System

Abstract

A system is provided.SOLUTION: A system comprising: means for allowing a user to upload an image of a store; means for allowing a terminal to analyze image data and acquire information on the store; means for allowing the terminal to request detailed information from generative artificial intelligence based on the acquired store information; means for allowing the generative artificial intelligence to generate the detailed information and provide the detailed information to the terminal; and means for allowing the terminal to display the detailed information to the user.SELECTED DRAWING: Figure 1

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] Many users today use social media to plan meals and trips. However, there is a lack of a way to quickly obtain detailed information about restaurants, access methods, and surrounding areas found on social media. As a result, users must manually gather the necessary information from multiple sources, reducing planning efficiency. To solve this problem, a system is needed that allows users to quickly and comprehensively obtain information about restaurants found on social media. [Means for solving the problem]

[0005] The present invention provides a system including a means for a user to upload an image of a store, a means for a terminal to analyze the image data and obtain information about the store, a means for the terminal to request detailed information from a generative artificial intelligence based on the store information obtained, a means for the generative artificial intelligence to generate the detailed information and provide it to the terminal, and a means for the terminal to display the detailed information to the user. Furthermore, by extracting information about the store's name, address, and products offered from the image data via a camera search API and requesting detailed information including nearby tourist spots and directions from the generative artificial intelligence, it becomes possible to provide users with efficient and comprehensive information.

[0006] A "user" is an individual or organization that uses the system to search for store information and obtain detailed information.

[0007] "Image data" refers to store photos and image files that users upload to the system.

[0008] A "terminal" is a device used by a user (such as a smartphone, tablet, or PC) that executes system processing.

[0009] The "Camera Search API" is an application programming interface that analyzes image data sent from a terminal and extracts information about the corresponding store.

[0010] "Generative artificial intelligence" refers to AI models and systems that are capable of generating detailed information that users need (e.g., store details, nearby tourist attractions, directions, etc.).

[0011] "Detailed information" refers to content that includes basic information about the store as well as additional information required by the user, such as nearby tourist spots and directions.

[0012] A "prompt" is an instruction or question sent to a generative artificial intelligence to generate more information. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

[0022] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0035] User operations

[0036] Users first use a device such as a smartphone or PC to take a photo of the store they want to visit or upload an existing image to the device, and then send the store image file to the system via a dedicated application or web interface on the device.

[0037] Terminal handling

[0038] The device receives the image file sent by the user and reads it as image data. At this time, the image is converted into byte data. The device then sends a request including the image data to the Camera Search API. The Camera Search API extracts information about the corresponding store from the image data (e.g., store name, address, and types of products offered).

[0039] After receiving the information from the camera search API, the device then sends a request for more information to the API of a generative artificial intelligence (e.g., ChatGPT), which includes basic information about the store, as well as prompts to generate information about nearby attractions and directions.

[0040] Server Processing

[0041] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic information about the store the user wants to visit, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0042] Displaying results on a terminal

[0043] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and use it as a reference when planning a visit.

[0044] Specific examples

[0045] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." Next, based on this information, the device asks a generative AI to generate detailed information, including nearby tourist spots and how to get there.

[0046] The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Ramen Shop A," making it easier to visit.

[0047] From the above, it can be seen that the present invention is a useful system that enables a user to efficiently obtain store information and plan a visit.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] Users upload images of the store they want to visit to the terminal. Specifically, they use their smartphone or PC to provide the system with photos they have taken or saved image files via a dedicated application or web interface.

[0051] Step 2:

[0052] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request.

[0053] Step 3:

[0054] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0055] Step 4:

[0056] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0057] Step 5:

[0058] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0059] Step 6:

[0060] Using the store information acquired by the device (store name, address, types of products offered), the device prepares a request for more information from the API of a generative artificial intelligence (e.g., ChatGPT). The prompt includes basic store information as well as a request to generate information about nearby tourist attractions and how to get there.

[0061] Step 7:

[0062] The device sends a request to the generative AI API containing the prepared prompt, and the generative AI generates detailed information based on this request.

[0063] Step 8:

[0064] The server (generative artificial intelligence) analyzes the received prompt and generates the requested detailed information, including the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, etc.

[0065] Step 9:

[0066] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0067] Step 10:

[0068] The device displays the received detailed information to the user. The display content is formatted in an easy-to-understand manner and includes store information, access methods, nearby spots, etc. This allows the user to efficiently obtain store details and plan their visit.

[0069] Example 1

[0070] 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."

[0071] In the past, users had to use multiple websites and applications to efficiently obtain facility information, which made information gathering cumbersome and time-consuming. Furthermore, the accuracy and detail of the information obtained was insufficient, often resulting in a lack of specific information when planning a visit. To solve this problem, there was a need for a single system that could efficiently and accurately obtain facility information, thereby improving user convenience.

[0072] 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.

[0073] In this invention, the server includes: means for a user to send an image of a facility; means for a terminal to read image data and convert the image data into byte data; means for the terminal to send the image data to an analysis API and acquire basic information about the facility; means for the terminal to request detailed information from a generative AI model based on the facility information acquired; means for the generative AI model to generate the detailed information and provide it to the terminal; and means for the terminal to display the detailed information to the user. This allows users to quickly obtain detailed facility information through a single system, enabling them to effectively plan their visit.

[0074] "User" refers to an individual or corporation that uses the system to obtain facility information.

[0075] "Facility" refers to the physical location visited or where the service is provided.

[0076] "Image data" refers to image files of a facility that have been photographed or uploaded.

[0077] "Byte data" refers to a format converted to handle image data as numerical information.

[0078] "Terminal" refers to a device such as a smartphone or PC operated by a user.

[0079] "Analysis API" refers to a program interface for analyzing image data and obtaining basic information about a facility.

[0080] A "generative AI model" refers to a program that uses artificial intelligence to generate detailed information from data.

[0081] "Basic information" refers to information about the facility's name, location, and services offered.

[0082] "Detailed information" refers to basic information plus additional information such as points of interest around the facility and how to access it.

[0083] "Prompt" refers to the wording used to request information generation from a generative AI model.

[0084] "Points of interest" refers to tourist attractions and noteworthy locations around the facility.

[0085] "Access method" refers to information about the means and route that a user can take to reach a facility.

[0086] The term "system" refers to a set of mechanisms and means that allow users to efficiently obtain facility information.

[0087] The present invention relates to a system that allows a user to transmit an image of a facility that the user wants to visit and obtains detailed information about the facility based on the image. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0088] User operations

[0089] Users take images of the facility using a device such as a smartphone or PC, and then send the images to the system using a dedicated application or web interface on the device.

[0090] Terminal handling

[0091] The device receives the image data sent by the user and stores it in its internal memory. This image data is then converted into bytes. The device then sends a request containing the image data to an analytics API, such as the Google Cloud Vision API, which retrieves basic information about the facility (name, address, and services offered) from the API.

[0092] Based on the acquired basic information, the device requests a generative AI model (e.g., OpenAI's ChatGPT) to generate detailed information. This request is designed to include basic information about the facility, as well as nearby points of interest and access methods.

[0093] Server Processing

[0094] The server uses a generative AI model to generate detailed information based on prompts received from the device, including basic information about the facility, directions from the nearest station, nearby points of interest, recommended menu items, etc. The final generated information is sent to the device in a data format such as JSON.

[0095] Displaying results on a terminal

[0096] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. The displayed information includes the facility name, location, products offered, access methods, nearby points of interest, recommended menu items, etc. This allows the user to efficiently obtain facility information and plan their visit.

[0097] Specific examples

[0098] For example, consider a case where a user takes a photo of "Restaurant A" and sends it to their device. The device sends this image to an analytics API, which extracts the name, address, and type of cuisine (e.g., Italian) of "Restaurant A." Using this information, the device then asks a generative AI model to generate more information about the restaurant, including nearby tourist attractions and how to get there.

[0099] Examples of specific prompts are:

[0100] Use the following information to generate facility details:

[0101] Facility name: Restaurant A

[0102] Address: Shinjuku Ward, Tokyo

[0103] Type of cuisine served: Italian

[0104] Please also tell me about nearby tourist spots and how to access them.

[0105] The information returned by the generative AI model includes the address of "Restaurant A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist attractions (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Restaurant A" and easily plan their visit.

[0106] The system of the present invention allows users to efficiently obtain detailed information and plan their visits effectively on one platform.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] Users can take a photo of the facility they want to visit using a device such as a smartphone or PC, or save an existing image to the device. Then, they can send this image file to the system using a dedicated application or web interface. The input is the image file of the facility, and the output is the image data sent to the device.

[0110] Step 2:

[0111] The terminal receives image data sent by the user and stores it in its internal memory. It then converts this image data into byte data. Specifically, it reads the image file and converts it into byte data format, preparing the data to be handled as numerical information. The input is the image data received from the user, and the output is byte data.

[0112] Step 3:

[0113] The device creates a request to send the converted byte data to an object recognition API (e.g., Google Cloud Vision API). This request includes image data and is analyzed by the object recognition API. The input is the byte data and request information to the object recognition API, and the output is the basic information of the facility returned by the API.

[0114] Step 4:

[0115] The object recognition API analyzes the received image data and extracts basic information about the facility (name, location, and services offered). This information is then returned to the device. The input is a request to the object recognition API, and the output is information about the facility's name, location, and services offered.

[0116] Step 5:

[0117] The device creates a prompt message requesting the generative AI model to generate detailed information based on the basic information about the facility obtained from the object recognition API. This prepares the message to be sent to the generative AI model. The input is the basic information about the facility, and the output is the prompt message to the generative AI model.

[0118] Step 6:

[0119] The terminal uses the generated prompt sentence to request the generative AI model to generate detailed information. This request includes basic information about the facility, as well as information about nearby points of interest and how to access them. The input is the prompt sentence, and the output is a request to the generative AI model.

[0120] Step 7:

[0121] The generative AI model generates detailed information based on the prompt it receives, including the facility's name, location, services offered, directions from the nearest station, nearby points of interest, recommended menu items, etc. The input is a request to the generative AI model, and the output is the generated detailed information.

[0122] Step 8:

[0123] The server converts the generated detailed information into a data format such as JSON and sends it to the terminal. The input is the generated detailed information, and the output is the formatted detailed information.

[0124] Step 9:

[0125] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility name, location, services offered, access instructions, nearby points of interest, recommended menu items, etc. The input is the detailed information received from the server, and the output is the information displayed on the user interface.

[0126] (Application example 1)

[0127] 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."

[0128] Currently, there is a lack of methods for users to quickly and comprehensively obtain information about stores they want to visit. In particular, while there are methods for obtaining store information based on images, the information is insufficiently detailed and provides insufficient additional related information. As a result, users must sequentially investigate multiple information sources, which is time-consuming and labor-intensive. In addition, display methods using generative AI are limited, making it difficult to obtain information easily.

[0129] 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.

[0130] In this invention, the server includes means for a user to upload an image via a smartphone application and send the image data to the server, means for the terminal to send the image data to a camera search API, means for the camera search API to analyze the image data and extract information about the store's name, address, and products offered, means for requesting the generative artificial intelligence to present detailed store information as well as nearby tourist spots and directions, and means for the generative artificial intelligence to generate the detailed store information and surrounding area information and provide it to the terminal. This allows the user to efficiently obtain detailed information and easily plan their visit.

[0131] "User" refers to a person who uploads an image to obtain store information.

[0132] "Store image" refers to a photo of the store that the user wants to visit, taken or prepared by the user.

[0133] "Terminal" refers to an electronic device used by a user, such as a smartphone or computer, that can upload store images.

[0134] "Image data" refers to an image file of a store uploaded by a user.

[0135] "Analysis" refers to the process of extracting specific store information from image data.

[0136] "Camera Search API" refers to an application program interface for obtaining specific information based on image data.

[0137] "Store information" refers to basic information that users want to know, such as the store's name, address, and products offered.

[0138] "Generative AI" refers to AI technology that generates detailed information based on given information.

[0139] "Detailed information" refers to additional information generated by generative artificial intelligence, such as tourist spots and directions in addition to basic store information.

[0140] "Smartphone application" refers to a dedicated application that is installed on a device and allows users to upload images.

[0141] "Nearby tourist spots" refers to new tourist attractions or points that are located near the store and that users can visit.

[0142] "Directions" refers to the method or route to access a particular store.

[0143] "Means" refers to a method or device used to achieve a particular purpose.

[0144] "Display" refers to the operation of visually showing information on a terminal screen, etc.

[0145] "Extraction" refers to the process by which the camera search API extracts the necessary information from image data.

[0146] The present invention relates to a system that allows users to upload store images and quickly obtain detailed store information. This system is primarily composed of user, terminal, and server components.

[0147] User operations

[0148] Users can take pictures of the stores they want to visit or upload existing images using a smartphone application, which has the function of sending the images to a server.

[0149] Terminal handling

[0150] The device, typically a smartphone, receives the image data sent by the user and sends it to the Camera Search API, which converts the image data into bytes. The Camera Search API then analyzes the image data and extracts information about the store's name, address, and products offered.

[0151] The device requests the API of a generative artificial intelligence (e.g., OpenAI GPT-3) to generate detailed information based on the basic information obtained from the camera search API. This request sets up a prompt to include information about nearby tourist spots and directions to the store, along with basic store information.

[0152] Server Processing

[0153] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic store information, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0154] Displaying results on a terminal

[0155] The terminal receives the detailed information sent from the server and displays it to the user. The displayed content includes detailed information such as the store name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and plan their visit.

[0156] Example

[0157] For example, consider the case where a user takes a photo of a ramen shop and uploads it to their device. The device sends this image data to a camera search API, which extracts the name of the ramen shop, its address, and the type of ramen it serves (e.g., tonkotsu ramen). Based on this information, the device then asks a generative AI to generate detailed information about the shop, including nearby tourist spots and how to get there.

[0158] Here are some examples of prompts for generative AI models:

[0159] Please generate your details based on the store information below.

[0160] Store name: Ramen shop

[0161] Address: Shinjuku Ward, Tokyo

[0162] Serving item: Tonkotsu ramen

[0163] Generates the following information:

[0164] 1. Directions from the nearest station

[0165] 2. Nearby tourist spots

[0166] 3. Recommended Menu

[0167] The hardware and software used in this system include a camera search API (e.g., Google Vision API), generative artificial intelligence (e.g., OpenAI GPT-3), and a smartphone application (e.g., a mobile app using React Native).

[0168] As a result, the present invention enables users to easily obtain detailed store information and efficiently plan their visit.

[0169] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0170] Step 1:

[0171] The user launches the smartphone application, takes a photo of the store they want to visit, selects it, and uploads it.

[0172] Input: Store image (taken or selected by user)

[0173] Output: Uploaded image data

[0174] Specific operation: Select an image from your smartphone's camera or photo gallery and press the upload button to the dedicated application.

[0175] Step 2:

[0176] The device receives the uploaded image data, converts it into byte format, and then sends the image data to the camera search API.

[0177] Input: Uploaded image data

[0178] Output: Camera search API request

[0179] Specific operation: The device converts the image data into byte format and sends it as an HTTP request to the camera search API.

[0180] Step 3:

[0181] The camera search API analyzes the image data and extracts information about the store's name, address, and products offered.

[0182] Input: Image data

[0183] Output: Store name, address, and product information

[0184] Specific operation: The camera search API uses image recognition technology to analyze the characteristics of the store and extract relevant information.

[0185] Step 4:

[0186] The device receives basic store information obtained from the camera search API and sends a request to the generative AI to generate detailed information. A prompt is set, and information about nearby tourist spots and how to get there is also included.

[0187] Input: Basic store information

[0188] Output: A request to the generative AI

[0189] Specific operation: The device generates a prompt sentence based on the acquired information and sends a request to the generative artificial intelligence API.

[0190] Step 5:

[0191] The generative artificial intelligence generates detailed information based on the input prompt sentence and returns it to the server.

[0192] Input: Prompt text (basic store information, nearby tourist spots, directions)

[0193] Output: Detailed information generated

[0194] Specific operation: Generative AI uses natural language processing technology to generate detailed information and respond in data format such as JSON.

[0195] Step 6:

[0196] The device receives the detailed information returned by the generative artificial intelligence and displays it in a format that can be viewed by the user.

[0197] Input: Generated details

[0198] Output: Displayable store details

[0199] Specific operation: The device displays the received information on the application screen in an appropriate format and provides it to the user.

[0200] Specific examples

[0201] For example, if a user takes a photo of a ramen shop and uploads the image, the process is as follows: The device receives the image and sends it to the camera search API, which extracts basic information about the "ramen shop." Next, the device uses this information to send a prompt to the generative AI, asking it to generate more information. The generative AI generates information such as directions from the nearest station, nearby tourist spots, and recommended menu items, and returns this information to the device. Finally, the device displays the detailed information to the user, allowing them to efficiently obtain store information and plan their visit.

[0202] 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.

[0203] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. The roles of the user, terminal, and server in one embodiment of this system are described in detail below.

[0204] User operations

[0205] First, a user uses a device such as a smartphone or PC to take a photo of the store they want to visit, or upload an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the user sends the store's image file and emotional data to the system via a dedicated application or web interface on the device.

[0206] Terminal handling

[0207] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it into byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion.

