system

Abstract

Provide a system. The method includes: receiving a text input from a user indicating a scenic image; means for transmitting the text input to a landscape image generation AI to generate a landscape image; A means for searching for similar existing places based on the generated landscape image; means for providing the search results to a user; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In today's busy lifestyles, users often spend a great deal of time and effort deciding on specific destinations and tourist spots when planning a trip. It is particularly difficult for users with only a vague image of a landscape to find a specific travel destination that matches that image. Conventional travel guides and internet search engines lack the means to quickly identify destinations that perfectly match the user's desired landscape. Therefore, a system that can link a user's vague image of a landscape to a specific travel destination is needed. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention proposes a system that includes a means for receiving text input indicating a landscape image from a user, a means for transmitting the text input to a landscape image generation AI to generate a landscape image, a means for searching for similar existing places based on the generated landscape image, and a means for providing the search results to the user. This system allows a user to quickly obtain existing travel destination candidates that match a vague landscape image simply by inputting it in text. As a result, the user's travel planning becomes more efficient and it becomes easier to decide on places they actually want to visit.

[0006] "User" refers to an individual who intends to use the system to make travel plans.

[0007] "Landscape image" refers to the visual impression of a particular natural landscape or tourist spot.

[0008] "Text input" refers to character string information used by the user to describe an image of the scenery they would like to travel to.

[0009] "Landscape image generation AI" refers to an artificial intelligence model that generates corresponding visual images from text input.

[0010] "Means" refers to methods or techniques for performing a specific function or role.

[0011] "Generated landscape image" refers to a visual image generated by landscape image generation AI.

[0012] "Existing places" refers to tourist attractions and scenic spots that exist in real geographical locations.

[0013] "Searching means" refers to methods and techniques for identifying similar existing places based on the generated landscape image.

[0014] "Means of providing" refers to the methods and technologies for displaying or notifying the user of search results. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, 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), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 1, a 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.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the 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.

[0029] 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 of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 2, in the data processing device 12, a specific process 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" according to the technology of the present 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 process 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.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0037] System Configuration

[0038] User operations

[0039] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0040] Terminals that can be used include devices such as PCs, smartphones, and tablets.

[0041] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[0042] Device operation

[0043] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[0044] Server Processing

[0045] 3. The server analyzes the received text data and sends it to the landscape image generation AI.

[0046] In this process, the text data is formatted into the appropriate format.

[0047] 4. The landscape image generation AI on the server generates a landscape image based on the text data sent.

[0048] The generated landscape images are stored in the server.

[0049] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing travel destinations that are similar to this image.

[0050] Image recognition algorithms identify tourist spots with similar landscapes.

[0051] Example: Based on the generated cherry blossom scenery, "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture will be searched.

[0052] Providing search results

[0053] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[0054] Displaying the results

[0055] 7. The device analyzes the search results received from the server and displays the results to the user.

[0056] Possible display methods include list format and marker display on a map.

[0057] Example: Information about "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0058] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[0059] Specific examples

[0060] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0061] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0062] 2. The device sends this text to the server.

[0063] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0064] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0065] 5. The server sends these search results and detailed information to the user's device.

[0066] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0067] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0068] The processing flow will be explained below.

[0069] Step 1:

[0070] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0071] Example: Enter "A quiet place with a view of the lake and mountains."

[0072] Step 2:

[0073] The user clicks the "Submit" button.

[0074] Step 3:

[0075] The device receives the user's text input and sends it to the server as an HTTP POST request.

[0076] The transmitted data includes the text prompt entered by the user.

[0077] Step 4:

[0078] The server receives the incoming request and parses the prompt.

[0079] Step 5:

[0080] The server analyzes the text prompt and sends it to the landscape image generation AI, which then generates a corresponding landscape image.

[0081] Step 6:

[0082] The landscape image generation AI in the server generates landscape images based on the user's prompts.

[0083] Example: Generate a landscape image based on the text "A quiet place with a view of a lake and mountains."

[0084] The generated image is stored in the server.

[0085] Step 7:

[0086] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[0087] Step 8:

[0088] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[0089] Example: Detect potential locations such as "Fuji Five Lakes" and "Lake Biwa."

[0090] Step 9:

[0091] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[0092] Step 10:

[0093] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[0094] Step 11:

[0095] The server sends the formatted search results to the user's terminal as an HTTP response.

[0096] Step 12:

[0097] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[0098] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[0099] Step 13:

[0100] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[0101] Example 1

[0102] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0103] Conventional travel planning support systems assume that users know specific locations, so when users want to choose a travel destination based on a vague image of scenery, it is difficult to find an appropriate destination. Also, there is a lack of a mechanism that allows users to easily realize their ideal scenery and suggest specific travel destinations based on that.

[0104] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0105] In this invention, the server includes means for receiving text input indicating a scenic image from a user, means for transmitting the text input to the server, means for formatting the text input into an appropriate format and transmitting it to a scenic image generation AI, means for storing the scenic image generated by the scenic image generation AI in a database, means for analyzing the generated scenic image with an image recognition algorithm and searching for similar existing places, means for adding detailed information about each existing place to the search results and transmitting them to the user's terminal, and means for displaying the search results to the user, thereby enabling a user to quickly find a specific travel destination from a vague scenic image and efficiently plan a trip.

[0106] "User" means an individual or organization that uses this system to make travel plans.

[0107] "Text input" is a character string representing a landscape image that is input by the user through the terminal.

[0108] A "terminal" is an electronic device used by a user to input text, and includes PCs, smartphones, tablets, etc.

[0109] A "server" is a computer system that receives and processes text input submitted by a user.

[0110] "Transmitting means" refers to the communications protocol and associated technology used to transmit the text input to the server.

[0111] The "formatting method" is the process of converting the received text input into a form that can be processed by the landscape image generation AI.

[0112] "Landscape image generation AI" is an artificial intelligence that generates landscape images based on text input.

[0113] A "database" is a data storage system used within the server to store the generated landscape images.

[0114] "Image recognition algorithm" is a technology for analyzing generated landscape images and identifying similar existing places.

[0115] The "searching means" is a process that uses image recognition algorithms to identify similar existing places.

[0116] "Detailed information" refers to specific information such as location, access methods, tourist information, etc. included in the search results.

[0117] The "display means" is a method for visually displaying the search results on the user's terminal.

[0118] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0119] System Configuration

[0120] User operations

[0121] The user inputs an image of the scenery they want to travel to in text format into the terminal. The terminal can be a PC, smartphone, tablet, or other device. For example, the user might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom."

[0122] Device operation

[0123] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[0124] Server Processing

[0125] The server parses the received text data and sends it to the landscape image generation AI. During this process, the text data is formatted into an appropriate format. For example, a Python library (such as Flask) is used to format the data.

[0126] The landscape image generation AI (inside the server) generates landscape images based on the transmitted text data. For example, it uses a generative AI model such as GPT-3 (registered trademark) or DALLE-2. The generated landscape images are stored in a database (e.g., MySQL (registered trademark)) on the server.

[0127] The server then passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm uses OpenCV or similar. For example, based on the generated cherry blossom landscape, travel destinations identified include Takato Castle Park in Nagano Prefecture and Hirosaki Park in Aomori Prefecture.

[0128] Providing search results

[0129] The server formats the search results, adds detailed information about each existing location (location, access method, tourist information, etc.), and sends it to the user's device. The results and detailed information are formatted in JSON format using an HTTP response and sent.

[0130] Displaying the results

[0131] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0132] User's travel plans

[0133] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0134] Specific examples

[0135] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0136] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0137] 2. The device sends this text to the server.

[0138] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0139] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0140] 5. The server sends these search results and detailed information to the user's device.

[0141] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0142] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0144] Step 1:

[0145] The user inputs the image of the scenery they want to travel to in text format into the device. For example, they might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom." The input data is in text format, allowing the user to freely express the scenery they want.

[0146] Input: Text showing a landscape image

[0147] Output: Text data

[0148] Step 2:

[0149] The terminal sends the entered text to the server using a standard communication protocol such as an HTTP POST request, including the text data in the request body and sending it to the appropriate endpoint.

[0150] Input: Text data

[0151] Output: HTTP POST request to the server

[0152] Step 3:

[0153] The server parses the received text data, adjusts the format, and sends it to the landscape image generation AI. In this process, the text data is converted to JSON format and the appropriate API call is made.

[0154] Input: Text data

[0155] Output: JSON format data

[0156] Step 4:

[0157] The landscape image generation AI (on the server) generates landscape images based on the submitted JSON-formatted text data. The generation uses cutting-edge generative AI models (such as GPT-3 and DALLE-2). The generated landscape images are stored in a database on the server.

[0158] Input: JSON format text data

[0159] Output: Generated landscape image

[0160] Step 5:

[0161] The server then passes the generated landscape image to an image recognition algorithm, such as OpenCV, to search for existing travel destinations that are similar to the image. This process calculates the similarity between the generated landscape image and existing images in the database.

[0162] Input: Generated landscape image

[0163] Output: A list of similar travel destinations

[0164] Step 6:

[0165] The server adds detailed information about each existing location (location, access method, tourist information, etc.) to the search results and sends them to the user's device. The detailed information is retrieved from the database and formatted in JSON format along with the search results.

[0166] Input: A list of similar destinations

[0167] Output: Search results with detailed information

[0168] Step 7:

[0169] The device analyzes the search results received from the server and displays them to the user. The results can be displayed in list format or as markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture can be displayed in list format.

[0170] Input: Search results with detailed information

[0171] Output: Search results displayed to the user

[0172] Step 8:

[0173] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0174] Input: Search results displayed to the user

[0175] Output: User selected travel destinations and travel plans

[0176] (Application example 1)

[0177] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0178] In conventional travel suggestion systems, users had to specify specific locations and tourist attractions, making it difficult to find a travel destination based on a vague image. Furthermore, users had to refer to external resources to learn more about the suggested travel destinations, which took time to gather information. Furthermore, there was no way for users to visually check the suggested travel destinations in advance, which could cause anxiety when planning a trip.

[0179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0180] In this invention, the server includes means for receiving a text input indicating a scenic image from a user, means for transmitting the text input to a scenic image generation AI to generate a scenic image, means for searching for similar existing places based on the generated scenic image, means for providing the search results to the user, and means for the user to perform a virtual preview of the suggested places. This allows the user to quickly find a travel destination even from a vague image, and also allows the user to visually check the suggested places in advance.

[0181] The "text input indicating a scenery image" is character information that expresses in words the characteristics of the scenery or place that the user wants to travel to.

[0182] "Landscape image generation AI" refers to artificial intelligence that creates synthetic or generated landscape images based on input text information.

[0183] "Similar existing locations" are actual tourist attractions or natural landscapes that resemble the landscapes generated by the landscape image generation AI.

[0184] "Search results" are information on specific travel destinations suggested to users based on landscape images generated by the landscape image generation AI.

[0185] "Virtual Preview" is a feature that allows users to visually check suggested travel destinations in advance using virtual reality technology.

[0186] The embodiment for carrying out the invention comprises the following steps: The system comprises a user, a terminal, and a server.

[0187] First, the user uses a device such as a smartphone or smart glasses to input a text image of the scenery they want to travel to. This input does not refer to a specific location, but rather to a vague image, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains," expressing the user's desire in words.

[0188] Next, the device sends the entered text to the server using a standard communication protocol such as an HTTP POST request. The server receives this text data and sends it to a landscape image generation AI (generative AI model). The AI ​​generates a landscape image based on the received text data. The generated landscape image is saved on the server.

[0189] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. Specifically, the image recognition algorithm identifies tourist spots with similar landscapes. For example, if the search term is "Japanese countryside scenery with beautiful cherry blossoms in full bloom," it will retrieve information such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0190] The server then formats the search results, adds detailed information about each existing location (such as location, access methods, and tourist information), and sends them to the user's device. The device then analyzes the received search results and displays them to the user. Possible display methods include a list format or markers on a map. The user can virtually preview the suggested travel destinations using smart glasses or the AR function of their smartphone. This allows the user to decide which places to actually visit based on the provided information and proceed with their travel planning.

[0191] For example, if a user types "a quiet place with a view of a lake and mountains," the device will send this text to the server. The server will then send the received text to a landscape image generation AI to create a landscape image. The server will then analyze the generated landscape image using an image recognition algorithm to obtain information on travel destinations such as the Fuji Five Lakes and Lake Biwa. The server will then send these search results and detailed information to the user's device, which will then display the results to the user. Based on this information, the user can select a travel destination and enjoy a virtual preview of the suggested locations using the smart glasses.

[0192] Example prompt sentence:

[0193] "A user inputs 'a beautiful beach with a sunset.' Send this information to a generative AI model to generate the ideal landscape image."

[0194] "Please suggest tourist spots (e.g., Shonan coast and sandy beaches) based on the generated landscape images."

[0195] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0196] Step 1:

[0197] The user inputs an image of the scenery they would like to travel to in text format. Using a device such as a smartphone or smart glasses, they input specific text information such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains." This input data is sent to the server in the next step.

[0198] Step 2:

[0199] The terminal sends the text entered by the user to the server using a standard communication protocol such as an HTTP POST request. A request is generated to send the input data to the server, and the text data is sent to the server as input.

[0200] Step 3:

[0201] The server receives the input text data and sends it to the landscape image generation AI. The server formats the received text data into an appropriate format and then sends it to the generative AI model as a prompt. This prompt is in the format of "The user inputs 'A beautiful Japanese countryside landscape with cherry blossoms in full bloom.' Please send this information to the generative AI model to generate an ideal landscape image."

[0202] Step 4:

[0203] The landscape image generation AI generates landscape images based on the text data sent to it. The generated landscape images are stored on the server. In this process, the AI ​​model analyzes the content of the text and generates image data corresponding to that content as output.

[0204] Step 5:

[0205] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm analyzes the landscape image and searches a database for similar tourist spots. The search results output specific travel destination information, such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0206] Step 6:

[0207] The server formats the search results, adds detailed information about each existing place (location, access, tourist information, etc.), and sends it to the user's device. The detailed information retrieved from the database is added, and the formatted results are sent to the device.

[0208] Step 7:

[0209] The device analyzes the search results received from the server and displays them to the user in various ways, such as as a list or as markers on a map, and specific travel destination information is displayed on the device screen.

[0210] Step 8:

[0211] Users can virtually preview the proposed travel destinations. Using smart glasses or the AR function of their smartphone, they can virtually experience the proposed locations. Based on this information, users can decide which places to visit and move forward with their trip planning.

[0212] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0213] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[0214] System Configuration

[0215] User operations

[0216] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0217] Terminals that can be used include PCs, smartphones, and tablets.

[0218] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[0219] Device operation

[0220] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[0221] Server Processing

[0222] 3. The server analyzes the received text data and sends it to the emotion engine.

[0223] The emotion engine analyzes the user's emotions from text input and adjusts prompts to the landscape image generation AI based on those emotions.

[0224] Example: If the user's input includes an emotion such as "I want to relax," the landscape image generation AI is instructed to generate a relaxing landscape image.

[0225] 4. The landscape image generation AI in the server generates landscape images based on the prompts adjusted from the emotion engine.

[0226] Example: "Relaxing lake scene" is generated.

[0227] The generated landscape images are stored in the server.

[0228] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing places that resemble this image.

