data.

[0360] Specific actions:

[0361] The server analyzes the extracted data (preferences, budget, location, emotions).

[0362] Based on the analysis results, a prompt message is created to send to the generative AI (e.g., "User preference: likes nature, User hobby: hiking, Budget: 10,000 yen, Location: Hakone, Sentiment data: seems fun. Based on this information, please generate the best outing plan.").

[0363] Input: Extracted user preferences, budget, location, and sentiment data.

[0364] Output: A prompt message for the generative artificial intelligence.

[0365] Step 6:

[0366] The server sends a request to the generative artificial intelligence API.

[0367] Specific actions:

[0368] The server sends the prompt message to the generative artificial intelligence API.

[0369] Input: A prompt message for a generative artificial intelligence system.

[0370] Output: Sending a request to a generative artificial intelligence.

[0371] Step 7:

[0372] The generative artificial intelligence generates an outing plan based on the request and sends the response data back to the server.

[0373] Specific actions:

[0374] Generative artificial intelligence analyzes the received prompt text.

[0375] Based on the analysis results, the system generates the optimal outing plan.

[0376] The generated outing plan is sent back to the server as response data (e.g., "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway...").

[0377] Input: A request to a generative artificial intelligence.

[0378] Output: The generated outing plan.

[0379] Step 8:

[0380] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[0381] Specific actions:

[0382] The server receives response data from the generative artificial intelligence.

[0383] Convert the received response data into JSON format (e.g., {"plan":"1. Arrive at Hakone-Yumoto Station in the morning.."}).

[0384] Input: Response data from a generative artificial intelligence.

[0385] Output: Response data in JSON format.

[0386] Step 9:

[0387] The server prepares to send the converted JSON data to the user's terminal and then sends it.

[0388] Specific actions:

[0389] The server prepares to send response data in JSON format to the user's terminal.

[0390] Once preparations are complete, JSON data will be sent to the user's terminal as an HTTP response.

[0391] Input: Response data in JSON format.

[0392] Output: Send to the user's terminal.

[0393] Step 10:

[0394] The user terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface.

[0395] Specific actions:

[0396] The user's browser receives the JSON data sent back from the server.

[0397] Browser scripts parse the data and format it into a highly readable format.

[0398] The user interface displays details of the outing plan (e.g., which tourist spots to visit, which restaurants to eat at, etc.).

[0399] Input: JSON data returned from the server.

[0400] Output: Details of the outing plan displayed in the user interface.

[0401] (Application Example 2)

[0402] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0403] Conventional autonomous vehicles have not adequately offered travel plans and destination suggestions tailored to the individual needs of passengers, such as their emotions, preferences, and budgets. In particular, there have been many technical challenges in suggesting optimal routes and destinations that take into account the emotional state of passengers. Furthermore, there has been a lack of means to utilize collected emotional data in real time to improve the passenger experience. Therefore, the present invention aims to solve these technical challenges by providing a system that offers individually customized destination plans and routes based on the user's emotional data and preferences.

[0404] 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 user input data, means for sending a request to a generative artificial intelligence based on the user input data and emotion data, means for receiving a response from the generative artificial intelligence and transmitting the response data to a user terminal or in-vehicle display, and means for collecting passenger emotion data using a camera and microphone. This makes it possible to suggest optimal travel plans and destinations according to the passenger's emotional state, preferences, and budget.

[0405] Definitions of important words

[0406] "User input data" refers to information provided by users, such as their personal preferences, budget, and places they wish to visit.

[0407] "Emotional data" refers to information about a user's emotional state, obtained from their facial expressions, tone of voice, and other similar data.

[0408] "Generative artificial intelligence" refers to an artificial intelligence system that generates new data or plans based on input data.

[0409] "Means of sending requests" refers to means that have the function of sending user input data and emotional data to a generative artificial intelligence system.

[0410] "Response data" refers to data that a generative artificial intelligence generates based on a user's request and sends back to the server.

[0411] "User terminal" refers to devices such as smartphones, tablets, and PCs used by the user.

[0412] "In-vehicle display" refers to a screen installed inside an autonomous vehicle for displaying information.

[0413] "Camera and microphone" refers to video and audio input devices used to capture the user's facial expressions and voice.

[0414] Modes for carrying out the invention

[0415] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user terminal or in-vehicle display.

[0416] System Overview

[0417] This system consists mainly of the following means:

[0418] 1. Means for receiving user input data

[0419] 2. Means for collecting emotional data using cameras and microphones

[0420] 3. Means for sending requests to a generative artificial intelligence based on user input data and sentiment data.

[0421] 4. Means for transmitting response data from a generative artificial intelligence to a user terminal or in-vehicle display.

[0422] User input

[0423] First, the user boards an autonomous vehicle and uses an interface installed inside the vehicle to input their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone). Additionally, emotional data such as the user's facial expressions and voice tone are collected via the camera and microphone. This data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[0424] Server-side processing

[0425] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. The server then generates a request to a generative artificial intelligence (AI) based on this information. The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the API of the generative AI (e.g., a GPT model).

[0426] Responses and processing of generative artificial intelligence

[0427] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it again to the user terminal or in-vehicle display.

[0428] Display on the user's terminal

[0429] The user terminal and in-vehicle display receive JSON data sent back from the server, parse the data, and display it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[0430] Specific examples

[0431] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, the generative AI will generate a plan using prompts like the following:

[0432] Based on the user's preferences (nature lover), budget (10,000 yen), location (Hakone), and emotional data (enjoyable), please generate the optimal outing plan.

[0433] The generated outing plan includes detailed activity suggestions, such as the following:

[0434] Outing plans:

[0435] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[0436] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0437] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[0438] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0439] budget:

[0440] Transportation expenses: 3000 yen

[0441] Food and drinks: 3000 yen

[0442] Admission fee and other charges: 3000 yen

[0443] Other contingency funds: 1000 yen

[0444] This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining it with an emotion engine, plans that take user emotions into consideration are provided, resulting in the generation of even more satisfying travel plans.

[0445] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0446] Program processing steps

[0447] Step 1:

[0448] The user inputs their preferences, budget, and destination using an in-vehicle interface. The terminal also uses a camera and microphone to collect emotional data such as the user's facial expressions and tone of voice (Input: User preferences, budget, location, emotional data), (Output: Collected input data and emotional data). This data is converted to JSON format and sent to the server as an HTTP POST request (Operation: JSON conversion and HTTP POST request transmission).

[0449] Step 2:

[0450] The server receives an HTTP POST request sent from the terminal (Input: HTTP POST request), (Output: JSON data). JSON data is extracted from the request body (Operation: Request parsing and JSON data extraction). This JSON data includes user preferences, budget, location information, and sentiment data (Operation: JSON parsing).

[0451] Step 3:

[0452] The server generates a request to a generative artificial intelligence (e.g., a GPT model) based on the JSON data (input: JSON data), (output: AI request). The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data (action: request generation).

[0453] Step 4:

[0454] The server sends a request to the generative artificial intelligence API (input: AI request), (output: AI response). The generative artificial intelligence generates the optimal outing plan based on the request received from the server (operation: AI-generated plan).

[0455] Step 5:

[0456] The generative artificial intelligence generates a plan and returns it to the server in text format (input: AI request), (output: response data in text format). The server converts the received response data into JSON format (operation: JSON conversion of response data).

[0457] Step 6:

[0458] The server sends the converted JSON data back to the terminal or in-vehicle display (input: JSON response data), (output: data sent to the user terminal or in-vehicle display). The user terminal or in-vehicle display parses the received data and displays it on the user interface (operation: JSON data parsing and display).

[0459] Step 7:

[0460] Users can view outing plans that best suit their preferences, conditions, and even emotions (Input: Analyzed data), (Output: Display to the user). Guidance based on the plan is provided via terminals or in-vehicle displays (Operation: Plan guidance).

[0461] 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.

[0462] 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.

[0463] 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.

[0464] [Second Embodiment]

[0465] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0466] 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.

[0467] 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).

[0468] 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.

[0469] 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.

[0470] 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).

[0471] 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.

[0472] 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.

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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".

[0477] This invention provides a system that automatically suggests an optimal outing plan based on the user's individual preferences and conditions. This system has the function of receiving user input data, sending a request to a generative artificial intelligence based on that data, receiving a response from the generative artificial intelligence, and providing the response data to the user's terminal.

[0478] System Overview

[0479] This system generates an optimal outing plan based on user input regarding preferences, budget, and location. A specific implementation is described below.

[0480] User input

[0481] First, the user accesses the web interface using their device (smartphone or PC). Then, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0482] Server-side processing

[0483] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[0484] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[0485] Responses and processing of generative artificial intelligence

[0486] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0487] Display on the user's terminal

[0488] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[0489] Specific examples

[0490] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," a generative AI might generate a plan like the following:

[0491] Outing plans:

[0492] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0493] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0494] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0495] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0496] budget:

[0497] Transportation expenses: 3000 yen

[0498] Food and drinks: 3000 yen

[0499] Admission fee and other charges: 3000 yen

[0500] Other contingency funds: 1000 yen

[0501] It can be confirmed that such detailed outing plans are provided to perfectly match the user's budget and preferences.

[0502] The above is one embodiment of the present invention. This system allows users to easily obtain a travel plan that is best suited to them, significantly reducing the time and effort required when planning a trip.

[0503] The following describes the processing flow.

[0504] Step 1:

[0505] The user accesses their device and enters information about their preferences, budget, and location via a web interface.

[0506] Step 2:

[0507] The terminal converts the entered information into JSON format and sends it to the server as an HTTP POST request.

[0508] Step 3:

[0509] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes information about the user's preferences, budget, and location.

[0510] Step 4:

[0511] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the system to generate the optimal outing plan based on the information entered by the user.

[0512] Step 5:

[0513] The server sends a request to the generative artificial intelligence API.

[0514] Step 6:

[0515] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[0516] Step 7:

[0517] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[0518] Step 8:

[0519] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[0520] Step 9:

[0521] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[0522] (Example 1)

[0523] 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".

[0524] Traditional travel planning systems lacked the ability to automatically suggest optimal travel plans based on individual user preferences and conditions. This meant users had to gather information and plan their trips themselves, which was time-consuming and cumbersome.

[0525] 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.

[0526] In this invention, the server includes means for converting user input data into JSON format and sending it to the server; means for the server to generate a prompt message for a generative artificial intelligence based on the user input data and send a request; and means for receiving a response from the generative artificial intelligence, converting the response data into JSON format, and sending it to the user terminal. This makes it possible for the user to easily obtain the optimal travel plan that suits their preferences and conditions.

[0527] "User input data" refers to information about user preferences, budget, and destinations entered by the user through their device.

[0528] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a standard format for organizing and exchanging data in text format.

[0529] A "server" is a computer system that receives requests sent from a user's terminal, sends prompt messages to a generative artificial intelligence system, and returns the response to the user's terminal.

[0530] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal travel plan based on given data.

[0531] A "prompt statement" is a document containing questions or instructions used when making a specific request to a generative artificial intelligence system.

[0532] An "HTTP POST request" is one of the HTTP methods used to send data from a client to a server.

[0533] A "user terminal" refers to a device such as a computer or smartphone that is operated by the user.

[0534] "Response data" refers to travel plan information generated by generative artificial intelligence, and is data sent from the server to the user's terminal.

[0535] A "user interface" refers to the screen display and operating methods that allow a user to input information or confirm received data through a device.

[0536] This invention is a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. A specific embodiment of this system is described below.

[0537] System Overview

[0538] This system allows users to input information about their preferences, budget, and location using their own devices (smartphones or PCs). Based on this information, a generative artificial intelligence system generates and provides the user with an optimal outing plan.

[0539] User input

[0540] First, the user accesses the web interface using their device. There, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0541] Server-side processing

[0542] The server receives an HTTP POST request sent from the terminal. The request contains user preferences, budget, and location information in JSON format. The server parses this JSON data and extracts the necessary information. Based on this information, it generates a request for the generative artificial intelligence.

[0543] The request content creates a prompt message based on the user's input information and includes that information. For example, it generates a prompt message like the following:

[0544] Please generate the optimal outing plan based on the user's input information. The information required is as follows:

[0545] Preferences: I like nature.

[0546] Hobbies: Hiking

[0547] Budget: 10,000 yen

[0548] Location: Hakone

[0549] The server sends this prompt message to the generative artificial intelligence API.