[0208] The device first generates a prompt that takes into account the user's emotional data, and then sends image data to the camera search API based on the prompt to obtain information about the store. The basic information obtained from the image data includes the user's name, address, and information about the products offered.

[0209] Server Processing

[0210] The server analyzes the user's emotional data using an emotion engine. Emotional data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This allows for the generation of detailed information based on the user's emotions.

[0211] After receiving the information obtained from the camera search API, the device sends a request for more information to a generative AI (e.g., ChatGPT). The request includes basic store information, as well as the user's emotional data and a request to generate information about nearby tourist spots and directions.

[0212] Generate detailed information

[0213] The generative AI generates detailed information based on the prompts. This information includes the store's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[0214] Displaying results on a terminal

[0215] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed store information and plan their visit.

[0216] Specific examples

[0217] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited.

[0218] Based on this, a request for detailed information is sent to the generative AI, including nearby tourist spots and how to access them, as well as events and activities that will satisfy the user's sense of excitement.The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho), and events that will satisfy the user's sense of excitement (e.g., nearby live music venues and bowling alleys).

[0219] As described above, the present invention is a useful system that enables users to efficiently obtain store information and plan their visit, and makes it possible to provide personalized information that takes into account the user's emotions.

[0220] The processing flow will be explained below.

[0221] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. As an embodiment of this system, the roles of the user, terminal, and server, as well as the specific processing flow, are described in detail below.

[0222] User operations

[0223] Step 1:

[0224] The user takes a photo of the store they want to visit or selects an existing image and uploads it to the terminal. The user then sends the store image to the system via a dedicated application on the terminal or a web interface.

[0225] Step 2:

[0226] The user is analyzed in real time by the emotion engine, and emotion data is collected. This emotion data is obtained from the user's facial expressions and voice and reflects the user's state.

[0227] Terminal handling

[0228] Step 3:

[0229] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request, along with any emotion data received from the emotion engine.

[0230] Step 4:

[0231] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0232] Server Processing

[0233] Step 5:

[0234] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0235] Step 6:

[0236] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0237] Generative AI processing

[0238] Step 7:

[0239] The device generates prompts based on store information (store name, address, types of products offered) and emotion data. The generated prompts are sent to a generative AI (e.g., ChatGPT).

[0240] Step 8:

[0241] The device sends a request containing a prompt to the generative AI API. This request includes basic store information as well as a request to generate information about nearby tourist spots and how to access them based on the user's emotions.

[0242] Step 9:

[0243] The server (generative artificial intelligence) analyzes the prompt and generates detailed information, including the store's name, address, directions from the nearest station, nearby tourist spots, and recommended menu items. It also generates information appropriate to the user's state of mind (e.g., a cafe with a relaxing atmosphere, a lively event) based on the user's emotional data.

[0244] Step 10:

[0245] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0246] Displaying results on a terminal

[0247] Step 11:

[0248] The device then displays the received detailed information to the user in an easy-to-understand format, including store information, access instructions, nearby attractions, and more. It also displays personalized information based on emotion data.

[0249] Specific examples

[0250] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to the terminal.

[0251] Step 1:

[0252] A user uploads an image of "Ramen Shop A" to their device.

[0253] Step 2:

[0254] The emotion engine analyzes the user's emotions in real time and collects emotional data. It determines that the user is excited.

[0255] Step 3:

[0256] The device receives the image file, converts it into byte data, and sends it to the camera search API.

[0257] Step 4:

[0258] The camera search API analyzes the image and extracts information about "Ramen Shop A."

[0259] Step 5:

[0260] The server returns store information in JSON format to the terminal.

[0261] Step 6:

[0262] The device generates prompts based on store information and emotional data and sends them to the generative artificial intelligence.

[0263] Step 7:

[0264] Generative AI generates detailed information and sends it back to the device.

[0265] Step 8:

[0266] The device receives the detailed information and displays it to the user, including the address of "Ramen Shop A," directions from the nearest station, tourist spots such as Shinjuku Gyoen and Kabukicho, and nearby live music venues and activities that are suitable for the excited user.

[0267] As described above, it has been shown that the present invention functions as a system that enables a user to efficiently obtain store information and make a visiting plan that takes into account the user's emotions.

[0268] Example 2

[0269] 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."

[0270] Conventional store information acquisition systems have difficulty effectively providing the detailed store information desired by users, and in particular have a lack of personalized information provision that responds to the user's emotions. In addition, there has been a lack of appropriate means for users to easily obtain information that interests them or the detailed information needed to plan their visit.

[0271] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing image data and acquiring store information, a means for analyzing emotion data and identifying the user's state, and a means for requesting detailed information from the generative artificial intelligence based on the acquired store information and emotion data. This makes it possible to provide detailed store information and personalized surrounding information according to the user's emotions.

[0272] "User" refers to a person who uses a service or application.

[0273] "Terminal" refers to electronic devices such as computers, smartphones, and tablets used by users.

[0274] "Image data" refers to photographs and image files taken or uploaded by a user using a terminal.

[0275] "Emotion data" refers to data related to emotions obtained by analyzing the user's facial expressions and voice.

[0276] "Server" refers to a computer system on a network that processes, stores, and manages data.

[0277] "Camera Search API" refers to an application programming interface for analyzing image data and obtaining information about objects.

[0278] "Generative AI" refers to an AI system that has the ability to generate responses in natural language based on specific prompts.

[0279] "Detailed information" refers to basic information about the store (name, address, products offered) and additional information customized according to the user's emotions.

[0280] A "prompt" refers to an input sentence that requests the generative artificial intelligence to generate detailed information.

[0281] "Store Information" refers to information about a specific store, including its name, address, and products offered, obtained through the Camera Search API.

[0282] "Nearby information" refers to information about tourist spots around the store and how to get there.

[0283] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. Specific embodiments for implementing this system will now be described in detail.

[0284] User operations

[0285] Users use devices such as smartphones or PCs to take pictures of the store they want to visit or upload existing images to their devices. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotion data. The user then sends the store's image file and emotion data to the system via a dedicated application or web interface.

[0286] Terminal handling

[0287] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG format) and converts it into byte data. The emotion data is then quantified or categorized to represent the user's emotion. Based on this data, the device prepares the data for the API request.

[0288] Server Processing

[0289] The server sends the image data sent from the device to the camera search API and obtains basic information about the store (e.g., store name, address, and products offered). The server also analyzes the emotional data using an emotion engine to identify the user's state (e.g., excited, relaxed). Based on this, the server sends a request for more information to a generative artificial intelligence (e.g., ChatGPT).

[0290] Generate detailed information

[0291] The generative AI generates detailed information based on prompts received from the server, including basic store information (name, address, directions from the nearest station), nearby tourist spots, and recommended menu items. It also generates specific information based on the user's emotional data (e.g., relaxing cafes and lively events).

[0292] Displaying results on a terminal

[0293] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. This information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. Personalized information based on the user's emotions is also provided, allowing the user to efficiently plan their visit.

[0294] Specific examples

[0295] For example, if a user uploads an image of "Ramen Shop A," the device sends this image to the camera search API, which retrieves the name, address, and type of product offered (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited. Based on this, it generates a prompt to the generative AI and sends a request for more information.

[0296] Prompt Sentence Examples

[0297] "Please provide basic store information: Generate detailed information based on the image of "Ramen Shop A" and the user's emotion data. Specifically, please include the store's name, address, information about the products offered (e.g., tonkotsu ramen), directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen, Kabukicho), and events that users can enjoy in an excited state (e.g., nearby live music venues and bowling alleys)."

[0298] As described above, the present invention is a useful system for enabling users to efficiently obtain store information and plan their visit by providing personalized information that takes emotions into consideration.

[0299] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0300] Step 1:

[0301] Users use their smartphones or PCs to take pictures of the stores they want to visit or upload existing images to the device. Users then collect emotion data along with the image data via a dedicated application or web interface. The input is the taken or uploaded store image and the user's emotion data, and the output is the image and emotion data stored on the device.

[0302] Step 2:

[0303] The device converts the image data acquired from the user into an appropriate format (e.g., JPEG format). The emotion data is then quantified or categorized using an emotion analysis engine. In this process, the input is the image data and emotion data from the user, and the output is a JPEG image and quantified or categorized emotion data.

[0304] Step 3:

[0305] The device formats the preprocessed image data and emotion data for an API request and sends it to the server. This API request contains the image data and quantified emotion data. The input is a JPEG image and numeric data, and the output is an API request sent to the server.

[0306] Step 4:

[0307] The server sends the received image data to the camera search API and obtains basic information about the store. The data processing performed here involves analyzing the image data, and the output is basic store information (e.g., store name, address, and products offered). At the same time, the server uses an emotion engine to analyze the emotion data and identify the user's current state. The inputs to this process are the received image data and emotion data, and the output is the obtained store information and the identified user's emotional state.

[0308] Step 5:

[0309] The server sends a request to generate detailed information to the generative AI based on basic store information and user emotion data. The input is the basic store information and user emotion data, and a prompt sentence including this data is generated and sent to the generative AI. The output is the detailed information request sent to the generative AI.

[0310] Step 6:

[0311] Generative AI generates detailed information based on the received prompt. This information includes the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, and more, as well as specific information based on the user's emotional data (e.g., a relaxing cafe or a lively event). The input to this process is the prompt, and the output is the generated detailed information.

[0312] Step 7:

[0313] The server transmits the detailed information obtained from the generative AI to the terminal. The input is the detailed information received from the generative AI, and the output is the detailed information transmitted to the terminal.

[0314] Step 8:

[0315] The terminal analyzes the detailed information received from the server and displays it in a user-friendly format. The displayed information includes the store name, address, products offered, access instructions, and nearby tourist attractions. The user can use this information to efficiently plan their visit. The input is the detailed information received from the server, and the output is the displayed detailed information and information used to plan the user's visit.

[0316] (Application example 2)

[0317] 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."

[0318] Conventional store information systems allowed users to upload images and obtain basic information, but they were unable to provide personalized information based on the user's current emotional state. As a result, it was difficult for users to obtain optimal information based on their interests and mood, limiting the user experience. Furthermore, they lacked a mechanism for providing comprehensive information on nearby tourist attractions and access methods.

[0319] 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 collecting user emotion data, means for analyzing the emotion data and generating detailed information based on the emotion, and means for requesting detailed information from the generative artificial intelligence. This makes it possible to provide personalized facility information according to the user's current emotional state, as well as information on surrounding tourist attractions and access methods, in an integrated manner.

[0320] "User" refers to a user who wishes to obtain facility information.

[0321] "Image of facility" refers to image data that a user takes or uploads, showing a facility that the user wants to visit.

[0322] "Device" refers to the electronic device, such as a computer, smartphone, or tablet, that a user uses to upload images and view information.

[0323] "Image Data" refers to digital image files containing images of a facility uploaded by a User.

[0324] "Establishment Information" means the name, address, and details of the establishment regarding the products and services offered.

[0325] "Generative AI" refers to an AI system that generates detailed information based on user requests.

[0326] "Detailed information" refers to data that includes basic information about the facility, as well as information about nearby tourist attractions, access methods, and personalized information based on the user's emotions.

[0327] "Emotion data" refers to information indicating the emotional state of a user that is obtained by analyzing facial expressions and voice data.

[0328] "Camera Search API" refers to an application programming interface for analyzing image data and extracting basic information about a facility.

[0329] "Tourist spots" refer to the sights and attractions that tourists should visit in the vicinity of the facility.

[0330] "Access method" refers to the means of transportation and route that a user takes to reach a facility or a nearby tourist spot.

[0331] The present invention is a system that allows users to upload images of facilities and obtain detailed information based on those images. This system can provide more personalized information by combining an emotion engine that recognizes the user's emotional state. Specific embodiments of the system are described in detail below.

[0332] User operations

[0333] First, a user takes a photo of the facility they want to visit using a device such as a smartphone or PC, or uploads an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the image file of the facility and the emotional data are sent to the system via a dedicated application or web interface on the device.

[0334] Terminal handling

[0335] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it to byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion. The device first generates a prompt that takes the user's emotion data into consideration, and then sends image data to the camera search API based on the prompt to obtain information about the facility. Basic information obtained from the image data includes the user's name, address, and information about the products offered.

[0336] Server Processing

[0337] The server uses an emotion engine to analyze the user's emotion data. Emotion data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This makes it possible to generate detailed information based on the user's emotion. After receiving the information obtained from the camera search API, the device further sends a request for detailed information to a generative artificial intelligence (e.g., ChatGPT). The request includes basic information about the facility, as well as the user's emotion data and a request to generate information about nearby tourist spots and how to get there.

[0338] Generate detailed information

[0339] The generative AI generates detailed information based on the prompts. This information includes the facility's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[0340] Displaying results on a terminal

[0341] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility's name, address, products offered, access methods, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed facility information and plan their visit.

[0342] Specific examples

[0343] For example, consider the case where a user takes a photo of Kiyomizu-dera Temple in Kyoto and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and services offered by "Kiyomizu-dera Temple." At the same time, the emotion engine analyzes the user's emotions and determines that the user is in a relaxed state. Based on this, a request is sent to the generative AI for more information, including nearby tourist attractions and how to access them, as well as recommended places to satisfy the user's sense of relaxation. The information returned by the generative AI includes the address of "Kiyomizu-dera Temple," directions to get there from the nearest station, nearby tourist attractions (e.g., Gion, Yasaka Shrine), and places to satisfy the user's sense of relaxation (e.g., nearby quiet cafes and gardens).

[0344] Prompt Sentence Examples

[0345] "Please tell me about sightseeing information for Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state and is looking for a comfortable cafe or a quiet walking route."

[0346] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0347] Step 1:

[0348] The user takes or uploads an image of the facility. Using a device such as a smartphone or PC, the user can take an image of the facility they want to visit or select an existing image and upload it. At the same time, the device analyzes the user's facial expressions and voice in real time to collect emotional data. The input is the image data of the facility and the user's emotional data, and the output is that this data is saved on the device.

[0349] Step 2:

[0350] The device sends image data and emotion data to the server. The device converts the image data sent by the user into an appropriate format (e.g., JPEG) and prepares the data for the API request as byte data. The emotion data is also used to quantify or categorize the user's emotion. The input is the image data and emotion data collected in step 1, and the output is the data for the API request.

[0351] Step 3:

[0352] The server uses the camera search API to obtain facility information. The server sends the received image data to the camera search API, which analyzes it and obtains basic information about the facility (e.g., name, address, services provided). The input is the image data sent from the device, and the output is the basic information about the facility.

[0353] Step 4:

[0354] The server analyzes the user's emotional data using an emotion engine. The server analyzes the received emotional data based on the emotion engine and identifies the user's current emotional state (e.g., relaxed, excited). This emotional data is used to generate detailed information in the future. The input is the emotional data sent from the device, and the output is the analyzed user's emotional state.

[0355] Step 5:

[0356] The server creates a prompt for the generative AI and requests detailed information. The server generates a prompt based on the acquired basic information about the facility and the user's emotional data obtained as a result of the analysis, and asks the generative AI to generate detailed information. For example, a prompt might be sent saying, "Please tell me about tourist information about Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state. I'm looking for a comfortable cafe or a quiet walking course." The input is the basic information about the facility and the user's emotional state, and the output is a prompt sent to the generative AI.

[0357] Step 6:

[0358] The generative AI generates detailed information and sends it back to the server. Based on the prompt, the generative AI generates detailed information such as basic information about the facility, nearby tourist attractions, how to get there, and recommended places based on the user's emotions. The input is the prompt, and the output is the generated detailed information.

[0359] Step 7:

[0360] The server sends detailed information to the terminal. The detailed information received from the generative AI is sent to the terminal in a data format such as JSON. The input is the detailed information from the generative AI, and the output is the data sent to the terminal.

[0361] Step 8:

[0362] The terminal displays detailed information to the user. The terminal analyzes the received detailed information and displays it in a format that is easy for the user to view. The displayed content includes the facility name, address, services provided, access methods, nearby tourist attractions, and recommended places based on the user's emotions. The input is the detailed information sent from the server, and the output is the information displayed on the user's terminal screen.

[0363] 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.

[0364] 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.

[0365] 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.

[0366] [Second embodiment]

[0367] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0368] 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.

[0369] 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).

[0370] 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.

[0371] 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.

[0372] 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).

[0373] 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.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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.

[0378] 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."

[0379] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0380] User operations

[0381] Users first use a device such as a smartphone or PC to take a photo of the store they want to visit or upload an existing image to the device, and then send the store image file to the system via a dedicated application or web interface on the device.

[0382] Terminal handling

[0383] The device receives the image file sent by the user and reads it as image data. At this time, the image is converted into byte data. The device then sends a request including the image data to the Camera Search API. The Camera Search API extracts information about the corresponding store from the image data (e.g., store name, address, and types of products offered).

[0384] After receiving the information from the camera search API, the device then sends a request for more information to the API of a generative artificial intelligence (e.g., ChatGPT), which includes basic information about the store, as well as prompts to generate information about nearby attractions and directions.

[0385] Server Processing

[0386] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic information about the store the user wants to visit, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0387] Displaying results on a terminal

[0388] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and use it as a reference when planning a visit.

[0389] Specific examples

[0390] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." Next, based on this information, the device asks a generative AI to generate detailed information, including nearby tourist spots and how to get there.

