System

Abstract

A system is provided.SOLUTION: A system comprising: server means for managing an application database; server means for receiving a request from a user terminal; server means for returning an application list to the user terminal; server means for processing a request from the user to install a particular application and updating user data; and server means for obtaining an installed application list of the user and returning it to the user terminal.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] In recent years, the number of various applications using artificial intelligence (AI) has increased, creating a demand for an environment where these applications can be easily used. However, currently, users require advanced technical knowledge to efficiently find, install, and use each AI application, making it difficult to use. In addition, the system for providing compensation to AI developers is unclear, hindering the improvement of the diversity and quality of AI applications. Therefore, there is a need to provide an environment where users can easily use AI applications and establish a system for providing appropriate compensation to AI developers. [Means for solving the problem]

[0005] The present invention provides a system including a server means for managing an application database, a server means for receiving requests from a user's device, a server means for returning an application list to the user's device, a server means for processing a user's request to install a specific application and updating user data, and a server means for acquiring a list of the user's installed applications and returning it to the user's device. This system allows users to easily install and use the necessary applications without having to create prompts. Furthermore, the system analyzes the user ID and application ID when installing an application, checks whether the application exists in the database, and adds or updates the user data, thereby efficiently managing applications. Furthermore, the system has a means for structuring application data in JSON format and returning it to the device, enabling smooth data communication with the user.

[0006] An "application database" is a data storage system used to manage information for an application.

[0007] A "server means" is a server that has the function of receiving a request from a user, querying a database, and returning a response.

[0008] "User" refers to a person who uses or installs an application via this system.

[0009] "Terminal" refers to a device used by a user, such as a computer, smartphone, or tablet.

[0010] An "application list" is a list that includes the names and descriptions of available applications.

[0011] "Installation" refers to the process of making a selected application available to a particular user.

[0012] "User Data" means data that contains information related to a user (e.g., user ID, list of installed applications, etc.).

[0013] "Handling a request" refers to the set of actions that receive a request from a user and perform appropriate operations based on that request.

[0014] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation (JSON), a lightweight data exchange format for structuring, storing, and transmitting data.

[0015] "Structuring" refers to the process of organizing data into a particular format for storage or transmission. [Brief explanation of the drawings]

[0016] [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 illustrating 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

[0017] 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.

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

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

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

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0031] 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.

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

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The present invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications. Specific embodiments of the system are described below.

[0038] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[0039] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0040] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0041] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[0042] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0043] As described above, this system allows users to intuitively search for, install, and use AI applications. Furthermore, by establishing a mechanism for providing appropriate rewards to developers, the system will improve the quality and diversity of applications and contribute to the development of AI.

[0044] The processing flow will be explained below.

[0045] Step 1:

[0046] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[0047] Step 2:

[0048] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[0049] Step 3:

[0050] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[0051] Step 4:

[0052] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[0053] Step 5:

[0054] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[0055] Step 6:

[0056] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[0057] Step 7:

[0058] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[0059] Step 8:

[0060] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[0061] Step 9:

[0062] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[0063] Step 10:

[0064] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[0065] Step 11:

[0066] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[0067] Step 12:

[0068] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[0069] Step 13:

[0070] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[0071] Example 1

[0072] 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."

[0073] In conventional systems, it has been difficult for users to search for, easily install, and use artificial intelligence (AI) applications. It has also been cumbersome for users to manage installed applications. Due to these issues, there is a demand for improved user convenience and efficiency.

[0074] 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.

[0075] In this invention, the server includes information processing means for managing an application database, information processing means for receiving requests from a user's terminal, information processing means for returning an application list to the user's terminal, information processing means for processing a user's request to install a specific application and updating user data, information processing means for obtaining a list of the user's installed applications and returning it to the user's terminal, information display means for allowing a user to access an application market from their terminal, select an application from the list, and request installation, information generation means for the server to generate a message indicating successful installation and return it to the terminal, information display means for the terminal to render the application list received from the server on the screen and display it to the user, and communication processing means for the terminal to send an HTTP request to the server to request a list of available applications. This enables users to easily search for, install, and use AI applications.