[0550] Responses and processing of generative artificial intelligence

[0551] Generative artificial intelligence generates the optimal outing plan based on requests received from the server. This generated plan is in text format and is returned to the server. For example, the following plan may be generated:

[0552] Outing plans:

[0553] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0554] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0555] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0556] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0557] budget:

[0558] Transportation expenses: 3000 yen

[0559] Food and drinks: 3000 yen

[0560] Admission fee and other charges: 3000 yen

[0561] Other contingency funds: 1000 yen

[0562] The server converts this response back into JSON format and sends it to the user's terminal as an HTTP response.

[0563] Display on the user's terminal

[0564] The user terminal receives JSON data sent back from the server, parses the data, and displays it on the user interface. The user can then review this displayed outing plan and create a detailed travel plan.

[0565] The system of this invention allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip.

[0566] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0567] Step 1:

[0568] The user accesses the web interface using their device and enters information about their preferences, budget, and location into a form. Specifically, they might enter information such as "I like nature," "Hiking is my hobby," "My budget is 10,000 yen," and "Hakone." This entered data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[0569] Input: User preferences, budget, and location information

[0570] Output: Data in JSON format

[0571] Step 2:

[0572] The server receives an HTTP POST request sent from the user's terminal. The request contains the user's input data in JSON format. The server parses this JSON data and extracts information about the user's preferences, budget, and location.

[0573] Input: User input data in JSON format

[0574] Output: Information about user preferences, budget, and location.

[0575] Step 3:

[0576] The server generates prompt messages for the generative artificial intelligence based on the extracted data. Specifically, it creates prompt messages like the following: "Please generate the optimal outing plan based on the user's input information. The information is as follows: - Preferences: Likes nature - Hobbies: Hiking - Budget: 10,000 yen - Location: Hakone."

[0577] Input: User preferences, budget, and location information

[0578] Output: Prompt message

[0579] Step 4:

[0580] The server sends the generated prompt message to the generative artificial intelligence API. The prompt message is sent as a specific HTTP request using the POST method, instructing the AI ​​model to generate the optimal plan.

[0581] Input: Prompt message

[0582] Output: HTTP request

[0583] Step 5:

[0584] The generative artificial intelligence generates the optimal outing plan based on prompt messages sent from the server. The generated plan is returned to the server in text format.

[0585] Input: HTTP request (prompt text)

[0586] Output: Text-formatted response

[0587] Step 6:

[0588] The server receives the text-based response from the generative artificial intelligence and converts it back into JSON format. For example, it converts the response text: "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway. 2. After hiking, relax in a hot spring..." into JSON format.

[0589] Input: Text-formatted response

[0590] Output: Data in JSON format

[0591] Step 7:

[0592] The server sends the converted JSON data to the user's terminal as an HTTP response.

[0593] Input: Data in JSON format

[0594] Output: HTTP response

[0595] Step 8:

[0596] The user terminal receives JSON data sent from the server, parses that data, and displays it on the user interface. Specifically, it parses the JSON data to display the outing plan in an easy-to-understand visual format.

[0597] Input: HTTP response (JSON data)

[0598] Output: Outing plan displayed in the user interface

[0599] (Application Example 1)

[0600] 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."

[0601] To address the problem of users having difficulty easily finding the optimal plan based on their preferences and circumstances, there is a need for a system that automatically analyzes this information and suggests appropriate outing plans. Furthermore, a method for effectively utilizing generative artificial intelligence is required to make this possible.

[0602] 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.

[0603] In this invention, the server includes means for receiving user input data, means for sending a request to a generative artificial intelligence based on the user input data, means for receiving a response from the generative artificial intelligence and sending the response data to the user terminal, means for generating a prompt containing information about a content generation service based on the user input data, and means for generating and displaying an outing plan based on the prompt. This makes it possible to automatically generate and provide the user with an optimal outing plan based on the user's preferences and conditions.

[0604] "User input data" refers to information that users provide to the system, such as their individual preferences, budget, and location.

[0605] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal plan based on user input data, and produces responses to specific tasks.

[0606] "Means of sending requests" refers to the part of the system that uses user input data to send requests to a generative artificial intelligence.

[0607] "Means for transmitting response data to the user terminal" refers to the part of the system that has the function of transmitting response data obtained from generative artificial intelligence to the user's device.

[0608] A "content generation service" refers to an online service that automatically generates travel plans and other information based on user input data.

[0609] A "prompt" refers to text data containing detailed instructions about the user's preferences and conditions, used when sending a request to a generative artificial intelligence system.

[0610] An "outing plan" refers to a specific travel or event schedule or suggestion tailored to the user's preferences and requirements.

[0611] This invention provides a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. The system is configured as follows:

[0612] System Overview

[0613] The system has the function of receiving user input data, sending requests to a generative artificial intelligence system based on that data, and providing the response to the user's terminal. Specifically, it generates an optimal plan using information about the user's preferences, budget, and location.

[0614] User input

[0615] Users access the interface using their own devices (smartphones or computers). Users enter their preferences (e.g., they like nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0616] Server-side processing

[0617] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[0618] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[0619] Responses and processing of generative artificial intelligence

[0620] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0621] Display on the user's terminal

[0622] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[0623] Hardware and software to be used

[0624] Hardware: Smartphones, personal computers

[0625] software:

[0626] Python: Main logic of the program

[0627] requests: A library for sending API requests.

[0628] JSON: Data Format

[0629] Specific examples

[0630] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," the generative artificial intelligence will generate a plan like the following.

[0631] Outing plans

[0632] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0633] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0634] 3. In the afternoon, visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0635] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0636] Examples of prompts for generative AI models

[0637] "I love nature, hiking is my hobby, my budget is 10,000 yen, and the location is Hakone."

[0638] This allows users to easily find outing plans that suit their preferences and circumstances.

[0639] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0640] Step 1:

[0641] Users access the interface using their own devices (smartphones or computers) and display the data entry screen.

[0642] Input: User preferences (e.g., likes nature), budget (e.g., 10,000 yen), destination (e.g., Hakone)

[0643] Output: Input data in JSON format

[0644] Specific operation: When the user enters information into each form field and presses the "Submit" button, the device converts the entered data into JSON format and sends it to the server as an HTTP POST request.

[0645] Step 2:

[0646] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body.

[0647] Input: HTTP POST request

[0648] Output: User input data in JSON format

[0649] Specific operation: The server reads JSON data from the request body, which includes information about the user's preferences, budget, and location.

[0650] Step 3:

[0651] The server generates requests for the generative artificial intelligence based on the user's input data.

[0652] Input: User input data in JSON format

[0653] Output: Request (prompt) for generative artificial intelligence

[0654] Specific operation: The server extracts user input data and generates a prompt message based on it. This prompt message includes information about the user's preferences, budget, and location.

[0655] Step 4:

[0656] The server sends a request to the generative artificial intelligence API based on the generated prompt message.

[0657] Input: Request (prompt) for generative artificial intelligence

[0658] Output: Response data from generative artificial intelligence

[0659] Specific operation: The server issues an HTTP POST request to the generative artificial intelligence API endpoint and sends a prompt message.

[0660] Step 5:

[0661] The generative artificial intelligence generates the optimal outing plan based on the request received from the server and responds to the server.

[0662] Input: Request (prompt) for generative artificial intelligence

[0663] Output: Optimal outing plan (text format)

[0664] Specific operation: The generative artificial intelligence analyzes the prompt text, generates the most suitable outing plan based on the user's conditions, and sends it back to the server.

[0665] Step 6:

[0666] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[0667] Input: Response data from a generative artificial intelligence (text format)

[0668] Output: Response data in JSON format

[0669] Specific operation: The server receives the response data sent back from the generative artificial intelligence and converts it into JSON format.

[0670] Step 7:

[0671] The server sends the converted JSON-formatted response data to the user's terminal.

[0672] Input: Response data in JSON format

[0673] Output: Sent to the user's terminal as an HTTP response

[0674] Specific operation: The server uses the converted JSON data to generate an HTTP response and sends that response to the user's terminal.

[0675] Step 8:

[0676] The user terminal parses the JSON data received from the server and displays it on the user interface.

[0677] Input: Response data in JSON format

[0678] Output: Optimal outing plan displayed in the user interface

[0679] Specific operation: The user's terminal parses the received JSON data and displays it in the user interface in the appropriate format. This allows the user to see the outing plan that best suits their preferences and conditions.

[0680] Through the processing steps described above, users can easily obtain the outing plan that best suits their preferences and circumstances.

[0681] 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.

[0682] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user's terminal.

[0683] System Overview

[0684] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[0685] User input

[0686] First, the user accesses a web interface using their device (smartphone or PC). They then enter their preferences (e.g., love nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine to collect the user's emotional data (e.g., tone of voice and facial expressions). This data is converted into JSON format by the device and sent to the server as an HTTP POST request.

[0687] Server-side processing

[0688] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Subsequently, a generative artificial intelligence generates a request based on this information.

[0689] The request instructs the system to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the generative artificial intelligence API.

[0690] Responses and processing of generative artificial intelligence

[0691] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0692] Display on the user's terminal

[0693] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[0694] Specific examples

[0695] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[0696] Outing plans:

[0697] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[0698] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0699] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[0700] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0701] budget:

[0702] Transportation expenses: 3000 yen

[0703] Food and drinks: 3000 yen

[0704] Admission fee and other charges: 3000 yen

[0705] Other contingency funds: 1000 yen

[0706] It can be seen that such detailed outing plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data.

[0707] The above is one embodiment of the present invention. This system allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip. Furthermore, by combining it with an emotion engine, plans that take the user's emotions into consideration can be provided, enabling the generation of even more satisfying plans.

[0708] The following describes the processing flow.

[0709] Step 1:

[0710] Users access their devices and enter their preferences, budget, and location information via a web interface.

[0711] Step 2:

[0712] The device uses an emotion engine to collect emotional data from the user's voice and facial expressions. For example, it uses the device's microphone and camera to analyze what emotions the user is expressing when inputting data.

[0713] Step 3:

[0714] The terminal converts the entered information and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[0715] Step 4:

[0716] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes user preferences, budget, location information, and sentiment data.

[0717] Step 5:

[0718] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the AI ​​to generate the optimal outing plan based on the user's input information and emotional data.

[0719] Step 6:

[0720] The server sends a request to the generative artificial intelligence API.

[0721] Step 7:

[0722] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[0723] Step 8:

[0724] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[0725] Step 9:

[0726] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[0727] Step 10:

[0728] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[0729] (Example 2)

[0730] 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".

[0731] Conventional travel plan creation systems could provide plans based on basic information such as user preferences, budget, and location, but they struggled to create plans that took into account the user's emotional state. Therefore, there is a need to automatically generate highly satisfying plans that consider the user's emotions. Furthermore, a system is needed that efficiently processes multiple pieces of information entered by the user and sends appropriate requests to a generative artificial intelligence.

[0732] 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.

[0733] In this invention, the server includes means for receiving user input data, means for collecting user emotion data, means for sending requests to a generative artificial intelligence based on the user input data and emotion data, and means for receiving responses from the generative artificial intelligence and sending response data to the user terminal. This makes it possible to automatically generate an optimal travel plan that takes into account the user's preferences, budget, location, and emotion data.

[0734] "User input data" refers to data such as preferences, budget, and destinations that users provide as information necessary for generating travel plans.

[0735] "Emotional data" refers to data that indicates a user's emotional state, and is collected from sources such as voice and facial expressions.

[0736] "Generative artificial intelligence" refers to an artificial intelligence system that automatically generates optimal travel plans based on user input data and emotional data.

[0737] The "means of sending requests" refer to a mechanism for instructing a generative artificial intelligence to generate the optimal plan based on user input data and emotional data.

[0738] "Response data" refers to data about travel plans provided by generative artificial intelligence, which is transmitted to the user's terminal via a server.

[0739] A "user terminal" is an electronic device used by a user to access the system and view travel plans.

[0740] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system receives user input data and emotion data, sends a request to a generative artificial intelligence system based on this data, and provides the generated plan to the user's terminal. A specific embodiment of this system is described below.