[0391] The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Ramen Shop A," making it easier to visit.

[0392] From the above, it can be seen that the present invention is a useful system that enables a user to efficiently obtain store information and plan a visit.

[0393] The processing flow will be explained below.

[0394] Step 1:

[0395] Users upload images of the store they want to visit to the terminal. Specifically, they use their smartphone or PC to provide the system with photos they have taken or saved image files via a dedicated application or web interface.

[0396] Step 2:

[0397] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request.

[0398] Step 3:

[0399] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0400] Step 4:

[0401] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0402] Step 5:

[0403] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0404] Step 6:

[0405] Using the store information acquired by the device (store name, address, types of products offered), the device prepares a request for more information from the API of a generative artificial intelligence (e.g., ChatGPT). The prompt includes basic store information as well as a request to generate information about nearby tourist attractions and how to get there.

[0406] Step 7:

[0407] The device sends a request to the generative AI API containing the prepared prompt, and the generative AI generates detailed information based on this request.

[0408] Step 8:

[0409] The server (generative artificial intelligence) analyzes the received prompt and generates the requested detailed information, including the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, etc.

[0410] Step 9:

[0411] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0412] Step 10:

[0413] The device displays the received detailed information to the user. The display content is formatted in an easy-to-understand manner and includes store information, access methods, nearby spots, etc. This allows the user to efficiently obtain store details and plan their visit.

[0414] Example 1

[0415] 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."

[0416] In the past, users had to use multiple websites and applications to efficiently obtain facility information, which made information gathering cumbersome and time-consuming. Furthermore, the accuracy and detail of the information obtained was insufficient, often resulting in a lack of specific information when planning a visit. To solve this problem, there was a need for a single system that could efficiently and accurately obtain facility information, thereby improving user convenience.

[0417] 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.

[0418] In this invention, the server includes: means for a user to send an image of a facility; means for a terminal to read image data and convert the image data into byte data; means for the terminal to send the image data to an analysis API and acquire basic information about the facility; means for the terminal to request detailed information from a generative AI model based on the facility information acquired; means for the generative AI model to generate the detailed information and provide it to the terminal; and means for the terminal to display the detailed information to the user. This allows users to quickly obtain detailed facility information through a single system, enabling them to effectively plan their visit.

[0419] "User" refers to an individual or corporation that uses the system to obtain facility information.

[0420] "Facility" refers to the physical location visited or where the service is provided.

[0421] "Image data" refers to image files of a facility that have been photographed or uploaded.

[0422] "Byte data" refers to a format converted to handle image data as numerical information.

[0423] "Terminal" refers to a device such as a smartphone or PC operated by a user.

[0424] "Analysis API" refers to a program interface for analyzing image data and obtaining basic information about a facility.

[0425] A "generative AI model" refers to a program that uses artificial intelligence to generate detailed information from data.

[0426] "Basic information" refers to information about the facility's name, location, and services offered.

[0427] "Detailed information" refers to basic information plus additional information such as points of interest around the facility and how to access it.

[0428] "Prompt" refers to the wording used to request information generation from a generative AI model.

[0429] "Points of interest" refers to tourist attractions and noteworthy locations around the facility.

[0430] "Access method" refers to information about the means and route that a user can take to reach a facility.

[0431] The term "system" refers to a set of mechanisms and means that allow users to efficiently obtain facility information.

[0432] The present invention relates to a system that allows a user to transmit an image of a facility that the user wants to visit and obtains detailed information about the facility based on the image. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0433] User operations

[0434] Users take images of the facility using a device such as a smartphone or PC, and then send the images to the system using a dedicated application or web interface on the device.

[0435] Terminal handling

[0436] The device receives the image data sent by the user and stores it in its internal memory. This image data is then converted into bytes. The device then sends a request containing the image data to an analytics API, such as the Google Cloud Vision API, which retrieves basic information about the facility (name, address, and services offered) from the API.

[0437] Based on the acquired basic information, the device requests a generative AI model (e.g., OpenAI's ChatGPT) to generate detailed information. This request is designed to include basic information about the facility, as well as nearby points of interest and access methods.

[0438] Server Processing

[0439] The server uses a generative AI model to generate detailed information based on prompts received from the device, including basic information about the facility, directions from the nearest station, nearby points of interest, recommended menu items, etc. The final generated information is sent to the device in a data format such as JSON.

[0440] Displaying results on a terminal

[0441] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. The displayed information includes the facility name, location, products offered, access methods, nearby points of interest, recommended menu items, etc. This allows the user to efficiently obtain facility information and plan their visit.

[0442] Specific examples

[0443] For example, consider a case where a user takes a photo of "Restaurant A" and sends it to their device. The device sends this image to an analytics API, which extracts the name, address, and type of cuisine (e.g., Italian) of "Restaurant A." Using this information, the device then asks a generative AI model to generate more information about the restaurant, including nearby tourist attractions and how to get there.

[0444] Examples of specific prompts are:

[0445] Use the following information to generate facility details:

[0446] Facility name: Restaurant A

[0447] Address: Shinjuku Ward, Tokyo

[0448] Type of cuisine served: Italian

[0449] Please also tell me about nearby tourist spots and how to access them.

[0450] The information returned by the generative AI model includes the address of "Restaurant A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist attractions (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Restaurant A" and easily plan their visit.

[0451] The system of the present invention allows users to efficiently obtain detailed information and plan their visits effectively on one platform.

[0452] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0453] Step 1:

[0454] Users can take a photo of the facility they want to visit using a device such as a smartphone or PC, or save an existing image to the device. Then, they can send this image file to the system using a dedicated application or web interface. The input is the image file of the facility, and the output is the image data sent to the device.

[0455] Step 2:

[0456] The terminal receives image data sent by the user and stores it in its internal memory. It then converts this image data into byte data. Specifically, it reads the image file and converts it into byte data format, preparing the data to be handled as numerical information. The input is the image data received from the user, and the output is byte data.

[0457] Step 3:

[0458] The device creates a request to send the converted byte data to an object recognition API (e.g., Google Cloud Vision API). This request includes image data and is analyzed by the object recognition API. The input is the byte data and request information to the object recognition API, and the output is the basic information of the facility returned by the API.

[0459] Step 4:

[0460] The object recognition API analyzes the received image data and extracts basic information about the facility (name, location, and services offered). This information is then returned to the device. The input is a request to the object recognition API, and the output is information about the facility's name, location, and services offered.

[0461] Step 5:

[0462] The device creates a prompt message requesting the generative AI model to generate detailed information based on the basic information about the facility obtained from the object recognition API. This prepares the message to be sent to the generative AI model. The input is the basic information about the facility, and the output is the prompt message to the generative AI model.

[0463] Step 6:

[0464] The terminal uses the generated prompt sentence to request the generative AI model to generate detailed information. This request includes basic information about the facility, as well as information about nearby points of interest and how to access them. The input is the prompt sentence, and the output is a request to the generative AI model.

[0465] Step 7:

[0466] The generative AI model generates detailed information based on the prompt it receives, including the facility's name, location, services offered, directions from the nearest station, nearby points of interest, recommended menu items, etc. The input is a request to the generative AI model, and the output is the generated detailed information.

[0467] Step 8:

[0468] The server converts the generated detailed information into a data format such as JSON and sends it to the terminal. The input is the generated detailed information, and the output is the formatted detailed information.

[0469] Step 9:

[0470] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility name, location, services offered, access instructions, nearby points of interest, recommended menu items, etc. The input is the detailed information received from the server, and the output is the information displayed on the user interface.

[0471] (Application example 1)

[0472] 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."

[0473] Currently, there is a lack of methods for users to quickly and comprehensively obtain information about stores they want to visit. In particular, while there are methods for obtaining store information based on images, the information is insufficiently detailed and provides insufficient additional related information. As a result, users must sequentially investigate multiple information sources, which is time-consuming and labor-intensive. In addition, display methods using generative AI are limited, making it difficult to obtain information easily.

[0474] 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.

[0475] In this invention, the server includes means for a user to upload an image via a smartphone application and send the image data to the server, means for the terminal to send the image data to a camera search API, means for the camera search API to analyze the image data and extract information about the store's name, address, and products offered, means for requesting the generative artificial intelligence to present detailed store information as well as nearby tourist spots and directions, and means for the generative artificial intelligence to generate the detailed store information and surrounding area information and provide it to the terminal. This allows the user to efficiently obtain detailed information and easily plan their visit.

[0476] "User" refers to a person who uploads an image to obtain store information.

[0477] "Store image" refers to a photo of the store that the user wants to visit, taken or prepared by the user.

[0478] "Terminal" refers to an electronic device used by a user, such as a smartphone or computer, that can upload store images.

[0479] "Image data" refers to an image file of a store uploaded by a user.

[0480] "Analysis" refers to the process of extracting specific store information from image data.

[0481] "Camera Search API" refers to an application program interface for obtaining specific information based on image data.

[0482] "Store information" refers to basic information that users want to know, such as the store's name, address, and products offered.

[0483] "Generative AI" refers to AI technology that generates detailed information based on given information.

[0484] "Detailed information" refers to additional information generated by generative artificial intelligence, such as tourist spots and directions in addition to basic store information.

[0485] "Smartphone application" refers to a dedicated application that is installed on a device and allows users to upload images.

[0486] "Nearby tourist spots" refers to new tourist attractions or points that are located near the store and that users can visit.

[0487] "Directions" refers to the method or route to access a particular store.

[0488] "Means" refers to a method or device used to achieve a particular purpose.

[0489] "Display" refers to the operation of visually showing information on a terminal screen, etc.

[0490] "Extraction" refers to the process by which the camera search API extracts the necessary information from image data.

[0491] The present invention relates to a system that allows users to upload store images and quickly obtain detailed store information. This system is primarily composed of user, terminal, and server components.

[0492] User operations

[0493] Users can take pictures of the stores they want to visit or upload existing images using a smartphone application, which has the function of sending the images to a server.

[0494] Terminal handling

[0495] The device, typically a smartphone, receives the image data sent by the user and sends it to the Camera Search API, which converts the image data into bytes. The Camera Search API then analyzes the image data and extracts information about the store's name, address, and products offered.

[0496] The device requests the API of a generative artificial intelligence (e.g., OpenAI GPT-3) to generate detailed information based on the basic information obtained from the camera search API. This request sets up a prompt to include information about nearby tourist spots and directions to the store, along with basic store information.

[0497] Server Processing

[0498] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic store information, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0499] Displaying results on a terminal

[0500] The terminal receives the detailed information sent from the server and displays it to the user. The displayed content includes detailed information such as the store name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and plan their visit.

[0501] Example

[0502] For example, consider the case where a user takes a photo of a ramen shop and uploads it to their device. The device sends this image data to a camera search API, which extracts the name of the ramen shop, its address, and the type of ramen it serves (e.g., tonkotsu ramen). Based on this information, the device then asks a generative AI to generate detailed information about the shop, including nearby tourist spots and how to get there.

[0503] Here are some examples of prompts for generative AI models:

[0504] Please generate your details based on the store information below.

[0505] Store name: Ramen shop

[0506] Address: Shinjuku Ward, Tokyo

[0507] Serving item: Tonkotsu ramen

[0508] Generates the following information:

[0509] 1. Directions from the nearest station

[0510] 2. Nearby tourist spots

[0511] 3. Recommended Menu

[0512] The hardware and software used in this system include a camera search API (e.g., Google Vision API), generative artificial intelligence (e.g., OpenAI GPT-3), and a smartphone application (e.g., a mobile app using React Native).

[0513] As a result, the present invention enables users to easily obtain detailed store information and efficiently plan their visit.

[0514] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0515] Step 1:

[0516] The user launches the smartphone application, takes a photo of the store they want to visit, selects it, and uploads it.

[0517] Input: Store image (taken or selected by user)

[0518] Output: Uploaded image data

[0519] Specific operation: Select an image from your smartphone's camera or photo gallery and press the upload button to the dedicated application.

[0520] Step 2:

[0521] The device receives the uploaded image data, converts it into byte format, and then sends the image data to the camera search API.

[0522] Input: Uploaded image data

[0523] Output: Camera search API request

[0524] Specific operation: The device converts the image data into byte format and sends it as an HTTP request to the camera search API.

[0525] Step 3:

[0526] The camera search API analyzes the image data and extracts information about the store's name, address, and products offered.

[0527] Input: Image data

[0528] Output: Store name, address, and product information

[0529] Specific operation: The camera search API uses image recognition technology to analyze the characteristics of the store and extract relevant information.

[0530] Step 4:

[0531] The device receives basic store information obtained from the camera search API and sends a request to the generative AI to generate detailed information. A prompt is set, and information about nearby tourist spots and how to get there is also included.

[0532] Input: Basic store information

[0533] Output: A request to the generative AI

[0534] Specific operation: The device generates a prompt sentence based on the acquired information and sends a request to the generative artificial intelligence API.

[0535] Step 5:

[0536] The generative artificial intelligence generates detailed information based on the input prompt sentence and returns it to the server.

[0537] Input: Prompt text (basic store information, nearby tourist spots, directions)

[0538] Output: Detailed information generated

[0539] Specific operation: Generative AI uses natural language processing technology to generate detailed information and respond in data format such as JSON.

[0540] Step 6:

[0541] The device receives the detailed information returned by the generative artificial intelligence and displays it in a format that can be viewed by the user.

[0542] Input: Generated details

[0543] Output: Displayable store details

[0544] Specific operation: The device displays the received information on the application screen in an appropriate format and provides it to the user.

[0545] Specific examples

[0546] For example, if a user takes a photo of a ramen shop and uploads the image, the process is as follows: The device receives the image and sends it to the camera search API, which extracts basic information about the "ramen shop." Next, the device uses this information to send a prompt to the generative AI, asking it to generate more information. The generative AI generates information such as directions from the nearest station, nearby tourist spots, and recommended menu items, and returns this information to the device. Finally, the device displays the detailed information to the user, allowing them to efficiently obtain store information and plan their visit.

[0547] 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.

[0548] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. The roles of the user, terminal, and server in one embodiment of this system are described in detail below.

[0549] User operations

[0550] First, a user uses a device such as a smartphone or PC to take a photo of the store they want to visit, or upload an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the user sends the store's image file and emotional data to the system via a dedicated application or web interface on the device.

[0551] Terminal handling

[0552] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it into byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion.

[0553] The device first generates a prompt that takes into account the user's emotional data, and then sends image data to the camera search API based on the prompt to obtain information about the store. The basic information obtained from the image data includes the user's name, address, and information about the products offered.

[0554] Server Processing

[0555] The server analyzes the user's emotional data using an emotion engine. Emotional data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This allows for the generation of detailed information based on the user's emotions.

[0556] After receiving the information obtained from the camera search API, the device sends a request for more information to a generative AI (e.g., ChatGPT). The request includes basic store information, as well as the user's emotional data and a request to generate information about nearby tourist spots and directions.

[0557] Generate detailed information

[0558] The generative AI generates detailed information based on the prompts. This information includes the store's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[0559] Displaying results on a terminal

[0560] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed store information and plan their visit.

[0561] Specific examples

[0562] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited.

[0563] Based on this, a request for detailed information is sent to the generative AI, including nearby tourist spots and how to access them, as well as events and activities that will satisfy the user's sense of excitement.The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho), and events that will satisfy the user's sense of excitement (e.g., nearby live music venues and bowling alleys).

[0564] As described above, the present invention is a useful system that enables users to efficiently obtain store information and plan their visit, and makes it possible to provide personalized information that takes into account the user's emotions.

[0565] The processing flow will be explained below.

[0566] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. As an embodiment of this system, the roles of the user, terminal, and server, as well as the specific processing flow, are described in detail below.

[0567] User operations

[0568] Step 1:

[0569] The user takes a photo of the store they want to visit or selects an existing image and uploads it to the terminal. The user then sends the store image to the system via a dedicated application on the terminal or a web interface.

[0570] Step 2:

[0571] The user is analyzed in real time by the emotion engine, and emotion data is collected. This emotion data is obtained from the user's facial expressions and voice and reflects the user's state.

[0572] Terminal handling

[0573] Step 3:

[0574] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request, along with any emotion data received from the emotion engine.

[0575] Step 4:

[0576] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0577] Server Processing

[0578] Step 5:

[0579] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0580] Step 6:

[0581] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0582] Generative AI processing

[0583] Step 7:

[0584] The device generates prompts based on store information (store name, address, types of products offered) and emotion data. The generated prompts are sent to a generative AI (e.g., ChatGPT).

[0585] Step 8:

[0586] The device sends a request containing a prompt to the generative AI API. This request includes basic store information as well as a request to generate information about nearby tourist spots and how to access them based on the user's emotions.

[0587] Step 9:

[0588] The server (generative artificial intelligence) analyzes the prompt and generates detailed information, including the store's name, address, directions from the nearest station, nearby tourist spots, and recommended menu items. It also generates information appropriate to the user's state of mind (e.g., a cafe with a relaxing atmosphere, a lively event) based on the user's emotional data.

[0589] Step 10:

[0590] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0591] Displaying results on a terminal

[0592] Step 11:

[0593] The device then displays the received detailed information to the user in an easy-to-understand format, including store information, access instructions, nearby attractions, and more. It also displays personalized information based on emotion data.

[0594] Specific examples

[0595] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to the terminal.