[0076] An "application database" is a collective data storage used to manage information about artificial intelligence applications.

[0077] "Information processing means" refers to a functional module that enables a computer system or server to perform specific data processing.

[0078] "User's device" refers to a computing device used by a user, such as a smartphone, tablet, or PC.

[0079] A "request" refers to an operation or the content of an operation in which a user requests specific information or service through a terminal.

[0080] An "application list" is a list of information about multiple artificial intelligence applications.

[0081] "User Data" means a data set containing identifying information and activity records relating to a user.

[0082] "Information display means" refers to a function or module that enables a terminal to display visual information to a user.

[0083] "Information generation means" refers to a function or module that allows the server to generate specific information and transmit that information to users or other systems.

[0084] "Communication processing means" refers to the function for performing data communication between the terminal and the server.

[0085] The present invention provides a system for assisting users in easily searching for, installing, and using artificial intelligence (AI) applications. Detailed embodiments are described below.

[0086] The server first manages the application database. Specifically, the server uses an Amazon Web Services (AWS®) EC2 instance, and the database uses Amazon RDS (Relational Database Service). The application data includes information such as the application ID, name, and description.

[0087] When a user accesses the application market using a terminal, the terminal sends an HTTP request to the server to request a list of available applications. This request is performed using the HTTP GET method.

[0088] The server receives this request, retrieves all application information from the application database, and returns it to the device as a structured response in JSON format. This process uses Node.js on the server side. The device renders the received JSON-formatted application list on the screen and provides it to the user as a selection. The processing on the device side is implemented using React (a front-end library).

[0089] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request uses the HTTP POST method, and the body contains the user ID and application ID.

[0090] The server receives the request and analyzes the user ID and application ID based on it. It checks the database to see if the user and application exist, and if they do, it adds the application ID to the user data and updates the database. Through this series of operations, the user data is changed using an UPDATE query. The server then generates a message indicating that the installation was successful and sends it back to the terminal.

[0091] The user will then receive a message on their device indicating successful installation, and will be able to use the selected application. If the user wishes to check the list of their installed applications, they can send a request to the server from their device. The server will retrieve the list of installed applications from the user database and send a response structured in JSON format back to the device. The device will then display this on the screen, allowing the user to check the currently installed applications.

[0092] As a concrete example, the process for a user to install an application named "Image Classification AI" is shown below.

[0093] 1. The user accesses the URL "https: / / ai-market.com".

[0094] 2. The device sends a request "GET / api / applications" to the server.

[0095] 3. The server retrieves the application information from the database and returns it in JSON format.

[0096] 4. The device parses this JSON data and displays an application called "Image Classification AI" on the screen.

[0097] 5. When the user clicks the install button for "Image Classification AI," the device sends a "POST / api / install" request to the server. The body contains { userId: "user1", appId: "app1"}.

[0098] 6. The server receives the request, updates the database, and adds "app1" to the user data.

[0099] 7. The server generates a message indicating that the installation was successful and returns it to the terminal.

[0100] 8. The device displays the message "Installation successful" to the user.

[0101] This series of processes allows users to easily install and use the AI ​​applications they need without any complicated work.

[0102] Example prompts to input to a generative AI model:

[0103] "Please explain in a way that the Generative AI model can understand how a user accesses the AI ​​App Market and installs a specific application. Please provide a detailed explanation of the entire process, with particular emphasis on submitting and processing the install request."

[0104] This system will improve user convenience by making it easier for users to intuitively search for, install, and use AI applications. It will also establish an appropriate reward system for developers, improving the quality and diversity of applications and contributing to the development of AI technology.

[0105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0106] Step 1: User visits the App Market

[0107] Specific operation: The user opens the browser on their device and enters the URL of the AI ​​application market (e.g., https: / / ai-market.com) to access it.

[0108] Input: A user types a market URL into the browser's address bar.

[0109] Output: The terminal displays the initial Market screen.