[0229] Image recognition algorithms identify tourist spots with similar landscapes.

[0230] Example: Based on the generated lake scenery, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido are searched.

[0231] Providing search results

[0232] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[0233] Displaying the results

[0234] 7. The device analyzes the search results received from the server and displays the results to the user.

[0235] Possible display methods include list format and marker display on a map.

[0236] Example: Information about Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[0237] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[0238] Specific examples

[0239] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[0240] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[0241] 2. The device sends this text to the server.

[0242] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[0243] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the landscape image generation AI.

[0244] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[0245] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[0246] 7. The server sends these search results and detailed information to the user's device.

[0247] 8. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0248] The system allows users to receive emotion-based travel destination suggestions and efficiently plan trips that meet their personal needs.

[0249] The processing flow will be explained below.

[0250] Step 1:

[0251] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0252] For example, enter "A quiet place with a view of the lake and mountains."

[0253] Step 2:

[0254] The user clicks the "Submit" button.

[0255] Step 3:

[0256] The device receives the user's text input and sends it to the server as an HTTP POST request.

[0257] The transmitted data includes the text prompt entered by the user.

[0258] Step 4:

[0259] The server receives the incoming request and parses the prompt.

[0260] Step 5:

[0261] The server sends the analyzed text prompt to the emotion engine to analyze the user's emotion.

[0262] Step 6:

[0263] The emotion engine analyzes the user's emotions from the input text.

[0264] Example: The emotion "I want to relax" is detected.

[0265] Step 7:

[0266] The server receives the analysis results from the emotion engine, adjusts the prompts based on the emotion, and sends them to the landscape image generation AI.

[0267] Example: You are asked to generate a "relaxing, tranquil lake scene."

[0268] Step 8:

[0269] Scenery image generation AI generates scenery images based on tuned prompts.

[0270] Example: Given a prompt, generate a landscape image of a tranquil location with a lake and mountains.

[0271] The generated image is stored in the server.

[0272] Step 9:

[0273] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[0274] Step 10:

[0275] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[0276] Example: Detect candidate locations such as "Fuji Five Lakes" and "Lake Biwa."

[0277] Step 11:

[0278] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[0279] Step 12:

[0280] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[0281] Step 13:

[0282] The server sends the formatted search results to the user's terminal as an HTTP response.

[0283] Step 14:

[0284] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[0285] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[0286] Step 15:

[0287] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[0288] Example 2

[0289] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0290] Conventional travel recommendation systems have difficulty proposing travel destinations based on a user's specific feelings and desires, and as a result, they have sometimes proposed travel destinations that do not meet the user's expectations. The present invention aims to solve this problem and efficiently propose optimal travel destinations based on a user's feelings and desires.

[0291] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0292] In this invention, the server

[0293] 1. A means for analyzing received text data and sending it to the emotion engine;

[0294] 2. A means for the emotion engine to analyze user emotions from text data;

[0295] 3. A means to adjust prompts based on the output of the emotion engine and send them to the landscape image generation AI;

[0296] 4. A means for the landscape image generation AI to generate a landscape image based on the adjusted prompt;

[0297] 5. Includes a means for passing the generated landscape image to an image recognition algorithm to search for similar existing locations.

[0298] This makes it possible to generate specific landscape images based on the user's emotions and desires, and to suggest the most suitable existing travel destinations that correspond to them.

[0299] "User" refers to an individual user who uses the system to receive travel destination suggestions.

[0300] A "terminal" is a device used by a user to input text, and includes a personal computer, a smartphone, a tablet, and the like.

[0301] "Server" refers to a central processing unit that receives, analyzes, processes, and searches text data sent by users.

[0302] "Text input" refers to text data that a user inputs into a terminal using a keyboard, voice input, or the like.

[0303] "Emotion engine" refers to software or a system for analyzing emotions from a user's text input.

[0304] A "prompt" is an instruction given to a landscape image generation AI to generate a specific landscape image.

[0305] "Landscape image generation AI" refers to an artificial intelligence model that generates landscape images based on specified prompts.

[0306] "Landscape image" refers to a visual landscape image created by a generative AI model based on prompts.

[0307] "Image recognition algorithm" refers to an algorithm that analyzes generated landscape images and identifies similar existing landscapes or places.

[0308] "Search Results" refers to data that compiles information about existing travel destinations identified by image recognition algorithms.

[0309] "Detailed information" refers to information such as the location, access methods, tourist information, etc. of each existing location included in the search results.

[0310] System configuration

[0311] The system of the present invention allows users to input text images of landscapes they would like to travel to, and suggests existing travel destinations based on those images. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[0312] User operations

[0313] The user inputs an image of the scenery they would like to travel to in text form into the device. The device can be a personal computer, smartphone, tablet, etc. Examples of input text include "A beautiful Japanese countryside landscape with cherry blossoms in full bloom" and "I want to escape the hustle and bustle of the city."

[0314] Device operation

[0315] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[0316] Server Processing

[0317] The server analyzes the received text data and sends it to the emotion engine, which analyzes the user's emotions from the text input and adjusts the prompts to the landscape image generation AI based on those emotions.

[0318] For example, if a user's input includes the emotion "I want to relax," the landscape image generation AI is instructed to generate a "relaxing lake scene." This emotion analysis uses natural language processing models such as BERT and GPT-3.

[0319] Next, the server's landscape image generation AI generates landscape images based on the prompts adjusted by the emotion engine. This generation utilizes generative AI models such as GAN (generative adversarial network) and DALL-E. The generated landscape images are stored on the server and passed to an image recognition algorithm.

[0320] The server then passes the generated landscape image to an image recognition algorithm to search for existing locations similar to the image, which uses models such as ResNet and Inception to identify tourist spots with similar landscapes.

[0321] For example, if "relaxing lake scenery" is generated, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido will be searched for.

[0322] The search results are formatted by the server and sent to the user's device along with detailed information about each existing place (location, access method, tourist information, etc.).

[0323] Viewing the results on your device

[0324] The terminal analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido can be displayed in list format.

[0325] User's final decision

[0326] Based on the information provided, users can decide which places to visit and proceed with planning their trip.

[0327] Examples and prompts

[0328] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[0329] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[0330] 2. The device sends this text to the server.

[0331] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[0332] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the scenery image generation AI. An example prompt is generated: "A relaxing mountain landscape."

[0333] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[0334] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[0335] 7. The server sends these search results and detailed information to the user's device.

[0336] 8. The device displays the search results to the user.

[0337] This allows users to determine the best travel destination based on the information provided and efficiently plan their trip.

[0338] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0339] Step 1:

[0340] The user inputs an image of the scenery they want to travel to in text form into the device. Using a web browser on their PC or smartphone, the user inputs specific text, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom," into the system's input form. This generates text input data.

[0341] Step 2:

[0342] The device sends the entered text to the server. The device creates an HTTP POST request and sends this text data over the Internet to the specified endpoint on the server, allowing the server to receive the text input data.

[0343] Step 3:

[0344] The server analyzes the received text data and sends it to the emotion engine. The server serializes the received data into JSON format and sends it to the emotion engine's API endpoint. This process makes the text data input data for emotion analysis.

[0345] Step 4:

[0346] The emotion engine analyzes the user's emotions from the text data. The emotion engine uses natural language processing models such as BERT and GPT-3 to analyze the text data and extract emotions such as "I want to relax" or "I want to be adventurous." The results of this analysis are sent back to the server, and emotion data is generated.

[0347] Step 5:

[0348] The server adjusts the prompt based on the output of the emotion engine and sends it to the scenery image generation AI. The server generates a prompt sentence suitable for the scenery image generation AI based on the emotion data. For example, a prompt sentence such as "A relaxing lake view" is generated and sent to the scenery image generation AI's API endpoint.

[0349] Step 6:

[0350] The landscape image generation AI generates a landscape image based on the adjusted prompt. The generative AI model (e.g., DALL-E or GAN) generates a high-resolution landscape image based on the prompt. The generated image data is stored on the server.

[0351] Step 7:

[0352] The server passes the generated landscape image to an image recognition algorithm to search for similar existing locations. The server then inputs the generated image into an image recognition model such as ResNet or Inception to search for similar tourist spots in databases and online resources. This identifies candidate tourist spots.

[0353] Step 8:

[0354] The server sends the search results and detailed information about the current location to the user's device. The server formats the search results in JSON format, adds detailed information about the tourist spots (location, access method, tourist information, etc.), and sends it to the user's device.

[0355] Step 9:

[0356] The device displays the search results received to the user. The device analyzes the data received from the server and presents it to the user in list format or highlighted display. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[0357] Step 10:

[0358] The user decides on a travel destination based on the displayed results. Based on the displayed information, the user selects the travel destination that best suits their needs and makes specific travel plans using the detailed information as a reference.

[0359] (Application example 2)

[0360] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0361] In recent years, users generally choose travel destinations based on information on the Internet. However, the vast amount of information available makes it difficult for users to quickly find a destination that matches their individual emotions and preferences. Conventional systems are unable to make suggestions that take into account the user's emotions and specific requirements. As a result, travel planning takes time and users may not be able to find a satisfying destination. To solve this problem, a system is needed that can suggest appropriate travel destinations based on user input, taking into account individual emotions and specific scenic images.

[0362] The identification process by the identification 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 a text input indicating a scenic image from a user, means for sending the text input to a scenic image generation model to generate a scenic image, means for searching for similar existing places based on the generated scenic image, and means for suggesting travel destinations to the user in real time based on the search results. This allows for the generation of prompt sentences based on the scenic image and emotions input by the user, making it possible to suggest travel destinations that accurately reflect the emotions and specific requests of each individual user.

[0363] A "landscape image generation model" is an artificial intelligence model that generates visual landscape images based on text input.

[0364] A "prompt sentence" is a text instruction sentence input to a landscape image generation model or an emotion analysis engine, and is a sentence that reflects the user's intentions and emotions.

[0365] "Text input" refers to character information that a user inputs through a terminal, and specifically expresses the scenery or emotions that the user wants to travel to.

[0366] "Search results" are a collection of data containing detailed information about existing locations that are similar to the images generated by the landscape image generation model, as identified by an image recognition algorithm.

[0367] The "travel destination suggestion means" is a system function that suggests suitable travel destinations to the user in real time based on the generated landscape images and search results.

[0368] "Detailed information" refers to information about each existing location included in the search results, including location information, access methods, tourist information, etc.

[0369] The "user input means" is an interface that allows the user to input landscape images and emotions in text format using a terminal.

[0370] "Real-time suggestions" is a function that suggests travel destinations based on input immediately after the user makes the input.

[0371] This invention is a system that allows a user to input a text image of a landscape they would like to travel to, and suggests existing travel destinations based on that image. This system is configured such that a server processes the text input by the user, analyzes the user's emotions using an emotion engine, generates a landscape image using a landscape image generation model, and searches for existing places based on that landscape image.

[0372] 1. User operations

[0373] The user inputs an image of the scenery they would like to travel to in text format. The device used by the user can be a smartphone, tablet, or PC. For example, consider the case where the user inputs "a rural landscape with beautiful cherry blossoms in full bloom."

[0374] 2. Device Operation

[0375] The terminal receives the user's input and sends the entered text to the server using a standard communication protocol such as an HTTP POST request, which transmits the text data to the server.

[0376] 3. Server Processing

[0377] The server analyzes the received text data and sends it to the emotion engine. The emotion engine analyzes the user's emotion from the text input and adjusts the prompts to the scenery image generation model based on that emotion. For example, if the user's input includes the emotion "I want to relax," the scenery image generation model will be instructed to generate a relaxing scenery image.

[0378] 4. Landscape Image Generation

[0379] The landscape image generation model in the server generates landscape images based on the prompt sentence adjusted by the emotion engine. The generated landscape images are stored in the server. Deep learning frameworks such as TENSORFLOW (registered trademark) and Keras are suitable for use as AI models.

[0380] 5. Image Recognition and Place Search

[0381] The generated landscape image is passed to an image recognition algorithm in the server, which searches for existing locations similar to this image. For example, based on the generated image of a rural landscape with cherry blossoms, specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto) can be identified.

[0382] 6. Providing search results

[0383] The server formats the generated landscape image and the search results for existing places, adds detailed information (location information, access methods, tourist information, etc.), and sends it to the user's device.

[0384] 7. Displaying the results

[0385] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed in list format.

[0386] Specific examples

[0387] For example, if a user inputs "I want to escape the hustle and bustle of the city," the system will analyze the emotion of "stress relief" and generate an image of a relaxing mountain landscape. Based on the generated image, it will identify places like "Shosenkyo Gorge" or "Mount Aso," and provide detailed information about them to the user.

[0388] Prompt Sentence Examples

[0389] Relaxing and quiet beach

[0390] An amusement park for the whole family

[0391] A mountain resort where you can feel close to nature

[0392] As described above, the present invention provides a system that suggests travel destinations according to a user's emotions and specific requests, thereby enabling the user to quickly find a travel destination that matches their individual emotions and wishes.

[0393] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0394] Step 1:

[0395] The user inputs an image of the scenery they want to travel to in text format using the terminal. For example, the user inputs "a beautiful countryside scenery with cherry blossoms in full bloom." This input data is received by the terminal.

[0396] Step 2:

[0397] The terminal sends the text data entered by the user to the server using an HTTP POST request. The input data (in text format) is passed to the server, and the server receives the data.

[0398] Step 3:

[0399] The server analyzes the received text data and passes the analysis results to the emotion engine, which then analyzes the input data using a natural language processing engine or similar to extract the emotions contained in the text.

[0400] Step 4:

[0401] The emotion engine analyzes the user's emotions from the text input and generates prompt sentences based on the analysis results. For example, from the input "A beautiful rural landscape with cherry blossoms in full bloom," it extracts the emotion "I want to relax" and adjusts the prompt sentence for the scenery image generation model to "A relaxing cherry blossom landscape."

[0402] Step 5:

[0403] The server passes the prompt sentence received from the emotion engine to the scenery image generation model, which generates a visual scenery image based on the prompt sentence.

[0404] Step 6:

[0405] The generated landscape image is stored on a server and passed to an image recognition algorithm, which identifies existing locations that are similar to the generated image. For example, a generated image of a cherry blossom landscape could identify specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto).

[0406] Step 7:

[0407] The server collects detailed information about the locations identified by the image recognition algorithm (location information, access methods, tourist information, etc.), formats this data, and sends it to the user's device.

[0408] Step 8:

[0409] The device analyzes the search results received from the server and displays them to the user. The display format can be a list or a marker on a map. For example, information about "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed to the user in list format.

[0410] Through the above steps, users can quickly find travel destinations that suit their emotions and specific needs.

[0411] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the 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.

[0412] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0413] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0414] [Second embodiment]

[0415] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0416] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0417] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0418] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0419] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0420] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0421] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0422] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0423] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0424] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0425] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0426] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0427] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0428] System Configuration

[0429] User operations

[0430] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0431] Terminals that can be used include devices such as PCs, smartphones, and tablets.

[0432] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[0433] Device operation

[0434] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[0435] Server Processing

[0436] 3. The server analyzes the received text data and sends it to the landscape image generation AI.

[0437] In this process, the text data is formatted into the appropriate format.

[0438] 4. The landscape image generation AI on the server generates a landscape image based on the text data sent.

[0439] The generated landscape images are stored in the server.