[0741] System Overview

[0742] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[0743] User input

[0744] First, the user accesses a web interface using their device (smartphone or PC). Here, the user enters their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine (e.g., general emotion recognition software) to collect the user's emotional data (e.g., tone of voice and facial expressions). This collected data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0745] Server-side processing

[0746] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Based on this information, the server generates a request to the generative artificial intelligence. This request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server then sends this request to the generative artificial intelligence's API.

[0747] Responses and processing of generative artificial intelligence

[0748] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is sent back to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0749] Display on the user's terminal

[0750] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[0751] Specific examples

[0752] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[0753] Outing plans:

[0754] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[0755] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0756] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[0757] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0758] budget:

[0759] Transportation expenses: 3000 yen

[0760] Food and drinks: 3000 yen

[0761] Admission fee and other charges: 3000 yen

[0762] Other contingency funds: 1000 yen

[0763] Examples of prompts for generative artificial intelligence

[0764] Use prompts like the following to generate outing plans based on user preferences, budget, location, and sentiment data:

[0765] User preference: Loves nature

[0766] User's hobby: Hiking

[0767] Budget: 10,000 yen

[0768] Location: Hakone

[0769] Emotional data: Looks like they're having fun.

[0770] Based on this information, please generate the optimal outing plan.

[0771] Such detailed travel plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data. This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining this with an emotional engine, plans that take the user's emotions into consideration can be provided, resulting in the generation of even more satisfying travel plans.

[0772] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0773] Step 1:

[0774] The user accesses a web interface and enters information about their preferences, budget, and location.

[0775] Specific actions:

[0776] The user opens a browser and accesses the system's web interface.

[0777] The user enters their preferences (e.g., likes nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into an input form.

[0778] Input: Data about the user's preferences, budget, and location.

[0779] Output: Data on user preferences, budget, and location.

[0780] Step 2:

[0781] The device activates an emotion engine and collects emotional data from the user's voice tone and facial expressions.

[0782] Specific actions:

[0783] Once the user completes their input, the emotion engine built into the device will activate.

[0784] The device analyzes the user's voice tone and facial expressions in real time and collects emotional data (e.g., sounds happy, sounds sad).

[0785] Input: User's voice and facial expression data.

[0786] Output: Sentiment data.

[0787] Step 3:

[0788] The device converts the user's input data and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[0789] Specific actions:

[0790] The device then compiles the user's preferences, budget, location information, and sentiment data that were collected earlier.

[0791] Convert this information into JSON format (e.g., {"like":"Nature","budget":10000,"location":"Hakone","emotion":"Looks fun"}).

[0792] The device sends this JSON data to the server as an HTTP POST request.

[0793] Input: User preferences, budget, location information, and sentiment data.

[0794] Output: JSON data sent to the server.

[0795] Step 4:

[0796] The server receives an HTTP POST request sent from the terminal and extracts the JSON data from it.

[0797] Specific actions:

[0798] The server receives an HTTP POST request.

[0799] The server extracts JSON data from the request body.

[0800] Input: JSON data sent from the terminal.

[0801] Output: Extracted user preferences, budget, location, and sentiment data.

[0802] Step 5:

[0803] The server generates a request to the generative artificial intelligence based on the extracted data.

[0804] Specific actions:

[0805] The server analyzes the extracted data (preferences, budget, location, emotions).

[0806] Based on the analysis results, a prompt message is created to send to the generative AI (e.g., "User preference: likes nature, User hobby: hiking, Budget: 10,000 yen, Location: Hakone, Sentiment data: seems fun. Based on this information, please generate the best outing plan.").

[0807] Input: Extracted user preferences, budget, location, and sentiment data.

[0808] Output: A prompt message for the generative artificial intelligence.

[0809] Step 6:

[0810] The server sends a request to the generative artificial intelligence API.

[0811] Specific actions:

[0812] The server sends the prompt message to the generative artificial intelligence API.

[0813] Input: A prompt message for a generative artificial intelligence system.

[0814] Output: Sending a request to a generative artificial intelligence.

[0815] Step 7:

[0816] The generative artificial intelligence generates an outing plan based on the request and sends the response data back to the server.

[0817] Specific actions:

[0818] Generative artificial intelligence analyzes the received prompt text.

[0819] Based on the analysis results, the system generates the optimal outing plan.

[0820] The generated outing plan is sent back to the server as response data (e.g., "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway...").

[0821] Input: A request to a generative artificial intelligence.

[0822] Output: The generated outing plan.

[0823] Step 8:

[0824] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[0825] Specific actions:

[0826] The server receives response data from the generative artificial intelligence.

[0827] Convert the received response data into JSON format (e.g., {"plan":"1. Arrive at Hakone-Yumoto Station in the morning.."}).

[0828] Input: Response data from a generative artificial intelligence.

[0829] Output: Response data in JSON format.

[0830] Step 9:

[0831] The server prepares to send the converted JSON data to the user's terminal and then sends it.

[0832] Specific actions:

[0833] The server prepares to send response data in JSON format to the user's terminal.

[0834] Once preparations are complete, JSON data will be sent to the user's terminal as an HTTP response.

[0835] Input: Response data in JSON format.

[0836] Output: Send to the user's terminal.

[0837] Step 10:

[0838] The user terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface.

[0839] Specific actions:

[0840] The user's browser receives the JSON data sent back from the server.

[0841] Browser scripts parse the data and format it into a highly readable format.

[0842] The user interface displays details of the outing plan (e.g., which tourist spots to visit, which restaurants to eat at, etc.).

[0843] Input: JSON data returned from the server.

[0844] Output: Details of the outing plan displayed in the user interface.

[0845] (Application Example 2)

[0846] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0847] Conventional autonomous vehicles have not adequately offered travel plans and destination suggestions tailored to the individual needs of passengers, such as their emotions, preferences, and budgets. In particular, there have been many technical challenges in suggesting optimal routes and destinations that take into account the emotional state of passengers. Furthermore, there has been a lack of means to utilize collected emotional data in real time to improve the passenger experience. Therefore, the present invention aims to solve these technical challenges by providing a system that offers individually customized destination plans and routes based on the user's emotional data and preferences.

[0848] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving user input data, means for sending a request to a generative artificial intelligence based on the user input data and emotion data, means for receiving a response from the generative artificial intelligence and transmitting the response data to a user terminal or in-vehicle display, and means for collecting passenger emotion data using a camera and microphone. This makes it possible to suggest optimal travel plans and destinations according to the passenger's emotional state, preferences, and budget.

[0849] Definitions of important words

[0850] "User input data" refers to information provided by users, such as their personal preferences, budget, and places they wish to visit.

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

[0852] "Generative artificial intelligence" refers to an artificial intelligence system that generates new data or plans based on input data.

[0853] "Means of sending requests" refers to means that have the function of sending user input data and emotional data to a generative artificial intelligence system.

[0854] "Response data" refers to data that a generative artificial intelligence generates based on a user's request and sends back to the server.

[0855] "User terminal" refers to devices such as smartphones, tablets, and PCs used by the user.

[0856] "In-vehicle display" refers to a screen installed inside an autonomous vehicle for displaying information.

[0857] "Camera and microphone" refers to video and audio input devices used to capture the user's facial expressions and voice.

[0858] Modes for carrying out the invention

[0859] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user terminal or in-vehicle display.

[0860] System Overview

[0861] This system consists mainly of the following means:

[0862] 1. Means for receiving user input data

[0863] 2. Means for collecting emotional data using cameras and microphones

[0864] 3. Means for sending requests to a generative artificial intelligence based on user input data and sentiment data.

[0865] 4. Means for transmitting response data from a generative artificial intelligence to a user terminal or in-vehicle display.

[0866] User input

[0867] First, the user boards an autonomous vehicle and uses an interface installed inside the vehicle to input their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone). Additionally, emotional data such as the user's facial expressions and voice tone are collected via the camera and microphone. This data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[0868] Server-side processing

[0869] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. The server then generates a request to a generative artificial intelligence (AI) based on this information. The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the API of the generative AI (e.g., a GPT model).

[0870] Responses and processing of generative artificial intelligence

[0871] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it again to the user terminal or in-vehicle display.

[0872] Display on the user's terminal

[0873] The user terminal and in-vehicle display receive JSON data sent back from the server, parse the data, and display it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[0874] Specific examples

[0875] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, the generative AI will generate a plan using prompts like the following:

[0876] Based on the user's preferences (nature lover), budget (10,000 yen), location (Hakone), and emotional data (enjoyable), please generate the optimal outing plan.

[0877] The generated outing plan includes detailed activity suggestions, such as the following:

[0878] Outing plans:

[0879] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[0880] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0881] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[0882] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0883] budget:

[0884] Transportation expenses: 3000 yen

[0885] Food and drinks: 3000 yen

[0886] Admission fee and other charges: 3000 yen

[0887] Other contingency funds: 1000 yen

[0888] This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining it with an emotion engine, plans that take user emotions into consideration are provided, resulting in the generation of even more satisfying travel plans.

[0889] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0890] Program processing steps

[0891] Step 1:

[0892] The user inputs their preferences, budget, and destination using an in-vehicle interface. The terminal also uses a camera and microphone to collect emotional data such as the user's facial expressions and tone of voice (Input: User preferences, budget, location, emotional data), (Output: Collected input data and emotional data). This data is converted to JSON format and sent to the server as an HTTP POST request (Operation: JSON conversion and HTTP POST request transmission).

[0893] Step 2:

[0894] The server receives an HTTP POST request sent from the terminal (Input: HTTP POST request), (Output: JSON data). JSON data is extracted from the request body (Operation: Request parsing and JSON data extraction). This JSON data includes user preferences, budget, location information, and sentiment data (Operation: JSON parsing).

[0895] Step 3:

[0896] The server generates a request to a generative artificial intelligence (e.g., a GPT model) based on the JSON data (input: JSON data), (output: AI request). The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data (action: request generation).

[0897] Step 4:

[0898] The server sends a request to the generative artificial intelligence API (input: AI request), (output: AI response). The generative artificial intelligence generates the optimal outing plan based on the request received from the server (operation: AI-generated plan).

[0899] Step 5:

[0900] The generative artificial intelligence generates a plan and returns it to the server in text format (input: AI request), (output: response data in text format). The server converts the received response data into JSON format (operation: JSON conversion of response data).

[0901] Step 6:

[0902] The server sends the converted JSON data back to the terminal or in-vehicle display (input: JSON response data), (output: data sent to the user terminal or in-vehicle display). The user terminal or in-vehicle display parses the received data and displays it on the user interface (operation: JSON data parsing and display).

[0903] Step 7:

[0904] Users can view outing plans that best suit their preferences, conditions, and even emotions (Input: Analyzed data), (Output: Display to the user). Guidance based on the plan is provided via terminals or in-vehicle displays (Operation: Plan guidance).

[0905] 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.

[0906] 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.

[0907] 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.

[0908] [Third Embodiment]

[0909] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0910] 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.

[0911] 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).

[0912] 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.

[0913] 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.

[0914] 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).

[0915] 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.

[0916] 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.

[0917] 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.

[0918] 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.

[0919] 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.

[0920] 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".

[0921] This invention provides a system that automatically suggests an optimal outing plan based on the user's individual preferences and conditions. This system has the function of receiving user input data, sending a request to a generative artificial intelligence based on that data, receiving a response from the generative artificial intelligence, and providing the response data to the user's terminal.

[0922] System Overview

[0923] This system generates an optimal outing plan based on user input regarding preferences, budget, and location. A specific implementation is described below.

[0924] User input

[0925] First, the user accesses the web interface using their device (smartphone or PC). Then, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0926] Server-side processing

[0927] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[0928] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[0929] Responses and processing of generative artificial intelligence

[0930] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[0931] Display on the user's terminal

[0932] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[0933] Specific examples

[0934] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," a generative AI might generate a plan like the following:

[0935] Outing plans:

[0936] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0937] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0938] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[0939] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[0940] budget:

[0941] Transportation expenses: 3000 yen

[0942] Food and drinks: 3000 yen

[0943] Admission fee and other charges: 3000 yen

[0944] Other contingency funds: 1000 yen

[0945] It can be confirmed that such detailed outing plans are provided to perfectly match the user's budget and preferences.

[0946] The above is one embodiment of the present invention. This system allows users to easily obtain a travel plan that is best suited to them, significantly reducing the time and effort required when planning a trip.

[0947] The following describes the processing flow.