[0110] Step 2: The device requests an application list from the server.

[0111] Specific operation: The device sends an HTTP GET request to the server to request a list of available applications.

[0112] Input: HTTP GET request sent by the device: "GET / api / applications"

[0113] Output: The server receives the request.

[0114] Step 3: The server retrieves all application information from the application database

[0115] What it does: The server queries the database to get application information and structures it in JSON format.

[0116] Input: HTTP GET request received by the server and application information from the database

[0117] Output: Application information structured in JSON format

[0118] Step 4: The server returns the application information to the device.

[0119] Specific operation: The server returns application information structured in JSON format to the terminal as an HTTP response.

[0120] Input: Application information in JSON format

[0121] Output: The HTTP response received by the device

[0122] Step 5: Display the list of applications retrieved by the device on the screen.

[0123] Specific operation: The device parses the received JSON data, renders the application list on the screen, and displays it to the user.

[0124] Input: JSON format application information received by the device

[0125] Output: Application list displayed on the device screen

[0126] Step 6: User selects specific application and submits installation request

[0127] Specific behavior: The user selects a specific application from the list and clicks the install button, which causes the device to send an HTTP POST request to the server.

[0128] Input: User selected application

[0129] Output: HTTP POST request "POST / api / install" sent by the device. The body contains the user ID and application ID.

[0130] Step 7: The server receives the install request and parses the user ID and application ID.

[0131] Specific operation: The server receives the installation request and analyzes the user ID and application ID in the request.

[0132] Input: HTTP POST request sent by the device

[0133] Output: Parsed user ID and application ID

[0134] Step 8: Server checks database for user and application existence

[0135] What happens: The server queries the database and verifies that the user ID and application ID exist.

[0136] Input: Parsed user ID and application ID

[0137] Output: User and application existence check results

[0138] Step 9: The server adds the application ID to the user data and updates the database

[0139] Specific operation: The server adds the application ID to the user data and updates the database.

[0140] Input: User data and verified application ID

[0141] Output: Updated user data

[0142] Step 10: The server sends a message back to the device confirming the installation was successful.

[0143] Specific operation: The server generates a message indicating that the installation was successful and sends it back to the terminal.

[0144] Input: Updated user data

[0145] Output: Installation successful message

[0146] Step 11: The terminal displays a successful installation message to the user

[0147] Specific operation: The device displays the installation success message to the user.

[0148] Input: Installation success message received from the server

[0149] Output: A successful installation message that is displayed to the user.

[0150] (Application example 1)

[0151] 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."

[0152] Modern consumers are trying to live comfortable lives by utilizing a wide variety of AI applications, but searching for and installing the appropriate applications from the vast number of available ones requires a great deal of effort and time. Online shopping sites, in particular, are required to quickly and accurately predict and recommend the product categories consumers desire, but current systems do not adequately meet this need. Therefore, there is a need for a system that allows consumers to easily search for and install the AI ​​applications they need, and also has the ability to predict and recommend product categories.

[0153] 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.

[0154] In this invention, the server includes means for managing an application database, means for receiving requests from a user's terminal, means for returning an application list to the user's terminal, means for processing a user's request to install a specific application and updating user data, means for obtaining a list of the user's installed applications and returning it to the user's terminal, and means for including a generative AI model that predicts and recommends product categories searched for by the user. This enables users to easily search for and install the AI ​​applications they need, and enables the prediction and recommendation of appropriate product categories on online shopping sites.

[0155] An "application database" is a database that holds information about available applications managed within the system.

[0156] "Server means" refers to the functions and devices of a server that manages an application database, receives and processes requests from users, and returns responses.

[0157] A "user device" is an electronic device used by a user to discover, install, and use applications.

[0158] A "request" is request data sent from a user's terminal to a server.

[0159] An "application list" is a list of available applications that is returned from the server to the user's terminal.

[0160] An "installation request" is a request made by a user to install a particular application on a terminal in order to use the application.

[0161] "User Data" is data in a database that contains user-specific information.