[0440] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing travel destinations that are similar to this image.

[0441] Image recognition algorithms identify tourist spots with similar landscapes.

[0442] Example: Based on the generated cherry blossom scenery, "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture will be searched.

[0443] Providing search results

[0444] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[0445] Displaying the results

[0446] 7. The device analyzes the search results received from the server and displays the results to the user.

[0447] Possible display methods include list format and marker display on a map.

[0448] Example: Information about "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0449] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[0450] Specific examples

[0451] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0452] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0453] 2. The device sends this text to the server.

[0454] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0455] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0456] 5. The server sends these search results and detailed information to the user's device.

[0457] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0458] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0462] Example: Enter "A quiet place with a view of the lake and mountains."

[0463] Step 2:

[0464] The user clicks the "Submit" button.

[0465] Step 3:

[0466] The device receives the user's text input and sends it to the server as an HTTP POST request.

[0467] The transmitted data includes the text prompt entered by the user.

[0468] Step 4:

[0469] The server receives the incoming request and parses the prompt.

[0470] Step 5:

[0471] The server analyzes the text prompt and sends it to the landscape image generation AI, which then generates a corresponding landscape image.

[0472] Step 6:

[0473] The landscape image generation AI in the server generates landscape images based on the user's prompts.

[0474] Example: Generate a landscape image based on the text "A quiet place with a view of a lake and mountains."

[0475] The generated image is stored in the server.

[0476] Step 7:

[0477] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[0478] Step 8:

[0479] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[0480] Example: Detect potential locations such as "Fuji Five Lakes" and "Lake Biwa."

[0481] Step 9:

[0482] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[0483] Step 10:

[0484] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[0485] Step 11:

[0486] The server sends the formatted search results to the user's terminal as an HTTP response.

[0487] Step 12:

[0488] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[0489] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[0490] Step 13:

[0491] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[0492] Example 1

[0493] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0494] Conventional travel planning support systems assume that users know specific locations, so when users want to choose a travel destination based on a vague image of scenery, it is difficult to find an appropriate destination. Also, there is a lack of a mechanism that allows users to easily realize their ideal scenery and suggest specific travel destinations based on that.

[0495] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0496] In this invention, the server includes means for receiving text input indicating a scenic image from a user, means for transmitting the text input to the server, means for formatting the text input into an appropriate format and transmitting it to a scenic image generation AI, means for storing the scenic image generated by the scenic image generation AI in a database, means for analyzing the generated scenic image with an image recognition algorithm and searching for similar existing places, means for adding detailed information about each existing place to the search results and transmitting them to the user's terminal, and means for displaying the search results to the user, thereby enabling a user to quickly find a specific travel destination from a vague scenic image and efficiently plan a trip.

[0497] "User" means an individual or organization that uses this system to make travel plans.

[0498] "Text input" is a character string representing a landscape image that is input by the user through the terminal.

[0499] A "terminal" is an electronic device used by a user to input text, and includes PCs, smartphones, tablets, etc.

[0500] A "server" is a computer system that receives and processes text input submitted by a user.

[0501] "Transmitting means" refers to the communications protocol and associated technology used to transmit the text input to the server.

[0502] The "formatting method" is the process of converting the received text input into a form that can be processed by the landscape image generation AI.

[0503] "Landscape image generation AI" is an artificial intelligence that generates landscape images based on text input.

[0504] A "database" is a data storage system used within the server to store the generated landscape images.

[0505] "Image recognition algorithm" is a technology for analyzing generated landscape images and identifying similar existing places.

[0506] The "searching means" is a process that uses image recognition algorithms to identify similar existing places.

[0507] "Detailed information" refers to specific information such as location, access methods, tourist information, etc. included in the search results.

[0508] The "display means" is a method for visually displaying the search results on the user's terminal.

[0509] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0510] System Configuration

[0511] User operations

[0512] The user inputs an image of the scenery they want to travel to in text format into the terminal. The terminal can be a PC, smartphone, tablet, or other device. For example, the user might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom."

[0513] Device operation

[0514] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[0515] Server Processing

[0516] The server parses the received text data and sends it to the landscape image generation AI. During this process, the text data is formatted into an appropriate format. For example, a Python library (such as Flask) is used to format the data.

[0517] The landscape image generation AI (in the server) generates landscape images based on the transmitted text data. For example, it uses a generative AI model such as GPT-3 or DALLE-2. The generated landscape images are stored in a database (e.g., MySQL) in the server.

[0518] The server then passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm uses OpenCV or similar. For example, based on the generated cherry blossom landscape, travel destinations identified include Takato Castle Park in Nagano Prefecture and Hirosaki Park in Aomori Prefecture.

[0519] Providing search results

[0520] The server formats the search results, adds detailed information about each existing location (location, access method, tourist information, etc.), and sends it to the user's device. The results and detailed information are formatted in JSON format using an HTTP response and sent.

[0521] Displaying the results

[0522] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0523] User's travel plans

[0524] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0525] Specific examples

[0526] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0527] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0528] 2. The device sends this text to the server.

[0529] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0530] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0531] 5. The server sends these search results and detailed information to the user's device.

[0532] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0533] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0534] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0535] Step 1:

[0536] The user inputs the image of the scenery they want to travel to in text format into the device. For example, they might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom." The input data is in text format, allowing the user to freely express the scenery they want.

[0537] Input: Text showing a landscape image

[0538] Output: Text data

[0539] Step 2:

[0540] The terminal sends the entered text to the server using a standard communication protocol such as an HTTP POST request, including the text data in the request body and sending it to the appropriate endpoint.

[0541] Input: Text data

[0542] Output: HTTP POST request to the server

[0543] Step 3:

[0544] The server parses the received text data, adjusts the format, and sends it to the landscape image generation AI. In this process, the text data is converted to JSON format and the appropriate API call is made.

[0545] Input: Text data

[0546] Output: JSON format data

[0547] Step 4:

[0548] The landscape image generation AI (on the server) generates landscape images based on the submitted JSON-formatted text data. The generation uses cutting-edge generative AI models (such as GPT-3 and DALLE-2). The generated landscape images are stored in a database on the server.

[0549] Input: JSON format text data

[0550] Output: Generated landscape image

[0551] Step 5:

[0552] The server then passes the generated landscape image to an image recognition algorithm, such as OpenCV, to search for existing travel destinations that are similar to the image. This process calculates the similarity between the generated landscape image and existing images in the database.

[0553] Input: Generated landscape image

[0554] Output: A list of similar travel destinations

[0555] Step 6:

[0556] The server adds detailed information about each existing location (location, access method, tourist information, etc.) to the search results and sends them to the user's device. The detailed information is retrieved from the database and formatted in JSON format along with the search results.

[0557] Input: A list of similar destinations

[0558] Output: Search results with detailed information

[0559] Step 7:

[0560] The device analyzes the search results received from the server and displays them to the user. The results can be displayed in list format or as markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture can be displayed in list format.

[0561] Input: Search results with detailed information

[0562] Output: Search results displayed to the user

[0563] Step 8:

[0564] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0565] Input: Search results displayed to the user

[0566] Output: User selected travel destinations and travel plans

[0567] (Application example 1)

[0568] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0569] In conventional travel suggestion systems, users had to specify specific locations and tourist attractions, making it difficult to find a travel destination based on a vague image. Furthermore, users had to refer to external resources to learn more about the suggested travel destinations, which took time to gather information. Furthermore, there was no way for users to visually check the suggested travel destinations in advance, which could cause anxiety when planning a trip.

[0570] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0571] In this invention, the server includes means for receiving a text input indicating a scenic image from a user, means for transmitting the text input to a scenic image generation AI to generate a scenic image, means for searching for similar existing places based on the generated scenic image, means for providing the search results to the user, and means for the user to perform a virtual preview of the suggested places. This allows the user to quickly find a travel destination even from a vague image, and also allows the user to visually check the suggested places in advance.

[0572] The "text input indicating a scenery image" is character information that expresses in words the characteristics of the scenery or place that the user wants to travel to.

[0573] "Landscape image generation AI" refers to artificial intelligence that creates synthetic or generated landscape images based on input text information.

[0574] "Similar existing locations" are actual tourist attractions or natural landscapes that resemble the landscapes generated by the landscape image generation AI.

[0575] "Search results" are information on specific travel destinations suggested to users based on landscape images generated by the landscape image generation AI.

[0576] "Virtual Preview" is a feature that allows users to visually check suggested travel destinations in advance using virtual reality technology.

[0577] The embodiment for carrying out the invention comprises the following steps: The system comprises a user, a terminal, and a server.

[0578] First, the user uses a device such as a smartphone or smart glasses to input a text image of the scenery they want to travel to. This input does not refer to a specific location, but rather to a vague image, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains," expressing the user's desire in words.

[0579] Next, the device sends the entered text to the server using a standard communication protocol such as an HTTP POST request. The server receives this text data and sends it to a landscape image generation AI (generative AI model). The AI ​​generates a landscape image based on the received text data. The generated landscape image is saved on the server.

[0580] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. Specifically, the image recognition algorithm identifies tourist spots with similar landscapes. For example, if the search term is "Japanese countryside scenery with beautiful cherry blossoms in full bloom," it will retrieve information such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0581] The server then formats the search results, adds detailed information about each existing location (such as location, access methods, and tourist information), and sends them to the user's device. The device then analyzes the received search results and displays them to the user. Possible display methods include a list format or markers on a map. The user can virtually preview the suggested travel destinations using smart glasses or the AR function of their smartphone. This allows the user to decide which places to actually visit based on the provided information and proceed with their travel planning.

[0582] For example, if a user types "a quiet place with a view of a lake and mountains," the device will send this text to the server. The server will then send the received text to a landscape image generation AI to create a landscape image. The server will then analyze the generated landscape image using an image recognition algorithm to obtain information on travel destinations such as the Fuji Five Lakes and Lake Biwa. The server will then send these search results and detailed information to the user's device, which will then display the results to the user. Based on this information, the user can select a travel destination and enjoy a virtual preview of the suggested locations using the smart glasses.

[0583] Example prompt sentence:

[0584] "A user inputs 'a beautiful beach with a sunset.' Send this information to a generative AI model to generate the ideal landscape image."

[0585] "Please suggest tourist spots (e.g., Shonan coast and sandy beaches) based on the generated landscape images."

[0586] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0587] Step 1:

[0588] The user inputs an image of the scenery they would like to travel to in text format. Using a device such as a smartphone or smart glasses, they input specific text information such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains." This input data is sent to the server in the next step.

[0589] Step 2:

[0590] The terminal sends the text entered by the user to the server using a standard communication protocol such as an HTTP POST request. A request is generated to send the input data to the server, and the text data is sent to the server as input.

[0591] Step 3:

[0592] The server receives the input text data and sends it to the landscape image generation AI. The server formats the received text data into an appropriate format and then sends it to the generative AI model as a prompt. This prompt is in the format of "The user inputs 'A beautiful Japanese countryside landscape with cherry blossoms in full bloom.' Please send this information to the generative AI model to generate an ideal landscape image."

[0593] Step 4:

[0594] The landscape image generation AI generates landscape images based on the text data sent to it. The generated landscape images are stored on the server. In this process, the AI ​​model analyzes the content of the text and generates image data corresponding to that content as output.

[0595] Step 5:

[0596] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm analyzes the landscape image and searches a database for similar tourist spots. The search results output specific travel destination information, such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0597] Step 6:

[0598] The server formats the search results, adds detailed information about each existing place (location, access, tourist information, etc.), and sends it to the user's device. The detailed information retrieved from the database is added, and the formatted results are sent to the device.

[0599] Step 7:

[0600] The device analyzes the search results received from the server and displays them to the user in various ways, such as as a list or as markers on a map, and specific travel destination information is displayed on the device screen.

[0601] Step 8:

[0602] Users can virtually preview the proposed travel destinations. Using smart glasses or the AR function of their smartphone, they can virtually experience the proposed locations. Based on this information, users can decide which places to visit and move forward with their trip planning.

[0603] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0604] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[0605] System Configuration

[0606] User operations

[0607] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0608] Terminals that can be used include PCs, smartphones, and tablets.

[0609] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[0610] Device operation

[0611] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[0612] Server Processing

[0613] 3. The server analyzes the received text data and sends it to the emotion engine.

[0614] The emotion engine analyzes the user's emotions from text input and adjusts prompts to the landscape image generation AI based on those emotions.

[0615] Example: If the user's input includes an emotion such as "I want to relax," the landscape image generation AI is instructed to generate a relaxing landscape image.

[0616] 4. The landscape image generation AI in the server generates landscape images based on the prompts adjusted from the emotion engine.

[0617] Example: "Relaxing lake scene" is generated.

[0618] The generated landscape images are stored in the server.

[0619] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing places that resemble this image.

[0620] Image recognition algorithms identify tourist spots with similar landscapes.

[0621] Example: Based on the generated lake scenery, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido are searched.

[0622] Providing search results

[0623] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[0624] Displaying the results

[0625] 7. The device analyzes the search results received from the server and displays the results to the user.

[0626] Possible display methods include list format and marker display on a map.

[0627] Example: Information about Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[0628] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[0629] Specific examples

[0630] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[0631] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[0632] 2. The device sends this text to the server.

[0633] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[0634] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the landscape image generation AI.

[0635] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[0636] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[0637] 7. The server sends these search results and detailed information to the user's device.

[0638] 8. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0639] The system allows users to receive emotion-based travel destination suggestions and efficiently plan trips that meet their personal needs.

[0640] The processing flow will be explained below.

[0641] Step 1:

[0642] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0643] For example, enter "A quiet place with a view of the lake and mountains."

[0644] Step 2:

[0645] The user clicks the "Submit" button.

[0646] Step 3:

[0647] The device receives the user's text input and sends it to the server as an HTTP POST request.

[0648] The transmitted data includes the text prompt entered by the user.

[0649] Step 4:

[0650] The server receives the incoming request and parses the prompt.

[0651] Step 5:

[0652] The server sends the analyzed text prompt to the emotion engine to analyze the user's emotion.

[0653] Step 6:

[0654] The emotion engine analyzes the user's emotions from the input text.

[0655] Example: The emotion "I want to relax" is detected.

[0656] Step 7:

[0657] The server receives the analysis results from the emotion engine, adjusts the prompts based on the emotion, and sends them to the landscape image generation AI.

[0658] Example: You are asked to generate a "relaxing, tranquil lake scene."

[0659] Step 8:

[0660] Scenery image generation AI generates scenery images based on tuned prompts.

[0661] Example: Given a prompt, generate a landscape image of a tranquil location with a lake and mountains.

[0662] The generated image is stored in the server.

[0663] Step 9:

[0664] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[0665] Step 10:

[0666] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[0667] Example: Detect candidate locations such as "Fuji Five Lakes" and "Lake Biwa."

[0668] Step 11:

[0669] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[0670] Step 12:

[0671] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[0672] Step 13:

[0673] The server sends the formatted search results to the user's terminal as an HTTP response.

[0674] Step 14:

[0675] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[0676] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[0677] Step 15:

[0678] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[0679] Example 2

[0680] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0681] Conventional travel recommendation systems have difficulty proposing travel destinations based on a user's specific feelings and desires, and as a result, they have sometimes proposed travel destinations that do not meet the user's expectations. The present invention aims to solve this problem and efficiently propose optimal travel destinations based on a user's feelings and desires.