[0596] Step 1:

[0597] A user uploads an image of "Ramen Shop A" to their device.

[0598] Step 2:

[0599] The emotion engine analyzes the user's emotions in real time and collects emotional data. It determines that the user is excited.

[0600] Step 3:

[0601] The device receives the image file, converts it into byte data, and sends it to the camera search API.

[0602] Step 4:

[0603] The camera search API analyzes the image and extracts information about "Ramen Shop A."

[0604] Step 5:

[0605] The server returns store information in JSON format to the terminal.

[0606] Step 6:

[0607] The device generates prompts based on store information and emotional data and sends them to the generative artificial intelligence.

[0608] Step 7:

[0609] Generative AI generates detailed information and sends it back to the device.

[0610] Step 8:

[0611] The device receives the detailed information and displays it to the user, including the address of "Ramen Shop A," directions from the nearest station, tourist spots such as Shinjuku Gyoen and Kabukicho, and nearby live music venues and activities that are suitable for the excited user.

[0612] As described above, it has been shown that the present invention functions as a system that enables a user to efficiently obtain store information and make a visiting plan that takes into account the user's emotions.

[0613] Example 2

[0614] 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."

[0615] Conventional store information acquisition systems have difficulty effectively providing the detailed store information desired by users, and in particular have a lack of personalized information provision that responds to the user's emotions. In addition, there has been a lack of appropriate means for users to easily obtain information that interests them or the detailed information needed to plan their visit.

[0616] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing image data and acquiring store information, a means for analyzing emotion data and identifying the user's state, and a means for requesting detailed information from the generative artificial intelligence based on the acquired store information and emotion data. This makes it possible to provide detailed store information and personalized surrounding information according to the user's emotions.

[0617] "User" refers to a person who uses a service or application.

[0618] "Terminal" refers to electronic devices such as computers, smartphones, and tablets used by users.

[0619] "Image data" refers to photographs and image files taken or uploaded by a user using a terminal.

[0620] "Emotion data" refers to data related to emotions obtained by analyzing the user's facial expressions and voice.

[0621] "Server" refers to a computer system on a network that processes, stores, and manages data.

[0622] "Camera Search API" refers to an application programming interface for analyzing image data and obtaining information about objects.

[0623] "Generative AI" refers to an AI system that has the ability to generate responses in natural language based on specific prompts.

[0624] "Detailed information" refers to basic information about the store (name, address, products offered) and additional information customized according to the user's emotions.

[0625] A "prompt" refers to an input sentence that requests the generative artificial intelligence to generate detailed information.

[0626] "Store Information" refers to information about a specific store, including its name, address, and products offered, obtained through the Camera Search API.

[0627] "Nearby information" refers to information about tourist spots around the store and how to get there.

[0628] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. Specific embodiments for implementing this system will now be described in detail.

[0629] User operations

[0630] Users use devices such as smartphones or PCs to take pictures of the store they want to visit or upload existing images to their devices. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotion data. The user then sends the store's image file and emotion data to the system via a dedicated application or web interface.

[0631] Terminal handling

[0632] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG format) and converts it into byte data. The emotion data is then quantified or categorized to represent the user's emotion. Based on this data, the device prepares the data for the API request.

[0633] Server Processing

[0634] The server sends the image data sent from the device to the camera search API and obtains basic information about the store (e.g., store name, address, and products offered). The server also analyzes the emotional data using an emotion engine to identify the user's state (e.g., excited, relaxed). Based on this, the server sends a request for more information to a generative artificial intelligence (e.g., ChatGPT).

[0635] Generate detailed information

[0636] The generative AI generates detailed information based on prompts received from the server, including basic store information (name, address, directions from the nearest station), nearby tourist spots, and recommended menu items. It also generates specific information based on the user's emotional data (e.g., relaxing cafes and lively events).

[0637] Displaying results on a terminal

[0638] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. This information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. Personalized information based on the user's emotions is also provided, allowing the user to efficiently plan their visit.

[0639] Specific examples

[0640] For example, if a user uploads an image of "Ramen Shop A," the device sends this image to the camera search API, which retrieves the name, address, and type of product offered (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited. Based on this, it generates a prompt to the generative AI and sends a request for more information.

[0641] Prompt Sentence Examples

[0642] "Please provide basic store information: Generate detailed information based on the image of "Ramen Shop A" and the user's emotion data. Specifically, please include the store's name, address, information about the products offered (e.g., tonkotsu ramen), directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen, Kabukicho), and events that users can enjoy in an excited state (e.g., nearby live music venues and bowling alleys)."

[0643] As described above, the present invention is a useful system for enabling users to efficiently obtain store information and plan their visit by providing personalized information that takes emotions into consideration.

[0644] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0645] Step 1:

[0646] Users use their smartphones or PCs to take pictures of the stores they want to visit or upload existing images to the device. Users then collect emotion data along with the image data via a dedicated application or web interface. The input is the taken or uploaded store image and the user's emotion data, and the output is the image and emotion data stored on the device.

[0647] Step 2:

[0648] The device converts the image data acquired from the user into an appropriate format (e.g., JPEG format). The emotion data is then quantified or categorized using an emotion analysis engine. In this process, the input is the image data and emotion data from the user, and the output is a JPEG image and quantified or categorized emotion data.

[0649] Step 3:

[0650] The device formats the preprocessed image data and emotion data for an API request and sends it to the server. This API request contains the image data and quantified emotion data. The input is a JPEG image and numeric data, and the output is an API request sent to the server.

[0651] Step 4:

[0652] The server sends the received image data to the camera search API and obtains basic information about the store. The data processing performed here involves analyzing the image data, and the output is basic store information (e.g., store name, address, and products offered). At the same time, the server uses an emotion engine to analyze the emotion data and identify the user's current state. The inputs to this process are the received image data and emotion data, and the output is the obtained store information and the identified user's emotional state.

[0653] Step 5:

[0654] The server sends a request to generate detailed information to the generative AI based on basic store information and user emotion data. The input is the basic store information and user emotion data, and a prompt sentence including this data is generated and sent to the generative AI. The output is the detailed information request sent to the generative AI.

[0655] Step 6:

[0656] Generative AI generates detailed information based on the received prompt. This information includes the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, and more, as well as specific information based on the user's emotional data (e.g., a relaxing cafe or a lively event). The input to this process is the prompt, and the output is the generated detailed information.

[0657] Step 7:

[0658] The server transmits the detailed information obtained from the generative AI to the terminal. The input is the detailed information received from the generative AI, and the output is the detailed information transmitted to the terminal.

[0659] Step 8:

[0660] The terminal analyzes the detailed information received from the server and displays it in a user-friendly format. The displayed information includes the store name, address, products offered, access instructions, and nearby tourist attractions. The user can use this information to efficiently plan their visit. The input is the detailed information received from the server, and the output is the displayed detailed information and information used to plan the user's visit.

[0661] (Application example 2)

[0662] 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."

[0663] Conventional store information systems allowed users to upload images and obtain basic information, but they were unable to provide personalized information based on the user's current emotional state. As a result, it was difficult for users to obtain optimal information based on their interests and mood, limiting the user experience. Furthermore, they lacked a mechanism for providing comprehensive information on nearby tourist attractions and access methods.

[0664] 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 collecting user emotion data, means for analyzing the emotion data and generating detailed information based on the emotion, and means for requesting detailed information from the generative artificial intelligence. This makes it possible to provide personalized facility information according to the user's current emotional state, as well as information on surrounding tourist attractions and access methods, in an integrated manner.

[0665] "User" refers to a user who wishes to obtain facility information.

[0666] "Image of facility" refers to image data that a user takes or uploads, showing a facility that the user wants to visit.

[0667] "Device" refers to the electronic device, such as a computer, smartphone, or tablet, that a user uses to upload images and view information.

[0668] "Image Data" refers to digital image files containing images of a facility uploaded by a User.

[0669] "Establishment Information" means the name, address, and details of the establishment regarding the products and services offered.

[0670] "Generative AI" refers to an AI system that generates detailed information based on user requests.

[0671] "Detailed information" refers to data that includes basic information about the facility, as well as information about nearby tourist attractions, access methods, and personalized information based on the user's emotions.

[0672] "Emotion data" refers to information indicating the emotional state of a user that is obtained by analyzing facial expressions and voice data.

[0673] "Camera Search API" refers to an application programming interface for analyzing image data and extracting basic information about a facility.

[0674] "Tourist spots" refer to the sights and attractions that tourists should visit in the vicinity of the facility.

[0675] "Access method" refers to the means of transportation and route that a user takes to reach a facility or a nearby tourist spot.

[0676] The present invention is a system that allows users to upload images of facilities and obtain detailed information based on those images. This system can provide more personalized information by combining an emotion engine that recognizes the user's emotional state. Specific embodiments of the system are described in detail below.

[0677] User operations

[0678] First, a user takes a photo of the facility they want to visit using a device such as a smartphone or PC, or uploads an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the image file of the facility and the emotional data are sent to the system via a dedicated application or web interface on the device.

[0679] Terminal handling

[0680] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it to byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion. The device first generates a prompt that takes the user's emotion data into consideration, and then sends image data to the camera search API based on the prompt to obtain information about the facility. Basic information obtained from the image data includes the user's name, address, and information about the products offered.

[0681] Server Processing

[0682] The server uses an emotion engine to analyze the user's emotion data. Emotion data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This makes it possible to generate detailed information based on the user's emotion. After receiving the information obtained from the camera search API, the device further sends a request for detailed information to a generative artificial intelligence (e.g., ChatGPT). The request includes basic information about the facility, as well as the user's emotion data and a request to generate information about nearby tourist spots and how to get there.

[0683] Generate detailed information

[0684] The generative AI generates detailed information based on the prompts. This information includes the facility's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[0685] Displaying results on a terminal

[0686] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility's name, address, products offered, access methods, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed facility information and plan their visit.

[0687] Specific examples

[0688] For example, consider the case where a user takes a photo of Kiyomizu-dera Temple in Kyoto and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and services offered by "Kiyomizu-dera Temple." At the same time, the emotion engine analyzes the user's emotions and determines that the user is in a relaxed state. Based on this, a request is sent to the generative AI for more information, including nearby tourist attractions and how to access them, as well as recommended places to satisfy the user's sense of relaxation. The information returned by the generative AI includes the address of "Kiyomizu-dera Temple," directions to get there from the nearest station, nearby tourist attractions (e.g., Gion, Yasaka Shrine), and places to satisfy the user's sense of relaxation (e.g., nearby quiet cafes and gardens).

[0689] Prompt Sentence Examples

[0690] "Please tell me about sightseeing information for Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state and is looking for a comfortable cafe or a quiet walking route."

[0691] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0692] Step 1:

[0693] The user takes or uploads an image of the facility. Using a device such as a smartphone or PC, the user can take an image of the facility they want to visit or select an existing image and upload it. At the same time, the device analyzes the user's facial expressions and voice in real time to collect emotional data. The input is the image data of the facility and the user's emotional data, and the output is that this data is saved on the device.

[0694] Step 2:

[0695] The device sends image data and emotion data to the server. The device converts the image data sent by the user into an appropriate format (e.g., JPEG) and prepares the data for the API request as byte data. The emotion data is also used to quantify or categorize the user's emotion. The input is the image data and emotion data collected in step 1, and the output is the data for the API request.

[0696] Step 3:

[0697] The server uses the camera search API to obtain facility information. The server sends the received image data to the camera search API, which analyzes it and obtains basic information about the facility (e.g., name, address, services provided). The input is the image data sent from the device, and the output is the basic information about the facility.

[0698] Step 4:

[0699] The server analyzes the user's emotional data using an emotion engine. The server analyzes the received emotional data based on the emotion engine and identifies the user's current emotional state (e.g., relaxed, excited). This emotional data is used to generate detailed information in the future. The input is the emotional data sent from the device, and the output is the analyzed user's emotional state.

[0700] Step 5:

[0701] The server creates a prompt for the generative AI and requests detailed information. The server generates a prompt based on the acquired basic information about the facility and the user's emotional data obtained as a result of the analysis, and asks the generative AI to generate detailed information. For example, a prompt might be sent saying, "Please tell me about tourist information about Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state. I'm looking for a comfortable cafe or a quiet walking course." The input is the basic information about the facility and the user's emotional state, and the output is a prompt sent to the generative AI.

[0702] Step 6:

[0703] The generative AI generates detailed information and sends it back to the server. Based on the prompt, the generative AI generates detailed information such as basic information about the facility, nearby tourist attractions, how to get there, and recommended places based on the user's emotions. The input is the prompt, and the output is the generated detailed information.

[0704] Step 7:

[0705] The server sends detailed information to the terminal. The detailed information received from the generative AI is sent to the terminal in a data format such as JSON. The input is the detailed information from the generative AI, and the output is the data sent to the terminal.

[0706] Step 8:

[0707] The terminal displays detailed information to the user. The terminal analyzes the received detailed information and displays it in a format that is easy for the user to view. The displayed content includes the facility name, address, services provided, access methods, nearby tourist attractions, and recommended places based on the user's emotions. The input is the detailed information sent from the server, and the output is the information displayed on the user's terminal screen.

[0708] 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.

[0709] 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.

[0710] 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.

[0711] [Third embodiment]

[0712] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0713] 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.

[0714] 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).

[0715] 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.

[0716] 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.

[0717] 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).

[0718] 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.

[0719] 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.

[0720] 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.

[0721] 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.

[0722] 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.

[0723] 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."

[0724] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0725] User operations

[0726] Users first use a device such as a smartphone or PC to take a photo of the store they want to visit or upload an existing image to the device, and then send the store image file to the system via a dedicated application or web interface on the device.

[0727] Terminal handling

[0728] The device receives the image file sent by the user and reads it as image data. At this time, the image is converted into byte data. The device then sends a request including the image data to the Camera Search API. The Camera Search API extracts information about the corresponding store from the image data (e.g., store name, address, and types of products offered).

[0729] After receiving the information from the camera search API, the device then sends a request for more information to the API of a generative artificial intelligence (e.g., ChatGPT), which includes basic information about the store, as well as prompts to generate information about nearby attractions and directions.

[0730] Server Processing

[0731] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic information about the store the user wants to visit, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0732] Displaying results on a terminal

[0733] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and use it as a reference when planning a visit.

[0734] Specific examples

[0735] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." Next, based on this information, the device asks a generative AI to generate detailed information, including nearby tourist spots and how to get there.

[0736] The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Ramen Shop A," making it easier to visit.

[0737] From the above, it can be seen that the present invention is a useful system that enables a user to efficiently obtain store information and plan a visit.

[0738] The processing flow will be explained below.

[0739] Step 1:

[0740] Users upload images of the store they want to visit to the terminal. Specifically, they use their smartphone or PC to provide the system with photos they have taken or saved image files via a dedicated application or web interface.

[0741] Step 2:

[0742] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request.

[0743] Step 3:

[0744] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0745] Step 4:

[0746] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0747] Step 5:

[0748] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0749] Step 6:

[0750] Using the store information acquired by the device (store name, address, types of products offered), the device prepares a request for more information from the API of a generative artificial intelligence (e.g., ChatGPT). The prompt includes basic store information as well as a request to generate information about nearby tourist attractions and how to get there.

[0751] Step 7:

[0752] The device sends a request to the generative AI API containing the prepared prompt, and the generative AI generates detailed information based on this request.

[0753] Step 8:

[0754] The server (generative artificial intelligence) analyzes the received prompt and generates the requested detailed information, including the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, etc.

[0755] Step 9:

[0756] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0757] Step 10:

[0758] The device displays the received detailed information to the user. The display content is formatted in an easy-to-understand manner and includes store information, access methods, nearby spots, etc. This allows the user to efficiently obtain store details and plan their visit.

[0759] Example 1

[0760] 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."

[0761] In the past, users had to use multiple websites and applications to efficiently obtain facility information, which made information gathering cumbersome and time-consuming. Furthermore, the accuracy and detail of the information obtained was insufficient, often resulting in a lack of specific information when planning a visit. To solve this problem, there was a need for a single system that could efficiently and accurately obtain facility information, thereby improving user convenience.

[0762] 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.

[0763] In this invention, the server includes: means for a user to send an image of a facility; means for a terminal to read image data and convert the image data into byte data; means for the terminal to send the image data to an analysis API and acquire basic information about the facility; means for the terminal to request detailed information from a generative AI model based on the facility information acquired; means for the generative AI model to generate the detailed information and provide it to the terminal; and means for the terminal to display the detailed information to the user. This allows users to quickly obtain detailed facility information through a single system, enabling them to effectively plan their visit.

[0764] "User" refers to an individual or corporation that uses the system to obtain facility information.

[0765] "Facility" refers to the physical location visited or where the service is provided.

[0766] "Image data" refers to image files of a facility that have been photographed or uploaded.

[0767] "Byte data" refers to a format converted to handle image data as numerical information.

[0768] "Terminal" refers to a device such as a smartphone or PC operated by a user.

[0769] "Analysis API" refers to a program interface for analyzing image data and obtaining basic information about a facility.

[0770] A "generative AI model" refers to a program that uses artificial intelligence to generate detailed information from data.

[0771] "Basic information" refers to information about the facility's name, location, and services offered.

[0772] "Detailed information" refers to basic information plus additional information such as points of interest around the facility and how to access it.