[0162] A "generative AI model" is a type of artificial intelligence that uses machine learning algorithms to perform a specific task, such as predicting product categories.

[0163] A "prompt" is input text that gives specific instructions to an AI.

[0164] The present invention relates to a system that enables users to easily search for, install, and use AI applications. Specific embodiments of the system are described below.

[0165] The server first manages an application database, which stores information about available applications. Application data includes the application's ID, name, description, etc.

[0166] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0167] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0168] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0169] Furthermore, this invention uses a generative AI model to predict and recommend the product category a user is searching for. Specifically, when a user accesses the application market or searches for a specific product category, the generative AI model analyzes product images and text data to predict and recommend the appropriate category. This function allows users to intuitively find the applications and products they need.

[0170] The hardware used includes smartphones and servers (virtual or physical), and the software used includes Flask, which is used to create API endpoints on the server side, requests, which is used to make HTTP requests, and the JSON format, which is used to structure and parse the data.

[0171] As a concrete example, consider the process in which a user installs an application called "Image Classification AI" and uses that AI to predict product categories on an online shopping website. The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request is sent from the device to the server stating, "User 1 installs App 1." The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user data, and returns a message to the device indicating successful installation.

[0172] An example of a prompt is as follows:

[0173] "Predict the product category from this image."

[0174] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0175] Step 1:

[0176] A user accesses the application market from a smartphone device.

[0177] Input: User action (access to the market).

[0178] Output: The request is sent to the server.

[0179] Specific operation: The user taps the application market icon on the smartphone, launching the market app, which then sends a GET request to the server.

[0180] Step 2:

[0181] The server generates an application list in JSON format and returns it to the device.

[0182] Input: A request from the user's terminal.

[0183] Output: A list of applications in JSON format.

[0184] Specific operation: The server accesses the application database to obtain all available application information, structures the obtained information in JSON format, and returns it to the user device.

[0185] Step 3:

[0186] The terminal displays the received application list on the user interface.

[0187] Input: A list of applications in JSON format.

[0188] Output: The application list displayed on the screen.

[0189] Specific operation: The device parses the JSON data received from the server and visually displays the application list in the user interface.

[0190] Step 4:

[0191] The user selects a particular application and submits an installation request.

[0192] Input: User's choice (Application ID).

[0193] Output: The installation request sent to the server.

[0194] Specific operation: The user taps the application they want to install, and the device sends a POST request to the server containing the application ID and the user ID.

[0195] Step 5:

[0196] The server receives the installation request and parses and verifies the user ID and application ID.

[0197] Input: The user ID and application ID in the install request.

[0198] Output: User database updated and installation successful message.

[0199] Specific operation: The server accesses the database and checks the existence of the user ID and application ID. After checking, it adds the application ID to the user data and generates a message indicating successful installation and returns it to the user device.

[0200] Step 6:

[0201] The user submits a request to see a list of installed applications.

[0202] Input: User action (submitting a confirmation request).

[0203] Output: A confirmation request sent to the server.

[0204] Specific operation: The user taps the confirmation button, and the device sends a GET request to the server.

[0205] Step 7:

[0206] The server obtains a list of the user's installed applications and returns it to the device in JSON format.

[0207] Input: User confirmation request.

[0208] Output: A list of installed applications in JSON format.

[0209] Specific operation: The server retrieves information about installed applications from the user database, structures it in JSON format, and sends it back to the user's device.

[0210] Step 8:

[0211] The terminal displays the acquired list of installed applications on a user interface.

[0212] Input: A list of installed applications in JSON format.

[0213] Output: A list of installed applications displayed on the screen.

[0214] Specific operation: The device parses the received JSON data and visually displays a list of installed applications in the user interface.

[0215] Step 9:

[0216] The user enters a prompt sentence to predict the product category using the generative AI model.

[0217] Input: The prompt text entered by the user.

[0218] Output: A request to the generative AI model.

[0219] Specific operation: The user enters the prompt "Please predict the product category from this image" into the input field of the device and taps the send button. The device then sends the prompt and the product image to the generative AI model.