[0682] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0683] In this invention, the server

[0684] 1. A means for analyzing received text data and sending it to the emotion engine;

[0685] 2. A means for the emotion engine to analyze user emotions from text data;

[0686] 3. A means to adjust prompts based on the output of the emotion engine and send them to the landscape image generation AI;

[0687] 4. A means for the landscape image generation AI to generate a landscape image based on the adjusted prompt;

[0688] 5. Includes a means for passing the generated landscape image to an image recognition algorithm to search for similar existing locations.

[0689] This makes it possible to generate specific landscape images based on the user's emotions and desires, and to suggest the most suitable existing travel destinations that correspond to them.

[0690] "User" refers to an individual user who uses the system to receive travel destination suggestions.

[0691] A "terminal" is a device used by a user to input text, and includes a personal computer, a smartphone, a tablet, and the like.

[0692] "Server" refers to a central processing unit that receives, analyzes, processes, and searches text data sent by users.

[0693] "Text input" refers to text data that a user inputs into a terminal using a keyboard, voice input, or the like.

[0694] "Emotion engine" refers to software or a system for analyzing emotions from a user's text input.

[0695] A "prompt" is an instruction given to a landscape image generation AI to generate a specific landscape image.

[0696] "Landscape image generation AI" refers to an artificial intelligence model that generates landscape images based on specified prompts.

[0697] "Landscape image" refers to a visual landscape image created by a generative AI model based on prompts.

[0698] "Image recognition algorithm" refers to an algorithm that analyzes generated landscape images and identifies similar existing landscapes or places.

[0699] "Search Results" refers to data that compiles information about existing travel destinations identified by image recognition algorithms.

[0700] "Detailed information" refers to information such as the location, access methods, tourist information, etc. of each existing location included in the search results.

[0701] System configuration

[0702] The system of the present invention allows users to input text images of landscapes they would like to travel to, and suggests existing travel destinations based on those images. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[0703] User operations

[0704] The user inputs an image of the scenery they would like to travel to in text form into the device. The device can be a personal computer, smartphone, tablet, etc. Examples of input text include "A beautiful Japanese countryside landscape with cherry blossoms in full bloom" and "I want to escape the hustle and bustle of the city."

[0705] Device operation

[0706] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[0707] Server Processing

[0708] The server analyzes the received text data and sends it to the emotion engine, which analyzes the user's emotions from the text input and adjusts the prompts to the landscape image generation AI based on those emotions.

[0709] For example, if a user's input includes the emotion "I want to relax," the landscape image generation AI is instructed to generate a "relaxing lake scene." This emotion analysis uses natural language processing models such as BERT and GPT-3.

[0710] Next, the server's landscape image generation AI generates landscape images based on the prompts adjusted by the emotion engine. This generation utilizes generative AI models such as GAN (generative adversarial network) and DALL-E. The generated landscape images are stored on the server and passed to an image recognition algorithm.

[0711] The server then passes the generated landscape image to an image recognition algorithm to search for existing locations similar to the image, which uses models such as ResNet and Inception to identify tourist spots with similar landscapes.

[0712] For example, if "relaxing lake scenery" is generated, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido will be searched for.

[0713] The search results are formatted by the server and sent to the user's device along with detailed information about each existing place (location, access method, tourist information, etc.).

[0714] Viewing the results on your device

[0715] The terminal analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido can be displayed in list format.

[0716] User's final decision

[0717] Based on the information provided, users can decide which places to visit and proceed with planning their trip.

[0718] Examples and prompts

[0719] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[0720] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[0721] 2. The device sends this text to the server.

[0722] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[0723] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the scenery image generation AI. An example prompt is generated: "A relaxing mountain landscape."

[0724] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[0725] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[0726] 7. The server sends these search results and detailed information to the user's device.

[0727] 8. The device displays the search results to the user.

[0728] This allows users to determine the best travel destination based on the information provided and efficiently plan their trip.

[0729] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0730] Step 1:

[0731] The user inputs an image of the scenery they want to travel to in text form into the device. Using a web browser on their PC or smartphone, the user inputs specific text, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom," into the system's input form. This generates text input data.

[0732] Step 2:

[0733] The device sends the entered text to the server. The device creates an HTTP POST request and sends this text data over the Internet to the specified endpoint on the server, allowing the server to receive the text input data.

[0734] Step 3:

[0735] The server analyzes the received text data and sends it to the emotion engine. The server serializes the received data into JSON format and sends it to the emotion engine's API endpoint. This process makes the text data input data for emotion analysis.

[0736] Step 4:

[0737] The emotion engine analyzes the user's emotions from the text data. The emotion engine uses natural language processing models such as BERT and GPT-3 to analyze the text data and extract emotions such as "I want to relax" or "I want to be adventurous." The results of this analysis are sent back to the server, and emotion data is generated.

[0738] Step 5:

[0739] The server adjusts the prompt based on the output of the emotion engine and sends it to the scenery image generation AI. The server generates a prompt sentence suitable for the scenery image generation AI based on the emotion data. For example, a prompt sentence such as "A relaxing lake view" is generated and sent to the scenery image generation AI's API endpoint.

[0740] Step 6:

[0741] The landscape image generation AI generates a landscape image based on the adjusted prompt. The generative AI model (e.g., DALL-E or GAN) generates a high-resolution landscape image based on the prompt. The generated image data is stored on the server.

[0742] Step 7:

[0743] The server passes the generated landscape image to an image recognition algorithm to search for similar existing locations. The server then inputs the generated image into an image recognition model such as ResNet or Inception to search for similar tourist spots in databases and online resources. This identifies candidate tourist spots.

[0744] Step 8:

[0745] The server sends the search results and detailed information about the current location to the user's device. The server formats the search results in JSON format, adds detailed information about the tourist spots (location, access method, tourist information, etc.), and sends it to the user's device.

[0746] Step 9:

[0747] The device displays the search results received to the user. The device analyzes the data received from the server and presents it to the user in list format or highlighted display. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[0748] Step 10:

[0749] The user decides on a travel destination based on the displayed results. Based on the displayed information, the user selects the travel destination that best suits their needs and makes specific travel plans using the detailed information as a reference.

[0750] (Application example 2)

[0751] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0752] In recent years, users generally choose travel destinations based on information on the Internet. However, the vast amount of information available makes it difficult for users to quickly find a destination that matches their individual emotions and preferences. Conventional systems are unable to make suggestions that take into account the user's emotions and specific requirements. As a result, travel planning takes time and users may not be able to find a satisfying destination. To solve this problem, a system is needed that can suggest appropriate travel destinations based on user input, taking into account individual emotions and specific scenic images.

[0753] The identification process by the identification 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 a text input indicating a scenic image from a user, means for sending the text input to a scenic image generation model to generate a scenic image, means for searching for similar existing places based on the generated scenic image, and means for suggesting travel destinations to the user in real time based on the search results. This allows for the generation of prompt sentences based on the scenic image and emotions input by the user, making it possible to suggest travel destinations that accurately reflect the emotions and specific requests of each individual user.

[0754] A "landscape image generation model" is an artificial intelligence model that generates visual landscape images based on text input.

[0755] A "prompt sentence" is a text instruction sentence input to a landscape image generation model or an emotion analysis engine, and is a sentence that reflects the user's intentions and emotions.

[0756] "Text input" refers to character information that a user inputs through a terminal, and specifically expresses the scenery or emotions that the user wants to travel to.

[0757] "Search results" are a collection of data containing detailed information about existing locations that are similar to the images generated by the landscape image generation model, as identified by an image recognition algorithm.

[0758] The "travel destination suggestion means" is a system function that suggests suitable travel destinations to the user in real time based on the generated landscape images and search results.

[0759] "Detailed information" refers to information about each existing location included in the search results, including location information, access methods, tourist information, etc.

[0760] The "user input means" is an interface that allows the user to input landscape images and emotions in text format using a terminal.

[0761] "Real-time suggestions" is a function that suggests travel destinations based on input immediately after the user makes the input.

[0762] This invention is a system that allows a user to input a text image of a landscape they would like to travel to, and suggests existing travel destinations based on that image. This system is configured such that a server processes the text input by the user, analyzes the user's emotions using an emotion engine, generates a landscape image using a landscape image generation model, and searches for existing places based on that landscape image.

[0763] 1. User operations

[0764] The user inputs an image of the scenery they would like to travel to in text format. The device used by the user can be a smartphone, tablet, or PC. For example, consider the case where the user inputs "a rural landscape with beautiful cherry blossoms in full bloom."

[0765] 2. Device Operation

[0766] The terminal receives the user's input and sends the entered text to the server using a standard communication protocol such as an HTTP POST request, which transmits the text data to the server.

[0767] 3. Server Processing

[0768] The server analyzes the received text data and sends it to the emotion engine. The emotion engine analyzes the user's emotion from the text input and adjusts the prompts to the scenery image generation model based on that emotion. For example, if the user's input includes the emotion "I want to relax," the scenery image generation model will be instructed to generate a relaxing scenery image.

[0769] 4. Landscape Image Generation

[0770] The landscape image generation model in the server generates landscape images based on the prompt sentence adjusted by the emotion engine. The generated landscape images are stored in the server. Deep learning frameworks such as TensorFlow and Keras are suitable for the AI ​​model used.

[0771] 5. Image Recognition and Place Search

[0772] The generated landscape image is passed to an image recognition algorithm in the server, which searches for existing locations similar to this image. For example, based on the generated image of a rural landscape with cherry blossoms, specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto) can be identified.

[0773] 6. Providing search results

[0774] The server formats the generated landscape image and the search results for existing places, adds detailed information (location information, access methods, tourist information, etc.), and sends it to the user's device.

[0775] 7. Displaying the results

[0776] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed in list format.

[0777] Specific examples

[0778] For example, if a user inputs "I want to escape the hustle and bustle of the city," the system will analyze the emotion of "stress relief" and generate an image of a relaxing mountain landscape. Based on the generated image, it will identify places like "Shosenkyo Gorge" or "Mount Aso," and provide detailed information about them to the user.

[0779] Prompt Sentence Examples

[0780] Relaxing and quiet beach

[0781] An amusement park for the whole family

[0782] A mountain resort where you can feel close to nature

[0783] As described above, the present invention provides a system that suggests travel destinations according to a user's emotions and specific requests, thereby enabling the user to quickly find a travel destination that matches their individual emotions and wishes.

[0784] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0785] Step 1:

[0786] The user inputs an image of the scenery they want to travel to in text format using the terminal. For example, the user inputs "a beautiful countryside scenery with cherry blossoms in full bloom." This input data is received by the terminal.

[0787] Step 2:

[0788] The terminal sends the text data entered by the user to the server using an HTTP POST request. The input data (in text format) is passed to the server, and the server receives the data.

[0789] Step 3:

[0790] The server analyzes the received text data and passes the analysis results to the emotion engine, which then analyzes the input data using a natural language processing engine or similar to extract the emotions contained in the text.

[0791] Step 4:

[0792] The emotion engine analyzes the user's emotions from the text input and generates prompt sentences based on the analysis results. For example, from the input "A beautiful rural landscape with cherry blossoms in full bloom," it extracts the emotion "I want to relax" and adjusts the prompt sentence for the scenery image generation model to "A relaxing cherry blossom landscape."

[0793] Step 5:

[0794] The server passes the prompt sentence received from the emotion engine to the scenery image generation model, which generates a visual scenery image based on the prompt sentence.

[0795] Step 6:

[0796] The generated landscape image is stored on a server and passed to an image recognition algorithm, which identifies existing locations that are similar to the generated image. For example, a generated image of a cherry blossom landscape could identify specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto).

[0797] Step 7:

[0798] The server collects detailed information about the locations identified by the image recognition algorithm (location information, access methods, tourist information, etc.), formats this data, and sends it to the user's device.

[0799] Step 8:

[0800] The device analyzes the search results received from the server and displays them to the user. The display format can be a list or a marker on a map. For example, information about "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed to the user in list format.

[0801] Through the above steps, users can quickly find travel destinations that suit their emotions and specific needs.

[0802] 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 a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0803] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0804] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0805] [Third embodiment]

[0806] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0807] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0808] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0809] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0810] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0811] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0812] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0813] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0814] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[0815] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0816] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0817] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. 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."

[0818] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0819] System Configuration

[0820] User operations

[0821] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0822] Terminals that can be used include devices such as PCs, smartphones, and tablets.

[0823] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[0824] Device operation

[0825] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[0826] Server Processing

[0827] 3. The server analyzes the received text data and sends it to the landscape image generation AI.

[0828] In this process, the text data is formatted into the appropriate format.

[0829] 4. The landscape image generation AI on the server generates a landscape image based on the text data sent.

[0830] The generated landscape images are stored in the server.

[0831] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing travel destinations that are similar to this image.

[0832] Image recognition algorithms identify tourist spots with similar landscapes.

[0833] Example: Based on the generated cherry blossom scenery, "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture will be searched.

[0834] Providing search results

[0835] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[0836] Displaying the results

[0837] 7. The device analyzes the search results received from the server and displays the results to the user.

[0838] Possible display methods include list format and marker display on a map.

[0839] Example: Information about "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0840] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[0841] Specific examples

[0842] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0843] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0844] 2. The device sends this text to the server.

[0845] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0846] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0847] 5. The server sends these search results and detailed information to the user's device.

[0848] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0849] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0850] The processing flow will be explained below.

[0851] Step 1:

[0852] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0853] Example: Enter "A quiet place with a view of the lake and mountains."

[0854] Step 2:

[0855] The user clicks the "Submit" button.

[0856] Step 3:

[0857] The device receives the user's text input and sends it to the server as an HTTP POST request.

[0858] The transmitted data includes the text prompt entered by the user.

[0859] Step 4:

[0860] The server receives the incoming request and parses the prompt.

[0861] Step 5:

[0862] The server analyzes the text prompt and sends it to the landscape image generation AI, which then generates a corresponding landscape image.

[0863] Step 6:

[0864] The landscape image generation AI in the server generates landscape images based on the user's prompts.

[0865] Example: Generate a landscape image based on the text "A quiet place with a view of a lake and mountains."

[0866] The generated image is stored in the server.

[0867] Step 7:

[0868] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[0869] Step 8:

[0870] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[0871] Example: Detect potential locations such as "Fuji Five Lakes" and "Lake Biwa."

[0872] Step 9:

[0873] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[0874] Step 10:

[0875] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[0876] Step 11:

[0877] The server sends the formatted search results to the user's terminal as an HTTP response.

[0878] Step 12:

[0879] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[0880] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[0881] Step 13:

[0882] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[0883] Example 1

[0884] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0885] Conventional travel planning support systems assume that users know specific locations, so when users want to choose a travel destination based on a vague image of scenery, it is difficult to find an appropriate destination. Also, there is a lack of a mechanism that allows users to easily realize their ideal scenery and suggest specific travel destinations based on that.

[0886] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0887] In this invention, the server includes means for receiving text input indicating a scenic image from a user, means for transmitting the text input to the server, means for formatting the text input into an appropriate format and transmitting it to a scenic image generation AI, means for storing the scenic image generated by the scenic image generation AI in a database, means for analyzing the generated scenic image with an image recognition algorithm and searching for similar existing places, means for adding detailed information about each existing place to the search results and transmitting them to the user's terminal, and means for displaying the search results to the user, thereby enabling a user to quickly find a specific travel destination from a vague scenic image and efficiently plan a trip.