[0948] Step 1:

[0949] The user accesses their device and enters information about their preferences, budget, and location via a web interface.

[0950] Step 2:

[0951] The terminal converts the entered information into JSON format and sends it to the server as an HTTP POST request.

[0952] Step 3:

[0953] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes information about the user's preferences, budget, and location.

[0954] Step 4:

[0955] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the system to generate the optimal outing plan based on the information entered by the user.

[0956] Step 5:

[0957] The server sends a request to the generative artificial intelligence API.

[0958] Step 6:

[0959] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[0960] Step 7:

[0961] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[0962] Step 8:

[0963] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[0964] Step 9:

[0965] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[0966] (Example 1)

[0967] 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."

[0968] Traditional travel planning systems lacked the ability to automatically suggest optimal travel plans based on individual user preferences and conditions. This meant users had to gather information and plan their trips themselves, which was time-consuming and cumbersome.

[0969] 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.

[0970] In this invention, the server includes means for converting user input data into JSON format and sending it to the server; means for the server to generate a prompt message for a generative artificial intelligence based on the user input data and send a request; and means for receiving a response from the generative artificial intelligence, converting the response data into JSON format, and sending it to the user terminal. This makes it possible for the user to easily obtain the optimal travel plan that suits their preferences and conditions.

[0971] "User input data" refers to information about user preferences, budget, and destinations entered by the user through their device.

[0972] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a standard format for organizing and exchanging data in text format.

[0973] A "server" is a computer system that receives requests sent from a user's terminal, sends prompt messages to a generative artificial intelligence system, and returns the response to the user's terminal.

[0974] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal travel plan based on given data.

[0975] A "prompt statement" is a document containing questions or instructions used when making a specific request to a generative artificial intelligence system.

[0976] An "HTTP POST request" is one of the HTTP methods used to send data from a client to a server.

[0977] A "user terminal" refers to a device such as a computer or smartphone that is operated by the user.

[0978] "Response data" refers to travel plan information generated by generative artificial intelligence, and is data sent from the server to the user's terminal.

[0979] A "user interface" refers to the screen display and operating methods that allow a user to input information or confirm received data through a device.

[0980] This invention is a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. A specific embodiment of this system is described below.

[0981] System Overview

[0982] This system allows users to input information about their preferences, budget, and location using their own devices (smartphones or PCs). Based on this information, a generative artificial intelligence system generates and provides the user with an optimal outing plan.

[0983] User input

[0984] First, the user accesses the web interface using their device. There, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[0985] Server-side processing

[0986] The server receives an HTTP POST request sent from the terminal. The request contains user preferences, budget, and location information in JSON format. The server parses this JSON data and extracts the necessary information. Based on this information, it generates a request for the generative artificial intelligence.

[0987] The request content creates a prompt message based on the user's input information and includes that information. For example, it generates a prompt message like the following:

[0988] Please generate the optimal outing plan based on the user's input information. The information required is as follows:

[0989] Preferences: I like nature.

[0990] Hobbies: Hiking

[0991] Budget: 10,000 yen

[0992] Location: Hakone

[0993] The server sends this prompt message to the generative artificial intelligence API.

[0994] Responses and processing of generative artificial intelligence

[0995] Generative artificial intelligence generates the optimal outing plan based on requests received from the server. This generated plan is in text format and is returned to the server. For example, the following plan may be generated:

[0996] Outing plans:

[0997] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[0998] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[0999] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[1000] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1001] budget:

[1002] Transportation expenses: 3000 yen

[1003] Food and drinks: 3000 yen

[1004] Admission fee and other charges: 3000 yen

[1005] Other contingency funds: 1000 yen

[1006] The server converts this response back into JSON format and sends it to the user's terminal as an HTTP response.

[1007] Display on the user's terminal

[1008] The user terminal receives JSON data sent back from the server, parses the data, and displays it on the user interface. The user can then review this displayed outing plan and create a detailed travel plan.

[1009] The system of this invention allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip.

[1010] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1011] Step 1:

[1012] The user accesses the web interface using their device and enters information about their preferences, budget, and location into a form. Specifically, they might enter information such as "I like nature," "Hiking is my hobby," "My budget is 10,000 yen," and "Hakone." This entered data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[1013] Input: User preferences, budget, and location information

[1014] Output: Data in JSON format

[1015] Step 2:

[1016] The server receives an HTTP POST request sent from the user's terminal. The request contains the user's input data in JSON format. The server parses this JSON data and extracts information about the user's preferences, budget, and location.

[1017] Input: User input data in JSON format

[1018] Output: Information about user preferences, budget, and location.

[1019] Step 3:

[1020] The server generates prompt messages for the generative artificial intelligence based on the extracted data. Specifically, it creates prompt messages like the following: "Please generate the optimal outing plan based on the user's input information. The information is as follows: - Preferences: Likes nature - Hobbies: Hiking - Budget: 10,000 yen - Location: Hakone."

[1021] Input: User preferences, budget, and location information

[1022] Output: Prompt message

[1023] Step 4:

[1024] The server sends the generated prompt message to the generative artificial intelligence API. The prompt message is sent as a specific HTTP request using the POST method, instructing the AI ​​model to generate the optimal plan.

[1025] Input: Prompt message

[1026] Output: HTTP request

[1027] Step 5:

[1028] The generative artificial intelligence generates the optimal outing plan based on prompt messages sent from the server. The generated plan is returned to the server in text format.

[1029] Input: HTTP request (prompt text)

[1030] Output: Text-formatted response

[1031] Step 6:

[1032] The server receives the text-based response from the generative artificial intelligence and converts it back into JSON format. For example, it converts the response text: "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway. 2. After hiking, relax in a hot spring..." into JSON format.

[1033] Input: Text-formatted response

[1034] Output: Data in JSON format

[1035] Step 7:

[1036] The server sends the converted JSON data to the user's terminal as an HTTP response.

[1037] Input: Data in JSON format

[1038] Output: HTTP response

[1039] Step 8:

[1040] The user terminal receives JSON data sent from the server, parses that data, and displays it on the user interface. Specifically, it parses the JSON data to display the outing plan in an easy-to-understand visual format.

[1041] Input: HTTP response (JSON data)

[1042] Output: Outing plan displayed in the user interface

[1043] (Application Example 1)

[1044] 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."

[1045] To address the problem of users having difficulty easily finding the optimal plan based on their preferences and circumstances, there is a need for a system that automatically analyzes this information and suggests appropriate outing plans. Furthermore, a method for effectively utilizing generative artificial intelligence is required to make this possible.

[1046] 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.

[1047] In this invention, the server includes means for receiving user input data, means for sending a request to a generative artificial intelligence based on the user input data, means for receiving a response from the generative artificial intelligence and sending the response data to the user terminal, means for generating a prompt containing information about a content generation service based on the user input data, and means for generating and displaying an outing plan based on the prompt. This makes it possible to automatically generate and provide the user with an optimal outing plan based on the user's preferences and conditions.

[1048] "User input data" refers to information that users provide to the system, such as their individual preferences, budget, and location.

[1049] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal plan based on user input data, and produces responses to specific tasks.

[1050] "Means of sending requests" refers to the part of the system that uses user input data to send requests to a generative artificial intelligence.

[1051] "Means for transmitting response data to the user terminal" refers to the part of the system that has the function of transmitting response data obtained from generative artificial intelligence to the user's device.

[1052] A "content generation service" refers to an online service that automatically generates travel plans and other information based on user input data.

[1053] A "prompt" refers to text data containing detailed instructions about the user's preferences and conditions, used when sending a request to a generative artificial intelligence system.

[1054] An "outing plan" refers to a specific travel or event schedule or suggestion tailored to the user's preferences and requirements.

[1055] This invention provides a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. The system is configured as follows:

[1056] System Overview

[1057] The system has the function of receiving user input data, sending requests to a generative artificial intelligence system based on that data, and providing the response to the user's terminal. Specifically, it generates an optimal plan using information about the user's preferences, budget, and location.

[1058] User input

[1059] Users access the interface using their own devices (smartphones or computers). Users enter their preferences (e.g., they like nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1060] Server-side processing

[1061] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[1062] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[1063] Responses and processing of generative artificial intelligence

[1064] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1065] Display on the user's terminal

[1066] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[1067] Hardware and software to be used

[1068] Hardware: Smartphones, personal computers

[1069] software:

[1070] Python: Main logic of the program

[1071] requests: A library for sending API requests.

[1072] JSON: Data Format

[1073] Specific examples

[1074] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," the generative artificial intelligence will generate a plan like the following.

[1075] Outing plans

[1076] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[1077] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1078] 3. In the afternoon, visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[1079] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1080] Examples of prompts for generative AI models

[1081] "I love nature, hiking is my hobby, my budget is 10,000 yen, and the location is Hakone."

[1082] This allows users to easily find outing plans that suit their preferences and circumstances.

[1083] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1084] Step 1:

[1085] Users access the interface using their own devices (smartphones or computers) and display the data entry screen.

[1086] Input: User preferences (e.g., likes nature), budget (e.g., 10,000 yen), destination (e.g., Hakone)

[1087] Output: Input data in JSON format

[1088] Specific operation: When the user enters information into each form field and presses the "Submit" button, the device converts the entered data into JSON format and sends it to the server as an HTTP POST request.

[1089] Step 2:

[1090] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body.

[1091] Input: HTTP POST request

[1092] Output: User input data in JSON format

[1093] Specific operation: The server reads JSON data from the request body, which includes information about the user's preferences, budget, and location.

[1094] Step 3:

[1095] The server generates requests for the generative artificial intelligence based on the user's input data.

[1096] Input: User input data in JSON format

[1097] Output: Request (prompt) for generative artificial intelligence

[1098] Specific operation: The server extracts user input data and generates a prompt message based on it. This prompt message includes information about the user's preferences, budget, and location.

[1099] Step 4:

[1100] The server sends a request to the generative artificial intelligence API based on the generated prompt message.

[1101] Input: Request (prompt) for generative artificial intelligence

[1102] Output: Response data from generative artificial intelligence

[1103] Specific operation: The server issues an HTTP POST request to the generative artificial intelligence API endpoint and sends a prompt message.

[1104] Step 5:

[1105] The generative artificial intelligence generates the optimal outing plan based on the request received from the server and responds to the server.

[1106] Input: Request (prompt) for generative artificial intelligence

[1107] Output: Optimal outing plan (text format)

[1108] Specific operation: The generative artificial intelligence analyzes the prompt text, generates the most suitable outing plan based on the user's conditions, and sends it back to the server.

[1109] Step 6:

[1110] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[1111] Input: Response data from a generative artificial intelligence (text format)

[1112] Output: Response data in JSON format

[1113] Specific operation: The server receives the response data sent back from the generative artificial intelligence and converts it into JSON format.

[1114] Step 7:

[1115] The server sends the converted JSON-formatted response data to the user's terminal.

[1116] Input: Response data in JSON format

[1117] Output: Sent to the user's terminal as an HTTP response

[1118] Specific operation: The server uses the converted JSON data to generate an HTTP response and sends that response to the user's terminal.

[1119] Step 8:

[1120] The user terminal parses the JSON data received from the server and displays it on the user interface.

[1121] Input: Response data in JSON format

[1122] Output: Optimal outing plan displayed in the user interface

[1123] Specific operation: The user's terminal parses the received JSON data and displays it in the user interface in the appropriate format. This allows the user to see the outing plan that best suits their preferences and conditions.

[1124] Through the processing steps described above, users can easily obtain the outing plan that best suits their preferences and circumstances.

[1125] 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.

[1126] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user's terminal.

[1127] System Overview

[1128] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[1129] User input

[1130] First, the user accesses a web interface using their device (smartphone or PC). They then enter their preferences (e.g., love nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine to collect the user's emotional data (e.g., tone of voice and facial expressions). This data is converted into JSON format by the device and sent to the server as an HTTP POST request.

[1131] Server-side processing

[1132] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Subsequently, a generative artificial intelligence generates a request based on this information.

[1133] The request instructs the system to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the generative artificial intelligence API.

[1134] Responses and processing of generative artificial intelligence

[1135] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1136] Display on the user's terminal

[1137] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1138] Specific examples

[1139] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[1140] Outing plans:

[1141] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1142] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1143] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1144] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1145] budget:

[1146] Transportation expenses: 3000 yen

[1147] Food and drinks: 3000 yen

[1148] Admission fee and other charges: 3000 yen

[1149] Other contingency funds: 1000 yen

[1150] It can be seen that such detailed outing plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data.