[0220] Step 10:

[0221] The generative AI model predicts the product category and returns the prediction results to the terminal.

[0222] Input: Prompt text and product image.

[0223] Output: Product category prediction results.

[0224] Specific operation: The generative AI model analyzes the prompt text and product image to predict the product category, and returns the prediction result to the user's device.

[0225] Step 11:

[0226] The product category prediction result received by the terminal is displayed on a user interface.

[0227] Input: Product category prediction results.

[0228] Output: Product category prediction results displayed on the screen.

[0229] Specific operation: The device analyzes the prediction results received and displays them on the user interface.

[0230] 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.

[0231] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, and also provides a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[0232] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[0233] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0234] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect information such as the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time.

[0235] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0236] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[0237] The system also has the ability to recommend applications suitable for users based on their emotional data. For example, if the emotion engine detects that a user is stressed, it can recommend applications that help with relaxation. This recommendation function allows users to easily find the application that best suits their condition.

[0238] Furthermore, to check the applications installed by the user, the device can send a request to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0239] As described above, this system allows users to intuitively search for, install, and use AI applications, and also has the ability to recognize users' emotions in real time and recommend optimal applications based on that data, improving the user experience and promoting the use of AI applications.

[0240] The processing flow will be explained below.

[0241] Step 1:

[0242] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[0243] Step 2:

[0244] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[0245] Step 3:

[0246] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[0247] Step 4:

[0248] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[0249] Step 5:

[0250] The user's device uses an emotion engine to collect data from cameras, microphones, etc. to recognize the user's emotions. The device sends the collected data to the emotion engine, which then analyzes the emotions.

[0251] Step 6:

[0252] The emotion engine analyzes the user's emotions and sends the results to the server, which receives the emotion data and determines which applications to recommend based on the user's emotional state.

[0253] Step 7:

[0254] The server structures a list of suitable applications in JSON format based on the user's emotional state, and then sends the structured list of recommendations back to the device as an HTTP response.

[0255] Step 8:

[0256] The device analyzes the recommendation list received from the server and displays it on the screen. The user can then review the recommended applications and select them as needed.

[0257] Step 9:

[0258] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[0259] Step 10:

[0260] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[0261] Step 11:

[0262] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[0263] Step 12:

[0264] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[0265] Step 13:

[0266] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[0267] Step 14:

[0268] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[0269] Step 15:

[0270] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[0271] Step 16:

[0272] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[0273] Step 17:

[0274] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[0275] Example 2

[0276] 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."

[0277] Conventional systems require users to go through complicated procedures when installing AI applications, resulting in a poor user experience. Furthermore, the lack of a function to recommend appropriate applications based on user sentiment makes it difficult for users to find the application that best suits them. This does not promote the use of AI applications and reduces convenience for users.

[0278] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0279] In this invention, the server includes computer system means for managing an application database, computer system means for receiving requests from a user's computer device, computer system means for returning an application list to the user's computer device, computer system means for processing a user's request to install a specific application and updating user information, computer system means for obtaining the user's installed application list and returning it to the user's computer device, and emotion analysis means for recognizing the user's emotions and recommending appropriate applications based on that data. This allows users to intuitively and easily search for, install, and use AI applications, and further improves convenience by recommending optimal applications based on the user's emotions.

[0280] An "application database" is a database that manages information about multiple applications available to users.

[0281] "Computer system means" refers to the software and hardware running on a server or user's computing device that is used to provide a particular function or service.

[0282] A "request" refers to a request made from a user's computing device to a server, and includes operations such as retrieving or updating data.

[0283] A "structured language format" is a description format for representing data in an organized and consistent manner, and examples include JSON and XML.

[0284] "User information" refers to data about users managed within the system, including information such as user IDs and installed applications.

[0285] An "emotion analysis means" is a mechanism that recognizes emotions by analyzing data such as the user's facial expressions and voice, and recommends appropriate applications based on the results.

[0286] "User's computing device" refers to the electronic device used by the user to access the system, including smartphones, tablets, and personal computers.