[0773] "Prompt" refers to the wording used to request information generation from a generative AI model.

[0774] "Points of interest" refers to tourist attractions and noteworthy locations around the facility.

[0775] "Access method" refers to information about the means and route that a user can take to reach a facility.

[0776] The term "system" refers to a set of mechanisms and means that allow users to efficiently obtain facility information.

[0777] The present invention relates to a system that allows a user to transmit an image of a facility that the user wants to visit and obtains detailed information about the facility based on the image. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[0778] User operations

[0779] Users take images of the facility using a device such as a smartphone or PC, and then send the images to the system using a dedicated application or web interface on the device.

[0780] Terminal handling

[0781] The device receives the image data sent by the user and stores it in its internal memory. This image data is then converted into bytes. The device then sends a request containing the image data to an analytics API, such as the Google Cloud Vision API, which retrieves basic information about the facility (name, address, and services offered) from the API.

[0782] Based on the acquired basic information, the device requests a generative AI model (e.g., OpenAI's ChatGPT) to generate detailed information. This request is designed to include basic information about the facility, as well as nearby points of interest and access methods.

[0783] Server Processing

[0784] The server uses a generative AI model to generate detailed information based on prompts received from the device, including basic information about the facility, directions from the nearest station, nearby points of interest, recommended menu items, etc. The final generated information is sent to the device in a data format such as JSON.

[0785] Displaying results on a terminal

[0786] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. The displayed information includes the facility name, location, products offered, access methods, nearby points of interest, recommended menu items, etc. This allows the user to efficiently obtain facility information and plan their visit.

[0787] Specific examples

[0788] For example, consider a case where a user takes a photo of "Restaurant A" and sends it to their device. The device sends this image to an analytics API, which extracts the name, address, and type of cuisine (e.g., Italian) of "Restaurant A." Using this information, the device then asks a generative AI model to generate more information about the restaurant, including nearby tourist attractions and how to get there.

[0789] Examples of specific prompts are:

[0790] Use the following information to generate facility details:

[0791] Facility name: Restaurant A

[0792] Address: Shinjuku Ward, Tokyo

[0793] Type of cuisine served: Italian

[0794] Please also tell me about nearby tourist spots and how to access them.

[0795] The information returned by the generative AI model includes the address of "Restaurant A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist attractions (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Restaurant A" and easily plan their visit.

[0796] The system of the present invention allows users to efficiently obtain detailed information and plan their visits effectively on one platform.

[0797] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0798] Step 1:

[0799] Users can take a photo of the facility they want to visit using a device such as a smartphone or PC, or save an existing image to the device. Then, they can send this image file to the system using a dedicated application or web interface. The input is the image file of the facility, and the output is the image data sent to the device.

[0800] Step 2:

[0801] The terminal receives image data sent by the user and stores it in its internal memory. It then converts this image data into byte data. Specifically, it reads the image file and converts it into byte data format, preparing the data to be handled as numerical information. The input is the image data received from the user, and the output is byte data.

[0802] Step 3:

[0803] The device creates a request to send the converted byte data to an object recognition API (e.g., Google Cloud Vision API). This request includes image data and is analyzed by the object recognition API. The input is the byte data and request information to the object recognition API, and the output is the basic information of the facility returned by the API.

[0804] Step 4:

[0805] The object recognition API analyzes the received image data and extracts basic information about the facility (name, location, and services offered). This information is then returned to the device. The input is a request to the object recognition API, and the output is information about the facility's name, location, and services offered.

[0806] Step 5:

[0807] The device creates a prompt message requesting the generative AI model to generate detailed information based on the basic information about the facility obtained from the object recognition API. This prepares the message to be sent to the generative AI model. The input is the basic information about the facility, and the output is the prompt message to the generative AI model.

[0808] Step 6:

[0809] The terminal uses the generated prompt sentence to request the generative AI model to generate detailed information. This request includes basic information about the facility, as well as information about nearby points of interest and how to access them. The input is the prompt sentence, and the output is a request to the generative AI model.

[0810] Step 7:

[0811] The generative AI model generates detailed information based on the prompt it receives, including the facility's name, location, services offered, directions from the nearest station, nearby points of interest, recommended menu items, etc. The input is a request to the generative AI model, and the output is the generated detailed information.

[0812] Step 8:

[0813] The server converts the generated detailed information into a data format such as JSON and sends it to the terminal. The input is the generated detailed information, and the output is the formatted detailed information.

[0814] Step 9:

[0815] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility name, location, services offered, access instructions, nearby points of interest, recommended menu items, etc. The input is the detailed information received from the server, and the output is the information displayed on the user interface.

[0816] (Application example 1)

[0817] 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."

[0818] Currently, there is a lack of methods for users to quickly and comprehensively obtain information about stores they want to visit. In particular, while there are methods for obtaining store information based on images, the information is insufficiently detailed and provides insufficient additional related information. As a result, users must sequentially investigate multiple information sources, which is time-consuming and labor-intensive. In addition, display methods using generative AI are limited, making it difficult to obtain information easily.

[0819] 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.

[0820] In this invention, the server includes means for a user to upload an image via a smartphone application and send the image data to the server, means for the terminal to send the image data to a camera search API, means for the camera search API to analyze the image data and extract information about the store's name, address, and products offered, means for requesting the generative artificial intelligence to present detailed store information as well as nearby tourist spots and directions, and means for the generative artificial intelligence to generate the detailed store information and surrounding area information and provide it to the terminal. This allows the user to efficiently obtain detailed information and easily plan their visit.

[0821] "User" refers to a person who uploads an image to obtain store information.

[0822] "Store image" refers to a photo of the store that the user wants to visit, taken or prepared by the user.

[0823] "Terminal" refers to an electronic device used by a user, such as a smartphone or computer, that can upload store images.

[0824] "Image data" refers to an image file of a store uploaded by a user.

[0825] "Analysis" refers to the process of extracting specific store information from image data.

[0826] "Camera Search API" refers to an application program interface for obtaining specific information based on image data.

[0827] "Store information" refers to basic information that users want to know, such as the store's name, address, and products offered.

[0828] "Generative AI" refers to AI technology that generates detailed information based on given information.

[0829] "Detailed information" refers to additional information generated by generative artificial intelligence, such as tourist spots and directions in addition to basic store information.

[0830] "Smartphone application" refers to a dedicated application that is installed on a device and allows users to upload images.

[0831] "Nearby tourist spots" refers to new tourist attractions or points that are located near the store and that users can visit.

[0832] "Directions" refers to the method or route to access a particular store.

[0833] "Means" refers to a method or device used to achieve a particular purpose.

[0834] "Display" refers to the operation of visually showing information on a terminal screen, etc.

[0835] "Extraction" refers to the process by which the camera search API extracts the necessary information from image data.

[0836] The present invention relates to a system that allows users to upload store images and quickly obtain detailed store information. This system is primarily composed of user, terminal, and server components.

[0837] User operations

[0838] Users can take pictures of the stores they want to visit or upload existing images using a smartphone application, which has the function of sending the images to a server.

[0839] Terminal handling

[0840] The device, typically a smartphone, receives the image data sent by the user and sends it to the Camera Search API, which converts the image data into bytes. The Camera Search API then analyzes the image data and extracts information about the store's name, address, and products offered.

[0841] The device requests the API of a generative artificial intelligence (e.g., OpenAI GPT-3) to generate detailed information based on the basic information obtained from the camera search API. This request sets up a prompt to include information about nearby tourist spots and directions to the store, along with basic store information.

[0842] Server Processing

[0843] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic store information, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[0844] Displaying results on a terminal

[0845] The terminal receives the detailed information sent from the server and displays it to the user. The displayed content includes detailed information such as the store name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and plan their visit.

[0846] Example

[0847] For example, consider the case where a user takes a photo of a ramen shop and uploads it to their device. The device sends this image data to a camera search API, which extracts the name of the ramen shop, its address, and the type of ramen it serves (e.g., tonkotsu ramen). Based on this information, the device then asks a generative AI to generate detailed information about the shop, including nearby tourist spots and how to get there.

[0848] Here are some examples of prompts for generative AI models:

[0849] Please generate your details based on the store information below.

[0850] Store name: Ramen shop

[0851] Address: Shinjuku Ward, Tokyo

[0852] Serving item: Tonkotsu ramen

[0853] Generates the following information:

[0854] 1. Directions from the nearest station

[0855] 2. Nearby tourist spots

[0856] 3. Recommended Menu

[0857] The hardware and software used in this system include a camera search API (e.g., Google Vision API), generative artificial intelligence (e.g., OpenAI GPT-3), and a smartphone application (e.g., a mobile app using React Native).

[0858] As a result, the present invention enables users to easily obtain detailed store information and efficiently plan their visit.

[0859] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0860] Step 1:

[0861] The user launches the smartphone application, takes a photo of the store they want to visit, selects it, and uploads it.

[0862] Input: Store image (taken or selected by user)

[0863] Output: Uploaded image data

[0864] Specific operation: Select an image from your smartphone's camera or photo gallery and press the upload button to the dedicated application.

[0865] Step 2:

[0866] The device receives the uploaded image data, converts it into byte format, and then sends the image data to the camera search API.

[0867] Input: Uploaded image data

[0868] Output: Camera search API request

[0869] Specific operation: The device converts the image data into byte format and sends it as an HTTP request to the camera search API.

[0870] Step 3:

[0871] The camera search API analyzes the image data and extracts information about the store's name, address, and products offered.

[0872] Input: Image data

[0873] Output: Store name, address, and product information

[0874] Specific operation: The camera search API uses image recognition technology to analyze the characteristics of the store and extract relevant information.

[0875] Step 4:

[0876] The device receives basic store information obtained from the camera search API and sends a request to the generative AI to generate detailed information. A prompt is set, and information about nearby tourist spots and how to get there is also included.

[0877] Input: Basic store information

[0878] Output: A request to the generative AI

[0879] Specific operation: The device generates a prompt sentence based on the acquired information and sends a request to the generative artificial intelligence API.

[0880] Step 5:

[0881] The generative artificial intelligence generates detailed information based on the input prompt sentence and returns it to the server.

[0882] Input: Prompt text (basic store information, nearby tourist spots, directions)

[0883] Output: Detailed information generated

[0884] Specific operation: Generative AI uses natural language processing technology to generate detailed information and respond in data format such as JSON.

[0885] Step 6:

[0886] The device receives the detailed information returned by the generative artificial intelligence and displays it in a format that can be viewed by the user.

[0887] Input: Generated details

[0888] Output: Displayable store details

[0889] Specific operation: The device displays the received information on the application screen in an appropriate format and provides it to the user.

[0890] Specific examples

[0891] For example, if a user takes a photo of a ramen shop and uploads the image, the process is as follows: The device receives the image and sends it to the camera search API, which extracts basic information about the "ramen shop." Next, the device uses this information to send a prompt to the generative AI, asking it to generate more information. The generative AI generates information such as directions from the nearest station, nearby tourist spots, and recommended menu items, and returns this information to the device. Finally, the device displays the detailed information to the user, allowing them to efficiently obtain store information and plan their visit.

[0892] 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.

[0893] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. The roles of the user, terminal, and server in one embodiment of this system are described in detail below.

[0894] User operations

[0895] First, a user uses a device such as a smartphone or PC to take a photo of the store they want to visit, or upload an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the user sends the store's image file and emotional data to the system via a dedicated application or web interface on the device.

[0896] Terminal handling

[0897] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it into byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion.

[0898] The device first generates a prompt that takes into account the user's emotional data, and then sends image data to the camera search API based on the prompt to obtain information about the store. The basic information obtained from the image data includes the user's name, address, and information about the products offered.

[0899] Server Processing

[0900] The server analyzes the user's emotional data using an emotion engine. Emotional data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This allows for the generation of detailed information based on the user's emotions.

[0901] After receiving the information obtained from the camera search API, the device sends a request for more information to a generative AI (e.g., ChatGPT). The request includes basic store information, as well as the user's emotional data and a request to generate information about nearby tourist spots and directions.

[0902] Generate detailed information

[0903] The generative AI generates detailed information based on the prompts. This information includes the store's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[0904] Displaying results on a terminal

[0905] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed store information and plan their visit.

[0906] Specific examples

[0907] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited.

[0908] Based on this, a request for detailed information is sent to the generative AI, including nearby tourist spots and how to access them, as well as events and activities that will satisfy the user's sense of excitement.The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho), and events that will satisfy the user's sense of excitement (e.g., nearby live music venues and bowling alleys).

[0909] As described above, the present invention is a useful system that enables users to efficiently obtain store information and plan their visit, and makes it possible to provide personalized information that takes into account the user's emotions.

[0910] The processing flow will be explained below.

[0911] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. As an embodiment of this system, the roles of the user, terminal, and server, as well as the specific processing flow, are described in detail below.

[0912] User operations

[0913] Step 1:

[0914] The user takes a photo of the store they want to visit or selects an existing image and uploads it to the terminal. The user then sends the store image to the system via a dedicated application on the terminal or a web interface.

[0915] Step 2:

[0916] The user is analyzed in real time by the emotion engine, and emotion data is collected. This emotion data is obtained from the user's facial expressions and voice and reflects the user's state.

[0917] Terminal handling

[0918] Step 3:

[0919] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request, along with any emotion data received from the emotion engine.

[0920] Step 4:

[0921] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[0922] Server Processing

[0923] Step 5:

[0924] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[0925] Step 6:

[0926] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[0927] Generative AI processing

[0928] Step 7:

[0929] The device generates prompts based on store information (store name, address, types of products offered) and emotion data. The generated prompts are sent to a generative AI (e.g., ChatGPT).

[0930] Step 8:

[0931] The device sends a request containing a prompt to the generative AI API. This request includes basic store information as well as a request to generate information about nearby tourist spots and how to access them based on the user's emotions.

[0932] Step 9:

[0933] The server (generative artificial intelligence) analyzes the prompt and generates detailed information, including the store's name, address, directions from the nearest station, nearby tourist spots, and recommended menu items. It also generates information appropriate to the user's state of mind (e.g., a cafe with a relaxing atmosphere, a lively event) based on the user's emotional data.

[0934] Step 10:

[0935] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[0936] Displaying results on a terminal

[0937] Step 11:

[0938] The device then displays the received detailed information to the user in an easy-to-understand format, including store information, access instructions, nearby attractions, and more. It also displays personalized information based on emotion data.

[0939] Specific examples

[0940] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to the terminal.

[0941] Step 1:

[0942] A user uploads an image of "Ramen Shop A" to their device.

[0943] Step 2:

[0944] The emotion engine analyzes the user's emotions in real time and collects emotional data. It determines that the user is excited.

[0945] Step 3:

[0946] The device receives the image file, converts it into byte data, and sends it to the camera search API.

[0947] Step 4:

[0948] The camera search API analyzes the image and extracts information about "Ramen Shop A."

[0949] Step 5:

[0950] The server returns store information in JSON format to the terminal.

[0951] Step 6:

[0952] The device generates prompts based on store information and emotional data and sends them to the generative artificial intelligence.

[0953] Step 7:

[0954] Generative AI generates detailed information and sends it back to the device.

[0955] Step 8:

[0956] The device receives the detailed information and displays it to the user, including the address of "Ramen Shop A," directions from the nearest station, tourist spots such as Shinjuku Gyoen and Kabukicho, and nearby live music venues and activities that are suitable for the excited user.

[0957] As described above, it has been shown that the present invention functions as a system that enables a user to efficiently obtain store information and make a visiting plan that takes into account the user's emotions.

[0958] Example 2

[0959] 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."

[0960] Conventional store information acquisition systems have difficulty effectively providing the detailed store information desired by users, and in particular have a lack of personalized information provision that responds to the user's emotions. In addition, there has been a lack of appropriate means for users to easily obtain information that interests them or the detailed information needed to plan their visit.

[0961] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing image data and acquiring store information, a means for analyzing emotion data and identifying the user's state, and a means for requesting detailed information from the generative artificial intelligence based on the acquired store information and emotion data. This makes it possible to provide detailed store information and personalized surrounding information according to the user's emotions.

[0962] "User" refers to a person who uses a service or application.

[0963] "Terminal" refers to electronic devices such as computers, smartphones, and tablets used by users.

[0964] "Image data" refers to photographs and image files taken or uploaded by a user using a terminal.

[0965] "Emotion data" refers to data related to emotions obtained by analyzing the user's facial expressions and voice.

[0966] "Server" refers to a computer system on a network that processes, stores, and manages data.

[0967] "Camera Search API" refers to an application programming interface for analyzing image data and obtaining information about objects.

[0968] "Generative AI" refers to an AI system that has the ability to generate responses in natural language based on specific prompts.

[0969] "Detailed information" refers to basic information about the store (name, address, products offered) and additional information customized according to the user's emotions.

[0970] A "prompt" refers to an input sentence that requests the generative artificial intelligence to generate detailed information.

[0971] "Store Information" refers to information about a specific store, including its name, address, and products offered, obtained through the Camera Search API.

[0972] "Nearby information" refers to information about tourist spots around the store and how to get there.

[0973] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. Specific embodiments for implementing this system will now be described in detail.

[0974] User operations

[0975] Users use devices such as smartphones or PCs to take pictures of the store they want to visit or upload existing images to their devices. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotion data. The user then sends the store's image file and emotion data to the system via a dedicated application or web interface.