[1151] The above is one embodiment of the present invention. This system allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip. Furthermore, by combining it with an emotion engine, plans that take the user's emotions into consideration can be provided, enabling the generation of even more satisfying plans.

[1152] The following describes the processing flow.

[1153] Step 1:

[1154] Users access their devices and enter their preferences, budget, and location information via a web interface.

[1155] Step 2:

[1156] The device uses an emotion engine to collect emotional data from the user's voice and facial expressions. For example, it uses the device's microphone and camera to analyze what emotions the user is expressing when inputting data.

[1157] Step 3:

[1158] The terminal converts the entered information and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[1159] Step 4:

[1160] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes user preferences, budget, location information, and sentiment data.

[1161] Step 5:

[1162] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the AI ​​to generate the optimal outing plan based on the user's input information and emotional data.

[1163] Step 6:

[1164] The server sends a request to the generative artificial intelligence API.

[1165] Step 7:

[1166] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[1167] Step 8:

[1168] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[1169] Step 9:

[1170] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[1171] Step 10:

[1172] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[1173] (Example 2)

[1174] 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."

[1175] Conventional travel plan creation systems could provide plans based on basic information such as user preferences, budget, and location, but they struggled to create plans that took into account the user's emotional state. Therefore, there is a need to automatically generate highly satisfying plans that consider the user's emotions. Furthermore, a system is needed that efficiently processes multiple pieces of information entered by the user and sends appropriate requests to a generative artificial intelligence.

[1176] 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.

[1177] In this invention, the server includes means for receiving user input data, means for collecting user emotion data, means for sending requests to a generative artificial intelligence based on the user input data and emotion data, and means for receiving responses from the generative artificial intelligence and sending response data to the user terminal. This makes it possible to automatically generate an optimal travel plan that takes into account the user's preferences, budget, location, and emotion data.

[1178] "User input data" refers to data such as preferences, budget, and destinations that users provide as information necessary for generating travel plans.

[1179] "Emotional data" refers to data that indicates a user's emotional state, and is collected from sources such as voice and facial expressions.

[1180] "Generative artificial intelligence" refers to an artificial intelligence system that automatically generates optimal travel plans based on user input data and emotional data.

[1181] The "means of sending requests" refer to a mechanism for instructing a generative artificial intelligence to generate the optimal plan based on user input data and emotional data.

[1182] "Response data" refers to data about travel plans provided by generative artificial intelligence, which is transmitted to the user's terminal via a server.

[1183] A "user terminal" is an electronic device used by a user to access the system and view travel plans.

[1184] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system receives user input data and emotion data, sends a request to a generative artificial intelligence system based on this data, and provides the generated plan to the user's terminal. A specific embodiment of this system is described below.

[1185] System Overview

[1186] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[1187] User input

[1188] First, the user accesses a web interface using their device (smartphone or PC). Here, the user enters their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine (e.g., general emotion recognition software) to collect the user's emotional data (e.g., tone of voice and facial expressions). This collected data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1189] Server-side processing

[1190] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Based on this information, the server generates a request to the generative artificial intelligence. This request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server then sends this request to the generative artificial intelligence's API.

[1191] Responses and processing of generative artificial intelligence

[1192] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is sent back to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1193] Display on the user's terminal

[1194] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1195] Specific examples

[1196] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[1197] Outing plans:

[1198] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1199] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1200] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1201] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1202] budget:

[1203] Transportation expenses: 3000 yen

[1204] Food and drinks: 3000 yen

[1205] Admission fee and other charges: 3000 yen

[1206] Other contingency funds: 1000 yen

[1207] Examples of prompts for generative artificial intelligence

[1208] Use prompts like the following to generate outing plans based on user preferences, budget, location, and sentiment data:

[1209] User preference: Loves nature

[1210] User's hobby: Hiking

[1211] Budget: 10,000 yen

[1212] Location: Hakone

[1213] Emotional data: Looks like they're having fun.

[1214] Based on this information, please generate the optimal outing plan.

[1215] Such detailed travel plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data. This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining this with an emotional engine, plans that take the user's emotions into consideration can be provided, resulting in the generation of even more satisfying travel plans.

[1216] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1217] Step 1:

[1218] The user accesses a web interface and enters information about their preferences, budget, and location.

[1219] Specific actions:

[1220] The user opens a browser and accesses the system's web interface.

[1221] The user enters their preferences (e.g., likes nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into an input form.

[1222] Input: Data about the user's preferences, budget, and location.

[1223] Output: Data on user preferences, budget, and location.

[1224] Step 2:

[1225] The device activates an emotion engine and collects emotional data from the user's voice tone and facial expressions.

[1226] Specific actions:

[1227] Once the user completes their input, the emotion engine built into the device will activate.

[1228] The device analyzes the user's voice tone and facial expressions in real time and collects emotional data (e.g., sounds happy, sounds sad).

[1229] Input: User's voice and facial expression data.

[1230] Output: Sentiment data.

[1231] Step 3:

[1232] The device converts the user's input data and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[1233] Specific actions:

[1234] The device then compiles the user's preferences, budget, location information, and sentiment data that were collected earlier.

[1235] Convert this information into JSON format (e.g., {"like":"Nature","budget":10000,"location":"Hakone","emotion":"Looks fun"}).

[1236] The device sends this JSON data to the server as an HTTP POST request.

[1237] Input: User preferences, budget, location information, and sentiment data.

[1238] Output: JSON data sent to the server.

[1239] Step 4:

[1240] The server receives an HTTP POST request sent from the terminal and extracts the JSON data from it.

[1241] Specific actions:

[1242] The server receives an HTTP POST request.

[1243] The server extracts JSON data from the request body.

[1244] Input: JSON data sent from the terminal.

[1245] Output: Extracted user preferences, budget, location, and sentiment data.

[1246] Step 5:

[1247] The server generates a request to the generative artificial intelligence based on the extracted data.

[1248] Specific actions:

[1249] The server analyzes the extracted data (preferences, budget, location, emotions).

[1250] Based on the analysis results, a prompt message is created to send to the generative AI (e.g., "User preference: likes nature, User hobby: hiking, Budget: 10,000 yen, Location: Hakone, Sentiment data: seems fun. Based on this information, please generate the best outing plan.").

[1251] Input: Extracted user preferences, budget, location, and sentiment data.

[1252] Output: A prompt message for the generative artificial intelligence.

[1253] Step 6:

[1254] The server sends a request to the generative artificial intelligence API.

[1255] Specific actions:

[1256] The server sends the prompt message to the generative artificial intelligence API.

[1257] Input: A prompt message for a generative artificial intelligence system.

[1258] Output: Sending a request to a generative artificial intelligence.

[1259] Step 7:

[1260] The generative artificial intelligence generates an outing plan based on the request and sends the response data back to the server.

[1261] Specific actions:

[1262] Generative artificial intelligence analyzes the received prompt text.

[1263] Based on the analysis results, the system generates the optimal outing plan.

[1264] The generated outing plan is sent back to the server as response data (e.g., "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway...").

[1265] Input: A request to a generative artificial intelligence.

[1266] Output: The generated outing plan.

[1267] Step 8:

[1268] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[1269] Specific actions:

[1270] The server receives response data from the generative artificial intelligence.

[1271] Convert the received response data into JSON format (e.g., {"plan":"1. Arrive at Hakone-Yumoto Station in the morning.."}).

[1272] Input: Response data from a generative artificial intelligence.

[1273] Output: Response data in JSON format.

[1274] Step 9:

[1275] The server prepares to send the converted JSON data to the user's terminal and then sends it.

[1276] Specific actions:

[1277] The server prepares to send response data in JSON format to the user's terminal.

[1278] Once preparations are complete, JSON data will be sent to the user's terminal as an HTTP response.

[1279] Input: Response data in JSON format.

[1280] Output: Send to the user's terminal.

[1281] Step 10:

[1282] The user terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface.

[1283] Specific actions:

[1284] The user's browser receives the JSON data sent back from the server.

[1285] Browser scripts parse the data and format it into a highly readable format.

[1286] The user interface displays details of the outing plan (e.g., which tourist spots to visit, which restaurants to eat at, etc.).

[1287] Input: JSON data returned from the server.

[1288] Output: Details of the outing plan displayed in the user interface.

[1289] (Application Example 2)

[1290] 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."

[1291] Conventional autonomous vehicles have not adequately offered travel plans and destination suggestions tailored to the individual needs of passengers, such as their emotions, preferences, and budgets. In particular, there have been many technical challenges in suggesting optimal routes and destinations that take into account the emotional state of passengers. Furthermore, there has been a lack of means to utilize collected emotional data in real time to improve the passenger experience. Therefore, the present invention aims to solve these technical challenges by providing a system that offers individually customized destination plans and routes based on the user's emotional data and preferences.

[1292] 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 user input data, means for sending a request to a generative artificial intelligence based on the user input data and emotion data, means for receiving a response from the generative artificial intelligence and transmitting the response data to a user terminal or in-vehicle display, and means for collecting passenger emotion data using a camera and microphone. This makes it possible to suggest optimal travel plans and destinations according to the passenger's emotional state, preferences, and budget.

[1293] Definitions of important words

[1294] "User input data" refers to information provided by users, such as their personal preferences, budget, and places they wish to visit.

[1295] "Emotional data" refers to information about a user's emotional state, obtained from their facial expressions, tone of voice, and other similar data.

[1296] "Generative artificial intelligence" refers to an artificial intelligence system that generates new data or plans based on input data.

[1297] "Means of sending requests" refers to means that have the function of sending user input data and emotional data to a generative artificial intelligence system.

[1298] "Response data" refers to data that a generative artificial intelligence generates based on a user's request and sends back to the server.

[1299] "User terminal" refers to devices such as smartphones, tablets, and PCs used by the user.

[1300] "In-vehicle display" refers to a screen installed inside an autonomous vehicle for displaying information.

[1301] "Camera and microphone" refers to video and audio input devices used to capture the user's facial expressions and voice.

[1302] Modes for carrying out the invention

[1303] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user terminal or in-vehicle display.

[1304] System Overview

[1305] This system consists mainly of the following means:

[1306] 1. Means for receiving user input data

[1307] 2. Means for collecting emotional data using cameras and microphones

[1308] 3. Means for sending requests to a generative artificial intelligence based on user input data and sentiment data.

[1309] 4. Means for transmitting response data from a generative artificial intelligence to a user terminal or in-vehicle display.

[1310] User input

[1311] First, the user boards an autonomous vehicle and uses an interface installed inside the vehicle to input their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone). Additionally, emotional data such as the user's facial expressions and voice tone are collected via the camera and microphone. This data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[1312] Server-side processing

[1313] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. The server then generates a request to a generative artificial intelligence (AI) based on this information. The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the API of the generative AI (e.g., a GPT model).

[1314] Responses and processing of generative artificial intelligence

[1315] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it again to the user terminal or in-vehicle display.

[1316] Display on the user's terminal

[1317] The user terminal and in-vehicle display receive JSON data sent back from the server, parse the data, and display it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1318] Specific examples

[1319] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, the generative AI will generate a plan using prompts like the following:

[1320] Based on the user's preferences (nature lover), budget (10,000 yen), location (Hakone), and emotional data (enjoyable), please generate the optimal outing plan.

[1321] The generated outing plan includes detailed activity suggestions, such as the following:

[1322] Outing plans:

[1323] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1324] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1325] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1326] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1327] budget:

[1328] Transportation expenses: 3000 yen

[1329] Food and drinks: 3000 yen

[1330] Admission fee and other charges: 3000 yen

[1331] Other contingency funds: 1000 yen

[1332] This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining it with an emotion engine, plans that take user emotions into consideration are provided, resulting in the generation of even more satisfying travel plans.

[1333] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1334] Program processing steps

[1335] Step 1:

[1336] The user inputs their preferences, budget, and destination using an in-vehicle interface. The terminal also uses a camera and microphone to collect emotional data such as the user's facial expressions and tone of voice (Input: User preferences, budget, location, emotional data), (Output: Collected input data and emotional data). This data is converted to JSON format and sent to the server as an HTTP POST request (Operation: JSON conversion and HTTP POST request transmission).