[0888] "User" means an individual or organization that uses this system to make travel plans.

[0889] "Text input" is a character string representing a landscape image that is input by the user through the terminal.

[0890] A "terminal" is an electronic device used by a user to input text, and includes PCs, smartphones, tablets, etc.

[0891] A "server" is a computer system that receives and processes text input submitted by a user.

[0892] "Transmitting means" refers to the communications protocol and associated technology used to transmit the text input to the server.

[0893] The "formatting method" is the process of converting the received text input into a form that can be processed by the landscape image generation AI.

[0894] "Landscape image generation AI" is an artificial intelligence that generates landscape images based on text input.

[0895] A "database" is a data storage system used within the server to store the generated landscape images.

[0896] "Image recognition algorithm" is a technology for analyzing generated landscape images and identifying similar existing places.

[0897] The "searching means" is a process that uses image recognition algorithms to identify similar existing places.

[0898] "Detailed information" refers to specific information such as location, access methods, tourist information, etc. included in the search results.

[0899] The "display means" is a method for visually displaying the search results on the user's terminal.

[0900] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[0901] System Configuration

[0902] User operations

[0903] The user inputs an image of the scenery they want to travel to in text format into the terminal. The terminal can be a PC, smartphone, tablet, or other device. For example, the user might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom."

[0904] Device operation

[0905] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[0906] Server Processing

[0907] The server parses the received text data and sends it to the landscape image generation AI. During this process, the text data is formatted into an appropriate format. For example, a Python library (such as Flask) is used to format the data.

[0908] The landscape image generation AI (in the server) generates landscape images based on the transmitted text data. For example, it uses a generative AI model such as GPT-3 or DALLE-2. The generated landscape images are stored in a database (e.g., MySQL) in the server.

[0909] The server then passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm uses OpenCV or similar. For example, based on the generated cherry blossom landscape, travel destinations identified include Takato Castle Park in Nagano Prefecture and Hirosaki Park in Aomori Prefecture.

[0910] Providing search results

[0911] The server formats the search results, adds detailed information about each existing location (location, access method, tourist information, etc.), and sends it to the user's device. The results and detailed information are formatted in JSON format using an HTTP response and sent.

[0912] Displaying the results

[0913] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[0914] User's travel plans

[0915] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0916] Specific examples

[0917] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[0918] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[0919] 2. The device sends this text to the server.

[0920] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[0921] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[0922] 5. The server sends these search results and detailed information to the user's device.

[0923] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[0924] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[0925] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0926] Step 1:

[0927] The user inputs the image of the scenery they want to travel to in text format into the device. For example, they might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom." The input data is in text format, allowing the user to freely express the scenery they want.

[0928] Input: Text showing a landscape image

[0929] Output: Text data

[0930] Step 2:

[0931] The terminal sends the entered text to the server using a standard communication protocol such as an HTTP POST request, including the text data in the request body and sending it to the appropriate endpoint.

[0932] Input: Text data

[0933] Output: HTTP POST request to the server

[0934] Step 3:

[0935] The server parses the received text data, adjusts the format, and sends it to the landscape image generation AI. In this process, the text data is converted to JSON format and the appropriate API call is made.

[0936] Input: Text data

[0937] Output: JSON format data

[0938] Step 4:

[0939] The landscape image generation AI (on the server) generates landscape images based on the submitted JSON-formatted text data. The generation uses cutting-edge generative AI models (such as GPT-3 and DALLE-2). The generated landscape images are stored in a database on the server.

[0940] Input: JSON format text data

[0941] Output: Generated landscape image

[0942] Step 5:

[0943] The server then passes the generated landscape image to an image recognition algorithm, such as OpenCV, to search for existing travel destinations that are similar to the image. This process calculates the similarity between the generated landscape image and existing images in the database.

[0944] Input: Generated landscape image

[0945] Output: A list of similar travel destinations

[0946] Step 6:

[0947] The server adds detailed information about each existing location (location, access method, tourist information, etc.) to the search results and sends them to the user's device. The detailed information is retrieved from the database and formatted in JSON format along with the search results.

[0948] Input: A list of similar destinations

[0949] Output: Search results with detailed information

[0950] Step 7:

[0951] The device analyzes the search results received from the server and displays them to the user. The results can be displayed in list format or as markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture can be displayed in list format.

[0952] Input: Search results with detailed information

[0953] Output: Search results displayed to the user

[0954] Step 8:

[0955] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[0956] Input: Search results displayed to the user

[0957] Output: User selected travel destinations and travel plans

[0958] (Application example 1)

[0959] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0960] In conventional travel suggestion systems, users had to specify specific locations and tourist attractions, making it difficult to find a travel destination based on a vague image. Furthermore, users had to refer to external resources to learn more about the suggested travel destinations, which took time to gather information. Furthermore, there was no way for users to visually check the suggested travel destinations in advance, which could cause anxiety when planning a trip.

[0961] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0962] In this invention, the server includes means for receiving a text input indicating a scenic image from a user, means for transmitting the text input to a scenic image generation AI to generate a scenic image, means for searching for similar existing places based on the generated scenic image, means for providing the search results to the user, and means for the user to perform a virtual preview of the suggested places. This allows the user to quickly find a travel destination even from a vague image, and also allows the user to visually check the suggested places in advance.

[0963] The "text input indicating a scenery image" is character information that expresses in words the characteristics of the scenery or place that the user wants to travel to.

[0964] "Landscape image generation AI" refers to artificial intelligence that creates synthetic or generated landscape images based on input text information.

[0965] "Similar existing locations" are actual tourist attractions or natural landscapes that resemble the landscapes generated by the landscape image generation AI.

[0966] "Search results" are information on specific travel destinations suggested to users based on landscape images generated by the landscape image generation AI.

[0967] "Virtual Preview" is a feature that allows users to visually check suggested travel destinations in advance using virtual reality technology.

[0968] The embodiment for carrying out the invention comprises the following steps: The system comprises a user, a terminal, and a server.

[0969] First, the user uses a device such as a smartphone or smart glasses to input a text image of the scenery they want to travel to. This input does not refer to a specific location, but rather to a vague image, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains," expressing the user's desire in words.

[0970] Next, the device sends the entered text to the server using a standard communication protocol such as an HTTP POST request. The server receives this text data and sends it to a landscape image generation AI (generative AI model). The AI ​​generates a landscape image based on the received text data. The generated landscape image is saved on the server.

[0971] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. Specifically, the image recognition algorithm identifies tourist spots with similar landscapes. For example, if the search term is "Japanese countryside scenery with beautiful cherry blossoms in full bloom," it will retrieve information such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0972] The server then formats the search results, adds detailed information about each existing location (such as location, access methods, and tourist information), and sends them to the user's device. The device then analyzes the received search results and displays them to the user. Possible display methods include a list format or markers on a map. The user can virtually preview the suggested travel destinations using smart glasses or the AR function of their smartphone. This allows the user to decide which places to actually visit based on the provided information and proceed with their travel planning.

[0973] For example, if a user types "a quiet place with a view of a lake and mountains," the device will send this text to the server. The server will then send the received text to a landscape image generation AI to create a landscape image. The server will then analyze the generated landscape image using an image recognition algorithm to obtain information on travel destinations such as the Fuji Five Lakes and Lake Biwa. The server will then send these search results and detailed information to the user's device, which will then display the results to the user. Based on this information, the user can select a travel destination and enjoy a virtual preview of the suggested locations using the smart glasses.

[0974] Example prompt sentence:

[0975] "A user inputs 'a beautiful beach with a sunset.' Send this information to a generative AI model to generate the ideal landscape image."

[0976] "Please suggest tourist spots (e.g., Shonan coast and sandy beaches) based on the generated landscape images."

[0977] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0978] Step 1:

[0979] The user inputs an image of the scenery they would like to travel to in text format. Using a device such as a smartphone or smart glasses, they input specific text information such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains." This input data is sent to the server in the next step.

[0980] Step 2:

[0981] The terminal sends the text entered by the user to the server using a standard communication protocol such as an HTTP POST request. A request is generated to send the input data to the server, and the text data is sent to the server as input.

[0982] Step 3:

[0983] The server receives the input text data and sends it to the landscape image generation AI. The server formats the received text data into an appropriate format and then sends it to the generative AI model as a prompt. This prompt is in the format of "The user inputs 'A beautiful Japanese countryside landscape with cherry blossoms in full bloom.' Please send this information to the generative AI model to generate an ideal landscape image."

[0984] Step 4:

[0985] The landscape image generation AI generates landscape images based on the text data sent to it. The generated landscape images are stored on the server. In this process, the AI ​​model analyzes the content of the text and generates image data corresponding to that content as output.

[0986] Step 5:

[0987] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm analyzes the landscape image and searches a database for similar tourist spots. The search results output specific travel destination information, such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[0988] Step 6:

[0989] The server formats the search results, adds detailed information about each existing place (location, access, tourist information, etc.), and sends it to the user's device. The detailed information retrieved from the database is added, and the formatted results are sent to the device.

[0990] Step 7:

[0991] The device analyzes the search results received from the server and displays them to the user in various ways, such as as a list or as markers on a map, and specific travel destination information is displayed on the device screen.

[0992] Step 8:

[0993] Users can virtually preview the proposed travel destinations. Using smart glasses or the AR function of their smartphone, they can virtually experience the proposed locations. Based on this information, users can decide which places to visit and move forward with their trip planning.

[0994] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0995] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[0996] System Configuration

[0997] User operations

[0998] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[0999] Terminals that can be used include PCs, smartphones, and tablets.

[1000] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[1001] Device operation

[1002] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[1003] Server Processing

[1004] 3. The server analyzes the received text data and sends it to the emotion engine.

[1005] The emotion engine analyzes the user's emotions from text input and adjusts prompts to the landscape image generation AI based on those emotions.

[1006] Example: If the user's input includes an emotion such as "I want to relax," the landscape image generation AI is instructed to generate a relaxing landscape image.

[1007] 4. The landscape image generation AI in the server generates landscape images based on the prompts adjusted from the emotion engine.

[1008] Example: "Relaxing lake scene" is generated.

[1009] The generated landscape images are stored in the server.

[1010] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing places that resemble this image.

[1011] Image recognition algorithms identify tourist spots with similar landscapes.

[1012] Example: Based on the generated lake scenery, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido are searched.

[1013] Providing search results

[1014] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[1015] Displaying the results

[1016] 7. The device analyzes the search results received from the server and displays the results to the user.

[1017] Possible display methods include list format and marker display on a map.

[1018] Example: Information about Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[1019] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[1020] Specific examples

[1021] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[1022] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[1023] 2. The device sends this text to the server.

[1024] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[1025] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the landscape image generation AI.

[1026] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[1027] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[1028] 7. The server sends these search results and detailed information to the user's device.

[1029] 8. The device displays the search results to the user, who can then choose a travel destination based on that information.

[1030] The system allows users to receive emotion-based travel destination suggestions and efficiently plan trips that meet their personal needs.

[1031] The processing flow will be explained below.

[1032] Step 1:

[1033] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[1034] For example, enter "A quiet place with a view of the lake and mountains."

[1035] Step 2:

[1036] The user clicks the "Submit" button.

[1037] Step 3:

[1038] The device receives the user's text input and sends it to the server as an HTTP POST request.

[1039] The transmitted data includes the text prompt entered by the user.

[1040] Step 4:

[1041] The server receives the incoming request and parses the prompt.

[1042] Step 5:

[1043] The server sends the analyzed text prompt to the emotion engine to analyze the user's emotion.

[1044] Step 6:

[1045] The emotion engine analyzes the user's emotions from the input text.

[1046] Example: The emotion "I want to relax" is detected.

[1047] Step 7:

[1048] The server receives the analysis results from the emotion engine, adjusts the prompts based on the emotion, and sends them to the landscape image generation AI.

[1049] Example: You are asked to generate a "relaxing, tranquil lake scene."

[1050] Step 8:

[1051] Scenery image generation AI generates scenery images based on tuned prompts.

[1052] Example: Given a prompt, generate a landscape image of a tranquil location with a lake and mountains.

[1053] The generated image is stored in the server.

[1054] Step 9:

[1055] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[1056] Step 10:

[1057] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[1058] Example: Detect candidate locations such as "Fuji Five Lakes" and "Lake Biwa."

[1059] Step 11:

[1060] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[1061] Step 12:

[1062] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[1063] Step 13:

[1064] The server sends the formatted search results to the user's terminal as an HTTP response.

[1065] Step 14:

[1066] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[1067] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[1068] Step 15:

[1069] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[1070] Example 2

[1071] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1072] Conventional travel recommendation systems have difficulty proposing travel destinations based on a user's specific feelings and desires, and as a result, they have sometimes proposed travel destinations that do not meet the user's expectations. The present invention aims to solve this problem and efficiently propose optimal travel destinations based on a user's feelings and desires.

[1073] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1074] In this invention, the server

[1075] 1. A means for analyzing received text data and sending it to the emotion engine;

[1076] 2. A means for the emotion engine to analyze user emotions from text data;

[1077] 3. A means to adjust prompts based on the output of the emotion engine and send them to the landscape image generation AI;

[1078] 4. A means for the landscape image generation AI to generate a landscape image based on the adjusted prompt;

[1079] 5. Includes a means for passing the generated landscape image to an image recognition algorithm to search for similar existing locations.

[1080] This makes it possible to generate specific landscape images based on the user's emotions and desires, and to suggest the most suitable existing travel destinations that correspond to them.

[1081] "User" refers to an individual user who uses the system to receive travel destination suggestions.

[1082] A "terminal" is a device used by a user to input text, and includes a personal computer, a smartphone, a tablet, and the like.

[1083] "Server" refers to a central processing unit that receives, analyzes, processes, and searches text data sent by users.

[1084] "Text input" refers to text data that a user inputs into a terminal using a keyboard, voice input, or the like.

[1085] "Emotion engine" refers to software or a system for analyzing emotions from a user's text input.

[1086] A "prompt" is an instruction given to a landscape image generation AI to generate a specific landscape image.

[1087] "Landscape image generation AI" refers to an artificial intelligence model that generates landscape images based on specified prompts.

[1088] "Landscape image" refers to a visual landscape image created by a generative AI model based on prompts.

[1089] "Image recognition algorithm" refers to an algorithm that analyzes generated landscape images and identifies similar existing landscapes or places.

[1090] "Search Results" refers to data that compiles information about existing travel destinations identified by image recognition algorithms.

[1091] "Detailed information" refers to information such as the location, access methods, tourist information, etc. of each existing location included in the search results.

[1092] System configuration

[1093] The system of the present invention allows users to input text images of landscapes they would like to travel to, and suggests existing travel destinations based on those images. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[1094] User operations

[1095] The user inputs an image of the scenery they would like to travel to in text form into the device. The device can be a personal computer, smartphone, tablet, etc. Examples of input text include "A beautiful Japanese countryside landscape with cherry blossoms in full bloom" and "I want to escape the hustle and bustle of the city."

[1096] Device operation

[1097] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[1098] Server Processing

[1099] The server analyzes the received text data and sends it to the emotion engine, which analyzes the user's emotions from the text input and adjusts the prompts to the landscape image generation AI based on those emotions.