[0287] MODE FOR CARRYING OUT THE INVENTION

[0288] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, as well as a system that combines an emotion engine that recognizes the user's emotions.

[0289] Configuration and Hardware / Software Used

[0290] The server provides the core functionality of the system using the following hardware and software:

[0291] Hardware: High-performance server machine

[0292] Software: Apache (registered trademark) HTTP server, MySQL (registered trademark) database, Python (backend)

[0293] A terminal is a computing device used by a user (e.g., a smartphone) that has the following components:

[0294] Hardware: Smartphone (iOS or ANDROID (registered trademark))

[0295] Software: Dedicated application (front end), sensors such as cameras and microphones

[0296] The emotion engine is a component for recognizing user emotions in real time, using:

[0297] Software: Python, OpenCV, Google® Cloud Speech-to-Text API, deep learning framework (e.g., TENSORFLOW® or PyTorch)

[0298] Program processing

[0299] The server manages an application database that contains information about available applications, such as application IDs, names, and descriptions.

[0300] When a user accesses the AI ​​application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns it to the device in a structured language (JSON) format. The device then displays the received application list on the screen and allows the user to make a selection.

[0301] When a user wants to install a specific application (e.g., "Image Classification AI"), they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database. If the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database. The server then sends a message back to the device indicating that the installation was successful.

[0302] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time. If the emotion engine detects that the user is stressed, it can recommend applications that will help with relaxation.

[0303] Furthermore, the user can check their installed applications by sending a request from the device to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0304] Specific examples

[0305] For example, consider the process of a user installing an application named "Image Classification AI." The user accesses the market, retrieves the application list, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user information, and returns a message to the device indicating successful installation.

[0306] This series of processes allows users to easily install and use the necessary applications without having to go through complicated procedures.

[0307] Prompt Sentence Examples

[0308] "User 1 sends a request to the server to install app 1. The server checks the user database and application database for the existence of user 1 and app 1, and adds app 1's information to the user information. The server then sends a message that the installation was successful."

[0309] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0310] Step 1:

[0311] The user accesses the AI ​​application market from their device.

[0312] Input: None

[0313] Output: None

[0314] Specific operation: The user launches the "AI App Market" app on their smartphone.

[0315] Step 2:

[0316] The terminal sends a request to the server for a list of currently available applications.

[0317] Input: User access request

[0318] Output: HTTP request to the server

[0319] Specific operation: The device sends an HTTP request to the server in the format "GET / api / applications".

[0320] Step 3:

[0321] The server retrieves all application information from the application database.

[0322] Input: Request from terminal

[0323] Output: Application information

[0324] Specific operation: The server executes the MySQL query "SELECT FROM applications" to retrieve the data.

[0325] Step 4:

[0326] The server converts the acquired application information into a structured language (JSON) format and returns it to the terminal.

[0327] Input: Application Information

[0328] Output: HTTP response to the terminal (JSON format)

[0329] Specific operation: The server uses a Python library to convert the data into JSON format and returns it as an HTTP response.

[0330] Step 5:

[0331] The terminal displays the received application list on the screen and provides the user with a selection.

[0332] Input: Application list from the server (JSON format)

[0333] Output: Application list displayed on screen

[0334] Specific behavior: The device's app UI displays the application name and description in a list format.

[0335] Step 6:

[0336] The user selects the application they wish to install and clicks the install icon.

[0337] Input: Application list displayed on the screen

[0338] Output: Clicking the installation icon

[0339] Specific operation: The user selects "Image Classification AI" and clicks the install button.

[0340] Step 7:

[0341] The device sends a request to the server to install a specific application, which includes the user ID and the application ID.

[0342] Input: User ID, Application ID

[0343] Output: HTTP POST request to the server

[0344] Specific operation: The device sends an HTTP POST request "POST / api / install" and includes the user ID and application ID in the request body.

[0345] Step 8:

[0346] The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database.