[0976] Terminal handling

[0977] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG format) and converts it into byte data. The emotion data is then quantified or categorized to represent the user's emotion. Based on this data, the device prepares the data for the API request.

[0978] Server Processing

[0979] The server sends the image data sent from the device to the camera search API and obtains basic information about the store (e.g., store name, address, and products offered). The server also analyzes the emotional data using an emotion engine to identify the user's state (e.g., excited, relaxed). Based on this, the server sends a request for more information to a generative artificial intelligence (e.g., ChatGPT).

[0980] Generate detailed information

[0981] The generative AI generates detailed information based on prompts received from the server, including basic store information (name, address, directions from the nearest station), nearby tourist spots, and recommended menu items. It also generates specific information based on the user's emotional data (e.g., relaxing cafes and lively events).

[0982] Displaying results on a terminal

[0983] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. This information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. Personalized information based on the user's emotions is also provided, allowing the user to efficiently plan their visit.

[0984] Specific examples

[0985] For example, if a user uploads an image of "Ramen Shop A," the device sends this image to the camera search API, which retrieves the name, address, and type of product offered (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited. Based on this, it generates a prompt to the generative AI and sends a request for more information.

[0986] Prompt Sentence Examples

[0987] "Please provide basic store information: Generate detailed information based on the image of "Ramen Shop A" and the user's emotion data. Specifically, please include the store's name, address, information about the products offered (e.g., tonkotsu ramen), directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen, Kabukicho), and events that users can enjoy in an excited state (e.g., nearby live music venues and bowling alleys)."

[0988] As described above, the present invention is a useful system for enabling users to efficiently obtain store information and plan their visit by providing personalized information that takes emotions into consideration.

[0989] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0990] Step 1:

[0991] Users use their smartphones or PCs to take pictures of the stores they want to visit or upload existing images to the device. Users then collect emotion data along with the image data via a dedicated application or web interface. The input is the taken or uploaded store image and the user's emotion data, and the output is the image and emotion data stored on the device.

[0992] Step 2:

[0993] The device converts the image data acquired from the user into an appropriate format (e.g., JPEG format). The emotion data is then quantified or categorized using an emotion analysis engine. In this process, the input is the image data and emotion data from the user, and the output is a JPEG image and quantified or categorized emotion data.

[0994] Step 3:

[0995] The device formats the preprocessed image data and emotion data for an API request and sends it to the server. This API request contains the image data and quantified emotion data. The input is a JPEG image and numeric data, and the output is an API request sent to the server.

[0996] Step 4:

[0997] The server sends the received image data to the camera search API and obtains basic information about the store. The data processing performed here involves analyzing the image data, and the output is basic store information (e.g., store name, address, and products offered). At the same time, the server uses an emotion engine to analyze the emotion data and identify the user's current state. The inputs to this process are the received image data and emotion data, and the output is the obtained store information and the identified user's emotional state.

[0998] Step 5:

[0999] The server sends a request to generate detailed information to the generative AI based on basic store information and user emotion data. The input is the basic store information and user emotion data, and a prompt sentence including this data is generated and sent to the generative AI. The output is the detailed information request sent to the generative AI.

[1000] Step 6:

[1001] Generative AI generates detailed information based on the received prompt. This information includes the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, and more, as well as specific information based on the user's emotional data (e.g., a relaxing cafe or a lively event). The input to this process is the prompt, and the output is the generated detailed information.

[1002] Step 7:

[1003] The server transmits the detailed information obtained from the generative AI to the terminal. The input is the detailed information received from the generative AI, and the output is the detailed information transmitted to the terminal.

[1004] Step 8:

[1005] The terminal analyzes the detailed information received from the server and displays it in a user-friendly format. The displayed information includes the store name, address, products offered, access instructions, and nearby tourist attractions. The user can use this information to efficiently plan their visit. The input is the detailed information received from the server, and the output is the displayed detailed information and information used to plan the user's visit.

[1006] (Application example 2)

[1007] 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."

[1008] Conventional store information systems allowed users to upload images and obtain basic information, but they were unable to provide personalized information based on the user's current emotional state. As a result, it was difficult for users to obtain optimal information based on their interests and mood, limiting the user experience. Furthermore, they lacked a mechanism for providing comprehensive information on nearby tourist attractions and access methods.

[1009] 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 collecting user emotion data, means for analyzing the emotion data and generating detailed information based on the emotion, and means for requesting detailed information from the generative artificial intelligence. This makes it possible to provide personalized facility information according to the user's current emotional state, as well as information on surrounding tourist attractions and access methods, in an integrated manner.

[1010] "User" refers to a user who wishes to obtain facility information.

[1011] "Image of facility" refers to image data that a user takes or uploads, showing a facility that the user wants to visit.

[1012] "Device" refers to the electronic device, such as a computer, smartphone, or tablet, that a user uses to upload images and view information.

[1013] "Image Data" refers to digital image files containing images of a facility uploaded by a User.

[1014] "Establishment Information" means the name, address, and details of the establishment regarding the products and services offered.

[1015] "Generative AI" refers to an AI system that generates detailed information based on user requests.

[1016] "Detailed information" refers to data that includes basic information about the facility, as well as information about nearby tourist attractions, access methods, and personalized information based on the user's emotions.

[1017] "Emotion data" refers to information indicating the emotional state of a user that is obtained by analyzing facial expressions and voice data.

[1018] "Camera Search API" refers to an application programming interface for analyzing image data and extracting basic information about a facility.

[1019] "Tourist spots" refer to the sights and attractions that tourists should visit in the vicinity of the facility.

[1020] "Access method" refers to the means of transportation and route that a user takes to reach a facility or a nearby tourist spot.

[1021] The present invention is a system that allows users to upload images of facilities and obtain detailed information based on those images. This system can provide more personalized information by combining an emotion engine that recognizes the user's emotional state. Specific embodiments of the system are described in detail below.

[1022] User operations

[1023] First, a user takes a photo of the facility they want to visit using a device such as a smartphone or PC, or uploads an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the image file of the facility and the emotional data are sent to the system via a dedicated application or web interface on the device.

[1024] Terminal handling

[1025] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it to byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion. The device first generates a prompt that takes the user's emotion data into consideration, and then sends image data to the camera search API based on the prompt to obtain information about the facility. Basic information obtained from the image data includes the user's name, address, and information about the products offered.

[1026] Server Processing

[1027] The server uses an emotion engine to analyze the user's emotion data. Emotion data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This makes it possible to generate detailed information based on the user's emotion. After receiving the information obtained from the camera search API, the device further sends a request for detailed information to a generative artificial intelligence (e.g., ChatGPT). The request includes basic information about the facility, as well as the user's emotion data and a request to generate information about nearby tourist spots and how to get there.

[1028] Generate detailed information

[1029] The generative AI generates detailed information based on the prompts. This information includes the facility's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[1030] Displaying results on a terminal

[1031] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility's name, address, products offered, access methods, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed facility information and plan their visit.

[1032] Specific examples

[1033] For example, consider the case where a user takes a photo of Kiyomizu-dera Temple in Kyoto and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and services offered by "Kiyomizu-dera Temple." At the same time, the emotion engine analyzes the user's emotions and determines that the user is in a relaxed state. Based on this, a request is sent to the generative AI for more information, including nearby tourist attractions and how to access them, as well as recommended places to satisfy the user's sense of relaxation. The information returned by the generative AI includes the address of "Kiyomizu-dera Temple," directions to get there from the nearest station, nearby tourist attractions (e.g., Gion, Yasaka Shrine), and places to satisfy the user's sense of relaxation (e.g., nearby quiet cafes and gardens).

[1034] Prompt Sentence Examples

[1035] "Please tell me about sightseeing information for Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state and is looking for a comfortable cafe or a quiet walking route."

[1036] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1037] Step 1:

[1038] The user takes or uploads an image of the facility. Using a device such as a smartphone or PC, the user can take an image of the facility they want to visit or select an existing image and upload it. At the same time, the device analyzes the user's facial expressions and voice in real time to collect emotional data. The input is the image data of the facility and the user's emotional data, and the output is that this data is saved on the device.

[1039] Step 2:

[1040] The device sends image data and emotion data to the server. The device converts the image data sent by the user into an appropriate format (e.g., JPEG) and prepares the data for the API request as byte data. The emotion data is also used to quantify or categorize the user's emotion. The input is the image data and emotion data collected in step 1, and the output is the data for the API request.

[1041] Step 3:

[1042] The server uses the camera search API to obtain facility information. The server sends the received image data to the camera search API, which analyzes it and obtains basic information about the facility (e.g., name, address, services provided). The input is the image data sent from the device, and the output is the basic information about the facility.

[1043] Step 4:

[1044] The server analyzes the user's emotional data using an emotion engine. The server analyzes the received emotional data based on the emotion engine and identifies the user's current emotional state (e.g., relaxed, excited). This emotional data is used to generate detailed information in the future. The input is the emotional data sent from the device, and the output is the analyzed user's emotional state.

[1045] Step 5:

[1046] The server creates a prompt for the generative AI and requests detailed information. The server generates a prompt based on the acquired basic information about the facility and the user's emotional data obtained as a result of the analysis, and asks the generative AI to generate detailed information. For example, a prompt might be sent saying, "Please tell me about tourist information about Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state. I'm looking for a comfortable cafe or a quiet walking course." The input is the basic information about the facility and the user's emotional state, and the output is a prompt sent to the generative AI.

[1047] Step 6:

[1048] The generative AI generates detailed information and sends it back to the server. Based on the prompt, the generative AI generates detailed information such as basic information about the facility, nearby tourist attractions, how to get there, and recommended places based on the user's emotions. The input is the prompt, and the output is the generated detailed information.

[1049] Step 7:

[1050] The server sends detailed information to the terminal. The detailed information received from the generative AI is sent to the terminal in a data format such as JSON. The input is the detailed information from the generative AI, and the output is the data sent to the terminal.

[1051] Step 8:

[1052] The terminal displays detailed information to the user. The terminal analyzes the received detailed information and displays it in a format that is easy for the user to view. The displayed content includes the facility name, address, services provided, access methods, nearby tourist attractions, and recommended places based on the user's emotions. The input is the detailed information sent from the server, and the output is the information displayed on the user's terminal screen.

[1053] 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.

[1054] 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.

[1055] 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.

[1056] [Fourth embodiment]

[1057] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1058] 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.

[1059] 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).

[1060] 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.

[1061] 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.

[1062] 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).

[1063] 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.

[1064] 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.

[1065] 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.

[1066] 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.

[1067] 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.

[1068] 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.

[1069] 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."

[1070] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[1071] User operations

[1072] Users first use a device such as a smartphone or PC to take a photo of the store they want to visit or upload an existing image to the device, and then send the store image file to the system via a dedicated application or web interface on the device.

[1073] Terminal handling

[1074] The device receives the image file sent by the user and reads it as image data. At this time, the image is converted into byte data. The device then sends a request including the image data to the Camera Search API. The Camera Search API extracts information about the corresponding store from the image data (e.g., store name, address, and types of products offered).

[1075] After receiving the information from the camera search API, the device then sends a request for more information to the API of a generative artificial intelligence (e.g., ChatGPT), which includes basic information about the store, as well as prompts to generate information about nearby attractions and directions.

[1076] Server Processing

[1077] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic information about the store the user wants to visit, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[1078] Displaying results on a terminal

[1079] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and use it as a reference when planning a visit.

[1080] Specific examples

[1081] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." Next, based on this information, the device asks a generative AI to generate detailed information, including nearby tourist spots and how to get there.

[1082] The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Ramen Shop A," making it easier to visit.

[1083] From the above, it can be seen that the present invention is a useful system that enables a user to efficiently obtain store information and plan a visit.

[1084] The processing flow will be explained below.

[1085] Step 1:

[1086] Users upload images of the store they want to visit to the terminal. Specifically, they use their smartphone or PC to provide the system with photos they have taken or saved image files via a dedicated application or web interface.

[1087] Step 2:

[1088] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request.

[1089] Step 3:

[1090] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[1091] Step 4:

[1092] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[1093] Step 5:

[1094] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[1095] Step 6:

[1096] Using the store information acquired by the device (store name, address, types of products offered), the device prepares a request for more information from the API of a generative artificial intelligence (e.g., ChatGPT). The prompt includes basic store information as well as a request to generate information about nearby tourist attractions and how to get there.

[1097] Step 7:

[1098] The device sends a request to the generative AI API containing the prepared prompt, and the generative AI generates detailed information based on this request.

[1099] Step 8:

[1100] The server (generative artificial intelligence) analyzes the received prompt and generates the requested detailed information, including the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, etc.

[1101] Step 9:

[1102] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[1103] Step 10:

[1104] The device displays the received detailed information to the user. The display content is formatted in an easy-to-understand manner and includes store information, access methods, nearby spots, etc. This allows the user to efficiently obtain store details and plan their visit.

[1105] Example 1

[1106] 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."

[1107] In the past, users had to use multiple websites and applications to efficiently obtain facility information, which made information gathering cumbersome and time-consuming. Furthermore, the accuracy and detail of the information obtained was insufficient, often resulting in a lack of specific information when planning a visit. To solve this problem, there was a need for a single system that could efficiently and accurately obtain facility information, thereby improving user convenience.

[1108] 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.

[1109] In this invention, the server includes: means for a user to send an image of a facility; means for a terminal to read image data and convert the image data into byte data; means for the terminal to send the image data to an analysis API and acquire basic information about the facility; means for the terminal to request detailed information from a generative AI model based on the facility information acquired; means for the generative AI model to generate the detailed information and provide it to the terminal; and means for the terminal to display the detailed information to the user. This allows users to quickly obtain detailed facility information through a single system, enabling them to effectively plan their visit.

[1110] "User" refers to an individual or corporation that uses the system to obtain facility information.

[1111] "Facility" refers to the physical location visited or where the service is provided.

[1112] "Image data" refers to image files of a facility that have been photographed or uploaded.

[1113] "Byte data" refers to a format converted to handle image data as numerical information.

[1114] "Terminal" refers to a device such as a smartphone or PC operated by a user.

[1115] "Analysis API" refers to a program interface for analyzing image data and obtaining basic information about a facility.

[1116] A "generative AI model" refers to a program that uses artificial intelligence to generate detailed information from data.

[1117] "Basic information" refers to information about the facility's name, location, and services offered.

[1118] "Detailed information" refers to basic information plus additional information such as points of interest around the facility and how to access it.

[1119] "Prompt" refers to the wording used to request information generation from a generative AI model.

[1120] "Points of interest" refers to tourist attractions and noteworthy locations around the facility.

[1121] "Access method" refers to information about the means and route that a user can take to reach a facility.

[1122] The term "system" refers to a set of mechanisms and means that allow users to efficiently obtain facility information.

[1123] The present invention relates to a system that allows a user to transmit an image of a facility that the user wants to visit and obtains detailed information about the facility based on the image. In an embodiment of this system, the roles of the user, the terminal, and the server are described in detail below.

[1124] User operations

[1125] Users take images of the facility using a device such as a smartphone or PC, and then send the images to the system using a dedicated application or web interface on the device.

[1126] Terminal handling

[1127] The device receives the image data sent by the user and stores it in its internal memory. This image data is then converted into bytes. The device then sends a request containing the image data to an analytics API, such as the Google Cloud Vision API, which retrieves basic information about the facility (name, address, and services offered) from the API.

[1128] Based on the acquired basic information, the device requests a generative AI model (e.g., OpenAI's ChatGPT) to generate detailed information. This request is designed to include basic information about the facility, as well as nearby points of interest and access methods.

[1129] Server Processing

[1130] The server uses a generative AI model to generate detailed information based on prompts received from the device, including basic information about the facility, directions from the nearest station, nearby points of interest, recommended menu items, etc. The final generated information is sent to the device in a data format such as JSON.

[1131] Displaying results on a terminal

[1132] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. The displayed information includes the facility name, location, products offered, access methods, nearby points of interest, recommended menu items, etc. This allows the user to efficiently obtain facility information and plan their visit.

[1133] Specific examples

[1134] For example, consider a case where a user takes a photo of "Restaurant A" and sends it to their device. The device sends this image to an analytics API, which extracts the name, address, and type of cuisine (e.g., Italian) of "Restaurant A." Using this information, the device then asks a generative AI model to generate more information about the restaurant, including nearby tourist attractions and how to get there.

[1135] Examples of specific prompts are:

[1136] Use the following information to generate facility details:

[1137] Facility name: Restaurant A

[1138] Address: Shinjuku Ward, Tokyo

[1139] Type of cuisine served: Italian

[1140] Please also tell me about nearby tourist spots and how to access them.

[1141] The information returned by the generative AI model includes the address of "Restaurant A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), and nearby tourist attractions (e.g., Shinjuku Gyoen National Garden, Kabukicho). This allows users to quickly and comprehensively obtain information about "Restaurant A" and easily plan their visit.

[1142] The system of the present invention allows users to efficiently obtain detailed information and plan their visits effectively on one platform.

[1143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1144] Step 1:

[1145] Users can take a photo of the facility they want to visit using a device such as a smartphone or PC, or save an existing image to the device. Then, they can send this image file to the system using a dedicated application or web interface. The input is the image file of the facility, and the output is the image data sent to the device.