[1100] For example, if a user's input includes the emotion "I want to relax," the landscape image generation AI is instructed to generate a "relaxing lake scene." This emotion analysis uses natural language processing models such as BERT and GPT-3.

[1101] Next, the server's landscape image generation AI generates landscape images based on the prompts adjusted by the emotion engine. This generation utilizes generative AI models such as GAN (generative adversarial network) and DALL-E. The generated landscape images are stored on the server and passed to an image recognition algorithm.

[1102] The server then passes the generated landscape image to an image recognition algorithm to search for existing locations similar to the image, which uses models such as ResNet and Inception to identify tourist spots with similar landscapes.

[1103] For example, if "relaxing lake scenery" is generated, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido will be searched for.

[1104] The search results are formatted by the server and sent to the user's device along with detailed information about each existing place (location, access method, tourist information, etc.).

[1105] Viewing the results on your device

[1106] The terminal analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido can be displayed in list format.

[1107] User's final decision

[1108] Based on the information provided, users can decide which places to visit and proceed with planning their trip.

[1109] Examples and prompts

[1110] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[1111] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[1112] 2. The device sends this text to the server.

[1113] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[1114] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the scenery image generation AI. An example prompt is generated: "A relaxing mountain landscape."

[1115] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[1116] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[1117] 7. The server sends these search results and detailed information to the user's device.

[1118] 8. The device displays the search results to the user.

[1119] This allows users to determine the best travel destination based on the information provided and efficiently plan their trip.

[1120] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1121] Step 1:

[1122] The user inputs an image of the scenery they want to travel to in text form into the device. Using a web browser on their PC or smartphone, the user inputs specific text, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom," into the system's input form. This generates text input data.

[1123] Step 2:

[1124] The device sends the entered text to the server. The device creates an HTTP POST request and sends this text data over the Internet to the specified endpoint on the server, allowing the server to receive the text input data.

[1125] Step 3:

[1126] The server analyzes the received text data and sends it to the emotion engine. The server serializes the received data into JSON format and sends it to the emotion engine's API endpoint. This process makes the text data input data for emotion analysis.

[1127] Step 4:

[1128] The emotion engine analyzes the user's emotions from the text data. The emotion engine uses natural language processing models such as BERT and GPT-3 to analyze the text data and extract emotions such as "I want to relax" or "I want to be adventurous." The results of this analysis are sent back to the server, and emotion data is generated.

[1129] Step 5:

[1130] The server adjusts the prompt based on the output of the emotion engine and sends it to the scenery image generation AI. The server generates a prompt sentence suitable for the scenery image generation AI based on the emotion data. For example, a prompt sentence such as "A relaxing lake view" is generated and sent to the scenery image generation AI's API endpoint.

[1131] Step 6:

[1132] The landscape image generation AI generates a landscape image based on the adjusted prompt. The generative AI model (e.g., DALL-E or GAN) generates a high-resolution landscape image based on the prompt. The generated image data is stored on the server.

[1133] Step 7:

[1134] The server passes the generated landscape image to an image recognition algorithm to search for similar existing locations. The server then inputs the generated image into an image recognition model such as ResNet or Inception to search for similar tourist spots in databases and online resources. This identifies candidate tourist spots.

[1135] Step 8:

[1136] The server sends the search results and detailed information about the current location to the user's device. The server formats the search results in JSON format, adds detailed information about the tourist spots (location, access method, tourist information, etc.), and sends it to the user's device.

[1137] Step 9:

[1138] The device displays the search results received to the user. The device analyzes the data received from the server and presents it to the user in list format or highlighted display. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[1139] Step 10:

[1140] The user decides on a travel destination based on the displayed results. Based on the displayed information, the user selects the travel destination that best suits their needs and makes specific travel plans using the detailed information as a reference.

[1141] (Application example 2)

[1142] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1143] In recent years, users generally choose travel destinations based on information on the Internet. However, the vast amount of information available makes it difficult for users to quickly find a destination that matches their individual emotions and preferences. Conventional systems are unable to make suggestions that take into account the user's emotions and specific requirements. As a result, travel planning takes time and users may not be able to find a satisfying destination. To solve this problem, a system is needed that can suggest appropriate travel destinations based on user input, taking into account individual emotions and specific scenic images.

[1144] The identification process by the identification 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 a text input indicating a scenic image from a user, means for sending the text input to a scenic image generation model to generate a scenic image, means for searching for similar existing places based on the generated scenic image, and means for suggesting travel destinations to the user in real time based on the search results. This allows for the generation of prompt sentences based on the scenic image and emotions input by the user, making it possible to suggest travel destinations that accurately reflect the emotions and specific requests of each individual user.

[1145] A "landscape image generation model" is an artificial intelligence model that generates visual landscape images based on text input.

[1146] A "prompt sentence" is a text instruction sentence input to a landscape image generation model or an emotion analysis engine, and is a sentence that reflects the user's intentions and emotions.

[1147] "Text input" refers to character information that a user inputs through a terminal, and specifically expresses the scenery or emotions that the user wants to travel to.

[1148] "Search results" are a collection of data containing detailed information about existing locations that are similar to the images generated by the landscape image generation model, as identified by an image recognition algorithm.

[1149] The "travel destination suggestion means" is a system function that suggests suitable travel destinations to the user in real time based on the generated landscape images and search results.

[1150] "Detailed information" refers to information about each existing location included in the search results, including location information, access methods, tourist information, etc.

[1151] The "user input means" is an interface that allows the user to input landscape images and emotions in text format using a terminal.

[1152] "Real-time suggestions" is a function that suggests travel destinations based on input immediately after the user makes the input.

[1153] This invention is a system that allows a user to input a text image of a landscape they would like to travel to, and suggests existing travel destinations based on that image. This system is configured such that a server processes the text input by the user, analyzes the user's emotions using an emotion engine, generates a landscape image using a landscape image generation model, and searches for existing places based on that landscape image.

[1154] 1. User operations

[1155] The user inputs an image of the scenery they would like to travel to in text format. The device used by the user can be a smartphone, tablet, or PC. For example, consider the case where the user inputs "a rural landscape with beautiful cherry blossoms in full bloom."

[1156] 2. Device Operation

[1157] The terminal receives the user's input and sends the entered text to the server using a standard communication protocol such as an HTTP POST request, which transmits the text data to the server.

[1158] 3. Server Processing

[1159] The server analyzes the received text data and sends it to the emotion engine. The emotion engine analyzes the user's emotion from the text input and adjusts the prompts to the scenery image generation model based on that emotion. For example, if the user's input includes the emotion "I want to relax," the scenery image generation model will be instructed to generate a relaxing scenery image.

[1160] 4. Landscape Image Generation

[1161] The landscape image generation model in the server generates landscape images based on the prompt sentence adjusted by the emotion engine. The generated landscape images are stored in the server. Deep learning frameworks such as TensorFlow and Keras are suitable for the AI ​​model used.

[1162] 5. Image Recognition and Place Search

[1163] The generated landscape image is passed to an image recognition algorithm in the server, which searches for existing locations similar to this image. For example, based on the generated image of a rural landscape with cherry blossoms, specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto) can be identified.

[1164] 6. Providing search results

[1165] The server formats the generated landscape image and the search results for existing places, adds detailed information (location information, access methods, tourist information, etc.), and sends it to the user's device.

[1166] 7. Displaying the results

[1167] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed in list format.

[1168] Specific examples

[1169] For example, if a user inputs "I want to escape the hustle and bustle of the city," the system will analyze the emotion of "stress relief" and generate an image of a relaxing mountain landscape. Based on the generated image, it will identify places like "Shosenkyo Gorge" or "Mount Aso," and provide detailed information about them to the user.

[1170] Prompt Sentence Examples

[1171] Relaxing and quiet beach

[1172] An amusement park for the whole family

[1173] A mountain resort where you can feel close to nature

[1174] As described above, the present invention provides a system that suggests travel destinations according to a user's emotions and specific requests, thereby enabling the user to quickly find a travel destination that matches their individual emotions and wishes.

[1175] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1176] Step 1:

[1177] The user inputs an image of the scenery they want to travel to in text format using the terminal. For example, the user inputs "a beautiful countryside scenery with cherry blossoms in full bloom." This input data is received by the terminal.

[1178] Step 2:

[1179] The terminal sends the text data entered by the user to the server using an HTTP POST request. The input data (in text format) is passed to the server, and the server receives the data.

[1180] Step 3:

[1181] The server analyzes the received text data and passes the analysis results to the emotion engine, which then analyzes the input data using a natural language processing engine or similar to extract the emotions contained in the text.

[1182] Step 4:

[1183] The emotion engine analyzes the user's emotions from the text input and generates prompt sentences based on the analysis results. For example, from the input "A beautiful rural landscape with cherry blossoms in full bloom," it extracts the emotion "I want to relax" and adjusts the prompt sentence for the scenery image generation model to "A relaxing cherry blossom landscape."

[1184] Step 5:

[1185] The server passes the prompt sentence received from the emotion engine to the scenery image generation model, which generates a visual scenery image based on the prompt sentence.

[1186] Step 6:

[1187] The generated landscape image is stored on a server and passed to an image recognition algorithm, which identifies existing locations that are similar to the generated image. For example, a generated image of a cherry blossom landscape could identify specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto).

[1188] Step 7:

[1189] The server collects detailed information about the locations identified by the image recognition algorithm (location information, access methods, tourist information, etc.), formats this data, and sends it to the user's device.

[1190] Step 8:

[1191] The device analyzes the search results received from the server and displays them to the user. The display format can be a list or a marker on a map. For example, information about "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed to the user in list format.

[1192] Through the above steps, users can quickly find travel destinations that suit their emotions and specific needs.

[1193] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1194] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1195] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1196] [Fourth embodiment]

[1197] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1198] 7, a 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.

[1199] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1200] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1201] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1202] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1203] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1204] The control object 443 includes a display device, LEDs in the eyes, and motors for driving 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 emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1205] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1206] The specific processing program 56 is an example of a "program" according to the technology of the present 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.

[1207] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1208] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. 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 process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1209] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1210] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[1211] System Configuration

[1212] User operations

[1213] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[1214] Terminals that can be used include devices such as PCs, smartphones, and tablets.

[1215] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[1216] Device operation

[1217] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[1218] Server Processing

[1219] 3. The server analyzes the received text data and sends it to the landscape image generation AI.

[1220] In this process, the text data is formatted into the appropriate format.

[1221] 4. The landscape image generation AI on the server generates a landscape image based on the text data sent.

[1222] The generated landscape images are stored in the server.

[1223] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing travel destinations that are similar to this image.

[1224] Image recognition algorithms identify tourist spots with similar landscapes.

[1225] Example: Based on the generated cherry blossom scenery, "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture will be searched.

[1226] Providing search results

[1227] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[1228] Displaying the results

[1229] 7. The device analyzes the search results received from the server and displays the results to the user.

[1230] Possible display methods include list format and marker display on a map.

[1231] Example: Information about "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[1232] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[1233] Specific examples

[1234] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[1235] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[1236] 2. The device sends this text to the server.

[1237] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[1238] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[1239] 5. The server sends these search results and detailed information to the user's device.

[1240] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[1241] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[1242] The processing flow will be explained below.

[1243] Step 1:

[1244] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[1245] Example: Enter "A quiet place with a view of the lake and mountains."

[1246] Step 2:

[1247] The user clicks the "Submit" button.

[1248] Step 3:

[1249] The device receives the user's text input and sends it to the server as an HTTP POST request.

[1250] The transmitted data includes the text prompt entered by the user.

[1251] Step 4:

[1252] The server receives the incoming request and parses the prompt.

[1253] Step 5:

[1254] The server analyzes the text prompt and sends it to the landscape image generation AI, which then generates a corresponding landscape image.

[1255] Step 6:

[1256] The landscape image generation AI in the server generates landscape images based on the user's prompts.

[1257] Example: Generate a landscape image based on the text "A quiet place with a view of a lake and mountains."

[1258] The generated image is stored in the server.

[1259] Step 7:

[1260] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[1261] Step 8:

[1262] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[1263] Example: Detect potential locations such as "Fuji Five Lakes" and "Lake Biwa."

[1264] Step 9:

[1265] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[1266] Step 10:

[1267] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[1268] Step 11:

[1269] The server sends the formatted search results to the user's terminal as an HTTP response.

[1270] Step 12:

[1271] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[1272] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[1273] Step 13:

[1274] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[1275] Example 1

[1276] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1277] Conventional travel planning support systems assume that users know specific locations, so when users want to choose a travel destination based on a vague image of scenery, it is difficult to find an appropriate destination. Also, there is a lack of a mechanism that allows users to easily realize their ideal scenery and suggest specific travel destinations based on that.

[1278] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1279] In this invention, the server includes means for receiving text input indicating a scenic image from a user, means for transmitting the text input to the server, means for formatting the text input into an appropriate format and transmitting it to a scenic image generation AI, means for storing the scenic image generated by the scenic image generation AI in a database, means for analyzing the generated scenic image with an image recognition algorithm and searching for similar existing places, means for adding detailed information about each existing place to the search results and transmitting them to the user's terminal, and means for displaying the search results to the user, thereby enabling a user to quickly find a specific travel destination from a vague scenic image and efficiently plan a trip.

[1280] "User" means an individual or organization that uses this system to make travel plans.

[1281] "Text input" is a character string representing a landscape image that is input by the user through the terminal.

[1282] A "terminal" is an electronic device used by a user to input text, and includes PCs, smartphones, tablets, etc.

[1283] A "server" is a computer system that receives and processes text input submitted by a user.

[1284] "Transmitting means" refers to the communications protocol and associated technology used to transmit the text input to the server.

[1285] The "formatting method" is the process of converting the received text input into a form that can be processed by the landscape image generation AI.

[1286] "Landscape image generation AI" is an artificial intelligence that generates landscape images based on text input.

[1287] A "database" is a data storage system used within the server to store the generated landscape images.

[1288] "Image recognition algorithm" is a technology for analyzing generated landscape images and identifying similar existing places.

[1289] The "searching means" is a process that uses image recognition algorithms to identify similar existing places.

[1290] "Detailed information" refers to specific information such as location, access methods, tourist information, etc. included in the search results.

[1291] The "display means" is a method for visually displaying the search results on the user's terminal.

[1292] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, and a server.

[1293] System Configuration

[1294] User operations

[1295] The user inputs an image of the scenery they want to travel to in text format into the terminal. The terminal can be a PC, smartphone, tablet, or other device. For example, the user might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom."

[1296] Device operation

[1297] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[1298] Server Processing

[1299] The server parses the received text data and sends it to the landscape image generation AI. During this process, the text data is formatted into an appropriate format. For example, a Python library (such as Flask) is used to format the data.

[1300] The landscape image generation AI (in the server) generates landscape images based on the transmitted text data. For example, it uses a generative AI model such as GPT-3 or DALLE-2. The generated landscape images are stored in a database (e.g., MySQL) in the server.

[1301] The server then passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm uses OpenCV or similar. For example, based on the generated cherry blossom landscape, travel destinations identified include Takato Castle Park in Nagano Prefecture and Hirosaki Park in Aomori Prefecture.