[1337] Step 2:

[1338] The server receives an HTTP POST request sent from the terminal (Input: HTTP POST request), (Output: JSON data). JSON data is extracted from the request body (Operation: Request parsing and JSON data extraction). This JSON data includes user preferences, budget, location information, and sentiment data (Operation: JSON parsing).

[1339] Step 3:

[1340] The server generates a request to a generative artificial intelligence (e.g., a GPT model) based on the JSON data (input: JSON data), (output: AI request). The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data (action: request generation).

[1341] Step 4:

[1342] The server sends a request to the generative artificial intelligence API (input: AI request), (output: AI response). The generative artificial intelligence generates the optimal outing plan based on the request received from the server (operation: AI-generated plan).

[1343] Step 5:

[1344] The generative artificial intelligence generates a plan and returns it to the server in text format (input: AI request), (output: response data in text format). The server converts the received response data into JSON format (operation: JSON conversion of response data).

[1345] Step 6:

[1346] The server sends the converted JSON data back to the terminal or in-vehicle display (input: JSON response data), (output: data sent to the user terminal or in-vehicle display). The user terminal or in-vehicle display parses the received data and displays it on the user interface (operation: JSON data parsing and display).

[1347] Step 7:

[1348] Users can view outing plans that best suit their preferences, conditions, and even emotions (Input: Analyzed data), (Output: Display to the user). Guidance based on the plan is provided via terminals or in-vehicle displays (Operation: Plan guidance).

[1349] 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.

[1350] 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.

[1351] 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.

[1352] [Fourth Embodiment]

[1353] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1354] 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.

[1355] 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).

[1356] 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.

[1357] 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.

[1358] 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).

[1359] 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.

[1360] 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.

[1361] 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.

[1362] 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.

[1363] 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.

[1364] 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.

[1365] 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".

[1366] This invention provides a system that automatically suggests an optimal outing plan based on the user's individual preferences and conditions. This system has the function of receiving user input data, sending a request to a generative artificial intelligence based on that data, receiving a response from the generative artificial intelligence, and providing the response data to the user's terminal.

[1367] System Overview

[1368] This system generates an optimal outing plan based on user input regarding preferences, budget, and location. A specific implementation is described below.

[1369] User input

[1370] First, the user accesses the web interface using their device (smartphone or PC). Then, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1371] Server-side processing

[1372] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[1373] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[1374] Responses and processing of generative artificial intelligence

[1375] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1376] Display on the user's terminal

[1377] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[1378] Specific examples

[1379] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," a generative AI might generate a plan like the following:

[1380] Outing plans:

[1381] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[1382] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1383] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[1384] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1385] budget:

[1386] Transportation expenses: 3000 yen

[1387] Food and drinks: 3000 yen

[1388] Admission fee and other charges: 3000 yen

[1389] Other contingency funds: 1000 yen

[1390] It can be confirmed that such detailed outing plans are provided to perfectly match the user's budget and preferences.

[1391] The above is one embodiment of the present invention. This system allows users to easily obtain a travel plan that is best suited to them, significantly reducing the time and effort required when planning a trip.

[1392] The following describes the processing flow.

[1393] Step 1:

[1394] The user accesses their device and enters information about their preferences, budget, and location via a web interface.

[1395] Step 2:

[1396] The terminal converts the entered information into JSON format and sends it to the server as an HTTP POST request.

[1397] Step 3:

[1398] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes information about the user's preferences, budget, and location.

[1399] Step 4:

[1400] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the system to generate the optimal outing plan based on the information entered by the user.

[1401] Step 5:

[1402] The server sends a request to the generative artificial intelligence API.

[1403] Step 6:

[1404] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[1405] Step 7:

[1406] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[1407] Step 8:

[1408] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[1409] Step 9:

[1410] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[1411] (Example 1)

[1412] 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".

[1413] Traditional travel planning systems lacked the ability to automatically suggest optimal travel plans based on individual user preferences and conditions. This meant users had to gather information and plan their trips themselves, which was time-consuming and cumbersome.

[1414] 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.

[1415] In this invention, the server includes means for converting user input data into JSON format and sending it to the server; means for the server to generate a prompt message for a generative artificial intelligence based on the user input data and send a request; and means for receiving a response from the generative artificial intelligence, converting the response data into JSON format, and sending it to the user terminal. This makes it possible for the user to easily obtain the optimal travel plan that suits their preferences and conditions.

[1416] "User input data" refers to information about user preferences, budget, and destinations entered by the user through their device.

[1417] "JSON format" is an abbreviation for JavaScript Object Notation, and it is a standard format for organizing and exchanging data in text format.

[1418] A "server" is a computer system that receives requests sent from a user's terminal, sends prompt messages to a generative artificial intelligence system, and returns the response to the user's terminal.

[1419] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal travel plan based on given data.

[1420] A "prompt statement" is a document containing questions or instructions used when making a specific request to a generative artificial intelligence system.

[1421] An "HTTP POST request" is one of the HTTP methods used to send data from a client to a server.

[1422] A "user terminal" refers to a device such as a computer or smartphone that is operated by the user.

[1423] "Response data" refers to travel plan information generated by generative artificial intelligence, and is data sent from the server to the user's terminal.

[1424] A "user interface" refers to the screen display and operating methods that allow a user to input information or confirm received data through a device.

[1425] This invention is a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. A specific embodiment of this system is described below.

[1426] System Overview

[1427] This system allows users to input information about their preferences, budget, and location using their own devices (smartphones or PCs). Based on this information, a generative artificial intelligence system generates and provides the user with an optimal outing plan.

[1428] User input

[1429] First, the user accesses the web interface using their device. There, they enter their preferences (e.g., love nature, enjoy hiking), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1430] Server-side processing

[1431] The server receives an HTTP POST request sent from the terminal. The request contains user preferences, budget, and location information in JSON format. The server parses this JSON data and extracts the necessary information. Based on this information, it generates a request for the generative artificial intelligence.

[1432] The request content creates a prompt message based on the user's input information and includes that information. For example, it generates a prompt message like the following:

[1433] Please generate the optimal outing plan based on the user's input information. The information required is as follows:

[1434] Preferences: I like nature.

[1435] Hobbies: Hiking

[1436] Budget: 10,000 yen

[1437] Location: Hakone

[1438] The server sends this prompt message to the generative artificial intelligence API.

[1439] Responses and processing of generative artificial intelligence

[1440] Generative artificial intelligence generates the optimal outing plan based on requests received from the server. This generated plan is in text format and is returned to the server. For example, the following plan may be generated:

[1441] Outing plans:

[1442] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[1443] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1444] 3. In the afternoon, we will visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[1445] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1446] budget:

[1447] Transportation expenses: 3000 yen

[1448] Food and drinks: 3000 yen

[1449] Admission fee and other charges: 3000 yen

[1450] Other contingency funds: 1000 yen

[1451] The server converts this response back into JSON format and sends it to the user's terminal as an HTTP response.

[1452] Display on the user's terminal

[1453] The user terminal receives JSON data sent back from the server, parses the data, and displays it on the user interface. The user can then review this displayed outing plan and create a detailed travel plan.

[1454] The system of this invention allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip.

[1455] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1456] Step 1:

[1457] The user accesses the web interface using their device and enters information about their preferences, budget, and location into a form. Specifically, they might enter information such as "I like nature," "Hiking is my hobby," "My budget is 10,000 yen," and "Hakone." This entered data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[1458] Input: User preferences, budget, and location information

[1459] Output: Data in JSON format

[1460] Step 2:

[1461] The server receives an HTTP POST request sent from the user's terminal. The request contains the user's input data in JSON format. The server parses this JSON data and extracts information about the user's preferences, budget, and location.

[1462] Input: User input data in JSON format

[1463] Output: Information about user preferences, budget, and location.

[1464] Step 3:

[1465] The server generates prompt messages for the generative artificial intelligence based on the extracted data. Specifically, it creates prompt messages like the following: "Please generate the optimal outing plan based on the user's input information. The information is as follows: - Preferences: Likes nature - Hobbies: Hiking - Budget: 10,000 yen - Location: Hakone."

[1466] Input: User preferences, budget, and location information

[1467] Output: Prompt message

[1468] Step 4:

[1469] The server sends the generated prompt message to the generative artificial intelligence API. The prompt message is sent as a specific HTTP request using the POST method, instructing the AI ​​model to generate the optimal plan.

[1470] Input: Prompt message

[1471] Output: HTTP request

[1472] Step 5:

[1473] The generative artificial intelligence generates the optimal outing plan based on prompt messages sent from the server. The generated plan is returned to the server in text format.

[1474] Input: HTTP request (prompt text)

[1475] Output: Text-formatted response

[1476] Step 6:

[1477] The server receives the text-based response from the generative artificial intelligence and converts it back into JSON format. For example, it converts the response text: "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway. 2. After hiking, relax in a hot spring..." into JSON format.

[1478] Input: Text-formatted response

[1479] Output: Data in JSON format

[1480] Step 7:

[1481] The server sends the converted JSON data to the user's terminal as an HTTP response.

[1482] Input: Data in JSON format

[1483] Output: HTTP response

[1484] Step 8:

[1485] The user terminal receives JSON data sent from the server, parses that data, and displays it on the user interface. Specifically, it parses the JSON data to display the outing plan in an easy-to-understand visual format.

[1486] Input: HTTP response (JSON data)

[1487] Output: Outing plan displayed in the user interface

[1488] (Application Example 1)

[1489] 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".

[1490] To address the problem of users having difficulty easily finding the optimal plan based on their preferences and circumstances, there is a need for a system that automatically analyzes this information and suggests appropriate outing plans. Furthermore, a method for effectively utilizing generative artificial intelligence is required to make this possible.

[1491] 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.

[1492] In this invention, the server includes means for receiving user input data, means for sending a request to a generative artificial intelligence based on the user input data, means for receiving a response from the generative artificial intelligence and sending the response data to the user terminal, means for generating a prompt containing information about a content generation service based on the user input data, and means for generating and displaying an outing plan based on the prompt. This makes it possible to automatically generate and provide the user with an optimal outing plan based on the user's preferences and conditions.

[1493] "User input data" refers to information that users provide to the system, such as their individual preferences, budget, and location.

[1494] "Generative artificial intelligence" refers to an artificial intelligence model that generates the optimal plan based on user input data, and produces responses to specific tasks.

[1495] "Means of sending requests" refers to the part of the system that uses user input data to send requests to a generative artificial intelligence.

[1496] "Means for transmitting response data to the user terminal" refers to the part of the system that has the function of transmitting response data obtained from generative artificial intelligence to the user's device.

[1497] A "content generation service" refers to an online service that automatically generates travel plans and other information based on user input data.

[1498] A "prompt" refers to text data containing detailed instructions about the user's preferences and conditions, used when sending a request to a generative artificial intelligence system.

[1499] An "outing plan" refers to a specific travel or event schedule or suggestion tailored to the user's preferences and requirements.

[1500] This invention provides a system that automatically suggests the optimal outing plan based on the user's individual preferences and conditions. The system is configured as follows:

[1501] System Overview

[1502] The system has the function of receiving user input data, sending requests to a generative artificial intelligence system based on that data, and providing the response to the user's terminal. Specifically, it generates an optimal plan using information about the user's preferences, budget, and location.

[1503] User input

[1504] Users access the interface using their own devices (smartphones or computers). Users enter their preferences (e.g., they like nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. This entered data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1505] Server-side processing

[1506] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data contains information about the user's preferences, budget, and location. Subsequently, a request is generated to a generative artificial intelligence (e.g., a large-scale language model) based on this information.

[1507] The request explicitly includes the user's input information and instructs the system to generate the optimal plan based on that information. The server sends this request to the generative artificial intelligence API.

[1508] Responses and processing of generative artificial intelligence

[1509] Generative artificial intelligence generates an optimal outing plan based on a request received from the server. This generated plan is in text format and is returned to the server. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1510] Display on the user's terminal

[1511] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences and conditions.

[1512] Hardware and software to be used

[1513] Hardware: Smartphones, personal computers

[1514] software:

[1515] Python: Main logic of the program

[1516] requests: A library for sending API requests.

[1517] JSON: Data Format

[1518] Specific examples

[1519] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," the generative artificial intelligence will generate a plan like the following.