[1146] Step 2:

[1147] The terminal receives image data sent by the user and stores it in its internal memory. It then converts this image data into byte data. Specifically, it reads the image file and converts it into byte data format, preparing the data to be handled as numerical information. The input is the image data received from the user, and the output is byte data.

[1148] Step 3:

[1149] The device creates a request to send the converted byte data to an object recognition API (e.g., Google Cloud Vision API). This request includes image data and is analyzed by the object recognition API. The input is the byte data and request information to the object recognition API, and the output is the basic information of the facility returned by the API.

[1150] Step 4:

[1151] The object recognition API analyzes the received image data and extracts basic information about the facility (name, location, and services offered). This information is then returned to the device. The input is a request to the object recognition API, and the output is information about the facility's name, location, and services offered.

[1152] Step 5:

[1153] The device creates a prompt message requesting the generative AI model to generate detailed information based on the basic information about the facility obtained from the object recognition API. This prepares the message to be sent to the generative AI model. The input is the basic information about the facility, and the output is the prompt message to the generative AI model.

[1154] Step 6:

[1155] The terminal uses the generated prompt sentence to request the generative AI model to generate detailed information. This request includes basic information about the facility, as well as information about nearby points of interest and how to access them. The input is the prompt sentence, and the output is a request to the generative AI model.

[1156] Step 7:

[1157] The generative AI model generates detailed information based on the prompt it receives, including the facility's name, location, services offered, directions from the nearest station, nearby points of interest, recommended menu items, etc. The input is a request to the generative AI model, and the output is the generated detailed information.

[1158] Step 8:

[1159] The server converts the generated detailed information into a data format such as JSON and sends it to the terminal. The input is the generated detailed information, and the output is the formatted detailed information.

[1160] Step 9:

[1161] The terminal receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility name, location, services offered, access instructions, nearby points of interest, recommended menu items, etc. The input is the detailed information received from the server, and the output is the information displayed on the user interface.

[1162] (Application example 1)

[1163] 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."

[1164] Currently, there is a lack of methods for users to quickly and comprehensively obtain information about stores they want to visit. In particular, while there are methods for obtaining store information based on images, the information is insufficiently detailed and provides insufficient additional related information. As a result, users must sequentially investigate multiple information sources, which is time-consuming and labor-intensive. In addition, display methods using generative AI are limited, making it difficult to obtain information easily.

[1165] 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.

[1166] In this invention, the server includes means for a user to upload an image via a smartphone application and send the image data to the server, means for the terminal to send the image data to a camera search API, means for the camera search API to analyze the image data and extract information about the store's name, address, and products offered, means for requesting the generative artificial intelligence to present detailed store information as well as nearby tourist spots and directions, and means for the generative artificial intelligence to generate the detailed store information and surrounding area information and provide it to the terminal. This allows the user to efficiently obtain detailed information and easily plan their visit.

[1167] "User" refers to a person who uploads an image to obtain store information.

[1168] "Store image" refers to a photo of the store that the user wants to visit, taken or prepared by the user.

[1169] "Terminal" refers to an electronic device used by a user, such as a smartphone or computer, that can upload store images.

[1170] "Image data" refers to an image file of a store uploaded by a user.

[1171] "Analysis" refers to the process of extracting specific store information from image data.

[1172] "Camera Search API" refers to an application program interface for obtaining specific information based on image data.

[1173] "Store information" refers to basic information that users want to know, such as the store's name, address, and products offered.

[1174] "Generative AI" refers to AI technology that generates detailed information based on given information.

[1175] "Detailed information" refers to additional information generated by generative artificial intelligence, such as tourist spots and directions in addition to basic store information.

[1176] "Smartphone application" refers to a dedicated application that is installed on a device and allows users to upload images.

[1177] "Nearby tourist spots" refers to new tourist attractions or points that are located near the store and that users can visit.

[1178] "Directions" refers to the method or route to access a particular store.

[1179] "Means" refers to a method or device used to achieve a particular purpose.

[1180] "Display" refers to the operation of visually showing information on a terminal screen, etc.

[1181] "Extraction" refers to the process by which the camera search API extracts the necessary information from image data.

[1182] The present invention relates to a system that allows users to upload store images and quickly obtain detailed store information. This system is primarily composed of user, terminal, and server components.

[1183] User operations

[1184] Users can take pictures of the stores they want to visit or upload existing images using a smartphone application, which has the function of sending the images to a server.

[1185] Terminal handling

[1186] The device, typically a smartphone, receives the image data sent by the user and sends it to the Camera Search API, which converts the image data into bytes. The Camera Search API then analyzes the image data and extracts information about the store's name, address, and products offered.

[1187] The device requests the API of a generative artificial intelligence (e.g., OpenAI GPT-3) to generate detailed information based on the basic information obtained from the camera search API. This request sets up a prompt to include information about nearby tourist spots and directions to the store, along with basic store information.

[1188] Server Processing

[1189] The server uses generative artificial intelligence to generate detailed information based on the prompts received from the device. This information includes basic store information, as well as directions from the nearest station, nearby tourist spots, recommended menu items, etc. The generated information is returned to the device in a data format such as JSON.

[1190] Displaying results on a terminal

[1191] The terminal receives the detailed information sent from the server and displays it to the user. The displayed content includes detailed information such as the store name, address, products offered, access instructions, and nearby tourist attractions. This allows the user to efficiently obtain store information and plan their visit.

[1192] Example

[1193] For example, consider the case where a user takes a photo of a ramen shop and uploads it to their device. The device sends this image data to a camera search API, which extracts the name of the ramen shop, its address, and the type of ramen it serves (e.g., tonkotsu ramen). Based on this information, the device then asks a generative AI to generate detailed information about the shop, including nearby tourist spots and how to get there.

[1194] Here are some examples of prompts for generative AI models:

[1195] Please generate your details based on the store information below.

[1196] Store name: Ramen shop

[1197] Address: Shinjuku Ward, Tokyo

[1198] Serving item: Tonkotsu ramen

[1199] Generates the following information:

[1200] 1. Directions from the nearest station

[1201] 2. Nearby tourist spots

[1202] 3. Recommended Menu

[1203] The hardware and software used in this system include a camera search API (e.g., Google Vision API), generative artificial intelligence (e.g., OpenAI GPT-3), and a smartphone application (e.g., a mobile app using React Native).

[1204] As a result, the present invention enables users to easily obtain detailed store information and efficiently plan their visit.

[1205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1206] Step 1:

[1207] The user launches the smartphone application, takes a photo of the store they want to visit, selects it, and uploads it.

[1208] Input: Store image (taken or selected by user)

[1209] Output: Uploaded image data

[1210] Specific operation: Select an image from your smartphone's camera or photo gallery and press the upload button to the dedicated application.

[1211] Step 2:

[1212] The device receives the uploaded image data, converts it into byte format, and then sends the image data to the camera search API.

[1213] Input: Uploaded image data

[1214] Output: Camera search API request

[1215] Specific operation: The device converts the image data into byte format and sends it as an HTTP request to the camera search API.

[1216] Step 3:

[1217] The camera search API analyzes the image data and extracts information about the store's name, address, and products offered.

[1218] Input: Image data

[1219] Output: Store name, address, and product information

[1220] Specific operation: The camera search API uses image recognition technology to analyze the characteristics of the store and extract relevant information.

[1221] Step 4:

[1222] The device receives basic store information obtained from the camera search API and sends a request to the generative AI to generate detailed information. A prompt is set, and information about nearby tourist spots and how to get there is also included.

[1223] Input: Basic store information

[1224] Output: A request to the generative AI

[1225] Specific operation: The device generates a prompt sentence based on the acquired information and sends a request to the generative artificial intelligence API.

[1226] Step 5:

[1227] The generative artificial intelligence generates detailed information based on the input prompt sentence and returns it to the server.

[1228] Input: Prompt text (basic store information, nearby tourist spots, directions)

[1229] Output: Detailed information generated

[1230] Specific operation: Generative AI uses natural language processing technology to generate detailed information and respond in data format such as JSON.

[1231] Step 6:

[1232] The device receives the detailed information returned by the generative artificial intelligence and displays it in a format that can be viewed by the user.

[1233] Input: Generated details

[1234] Output: Displayable store details

[1235] Specific operation: The device displays the received information on the application screen in an appropriate format and provides it to the user.

[1236] Specific examples

[1237] For example, if a user takes a photo of a ramen shop and uploads the image, the process is as follows: The device receives the image and sends it to the camera search API, which extracts basic information about the "ramen shop." Next, the device uses this information to send a prompt to the generative AI, asking it to generate more information. The generative AI generates information such as directions from the nearest station, nearby tourist spots, and recommended menu items, and returns this information to the device. Finally, the device displays the detailed information to the user, allowing them to efficiently obtain store information and plan their visit.

[1238] 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.

[1239] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. The roles of the user, terminal, and server in one embodiment of this system are described in detail below.

[1240] User operations

[1241] First, a user uses a device such as a smartphone or PC to take a photo of the store they want to visit, or upload an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the user sends the store's image file and emotional data to the system via a dedicated application or web interface on the device.

[1242] Terminal handling

[1243] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it into byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion.

[1244] The device first generates a prompt that takes into account the user's emotional data, and then sends image data to the camera search API based on the prompt to obtain information about the store. The basic information obtained from the image data includes the user's name, address, and information about the products offered.

[1245] Server Processing

[1246] The server analyzes the user's emotional data using an emotion engine. Emotional data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This allows for the generation of detailed information based on the user's emotions.

[1247] After receiving the information obtained from the camera search API, the device sends a request for more information to a generative AI (e.g., ChatGPT). The request includes basic store information, as well as the user's emotional data and a request to generate information about nearby tourist spots and directions.

[1248] Generate detailed information

[1249] The generative AI generates detailed information based on the prompts. This information includes the store's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[1250] Displaying results on a terminal

[1251] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed store information and plan their visit.

[1252] Specific examples

[1253] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and type of ramen they serve (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited.

[1254] Based on this, a request for detailed information is sent to the generative AI, including nearby tourist spots and how to access them, as well as events and activities that will satisfy the user's sense of excitement.The information returned by the generative AI includes the address of "Ramen Shop A," directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen National Garden, Kabukicho), and events that will satisfy the user's sense of excitement (e.g., nearby live music venues and bowling alleys).

[1255] As described above, the present invention is a useful system that enables users to efficiently obtain store information and plan their visit, and makes it possible to provide personalized information that takes into account the user's emotions.

[1256] The processing flow will be explained below.

[1257] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on those images, and by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. As an embodiment of this system, the roles of the user, terminal, and server, as well as the specific processing flow, are described in detail below.

[1258] User operations

[1259] Step 1:

[1260] The user takes a photo of the store they want to visit or selects an existing image and uploads it to the terminal. The user then sends the store image to the system via a dedicated application on the terminal or a web interface.

[1261] Step 2:

[1262] The user is analyzed in real time by the emotion engine, and emotion data is collected. This emotion data is obtained from the user's facial expressions and voice and reflects the user's state.

[1263] Terminal handling

[1264] Step 3:

[1265] The device receives the uploaded image file, reads it in the appropriate format (e.g., JPEG), converts the image data to bytes, and prepares the data for the API request, along with any emotion data received from the emotion engine.

[1266] Step 4:

[1267] The device sends image data to the camera search API via a POST request, which includes an image of the store.

[1268] Server Processing

[1269] Step 5:

[1270] The server (camera search API) analyzes the image data and extracts information about the relevant store. Specifically, the server uses image recognition technology to identify the store's name, address, and the types of products offered.

[1271] Step 6:

[1272] The server returns the extracted store information in JSON format to the terminal. The terminal receives this JSON response, parses it, and obtains basic store information.

[1273] Generative AI processing

[1274] Step 7:

[1275] The device generates prompts based on store information (store name, address, types of products offered) and emotion data. The generated prompts are sent to a generative AI (e.g., ChatGPT).

[1276] Step 8:

[1277] The device sends a request containing a prompt to the generative AI API. This request includes basic store information as well as a request to generate information about nearby tourist spots and how to access them based on the user's emotions.

[1278] Step 9:

[1279] The server (generative artificial intelligence) analyzes the prompt and generates detailed information, including the store's name, address, directions from the nearest station, nearby tourist spots, and recommended menu items. It also generates information appropriate to the user's state of mind (e.g., a cafe with a relaxing atmosphere, a lively event) based on the user's emotional data.

[1280] Step 10:

[1281] The server (generative artificial intelligence) returns the generated detailed information to the terminal, which receives this detailed information.

[1282] Displaying results on a terminal

[1283] Step 11:

[1284] The device then displays the received detailed information to the user in an easy-to-understand format, including store information, access instructions, nearby attractions, and more. It also displays personalized information based on emotion data.

[1285] Specific examples

[1286] For example, consider the case where a user takes a photo of "Ramen Shop A" and uploads it to the terminal.

[1287] Step 1:

[1288] A user uploads an image of "Ramen Shop A" to their device.

[1289] Step 2:

[1290] The emotion engine analyzes the user's emotions in real time and collects emotional data. It determines that the user is excited.

[1291] Step 3:

[1292] The device receives the image file, converts it into byte data, and sends it to the camera search API.

[1293] Step 4:

[1294] The camera search API analyzes the image and extracts information about "Ramen Shop A."

[1295] Step 5:

[1296] The server returns store information in JSON format to the terminal.

[1297] Step 6:

[1298] The device generates prompts based on store information and emotional data and sends them to the generative artificial intelligence.

[1299] Step 7:

[1300] Generative AI generates detailed information and sends it back to the device.

[1301] Step 8:

[1302] The device receives the detailed information and displays it to the user, including the address of "Ramen Shop A," directions from the nearest station, tourist spots such as Shinjuku Gyoen and Kabukicho, and nearby live music venues and activities that are suitable for the excited user.

[1303] As described above, it has been shown that the present invention functions as a system that enables a user to efficiently obtain store information and make a visiting plan that takes into account the user's emotions.

[1304] Example 2

[1305] 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."

[1306] Conventional store information acquisition systems have difficulty effectively providing the detailed store information desired by users, and in particular have a lack of personalized information provision that responds to the user's emotions. In addition, there has been a lack of appropriate means for users to easily obtain information that interests them or the detailed information needed to plan their visit.

[1307] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for analyzing image data and acquiring store information, a means for analyzing emotion data and identifying the user's state, and a means for requesting detailed information from the generative artificial intelligence based on the acquired store information and emotion data. This makes it possible to provide detailed store information and personalized surrounding information according to the user's emotions.

[1308] "User" refers to a person who uses a service or application.

[1309] "Terminal" refers to electronic devices such as computers, smartphones, and tablets used by users.

[1310] "Image data" refers to photographs and image files taken or uploaded by a user using a terminal.

[1311] "Emotion data" refers to data related to emotions obtained by analyzing the user's facial expressions and voice.

[1312] "Server" refers to a computer system on a network that processes, stores, and manages data.

[1313] "Camera Search API" refers to an application programming interface for analyzing image data and obtaining information about objects.

[1314] "Generative AI" refers to an AI system that has the ability to generate responses in natural language based on specific prompts.

[1315] "Detailed information" refers to basic information about the store (name, address, products offered) and additional information customized according to the user's emotions.

[1316] A "prompt" refers to an input sentence that requests the generative artificial intelligence to generate detailed information.

[1317] "Store Information" refers to information about a specific store, including its name, address, and products offered, obtained through the Camera Search API.

[1318] "Nearby information" refers to information about tourist spots around the store and how to get there.

[1319] The present invention relates to a system that allows users to upload images of stores they wish to search for and obtain detailed information based on the images. Furthermore, by combining this with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized information. Specific embodiments for implementing this system will now be described in detail.

[1320] User operations

[1321] Users use devices such as smartphones or PCs to take pictures of the store they want to visit or upload existing images to their devices. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotion data. The user then sends the store's image file and emotion data to the system via a dedicated application or web interface.

[1322] Terminal handling

[1323] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG format) and converts it into byte data. The emotion data is then quantified or categorized to represent the user's emotion. Based on this data, the device prepares the data for the API request.

[1324] Server Processing

[1325] The server sends the image data sent from the device to the camera search API and obtains basic information about the store (e.g., store name, address, and products offered). The server also analyzes the emotional data using an emotion engine to identify the user's state (e.g., excited, relaxed). Based on this, the server sends a request for more information to a generative artificial intelligence (e.g., ChatGPT).

[1326] Generate detailed information

[1327] The generative AI generates detailed information based on prompts received from the server, including basic store information (name, address, directions from the nearest station), nearby tourist spots, and recommended menu items. It also generates specific information based on the user's emotional data (e.g., relaxing cafes and lively events).

[1328] Displaying results on a terminal

[1329] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner to the user. This information includes the store's name, address, products offered, access instructions, and nearby tourist attractions. Personalized information based on the user's emotions is also provided, allowing the user to efficiently plan their visit.

[1330] Specific examples

[1331] For example, if a user uploads an image of "Ramen Shop A," the device sends this image to the camera search API, which retrieves the name, address, and type of product offered (e.g., tonkotsu ramen) of "Ramen Shop A." At the same time, the emotion engine analyzes the user's emotions and determines that the user is excited. Based on this, it generates a prompt to the generative AI and sends a request for more information.