[1302] Providing search results

[1303] The server formats the search results, adds detailed information about each existing location (location, access method, tourist information, etc.), and sends it to the user's device. The results and detailed information are formatted in JSON format using an HTTP response and sent.

[1304] Displaying the results

[1305] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture is displayed in list format.

[1306] User's travel plans

[1307] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[1308] Specific examples

[1309] For example, if the user inputs "a quiet place with a view of a lake and mountains," the process proceeds as follows:

[1310] 1. The user enters the text "A quiet place with a view of the lake and mountains."

[1311] 2. The device sends this text to the server.

[1312] 3. The server sends the received text to the landscape image generation AI to create a landscape image.

[1313] 4. The server analyzes the generated landscape image using an image recognition algorithm and obtains information such as the "Fuji Five Lakes" or "Lake Biwa."

[1314] 5. The server sends these search results and detailed information to the user's device.

[1315] 6. The device displays the search results to the user, who can then choose a travel destination based on that information.

[1316] This system allows users to quickly find specific travel destinations from vague landscape images, enabling them to efficiently plan their trips.

[1317] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1318] Step 1:

[1319] The user inputs the image of the scenery they want to travel to in text format into the device. For example, they might input "a beautiful Japanese countryside landscape with cherry blossoms in full bloom." The input data is in text format, allowing the user to freely express the scenery they want.

[1320] Input: Text showing a landscape image

[1321] Output: Text data

[1322] Step 2:

[1323] The terminal sends the entered text to the server using a standard communication protocol such as an HTTP POST request, including the text data in the request body and sending it to the appropriate endpoint.

[1324] Input: Text data

[1325] Output: HTTP POST request to the server

[1326] Step 3:

[1327] The server parses the received text data, adjusts the format, and sends it to the landscape image generation AI. In this process, the text data is converted to JSON format and the appropriate API call is made.

[1328] Input: Text data

[1329] Output: JSON format data

[1330] Step 4:

[1331] The landscape image generation AI (on the server) generates landscape images based on the submitted JSON-formatted text data. The generation uses cutting-edge generative AI models (such as GPT-3 and DALLE-2). The generated landscape images are stored in a database on the server.

[1332] Input: JSON format text data

[1333] Output: Generated landscape image

[1334] Step 5:

[1335] The server then passes the generated landscape image to an image recognition algorithm, such as OpenCV, to search for existing travel destinations that are similar to the image. This process calculates the similarity between the generated landscape image and existing images in the database.

[1336] Input: Generated landscape image

[1337] Output: A list of similar travel destinations

[1338] Step 6:

[1339] The server adds detailed information about each existing location (location, access method, tourist information, etc.) to the search results and sends them to the user's device. The detailed information is retrieved from the database and formatted in JSON format along with the search results.

[1340] Input: A list of similar destinations

[1341] Output: Search results with detailed information

[1342] Step 7:

[1343] The device analyzes the search results received from the server and displays them to the user. The results can be displayed in list format or as markers on a map. For example, information on "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture can be displayed in list format.

[1344] Input: Search results with detailed information

[1345] Output: Search results displayed to the user

[1346] Step 8:

[1347] Based on the information provided, users can decide on the places they want to visit and proceed with their travel plans. Specifically, they can check detailed information about their travel destinations and make reservations for accommodations and transportation.

[1348] Input: Search results displayed to the user

[1349] Output: User selected travel destinations and travel plans

[1350] (Application example 1)

[1351] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1352] In conventional travel suggestion systems, users had to specify specific locations and tourist attractions, making it difficult to find a travel destination based on a vague image. Furthermore, users had to refer to external resources to learn more about the suggested travel destinations, which took time to gather information. Furthermore, there was no way for users to visually check the suggested travel destinations in advance, which could cause anxiety when planning a trip.

[1353] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1354] In this invention, the server includes means for receiving a text input indicating a scenic image from a user, means for transmitting the text input to a scenic image generation AI to generate a scenic image, means for searching for similar existing places based on the generated scenic image, means for providing the search results to the user, and means for the user to perform a virtual preview of the suggested places. This allows the user to quickly find a travel destination even from a vague image, and also allows the user to visually check the suggested places in advance.

[1355] The "text input indicating a scenery image" is character information that expresses in words the characteristics of the scenery or place that the user wants to travel to.

[1356] "Landscape image generation AI" refers to artificial intelligence that creates synthetic or generated landscape images based on input text information.

[1357] "Similar existing locations" are actual tourist attractions or natural landscapes that resemble the landscapes generated by the landscape image generation AI.

[1358] "Search results" are information on specific travel destinations suggested to users based on landscape images generated by the landscape image generation AI.

[1359] "Virtual Preview" is a feature that allows users to visually check suggested travel destinations in advance using virtual reality technology.

[1360] The embodiment for carrying out the invention comprises the following steps: The system comprises a user, a terminal, and a server.

[1361] First, the user uses a device such as a smartphone or smart glasses to input a text image of the scenery they want to travel to. This input does not refer to a specific location, but rather to a vague image, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains," expressing the user's desire in words.

[1362] Next, the device sends the entered text to the server using a standard communication protocol such as an HTTP POST request. The server receives this text data and sends it to a landscape image generation AI (generative AI model). The AI ​​generates a landscape image based on the received text data. The generated landscape image is saved on the server.

[1363] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. Specifically, the image recognition algorithm identifies tourist spots with similar landscapes. For example, if the search term is "Japanese countryside scenery with beautiful cherry blossoms in full bloom," it will retrieve information such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[1364] The server then formats the search results, adds detailed information about each existing location (such as location, access methods, and tourist information), and sends them to the user's device. The device then analyzes the received search results and displays them to the user. Possible display methods include a list format or markers on a map. The user can virtually preview the suggested travel destinations using smart glasses or the AR function of their smartphone. This allows the user to decide which places to actually visit based on the provided information and proceed with their travel planning.

[1365] For example, if a user types "a quiet place with a view of a lake and mountains," the device will send this text to the server. The server will then send the received text to a landscape image generation AI to create a landscape image. The server will then analyze the generated landscape image using an image recognition algorithm to obtain information on travel destinations such as the Fuji Five Lakes and Lake Biwa. The server will then send these search results and detailed information to the user's device, which will then display the results to the user. Based on this information, the user can select a travel destination and enjoy a virtual preview of the suggested locations using the smart glasses.

[1366] Example prompt sentence:

[1367] "A user inputs 'a beautiful beach with a sunset.' Send this information to a generative AI model to generate the ideal landscape image."

[1368] "Please suggest tourist spots (e.g., Shonan coast and sandy beaches) based on the generated landscape images."

[1369] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1370] Step 1:

[1371] The user inputs an image of the scenery they would like to travel to in text format. Using a device such as a smartphone or smart glasses, they input specific text information such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom" or "a quiet place with a view of a lake and mountains." This input data is sent to the server in the next step.

[1372] Step 2:

[1373] The terminal sends the text entered by the user to the server using a standard communication protocol such as an HTTP POST request. A request is generated to send the input data to the server, and the text data is sent to the server as input.

[1374] Step 3:

[1375] The server receives the input text data and sends it to the landscape image generation AI. The server formats the received text data into an appropriate format and then sends it to the generative AI model as a prompt. This prompt is in the format of "The user inputs 'A beautiful Japanese countryside landscape with cherry blossoms in full bloom.' Please send this information to the generative AI model to generate an ideal landscape image."

[1376] Step 4:

[1377] The landscape image generation AI generates landscape images based on the text data sent to it. The generated landscape images are stored on the server. In this process, the AI ​​model analyzes the content of the text and generates image data corresponding to that content as output.

[1378] Step 5:

[1379] The server passes the generated landscape image to an image recognition algorithm, which searches for existing travel destinations that are similar to the image. The image recognition algorithm analyzes the landscape image and searches a database for similar tourist spots. The search results output specific travel destination information, such as "Takato Castle Ruins Park" in Nagano Prefecture and "Hirosaki Park" in Aomori Prefecture.

[1380] Step 6:

[1381] The server formats the search results, adds detailed information about each existing place (location, access, tourist information, etc.), and sends it to the user's device. The detailed information retrieved from the database is added, and the formatted results are sent to the device.

[1382] Step 7:

[1383] The device analyzes the search results received from the server and displays them to the user in various ways, such as as a list or as markers on a map, and specific travel destination information is displayed on the device screen.

[1384] Step 8:

[1385] Users can virtually preview the proposed travel destinations. Using smart glasses or the AR function of their smartphone, they can virtually experience the proposed locations. Based on this information, users can decide which places to visit and move forward with their trip planning.

[1386] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1387] The present invention relates to a system that allows a user to input a text image of a landscape they would like to travel to, and then suggests existing travel destinations based on that image. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[1388] System Configuration

[1389] User operations

[1390] 1. The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[1391] Terminals that can be used include PCs, smartphones, and tablets.

[1392] Example: User types "Beautiful Japanese countryside with cherry blossoms in full bloom."

[1393] Device operation

[1394] 2. The device sends the entered text to the server using a standard communication protocol such as an HTTP POST request.

[1395] Server Processing

[1396] 3. The server analyzes the received text data and sends it to the emotion engine.

[1397] The emotion engine analyzes the user's emotions from text input and adjusts prompts to the landscape image generation AI based on those emotions.

[1398] Example: If the user's input includes an emotion such as "I want to relax," the landscape image generation AI is instructed to generate a relaxing landscape image.

[1399] 4. The landscape image generation AI in the server generates landscape images based on the prompts adjusted from the emotion engine.

[1400] Example: "Relaxing lake scene" is generated.

[1401] The generated landscape images are stored in the server.

[1402] 5. The server passes the generated landscape image to an image recognition algorithm to search for existing places that resemble this image.

[1403] Image recognition algorithms identify tourist spots with similar landscapes.

[1404] Example: Based on the generated lake scenery, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido are searched.

[1405] Providing search results

[1406] 6. The server formats the search results, adds detailed information about each existing place (location, access method, tourist information, etc.), and sends them to the user's device.

[1407] Displaying the results

[1408] 7. The device analyzes the search results received from the server and displays the results to the user.

[1409] Possible display methods include list format and marker display on a map.

[1410] Example: Information about Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[1411] 8. Based on the information provided, users can decide which places to visit and proceed with their travel plans.

[1412] Specific examples

[1413] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[1414] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[1415] 2. The device sends this text to the server.

[1416] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[1417] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the landscape image generation AI.

[1418] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[1419] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[1420] 7. The server sends these search results and detailed information to the user's device.

[1421] 8. The device displays the search results to the user, who can then choose a travel destination based on that information.

[1422] The system allows users to receive emotion-based travel destination suggestions and efficiently plan trips that meet their personal needs.

[1423] The processing flow will be explained below.

[1424] Step 1:

[1425] The user inputs an image of the scenery they would like to travel to in text format into the terminal.

[1426] For example, enter "A quiet place with a view of the lake and mountains."

[1427] Step 2:

[1428] The user clicks the "Submit" button.

[1429] Step 3:

[1430] The device receives the user's text input and sends it to the server as an HTTP POST request.

[1431] The transmitted data includes the text prompt entered by the user.

[1432] Step 4:

[1433] The server receives the incoming request and parses the prompt.

[1434] Step 5:

[1435] The server sends the analyzed text prompt to the emotion engine to analyze the user's emotion.

[1436] Step 6:

[1437] The emotion engine analyzes the user's emotions from the input text.

[1438] Example: The emotion "I want to relax" is detected.

[1439] Step 7:

[1440] The server receives the analysis results from the emotion engine, adjusts the prompts based on the emotion, and sends them to the landscape image generation AI.

[1441] Example: You are asked to generate a "relaxing, tranquil lake scene."

[1442] Step 8:

[1443] Scenery image generation AI generates scenery images based on tuned prompts.

[1444] Example: Given a prompt, generate a landscape image of a tranquil location with a lake and mountains.

[1445] The generated image is stored in the server.

[1446] Step 9:

[1447] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places.

[1448] Step 10:

[1449] The server uses image recognition algorithms to identify existing locations that are similar to the generated landscape image.

[1450] Example: Detect candidate locations such as "Fuji Five Lakes" and "Lake Biwa."

[1451] Step 11:

[1452] The server collects detailed information about the candidate locations (location, access methods, tourist information, etc.).

[1453] Step 12:

[1454] Based on the information collected by the server, the search results are formatted and prepared for transmission to the user's device.

[1455] Step 13:

[1456] The server sends the formatted search results to the user's terminal as an HTTP response.

[1457] Step 14:

[1458] The terminal analyzes the search results received and displays them to the user in a visually easy-to-understand format.

[1459] Example: Display information about the "Fuji Five Lakes" and "Lake Biwa" in list format.

[1460] Step 15:

[1461] The user reviews the displayed information and either finds out more about the place of interest or continues to plan their trip.

[1462] Example 2

[1463] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1464] Conventional travel recommendation systems have difficulty proposing travel destinations based on a user's specific feelings and desires, and as a result, they have sometimes proposed travel destinations that do not meet the user's expectations. The present invention aims to solve this problem and efficiently propose optimal travel destinations based on a user's feelings and desires.

[1465] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1466] In this invention, the server

[1467] 1. A means for analyzing received text data and sending it to the emotion engine;

[1468] 2. A means for the emotion engine to analyze user emotions from text data;

[1469] 3. A means to adjust prompts based on the output of the emotion engine and send them to the landscape image generation AI;

[1470] 4. A means for the landscape image generation AI to generate a landscape image based on the adjusted prompt;

[1471] 5. Includes a means for passing the generated landscape image to an image recognition algorithm to search for similar existing locations.

[1472] This makes it possible to generate specific landscape images based on the user's emotions and desires, and to suggest the most suitable existing travel destinations that correspond to them.

[1473] "User" refers to an individual user who uses the system to receive travel destination suggestions.

[1474] A "terminal" is a device used by a user to input text, and includes a personal computer, a smartphone, a tablet, and the like.

[1475] "Server" refers to a central processing unit that receives, analyzes, processes, and searches text data sent by users.

[1476] "Text input" refers to text data that a user inputs into a terminal using a keyboard, voice input, or the like.

[1477] "Emotion engine" refers to software or a system for analyzing emotions from a user's text input.

[1478] A "prompt" is an instruction given to a landscape image generation AI to generate a specific landscape image.

[1479] "Landscape image generation AI" refers to an artificial intelligence model that generates landscape images based on specified prompts.

[1480] "Landscape image" refers to a visual landscape image created by a generative AI model based on prompts.

[1481] "Image recognition algorithm" refers to an algorithm that analyzes generated landscape images and identifies similar existing landscapes or places.

[1482] "Search Results" refers to data that compiles information about existing travel destinations identified by image recognition algorithms.

[1483] "Detailed information" refers to information such as the location, access methods, tourist information, etc. of each existing location included in the search results.

[1484] System configuration

[1485] The system of the present invention allows users to input text images of landscapes they would like to travel to, and suggests existing travel destinations based on those images. This system is composed of multiple components, including a user, a terminal, a server, and an emotion engine.

[1486] User operations

[1487] The user inputs an image of the scenery they would like to travel to in text form into the device. The device can be a personal computer, smartphone, tablet, etc. Examples of input text include "A beautiful Japanese countryside landscape with cherry blossoms in full bloom" and "I want to escape the hustle and bustle of the city."

[1488] Device operation

[1489] The device sends the entered text to the server using standard communication protocols such as an HTTP POST request.