[1520] Outing plans

[1521] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway.

[1522] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1523] 3. In the afternoon, visit art museums and nature parks in Hakone. The Hakone Glass Forest Museum is especially recommended.

[1524] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1525] Examples of prompts for generative AI models

[1526] "I love nature, hiking is my hobby, my budget is 10,000 yen, and the location is Hakone."

[1527] This allows users to easily find outing plans that suit their preferences and circumstances.

[1528] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1529] Step 1:

[1530] Users access the interface using their own devices (smartphones or computers) and display the data entry screen.

[1531] Input: User preferences (e.g., likes nature), budget (e.g., 10,000 yen), destination (e.g., Hakone)

[1532] Output: Input data in JSON format

[1533] Specific operation: When the user enters information into each form field and presses the "Submit" button, the device converts the entered data into JSON format and sends it to the server as an HTTP POST request.

[1534] Step 2:

[1535] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body.

[1536] Input: HTTP POST request

[1537] Output: User input data in JSON format

[1538] Specific operation: The server reads JSON data from the request body, which includes information about the user's preferences, budget, and location.

[1539] Step 3:

[1540] The server generates requests for the generative artificial intelligence based on the user's input data.

[1541] Input: User input data in JSON format

[1542] Output: Request (prompt) for generative artificial intelligence

[1543] Specific operation: The server extracts user input data and generates a prompt message based on it. This prompt message includes information about the user's preferences, budget, and location.

[1544] Step 4:

[1545] The server sends a request to the generative artificial intelligence API based on the generated prompt message.

[1546] Input: Request (prompt) for generative artificial intelligence

[1547] Output: Response data from generative artificial intelligence

[1548] Specific operation: The server issues an HTTP POST request to the generative artificial intelligence API endpoint and sends a prompt message.

[1549] Step 5:

[1550] The generative artificial intelligence generates the optimal outing plan based on the request received from the server and responds to the server.

[1551] Input: Request (prompt) for generative artificial intelligence

[1552] Output: Optimal outing plan (text format)

[1553] Specific operation: The generative artificial intelligence analyzes the prompt text, generates the most suitable outing plan based on the user's conditions, and sends it back to the server.

[1554] Step 6:

[1555] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[1556] Input: Response data from a generative artificial intelligence (text format)

[1557] Output: Response data in JSON format

[1558] Specific operation: The server receives the response data sent back from the generative artificial intelligence and converts it into JSON format.

[1559] Step 7:

[1560] The server sends the converted JSON-formatted response data to the user's terminal.

[1561] Input: Response data in JSON format

[1562] Output: Sent to the user's terminal as an HTTP response

[1563] Specific operation: The server uses the converted JSON data to generate an HTTP response and sends that response to the user's terminal.

[1564] Step 8:

[1565] The user terminal parses the JSON data received from the server and displays it on the user interface.

[1566] Input: Response data in JSON format

[1567] Output: Optimal outing plan displayed in the user interface

[1568] Specific operation: The user's terminal parses the received JSON data and displays it in the user interface in the appropriate format. This allows the user to see the outing plan that best suits their preferences and conditions.

[1569] Through the processing steps described above, users can easily obtain the outing plan that best suits their preferences and circumstances.

[1570] 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.

[1571] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user's terminal.

[1572] System Overview

[1573] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[1574] User input

[1575] First, the user accesses a web interface using their device (smartphone or PC). They then enter their preferences (e.g., love nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine to collect the user's emotional data (e.g., tone of voice and facial expressions). This data is converted into JSON format by the device and sent to the server as an HTTP POST request.

[1576] Server-side processing

[1577] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Subsequently, a generative artificial intelligence generates a request based on this information.

[1578] The request instructs the system to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the generative artificial intelligence API.

[1579] Responses and processing of generative artificial intelligence

[1580] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1581] Display on the user's terminal

[1582] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1583] Specific examples

[1584] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[1585] Outing plans:

[1586] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1587] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1588] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1589] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1590] budget:

[1591] Transportation expenses: 3000 yen

[1592] Food and drinks: 3000 yen

[1593] Admission fee and other charges: 3000 yen

[1594] Other contingency funds: 1000 yen

[1595] It can be seen that such detailed outing plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data.

[1596] The above is one embodiment of the present invention. This system allows users to easily obtain the travel plan best suited to them, significantly reducing the time and effort required when planning a trip. Furthermore, by combining it with an emotion engine, plans that take the user's emotions into consideration can be provided, enabling the generation of even more satisfying plans.

[1597] The following describes the processing flow.

[1598] Step 1:

[1599] Users access their devices and enter their preferences, budget, and location information via a web interface.

[1600] Step 2:

[1601] The device uses an emotion engine to collect emotional data from the user's voice and facial expressions. For example, it uses the device's microphone and camera to analyze what emotions the user is expressing when inputting data.

[1602] Step 3:

[1603] The terminal converts the entered information and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[1604] Step 4:

[1605] The server receives an HTTP POST request and extracts JSON data from the request body. This data includes user preferences, budget, location information, and sentiment data.

[1606] Step 5:

[1607] The server generates a request to the generative artificial intelligence based on the extracted data. This request instructs the AI ​​to generate the optimal outing plan based on the user's input information and emotional data.

[1608] Step 6:

[1609] The server sends a request to the generative artificial intelligence API.

[1610] Step 7:

[1611] The generative artificial intelligence receives a request from the server and generates the optimal plan according to the instructions. The generated plan is returned to the server as response data in text format.

[1612] Step 8:

[1613] The server receives the response data sent from the generative artificial intelligence, converts it to JSON format, and prepares to send it to the terminal.

[1614] Step 9:

[1615] The terminal receives JSON data sent from the server, parses the data, and displays it on the user interface.

[1616] Step 10:

[1617] Users can view the outing plan displayed on their device and create a specific travel plan based on its contents.

[1618] (Example 2)

[1619] 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".

[1620] Conventional travel plan creation systems could provide plans based on basic information such as user preferences, budget, and location, but they struggled to create plans that took into account the user's emotional state. Therefore, there is a need to automatically generate highly satisfying plans that consider the user's emotions. Furthermore, a system is needed that efficiently processes multiple pieces of information entered by the user and sends appropriate requests to a generative artificial intelligence.

[1621] 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.

[1622] In this invention, the server includes means for receiving user input data, means for collecting user emotion data, means for sending requests to a generative artificial intelligence based on the user input data and emotion data, and means for receiving responses from the generative artificial intelligence and sending response data to the user terminal. This makes it possible to automatically generate an optimal travel plan that takes into account the user's preferences, budget, location, and emotion data.

[1623] "User input data" refers to data such as preferences, budget, and destinations that users provide as information necessary for generating travel plans.

[1624] "Emotional data" refers to data that indicates a user's emotional state, and is collected from sources such as voice and facial expressions.

[1625] "Generative artificial intelligence" refers to an artificial intelligence system that automatically generates optimal travel plans based on user input data and emotional data.

[1626] The "means of sending requests" refer to a mechanism for instructing a generative artificial intelligence to generate the optimal plan based on user input data and emotional data.

[1627] "Response data" refers to data about travel plans provided by generative artificial intelligence, which is transmitted to the user's terminal via a server.

[1628] A "user terminal" is an electronic device used by a user to access the system and view travel plans.

[1629] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system receives user input data and emotion data, sends a request to a generative artificial intelligence system based on this data, and provides the generated plan to the user's terminal. A specific embodiment of this system is described below.

[1630] System Overview

[1631] This system generates an optimal outing plan based on user input regarding preferences, budget, and location, and further utilizes an emotion engine that recognizes the user's emotions. A specific implementation is described below.

[1632] User input

[1633] First, the user accesses a web interface using their device (smartphone or PC). Here, the user enters their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into a form. The device also uses an emotion engine (e.g., general emotion recognition software) to collect the user's emotional data (e.g., tone of voice and facial expressions). This collected data is converted to JSON format by the device and sent to the server as an HTTP POST request.

[1634] Server-side processing

[1635] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. Based on this information, the server generates a request to the generative artificial intelligence. This request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server then sends this request to the generative artificial intelligence's API.

[1636] Responses and processing of generative artificial intelligence

[1637] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is sent back to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it back to the terminal.

[1638] Display on the user's terminal

[1639] The user's terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1640] Specific examples

[1641] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, a generative artificial intelligence might generate a plan like the following:

[1642] Outing plans:

[1643] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1644] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1645] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1646] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1647] budget:

[1648] Transportation expenses: 3000 yen

[1649] Food and drinks: 3000 yen

[1650] Admission fee and other charges: 3000 yen

[1651] Other contingency funds: 1000 yen

[1652] Examples of prompts for generative artificial intelligence

[1653] Use prompts like the following to generate outing plans based on user preferences, budget, location, and sentiment data:

[1654] User preference: Loves nature

[1655] User's hobby: Hiking

[1656] Budget: 10,000 yen

[1657] Location: Hakone

[1658] Emotional data: Looks like they're having fun.

[1659] Based on this information, please generate the optimal outing plan.

[1660] Such detailed travel plans are provided by reflecting not only the user's preferences, budget, and location, but also their emotional data. This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining this with an emotional engine, plans that take the user's emotions into consideration can be provided, resulting in the generation of even more satisfying travel plans.

[1661] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1662] Step 1:

[1663] The user accesses a web interface and enters information about their preferences, budget, and location.

[1664] Specific actions:

[1665] The user opens a browser and accesses the system's web interface.

[1666] The user enters their preferences (e.g., likes nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone) into an input form.

[1667] Input: Data about the user's preferences, budget, and location.

[1668] Output: Data on user preferences, budget, and location.

[1669] Step 2:

[1670] The device activates an emotion engine and collects emotional data from the user's voice tone and facial expressions.

[1671] Specific actions:

[1672] Once the user completes their input, the emotion engine built into the device will activate.

[1673] The device analyzes the user's voice tone and facial expressions in real time and collects emotional data (e.g., sounds happy, sounds sad).

[1674] Input: User's voice and facial expression data.

[1675] Output: Sentiment data.

[1676] Step 3:

[1677] The device converts the user's input data and sentiment data into JSON format and sends it to the server as an HTTP POST request.

[1678] Specific actions:

[1679] The device then compiles the user's preferences, budget, location information, and sentiment data that were collected earlier.

[1680] Convert this information into JSON format (e.g., {"like":"Nature","budget":10000,"location":"Hakone","emotion":"Looks fun"}).

[1681] The device sends this JSON data to the server as an HTTP POST request.

[1682] Input: User preferences, budget, location information, and sentiment data.

[1683] Output: JSON data sent to the server.

[1684] Step 4:

[1685] The server receives an HTTP POST request sent from the terminal and extracts the JSON data from it.

[1686] Specific actions:

[1687] The server receives an HTTP POST request.

[1688] The server extracts JSON data from the request body.

[1689] Input: JSON data sent from the terminal.

[1690] Output: Extracted user preferences, budget, location, and sentiment data.

[1691] Step 5:

[1692] The server generates a request to the generative artificial intelligence based on the extracted data.

[1693] Specific actions:

[1694] The server analyzes the extracted data (preferences, budget, location, emotions).

[1695] Based on the analysis results, a prompt message is created to send to the generative AI (e.g., "User preference: likes nature, User hobby: hiking, Budget: 10,000 yen, Location: Hakone, Sentiment data: seems fun. Based on this information, please generate the best outing plan.").

[1696] Input: Extracted user preferences, budget, location, and sentiment data.

[1697] Output: A prompt message for the generative artificial intelligence.

[1698] Step 6:

[1699] The server sends a request to the generative artificial intelligence API.

[1700] Specific actions:

[1701] The server sends the prompt message to the generative artificial intelligence API.

[1702] Input: A prompt message for a generative artificial intelligence system.

[1703] Output: Sending a request to a generative artificial intelligence.

[1704] Step 7:

[1705] The generative artificial intelligence generates an outing plan based on the request and sends the response data back to the server.

[1706] Specific actions:

[1707] Generative artificial intelligence analyzes the received prompt text.

[1708] Based on the analysis results, the system generates the optimal outing plan.

[1709] The generated outing plan is sent back to the server as response data (e.g., "Outing Plan: 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trails along the old highway...").

[1710] Input: A request to a generative artificial intelligence.

[1711] Output: The generated outing plan.