[1332] Prompt Sentence Examples

[1333] "Please provide basic store information: Generate detailed information based on the image of "Ramen Shop A" and the user's emotion data. Specifically, please include the store's name, address, information about the products offered (e.g., tonkotsu ramen), directions from the nearest station (e.g., a 10-minute walk from JR Shinjuku Station), nearby tourist spots (e.g., Shinjuku Gyoen, Kabukicho), and events that users can enjoy in an excited state (e.g., nearby live music venues and bowling alleys)."

[1334] As described above, the present invention is a useful system for enabling users to efficiently obtain store information and plan their visit by providing personalized information that takes emotions into consideration.

[1335] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1336] Step 1:

[1337] Users use their smartphones or PCs to take pictures of the stores they want to visit or upload existing images to the device. Users then collect emotion data along with the image data via a dedicated application or web interface. The input is the taken or uploaded store image and the user's emotion data, and the output is the image and emotion data stored on the device.

[1338] Step 2:

[1339] The device converts the image data acquired from the user into an appropriate format (e.g., JPEG format). The emotion data is then quantified or categorized using an emotion analysis engine. In this process, the input is the image data and emotion data from the user, and the output is a JPEG image and quantified or categorized emotion data.

[1340] Step 3:

[1341] The device formats the preprocessed image data and emotion data for an API request and sends it to the server. This API request contains the image data and quantified emotion data. The input is a JPEG image and numeric data, and the output is an API request sent to the server.

[1342] Step 4:

[1343] The server sends the received image data to the camera search API and obtains basic information about the store. The data processing performed here involves analyzing the image data, and the output is basic store information (e.g., store name, address, and products offered). At the same time, the server uses an emotion engine to analyze the emotion data and identify the user's current state. The inputs to this process are the received image data and emotion data, and the output is the obtained store information and the identified user's emotional state.

[1344] Step 5:

[1345] The server sends a request to generate detailed information to the generative AI based on basic store information and user emotion data. The input is the basic store information and user emotion data, and a prompt sentence including this data is generated and sent to the generative AI. The output is the detailed information request sent to the generative AI.

[1346] Step 6:

[1347] Generative AI generates detailed information based on the received prompt. This information includes the store name, address, directions from the nearest station, nearby tourist spots, recommended menu items, and more, as well as specific information based on the user's emotional data (e.g., a relaxing cafe or a lively event). The input to this process is the prompt, and the output is the generated detailed information.

[1348] Step 7:

[1349] The server transmits the detailed information obtained from the generative AI to the terminal. The input is the detailed information received from the generative AI, and the output is the detailed information transmitted to the terminal.

[1350] Step 8:

[1351] The terminal analyzes the detailed information received from the server and displays it in a user-friendly format. The displayed information includes the store name, address, products offered, access instructions, and nearby tourist attractions. The user can use this information to efficiently plan their visit. The input is the detailed information received from the server, and the output is the displayed detailed information and information used to plan the user's visit.

[1352] (Application example 2)

[1353] 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."

[1354] Conventional store information systems allowed users to upload images and obtain basic information, but they were unable to provide personalized information based on the user's current emotional state. As a result, it was difficult for users to obtain optimal information based on their interests and mood, limiting the user experience. Furthermore, they lacked a mechanism for providing comprehensive information on nearby tourist attractions and access methods.

[1355] 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 collecting user emotion data, means for analyzing the emotion data and generating detailed information based on the emotion, and means for requesting detailed information from the generative artificial intelligence. This makes it possible to provide personalized facility information according to the user's current emotional state, as well as information on surrounding tourist attractions and access methods, in an integrated manner.

[1356] "User" refers to a user who wishes to obtain facility information.

[1357] "Image of facility" refers to image data that a user takes or uploads, showing a facility that the user wants to visit.

[1358] "Device" refers to the electronic device, such as a computer, smartphone, or tablet, that a user uses to upload images and view information.

[1359] "Image Data" refers to digital image files containing images of a facility uploaded by a User.

[1360] "Establishment Information" means the name, address, and details of the establishment regarding the products and services offered.

[1361] "Generative AI" refers to an AI system that generates detailed information based on user requests.

[1362] "Detailed information" refers to data that includes basic information about the facility, as well as information about nearby tourist attractions, access methods, and personalized information based on the user's emotions.

[1363] "Emotion data" refers to information indicating the emotional state of a user that is obtained by analyzing facial expressions and voice data.

[1364] "Camera Search API" refers to an application programming interface for analyzing image data and extracting basic information about a facility.

[1365] "Tourist spots" refer to the sights and attractions that tourists should visit in the vicinity of the facility.

[1366] "Access method" refers to the means of transportation and route that a user takes to reach a facility or a nearby tourist spot.

[1367] The present invention is a system that allows users to upload images of facilities and obtain detailed information based on those images. This system can provide more personalized information by combining an emotion engine that recognizes the user's emotional state. Specific embodiments of the system are described in detail below.

[1368] User operations

[1369] First, a user takes a photo of the facility they want to visit using a device such as a smartphone or PC, or uploads an existing image to the device. The emotion engine then analyzes the user's facial expressions and voice in real time to collect emotional data. Next, the image file of the facility and the emotional data are sent to the system via a dedicated application or web interface on the device.

[1370] Terminal handling

[1371] The device receives the image file and emotion data sent by the user, reads the image file in an appropriate format (e.g., JPEG), converts it to byte data, and prepares the data for the API request. The emotion data is used for subsequent processing by quantifying or categorizing the user's emotion. The device first generates a prompt that takes the user's emotion data into consideration, and then sends image data to the camera search API based on the prompt to obtain information about the facility. Basic information obtained from the image data includes the user's name, address, and information about the products offered.

[1372] Server Processing

[1373] The server uses an emotion engine to analyze the user's emotion data. Emotion data is extracted from the user's image and voice data to identify the user's state (e.g., excited, relaxed, etc.). This makes it possible to generate detailed information based on the user's emotion. After receiving the information obtained from the camera search API, the device further sends a request for detailed information to a generative artificial intelligence (e.g., ChatGPT). The request includes basic information about the facility, as well as the user's emotion data and a request to generate information about nearby tourist spots and how to get there.

[1374] Generate detailed information

[1375] The generative AI generates detailed information based on the prompts. This information includes the facility's name, address, directions from the nearest station, nearby tourist attractions, recommended menu items, etc. Specific information that the user may be interested in (e.g., cafes with a relaxing atmosphere or lively events) is also generated based on the user's emotional data. This generated detailed information is returned to the device in a data format such as JSON.

[1376] Displaying results on a terminal

[1377] The device receives the detailed information sent from the server and displays it in an easy-to-understand manner for the user. The displayed content includes the facility's name, address, products offered, access methods, and nearby tourist attractions. The information also takes the user's emotions into consideration, providing customized information according to the user's interests and status. This allows the user to efficiently obtain detailed facility information and plan their visit.

[1378] Specific examples

[1379] For example, consider the case where a user takes a photo of Kiyomizu-dera Temple in Kyoto and uploads it to their device. The device sends this image to the camera search API, which extracts the name, address, and services offered by "Kiyomizu-dera Temple." At the same time, the emotion engine analyzes the user's emotions and determines that the user is in a relaxed state. Based on this, a request is sent to the generative AI for more information, including nearby tourist attractions and how to access them, as well as recommended places to satisfy the user's sense of relaxation. The information returned by the generative AI includes the address of "Kiyomizu-dera Temple," directions to get there from the nearest station, nearby tourist attractions (e.g., Gion, Yasaka Shrine), and places to satisfy the user's sense of relaxation (e.g., nearby quiet cafes and gardens).

[1380] Prompt Sentence Examples

[1381] "Please tell me about sightseeing information for Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state and is looking for a comfortable cafe or a quiet walking route."

[1382] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1383] Step 1:

[1384] The user takes or uploads an image of the facility. Using a device such as a smartphone or PC, the user can take an image of the facility they want to visit or select an existing image and upload it. At the same time, the device analyzes the user's facial expressions and voice in real time to collect emotional data. The input is the image data of the facility and the user's emotional data, and the output is that this data is saved on the device.

[1385] Step 2:

[1386] The device sends image data and emotion data to the server. The device converts the image data sent by the user into an appropriate format (e.g., JPEG) and prepares the data for the API request as byte data. The emotion data is also used to quantify or categorize the user's emotion. The input is the image data and emotion data collected in step 1, and the output is the data for the API request.

[1387] Step 3:

[1388] The server uses the camera search API to obtain facility information. The server sends the received image data to the camera search API, which analyzes it and obtains basic information about the facility (e.g., name, address, services provided). The input is the image data sent from the device, and the output is the basic information about the facility.

[1389] Step 4:

[1390] The server analyzes the user's emotional data using an emotion engine. The server analyzes the received emotional data based on the emotion engine and identifies the user's current emotional state (e.g., relaxed, excited). This emotional data is used to generate detailed information in the future. The input is the emotional data sent from the device, and the output is the analyzed user's emotional state.

[1391] Step 5:

[1392] The server creates a prompt for the generative AI and requests detailed information. The server generates a prompt based on the acquired basic information about the facility and the user's emotional data obtained as a result of the analysis, and asks the generative AI to generate detailed information. For example, a prompt might be sent saying, "Please tell me about tourist information about Kiyomizu-dera Temple and recommended spots in the area. The user is in a relaxed state. I'm looking for a comfortable cafe or a quiet walking course." The input is the basic information about the facility and the user's emotional state, and the output is a prompt sent to the generative AI.

[1393] Step 6:

[1394] The generative AI generates detailed information and sends it back to the server. Based on the prompt, the generative AI generates detailed information such as basic information about the facility, nearby tourist attractions, how to get there, and recommended places based on the user's emotions. The input is the prompt, and the output is the generated detailed information.

[1395] Step 7:

[1396] The server sends detailed information to the terminal. The detailed information received from the generative AI is sent to the terminal in a data format such as JSON. The input is the detailed information from the generative AI, and the output is the data sent to the terminal.

[1397] Step 8:

[1398] The terminal displays detailed information to the user. The terminal analyzes the received detailed information and displays it in a format that is easy for the user to view. The displayed content includes the facility name, address, services provided, access methods, nearby tourist attractions, and recommended places based on the user's emotions. The input is the detailed information sent from the server, and the output is the information displayed on the user's terminal screen.

[1399] 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.

[1400] 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.

[1401] 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.

[1402] 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.

[1403] 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.

[1404] 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.

[1405] 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).

[1406] 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.

[1407] 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."

[1408] 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.

[1409] 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).

[1410] 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.

[1411] 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.

[1412] 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.

[1413] 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.

[1414] 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.

[1415] 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.

[1416] 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.

[1417] 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.

[1418] 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.

[1419] 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.

[1420] The following is further disclosed regarding the above embodiment.

[1421] (Claim 1)

[1422] A means for users to upload images of their stores;

[1423] A means for the terminal to analyze image data and acquire information about the store;

[1424] A means for requesting detailed information from a generative artificial intelligence based on the store information acquired by the terminal;

[1425] A means for a generative artificial intelligence to generate the detailed information and provide it to a terminal;

[1426] a means for the terminal to display the detailed information to a user;

[1427] A system including:

[1428] (Claim 2)

[1429] A means for the terminal to transmit image data to the camera search API;

[1430] means for a camera search API to analyze the image data and extract information about the store's name, address, and products offered;

[1431] 10. The system of claim 1, comprising:

[1432] (Claim 3)

[1433] A means to request the generative artificial intelligence to provide detailed store information, as well as nearby tourist spots and directions;

[1434] A means for a generative artificial intelligence to generate the detailed information and peripheral information and provide them to a terminal;

[1435] 10. The system of claim 1, comprising:

[1436] "Example 1"

[1437] (Claim 1)

[1438] a means for a user to transmit an image of the facility;

[1439] A terminal reads image data and converts the image data into byte data;

[1440] A means for the terminal to transmit image data to an analysis API and acquire basic information about the facility;

[1441] A means for requesting detailed information from the generating AI model based on the facility information acquired by the terminal;

[1442] A means for the generative AI model to generate the detailed information and provide it to the terminal;

[1443] a means for the terminal to display the detailed information to a user;

[1444] A system including:

[1445] (Claim 2)

[1446] A means for the terminal to transmit image data to the object recognition API;

[1447] means for an object recognition API to analyze the image data and extract information about the name, location, and services offered of the facility;

[1448] 10. The system of claim 1, comprising:

[1449] (Claim 3)

[1450] a means for requesting the generative AI model to provide detailed facility information as well as surrounding points of interest and access methods;

[1451] A means for the generative AI model to generate the detailed information and peripheral information and provide them to the terminal;

[1452] 10. The system of claim 1, comprising:

[1453] "Application Example 1"

[1454] (Claim 1)

[1455] A means for users to upload images of their stores;

[1456] A means for the terminal to analyze image data and acquire information about the store;

[1457] A means for requesting detailed information from a generative artificial intelligence based on the store information acquired by the terminal;

[1458] A means for a generative artificial intelligence to generate the detailed information and provide it to a terminal;

[1459] a means for the terminal to display the detailed information to a user;

[1460] A means for the terminal to transmit image data to the camera search API;

[1461] means for a camera search API to analyze the image data and extract information about the store's name, address, and products offered;

[1462] A means to request the generative artificial intelligence to provide detailed store information, as well as nearby tourist spots and directions;

[1463] A means for a generative artificial intelligence to generate the detailed information and peripheral information and provide them to a terminal;

[1464] A means for a user to upload an image via a smartphone application and transmit the image data to a server;

[1465] A system including:

[1466] (Claim 2)

[1467] A means for the terminal to transmit image data to the camera search API;

[1468] means for a camera search API to analyze the image data and extract information about the store's name, address, and products offered;

[1469] The system according to claim 1, further comprising means for the generative artificial intelligence to generate detailed information based on the information and provide the information to the terminal.

[1470] (Claim 3)

[1471] A means to request the generative artificial intelligence to provide detailed store information, as well as nearby tourist spots and directions;

[1472] A means for a generative artificial intelligence to generate the detailed information and peripheral information and provide them to a terminal;

[1473] and means for a user to obtain the detailed information via a smartphone application.

[1474] "Example 2: Combining Emotion Engines"

[1475] (Claim 1)

[1476] A means for a user to upload image data and emotion data;

[1477] means for the terminal to convert the image data into an appropriate format;

[1478] A means for the terminal to quantify or categorize the user's emotion data;

[1479] a means for transmitting the image data and emotion data to a server by a terminal;

[1480] A means for the server to analyze image data and acquire information about the store;

[1481] A means for the server to analyze the emotion data and identify the state of the user;

[1482] A means for requesting detailed information from the generative artificial intelligence based on the store information and emotion data acquired by the server;

[1483] A means for a generative artificial intelligence to generate the detailed information and provide it to a server;

[1484] A means for the server to send the detailed information to the terminal;

[1485] a means for the terminal to display the detailed information to a user;

[1486] A system including:

[1487] (Claim 2)

[1488] A means for the device to send image data to a camera search API for analysis;

[1489] means for a camera search API to analyze the image data and extract information about the store's name, address, and products offered;

[1490] 10. The system of claim 1, comprising:

[1491] (Claim 3)

[1492] A means to request the generative artificial intelligence to provide detailed store information, as well as nearby tourist spots and directions;

[1493] A means for the generative artificial intelligence to generate the detailed information and peripheral information and provide them to a server;

[1494] 10. The system of claim 1, comprising:

[1495] "Application example 2 when combining emotion engines"

[1496] (Claim 1)

[1497] a means for users to upload images of the facility;

[1498] A means for the terminal to analyze image data and acquire information about the facility;

[1499] A means for requesting detailed information from a generative artificial intelligence based on facility information acquired by the terminal;

[1500] A means for a generative artificial intelligence to generate the detailed information and provide it to a terminal;

[1501] a means for the terminal to display the detailed information to a user;

[1502] means for collecting user emotion data;

[1503] means for analyzing the emotion data and generating emotion-based detailed information;

[1504] A system including:

[1505] (Claim 2)

[1506] A means for the terminal to transmit image data to the camera search API;

[1507] means for a camera search API to analyze the image data and extract information about the name, address, and products offered of the establishment;

[1508] 10. The system of claim 1, comprising:

[1509] (Claim 3)

[1510] A means for requesting the generative artificial intelligence to provide detailed facility information as well as nearby tourist attractions and directions to them;

[1511] A means for a generative artificial intelligence to generate the detailed information and peripheral information and provide them to a terminal;

[1512] 10. The system of claim 1, comprising: [Explanation of symbols]

[1513] 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. A means for users to upload images of their stores; A means for the terminal to analyze image data and acquire information about the store; A means for requesting detailed information from a generative artificial intelligence based on the store information acquired by the terminal; A means for a generative artificial intelligence to generate the detailed information and provide it to a terminal; a means for the terminal to display the detailed information to a user; A system including:

2. A means for the terminal to transmit image data to the camera search API; means for a camera search API to analyze the image data and extract information about the store's name, address, and products offered; The system of claim 1 , comprising:

3. A means to request the generative artificial intelligence to provide detailed store information, as well as nearby tourist spots and directions; A means for a generative artificial intelligence to generate the detailed information and peripheral information and provide them to a terminal; The system of claim 1 , comprising:

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