[1490] Server Processing

[1491] The server analyzes the received text data and sends it to the emotion engine, which analyzes the user's emotions from the text input and adjusts the prompts to the landscape image generation AI based on those emotions.

[1492] For example, if a user's input includes the emotion "I want to relax," the landscape image generation AI is instructed to generate a "relaxing lake scene." This emotion analysis uses natural language processing models such as BERT and GPT-3.

[1493] Next, the server's landscape image generation AI generates landscape images based on the prompts adjusted by the emotion engine. This generation utilizes generative AI models such as GAN (generative adversarial network) and DALL-E. The generated landscape images are stored on the server and passed to an image recognition algorithm.

[1494] The server then passes the generated landscape image to an image recognition algorithm to search for existing locations similar to the image, which uses models such as ResNet and Inception to identify tourist spots with similar landscapes.

[1495] For example, if "relaxing lake scenery" is generated, "Lake Suwa" in Nagano Prefecture and "Lake Mashu" in Hokkaido will be searched for.

[1496] The search results are formatted by the server and sent to the user's device along with detailed information about each existing place (location, access method, tourist information, etc.).

[1497] Viewing the results on your device

[1498] The terminal analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido can be displayed in list format.

[1499] User's final decision

[1500] Based on the information provided, users can decide which places to visit and proceed with planning their trip.

[1501] Examples and prompts

[1502] For example, if the user inputs "I want to escape the hustle and bustle of the city," the process proceeds as follows:

[1503] 1. A user types in the text "I want to escape the hustle and bustle of the city."

[1504] 2. The device sends this text to the server.

[1505] 3. The server sends the received text to the emotion engine and analyzes the emotion "relieve stress."

[1506] 4. Based on the analysis results from the emotion engine, the server adjusts the prompt and sends it to the scenery image generation AI. An example prompt is generated: "A relaxing mountain landscape."

[1507] 5. The AI ​​in the server generates a "relaxing mountain landscape."

[1508] 6. The server uses an image recognition algorithm to search the generated landscape image and identify, for example, "Shosenkyo Gorge" or "Mount Aso."

[1509] 7. The server sends these search results and detailed information to the user's device.

[1510] 8. The device displays the search results to the user.

[1511] This allows users to determine the best travel destination based on the information provided and efficiently plan their trip.

[1512] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1513] Step 1:

[1514] The user inputs an image of the scenery they want to travel to in text form into the device. Using a web browser on their PC or smartphone, the user inputs specific text, such as "a rural Japanese landscape with beautiful cherry blossoms in full bloom," into the system's input form. This generates text input data.

[1515] Step 2:

[1516] The device sends the entered text to the server. The device creates an HTTP POST request and sends this text data over the Internet to the specified endpoint on the server, allowing the server to receive the text input data.

[1517] Step 3:

[1518] The server analyzes the received text data and sends it to the emotion engine. The server serializes the received data into JSON format and sends it to the emotion engine's API endpoint. This process makes the text data input data for emotion analysis.

[1519] Step 4:

[1520] The emotion engine analyzes the user's emotions from the text data. The emotion engine uses natural language processing models such as BERT and GPT-3 to analyze the text data and extract emotions such as "I want to relax" or "I want to be adventurous." The results of this analysis are sent back to the server, and emotion data is generated.

[1521] Step 5:

[1522] The server adjusts the prompt based on the output of the emotion engine and sends it to the scenery image generation AI. The server generates a prompt sentence suitable for the scenery image generation AI based on the emotion data. For example, a prompt sentence such as "A relaxing lake view" is generated and sent to the scenery image generation AI's API endpoint.

[1523] Step 6:

[1524] The landscape image generation AI generates a landscape image based on the adjusted prompt. The generative AI model (e.g., DALL-E or GAN) generates a high-resolution landscape image based on the prompt. The generated image data is stored on the server.

[1525] Step 7:

[1526] The server passes the generated landscape image to an image recognition algorithm to search for similar existing locations. The server then inputs the generated image into an image recognition model such as ResNet or Inception to search for similar tourist spots in databases and online resources. This identifies candidate tourist spots.

[1527] Step 8:

[1528] The server sends the search results and detailed information about the current location to the user's device. The server formats the search results in JSON format, adds detailed information about the tourist spots (location, access method, tourist information, etc.), and sends it to the user's device.

[1529] Step 9:

[1530] The device displays the search results received to the user. The device analyzes the data received from the server and presents it to the user in list format or highlighted display. For example, information on Lake Suwa in Nagano Prefecture and Lake Mashu in Hokkaido is displayed in list format.

[1531] Step 10:

[1532] The user decides on a travel destination based on the displayed results. Based on the displayed information, the user selects the travel destination that best suits their needs and makes specific travel plans using the detailed information as a reference.

[1533] (Application example 2)

[1534] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1535] In recent years, users generally choose travel destinations based on information on the Internet. However, the vast amount of information available makes it difficult for users to quickly find a destination that matches their individual emotions and preferences. Conventional systems are unable to make suggestions that take into account the user's emotions and specific requirements. As a result, travel planning takes time and users may not be able to find a satisfying destination. To solve this problem, a system is needed that can suggest appropriate travel destinations based on user input, taking into account individual emotions and specific scenic images.

[1536] The identification process by the identification 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 a text input indicating a scenic image from a user, means for sending the text input to a scenic image generation model to generate a scenic image, means for searching for similar existing places based on the generated scenic image, and means for suggesting travel destinations to the user in real time based on the search results. This allows for the generation of prompt sentences based on the scenic image and emotions input by the user, making it possible to suggest travel destinations that accurately reflect the emotions and specific requests of each individual user.

[1537] A "landscape image generation model" is an artificial intelligence model that generates visual landscape images based on text input.

[1538] A "prompt sentence" is a text instruction sentence input to a landscape image generation model or an emotion analysis engine, and is a sentence that reflects the user's intentions and emotions.

[1539] "Text input" refers to character information that a user inputs through a terminal, and specifically expresses the scenery or emotions that the user wants to travel to.

[1540] "Search results" are a collection of data containing detailed information about existing locations that are similar to the images generated by the landscape image generation model, as identified by an image recognition algorithm.

[1541] The "travel destination suggestion means" is a system function that suggests suitable travel destinations to the user in real time based on the generated landscape images and search results.

[1542] "Detailed information" refers to information about each existing location included in the search results, including location information, access methods, tourist information, etc.

[1543] The "user input means" is an interface that allows the user to input landscape images and emotions in text format using a terminal.

[1544] "Real-time suggestions" is a function that suggests travel destinations based on input immediately after the user makes the input.

[1545] This invention is a system that allows a user to input a text image of a landscape they would like to travel to, and suggests existing travel destinations based on that image. This system is configured such that a server processes the text input by the user, analyzes the user's emotions using an emotion engine, generates a landscape image using a landscape image generation model, and searches for existing places based on that landscape image.

[1546] 1. User operations

[1547] The user inputs an image of the scenery they would like to travel to in text format. The device used by the user can be a smartphone, tablet, or PC. For example, consider the case where the user inputs "a rural landscape with beautiful cherry blossoms in full bloom."

[1548] 2. Device Operation

[1549] The terminal receives the user's input and sends the entered text to the server using a standard communication protocol such as an HTTP POST request, which transmits the text data to the server.

[1550] 3. Server Processing

[1551] The server analyzes the received text data and sends it to the emotion engine. The emotion engine analyzes the user's emotion from the text input and adjusts the prompts to the scenery image generation model based on that emotion. For example, if the user's input includes the emotion "I want to relax," the scenery image generation model will be instructed to generate a relaxing scenery image.

[1552] 4. Landscape Image Generation

[1553] The landscape image generation model in the server generates landscape images based on the prompt sentence adjusted by the emotion engine. The generated landscape images are stored in the server. Deep learning frameworks such as TensorFlow and Keras are suitable for the AI ​​model used.

[1554] 5. Image Recognition and Place Search

[1555] The generated landscape image is passed to an image recognition algorithm in the server, which searches for existing locations similar to this image. For example, based on the generated image of a rural landscape with cherry blossoms, specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto) can be identified.

[1556] 6. Providing search results

[1557] The server formats the generated landscape image and the search results for existing places, adds detailed information (location information, access methods, tourist information, etc.), and sends it to the user's device.

[1558] 7. Displaying the results

[1559] The device analyzes the search results received from the server and displays them to the user. Possible display methods include a list format or markers on a map. For example, information on "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed in list format.

[1560] Specific examples

[1561] For example, if a user inputs "I want to escape the hustle and bustle of the city," the system will analyze the emotion of "stress relief" and generate an image of a relaxing mountain landscape. Based on the generated image, it will identify places like "Shosenkyo Gorge" or "Mount Aso," and provide detailed information about them to the user.

[1562] Prompt Sentence Examples

[1563] Relaxing and quiet beach

[1564] An amusement park for the whole family

[1565] A mountain resort where you can feel close to nature

[1566] As described above, the present invention provides a system that suggests travel destinations according to a user's emotions and specific requests, thereby enabling the user to quickly find a travel destination that matches their individual emotions and wishes.

[1567] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1568] Step 1:

[1569] The user inputs an image of the scenery they want to travel to in text format using the terminal. For example, the user inputs "a beautiful countryside scenery with cherry blossoms in full bloom." This input data is received by the terminal.

[1570] Step 2:

[1571] The terminal sends the text data entered by the user to the server using an HTTP POST request. The input data (in text format) is passed to the server, and the server receives the data.

[1572] Step 3:

[1573] The server analyzes the received text data and passes the analysis results to the emotion engine, which then analyzes the input data using a natural language processing engine or similar to extract the emotions contained in the text.

[1574] Step 4:

[1575] The emotion engine analyzes the user's emotions from the text input and generates prompt sentences based on the analysis results. For example, from the input "A beautiful rural landscape with cherry blossoms in full bloom," it extracts the emotion "I want to relax" and adjusts the prompt sentence for the scenery image generation model to "A relaxing cherry blossom landscape."

[1576] Step 5:

[1577] The server passes the prompt sentence received from the emotion engine to the scenery image generation model, which generates a visual scenery image based on the prompt sentence.

[1578] Step 6:

[1579] The generated landscape image is stored on a server and passed to an image recognition algorithm, which identifies existing locations that are similar to the generated image. For example, a generated image of a cherry blossom landscape could identify specific tourist spots in Japan (e.g., Lake Suwa in Nagano Prefecture or the Philosopher's Path in Kyoto).

[1580] Step 7:

[1581] The server collects detailed information about the locations identified by the image recognition algorithm (location information, access methods, tourist information, etc.), formats this data, and sends it to the user's device.

[1582] Step 8:

[1583] The device analyzes the search results received from the server and displays them to the user. The display format can be a list or a marker on a map. For example, information about "Lake Suwa in Nagano Prefecture" and "Philosopher's Path in Kyoto" is displayed to the user in list format.

[1584] Through the above steps, users can quickly find travel destinations that suit their emotions and specific needs.

[1585] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1586] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1587] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1588] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1589] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1590] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1591] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1592] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1593] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1594] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1595] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1596] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1597] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1598] 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.

[1599] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1600] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1601] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1602] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1603] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1604] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1605] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1606] The following is further disclosed regarding the above embodiment.

[1607] (Claim 1)

[1608] means for receiving a text input from a user indicating a scenic image;

[1609] means for transmitting the text input to a landscape image generation AI to generate a landscape image;

[1610] A means for searching for similar existing places based on the generated landscape image;

[1611] means for providing the search results to a user;

[1612] A system including:

[1613] (Claim 2)

[1614] 10. The system of claim 1, wherein the search results include detailed information about each existing place.

[1615] (Claim 3)

[1616] The system according to claim 1, characterized in that the sending of the text input and the activation of the landscape image generation AI are performed automatically.

[1617] "Example 1"

[1618] (Claim 1)

[1619] means for receiving a text input from a user indicating a scenic image;

[1620] means for transmitting said text input to a server;

[1621] means for formatting said text input into an appropriate format and sending it to a landscape image generation AI;

[1622] A means for storing the landscape images generated by the landscape image generation AI in a database;

[1623] A method for analyzing the generated landscape image using an image recognition algorithm and searching for similar existing places;

[1624] means for adding detailed information about each existing location to the search results and transmitting the results to a user's terminal;

[1625] means for displaying the search results to a user;

[1626] A system including:

[1627] (Claim 2)

[1628] 2. The system of claim 1, wherein the detailed information for each existing place includes location, access instructions, and tourist information.

[1629] (Claim 3)

[1630] The system according to claim 1, characterized in that the sending of the text input and the activation of the landscape image generation AI are performed automatically.

[1631] "Application Example 1"

[1632] (Claim 1)

[1633] means for receiving a text input from a user indicating a scenic image;

[1634] means for transmitting the text input to a landscape image generation AI to generate a landscape image;

[1635] A means for searching for similar existing places based on the generated landscape image;

[1636] means for providing the search results to a user;

[1637] means for a user to virtually preview the proposed location;

[1638] A system including:

[1639] (Claim 2)

[1640] 10. The system of claim 1, wherein the search results include detailed information about each existing place.

[1641] (Claim 3)

[1642] The system according to claim 1, characterized in that the sending of the text input and the activation of the landscape image generation AI are performed automatically.

[1643] "Example 2: Combining Emotion Engines"

[1644] (Claim 1)

[1645] means for receiving a text input from a user indicating a scenic image;

[1646] means by the terminal for transmitting said text input to a server;

[1647] A means for analyzing the text data received by the server and transmitting it to the emotion engine;

[1648] A means for the emotion engine to analyze user emotions from text data;

[1649] The server adjusts the prompt based on the output of the emotion engine and sends it to the landscape image generation AI.

[1650] a means for the scenery image generation AI to generate a scenery image based on the adjusted prompt;

[1651] The server passes the generated landscape image to an image recognition algorithm to search for similar existing places;

[1652] means for providing the search results to a user;

[1653] A system including:

[1654] (Claim 2)

[1655] 10. The system of claim 1, wherein the search results include detailed information about each existing place.

[1656] (Claim 3)

[1657] The system according to claim 1, characterized in that the sending of the text input and the activation of the landscape image generation AI are performed automatically.

[1658] "Application example 2 when combining emotion engines"

[1659] (Claim 1)

[1660] means for receiving a text input from a user indicating a scenic image;

[1661] means for transmitting the text input to a landscape image generation model to generate a landscape image;

[1662] A means for searching for similar existing places based on the generated landscape image;

[1663] a means for suggesting travel destinations to users in real time based on the search results;

[1664] A system including:

[1665] (Claim 2)

[1666] 2. The system of claim 1, wherein the search results include detailed information and tourist information for each existing location.

[1667] (Claim 3)

[1668] The system of claim 1, wherein the text input is sent and the scenery image generation model is activated automatically to generate a prompt sentence based on the scenery image and emotion input by the user. [Explanation of symbols]

[1669] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving a text input from a user indicating a scenic image; means for transmitting the text input to a landscape image generation AI to generate a landscape image; A means for searching for similar existing places based on the generated landscape image; means for providing the search results to a user; A system including:

2. 10. The system of claim 1, wherein the search results include detailed information about each existing place.

3. 2. The system according to claim 1, wherein the sending of the text input and the activation of the scenery image generation AI are performed automatically.

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