[1712] Step 8:

[1713] The server receives response data from the generative artificial intelligence and converts it into JSON format.

[1714] Specific actions:

[1715] The server receives response data from the generative artificial intelligence.

[1716] Convert the received response data into JSON format (e.g., {"plan":"1. Arrive at Hakone-Yumoto Station in the morning.."}).

[1717] Input: Response data from a generative artificial intelligence.

[1718] Output: Response data in JSON format.

[1719] Step 9:

[1720] The server prepares to send the converted JSON data to the user's terminal and then sends it.

[1721] Specific actions:

[1722] The server prepares to send response data in JSON format to the user's terminal.

[1723] Once preparations are complete, JSON data will be sent to the user's terminal as an HTTP response.

[1724] Input: Response data in JSON format.

[1725] Output: Send to the user's terminal.

[1726] Step 10:

[1727] The user terminal receives JSON data sent back from the server, parses that data, and displays it on the user interface.

[1728] Specific actions:

[1729] The user's browser receives the JSON data sent back from the server.

[1730] Browser scripts parse the data and format it into a highly readable format.

[1731] The user interface displays details of the outing plan (e.g., which tourist spots to visit, which restaurants to eat at, etc.).

[1732] Input: JSON data returned from the server.

[1733] Output: Details of the outing plan displayed in the user interface.

[1734] (Application Example 2)

[1735] 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".

[1736] Conventional autonomous vehicles have not adequately offered travel plans and destination suggestions tailored to the individual needs of passengers, such as their emotions, preferences, and budgets. In particular, there have been many technical challenges in suggesting optimal routes and destinations that take into account the emotional state of passengers. Furthermore, there has been a lack of means to utilize collected emotional data in real time to improve the passenger experience. Therefore, the present invention aims to solve these technical challenges by providing a system that offers individually customized destination plans and routes based on the user's emotional data and preferences.

[1737] 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 user input data, means for sending a request to a generative artificial intelligence based on the user input data and emotion data, means for receiving a response from the generative artificial intelligence and transmitting the response data to a user terminal or in-vehicle display, and means for collecting passenger emotion data using a camera and microphone. This makes it possible to suggest optimal travel plans and destinations according to the passenger's emotional state, preferences, and budget.

[1738] Definitions of important words

[1739] "User input data" refers to information provided by users, such as their personal preferences, budget, and places they wish to visit.

[1740] "Emotional data" refers to information about a user's emotional state, obtained from their facial expressions, tone of voice, and other similar data.

[1741] "Generative artificial intelligence" refers to an artificial intelligence system that generates new data or plans based on input data.

[1742] "Means of sending requests" refers to means that have the function of sending user input data and emotional data to a generative artificial intelligence system.

[1743] "Response data" refers to data that a generative artificial intelligence generates based on a user's request and sends back to the server.

[1744] "User terminal" refers to devices such as smartphones, tablets, and PCs used by the user.

[1745] "In-vehicle display" refers to a screen installed inside an autonomous vehicle for displaying information.

[1746] "Camera and microphone" refers to video and audio input devices used to capture the user's facial expressions and voice.

[1747] Modes for carrying out the invention

[1748] This invention relates to a system that automatically generates outing plans that take into account the user's emotions. The system has the function of receiving user input data and emotion data, sending a request to a generative artificial intelligence based on that data, and providing the generated plan to the user terminal or in-vehicle display.

[1749] System Overview

[1750] This system consists mainly of the following means:

[1751] 1. Means for receiving user input data

[1752] 2. Means for collecting emotional data using cameras and microphones

[1753] 3. Means for sending requests to a generative artificial intelligence based on user input data and sentiment data.

[1754] 4. Means for transmitting response data from a generative artificial intelligence to a user terminal or in-vehicle display.

[1755] User input

[1756] First, the user boards an autonomous vehicle and uses an interface installed inside the vehicle to input their preferences (e.g., loves nature), budget (e.g., 10,000 yen), and destination (e.g., Hakone). Additionally, emotional data such as the user's facial expressions and voice tone are collected via the camera and microphone. This data is converted to JSON format by the user's device and sent to the server as an HTTP POST request.

[1757] Server-side processing

[1758] The server receives an HTTP POST request sent from the terminal and extracts JSON data from the request body. This JSON data includes user preferences, budget, location information, and sentiment data. The server then generates a request to a generative artificial intelligence (AI) based on this information. The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data. The server sends this request to the API of the generative AI (e.g., a GPT model).

[1759] Responses and processing of generative artificial intelligence

[1760] The generative artificial intelligence generates the optimal outing plan based on the request received from the server. This generated plan is returned to the server as text-based response data. The server converts the received response data into JSON format and prepares to send it again to the user terminal or in-vehicle display.

[1761] Display on the user's terminal

[1762] The user terminal and in-vehicle display receive JSON data sent back from the server, parse the data, and display it on the user interface. In this way, the user can see the outing plan that best suits their preferences, conditions, and even their emotions.

[1763] Specific examples

[1764] For example, if a user inputs "I like nature, my hobby is hiking, my budget is 10,000 yen, and the location is Hakone," and the emotion engine determines that the user seems to enjoy it, the generative AI will generate a plan using prompts like the following:

[1765] Based on the user's preferences (nature lover), budget (10,000 yen), location (Hakone), and emotional data (enjoyable), please generate the optimal outing plan.

[1766] The generated outing plan includes detailed activity suggestions, such as the following:

[1767] Outing plans:

[1768] 1. Arrive at Hakone-Yumoto Station in the morning and explore the hiking trail along the old highway. Rest areas and cafes are located along the way for your enjoyment.

[1769] 2. After hiking, relax in a hot spring. Have lunch at a local restaurant and enjoy delicious local cuisine.

[1770] 3. In the afternoon, we will visit art museums and nature parks in Hakone. In particular, based on emotional data, this plan emphasizes relaxation and includes visits to the Hakone Glass Forest Museum and a footbath cafe.

[1771] 4. In the evening, relax while watching the sunset around Lake Ashi, then take the free shuttle bus back to Hakone-Yumoto Station.

[1772] budget:

[1773] Transportation expenses: 3000 yen

[1774] Food and drinks: 3000 yen

[1775] Admission fee and other charges: 3000 yen

[1776] Other contingency funds: 1000 yen

[1777] This system allows users to easily obtain the most suitable travel plan, significantly reducing the time and effort required for travel planning. Furthermore, by combining it with an emotion engine, plans that take user emotions into consideration are provided, resulting in the generation of even more satisfying travel plans.

[1778] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1779] Program processing steps

[1780] Step 1:

[1781] The user inputs their preferences, budget, and destination using an in-vehicle interface. The terminal also uses a camera and microphone to collect emotional data such as the user's facial expressions and tone of voice (Input: User preferences, budget, location, emotional data), (Output: Collected input data and emotional data). This data is converted to JSON format and sent to the server as an HTTP POST request (Operation: JSON conversion and HTTP POST request transmission).

[1782] Step 2:

[1783] The server receives an HTTP POST request sent from the terminal (Input: HTTP POST request), (Output: JSON data). JSON data is extracted from the request body (Operation: Request parsing and JSON data extraction). This JSON data includes user preferences, budget, location information, and sentiment data (Operation: JSON parsing).

[1784] Step 3:

[1785] The server generates a request to a generative artificial intelligence (e.g., a GPT model) based on the JSON data (input: JSON data), (output: AI request). The request instructs the AI ​​to generate the optimal plan based on the user's input information and sentiment data (action: request generation).

[1786] Step 4:

[1787] The server sends a request to the generative artificial intelligence API (input: AI request), (output: AI response). The generative artificial intelligence generates the optimal outing plan based on the request received from the server (operation: AI-generated plan).

[1788] Step 5:

[1789] The generative artificial intelligence generates a plan and returns it to the server in text format (input: AI request), (output: response data in text format). The server converts the received response data into JSON format (operation: JSON conversion of response data).

[1790] Step 6:

[1791] The server sends the converted JSON data back to the terminal or in-vehicle display (input: JSON response data), (output: data sent to the user terminal or in-vehicle display). The user terminal or in-vehicle display parses the received data and displays it on the user interface (operation: JSON data parsing and display).

[1792] Step 7:

[1793] Users can view outing plans that best suit their preferences, conditions, and even emotions (Input: Analyzed data), (Output: Display to the user). Guidance based on the plan is provided via terminals or in-vehicle displays (Operation: Plan guidance).

[1794] 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.

[1795] 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.

[1796] 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.

[1797] 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.

[1798] 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.

[1799] 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.

[1800] 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.

[1801] 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.

[1802] 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."

[1803] 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.

[1804] 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.

[1805] 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.

[1806] 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.

[1807] 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.

[1808] 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.

[1809] 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.

[1810] 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.

[1811] 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.

[1812] 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.

[1813] 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.

[1814] 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 as being incorporated by reference.

[1815] The following is further disclosed regarding the embodiments described above.

[1816] (Claim 1)

[1817] A means of receiving user input data,

[1818] A means for sending a request to a generative artificial intelligence based on the user's input data,

[1819] A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data to the user terminal,

[1820] A system that includes this.

[1821] (Claim 2)

[1822] The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user input data received.

[1823] (Claim 3)

[1824] The system according to claim 1, further comprising means for generating prompts that include information about the user's preferences, budget, and location when generating requests to the generative artificial intelligence.

[1825] "Example 1"

[1826] (Claim 1)

[1827] A means of receiving user input data,

[1828] A means for converting the user's input data into JSON format and sending it to the server,

[1829] The server generates a prompt message for a generative artificial intelligence based on the user's input data and sends a request;

[1830] A means for receiving a response from the aforementioned generative artificial intelligence, converting the response data into JSON format, and sending it to the user terminal,

[1831] The user terminal includes means for analyzing response data and displaying it on the user interface,

[1832] A system that includes this.

[1833] (Claim 2)

[1834] The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user input data received.

[1835] (Claim 3)

[1836] The system according to claim 1, further comprising means for generating prompts that include information about the user's preferences, budget, and location when generating requests to the generative artificial intelligence.

[1837] "Application Example 1"

[1838] (Claim 1)

[1839] A means of receiving user input data,

[1840] A means for sending a request to a generative artificial intelligence based on the user's input data,

[1841] A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data to the user terminal,

[1842] A means for generating a prompt containing information about a content generation service based on user input data,

[1843] A means for generating and displaying an outing plan based on the aforementioned prompt,

[1844] A system that includes this.

[1845] (Claim 2)

[1846] The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user input data received.

[1847] (Claim 3)

[1848] The system according to claim 1, further comprising means for generating prompts that include information about the user's preferences, budget, and location when generating requests to the generative artificial intelligence.

[1849] "Example 2 of combining an emotion engine"

[1850] (Claim 1)

[1851] A means of receiving user input data,

[1852] A means for collecting the aforementioned user's emotional data,

[1853] A means for sending a request to a generative artificial intelligence based on the user's input data and emotion data,

[1854] A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data to the user terminal,

[1855] A system that includes this.

[1856] (Claim 2)

[1857] The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user's input data and sentiment data received.

[1858] (Claim 3)

[1859] The system according to claim 1, further comprising means for generating prompts that include user preferences, budget, location information and sentiment data when generating requests to the generative artificial intelligence.

[1860] "Application example 2 when combining with an emotional engine"

[1861] (Claim 1)

[1862] A means of receiving user input data,

[1863] A means for sending a request to a generative artificial intelligence based on the user's input data and emotion data,

[1864] A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data to a user terminal or in-vehicle display,

[1865] A means of collecting passenger emotional data using cameras and microphones,

[1866] A system that includes this.

[1867] (Claim 2)

[1868] The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user's input data and sentiment data received.

[1869] (Claim 3)

[1870] The system according to claim 1, further comprising means for generating a prompt sentence that includes information about the user's preferences, budget, location, and sentiment data when generating a request to the generative artificial intelligence. [Explanation of Symbols]

[1871] 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 user input data, A means for sending a request to a generative artificial intelligence based on the user's input data, A means for receiving a response from the aforementioned generative artificial intelligence and transmitting the response data to the user terminal, A system that includes this.

2. The system according to claim 1, further comprising means for generating a request to a generative artificial intelligence based on the user input data received.

3. The system according to claim 1, further comprising means for generating prompts that include information about the user's preferences, budget, and location when generating requests to the generative artificial intelligence.

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