[0347] Input: Installation request (user ID, application ID)

[0348] Output: User and application records retrieved from the database

[0349] Specific operation: The server executes the MySQL queries "SELECT FROM users WHERE id="user ID"" and "SELECT FROM applications WHERE id="application ID"".

[0350] Step 9:

[0351] After the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database.

[0352] Input: User and application records

[0353] Output: Updated user information

[0354] Specific operation: The server executes the MySQL query "INSERT INTO user_apps (user_id, app_id) VALUES ('user ID', 'application ID')".

[0355] Step 10:

[0356] The server will return a message to the terminal indicating that the installation was successful.

[0357] Input: Updated user information

[0358] Output: Installation successful message (JSON format)

[0359] Specific operation: The server returns an "Installation successful" message in JSON format in the HTTP response.

[0360] Step 11:

[0361] The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice.

[0362] Input: User's facial expression, tone of voice

[0363] Output: Collected emotion data

[0364] Specific operation: The device activates the camera to capture the user's face and collects audio data using the microphone.

[0365] Step 12:

[0366] The device sends the collected data to the emotion engine.

[0367] Input: Collected emotion data

[0368] Output: Input data to the emotion engine

[0369] Specific operation: Camera image data is analyzed using the OpenCV library, and audio data is processed using the Google Cloud Speech-to-Text API.

[0370] Step 13:

[0371] The emotion engine analyzes the user's emotions and recommends appropriate applications.

[0372] Input: Parsed emotion data

[0373] Output: A list of recommended applications

[0374] How it works: The emotion engine uses deep learning models (TensorFlow and PyTorch) to recognize emotions and recommends relaxation apps when stress is detected.

[0375] Step 14:

[0376] A user sends a request from the terminal to the server to check the installed applications.

[0377] Input: User verification request

[0378] Output: HTTP request to the server

[0379] What happens: The user accesses the "My Apps" section of their device.

[0380] Step 15:

[0381] The server retrieves a list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format.

[0382] Input: User request

[0383] Output: List of installed applications (JSON format)

[0384] Specific operation: The server executes the MySQL query "SELECT FROM user_apps WHERE user_id='User ID'" and returns the results in JSON format.

[0385] Step 16:

[0386] The terminal displays the acquired information and allows the user to check the currently installed applications.

[0387] Input: JSON response from the server

[0388] Output: A list of installed applications displayed on the screen.

[0389] Specific behavior: The device's app UI displays a list of installed applications.

[0390] (Application example 2)

[0391] 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."

[0392] The process of searching, installing, and using existing AI applications is complicated and unintuitive for users. Furthermore, it does not recommend optimal applications based on the user's emotional state. Therefore, a more efficient and user-friendly system is needed. In particular, it is essential to manage applications suitable for automation robots in factories and to provide optimal recommendations based on real-time emotional analysis.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0394] In this invention, the server includes a database server means for managing application data, a server means for receiving requests from a user terminal, a server means for returning an application list to the user terminal, a server means for processing a user's request to install a specific application and updating user data, a server means for acquiring a list of the user's installed applications and returning it to the user terminal, an emotion analysis engine means for recognizing the user's emotions, and a server means for recommending optimal applications based on the emotion analysis engine means. This allows users to intuitively search for, install, and use AI applications, and the recommendation of optimal applications based on emotional states can improve the operation of automated robots in factories, achieve predictive maintenance, parts management and supply, and increase efficiency.

[0395] "Database server means for managing application data" refers to a server that centrally manages information such as the ID, name, and description of various AI applications.

[0396] The "server means for receiving requests from user terminals" refers to a server that has the function of receiving requests that users send to the server from their own terminals.

[0397] "Server means for returning an application list to the user terminal" refers to the function of the server sending a list of AI applications to the user terminal in response to a user request.

[0398] The "server means for processing requests from users to install specific applications and updating user data" refers to a server that processes requests to install AI applications selected by users and updates user data.

[0399] The "server means for acquiring a list of applications already installed by the user and returning it to the user terminal" is a server having the function of acquiring a list of applications already installed and sending it to the user terminal.

[0400] The "emotion analysis engine means for recognizing the user's emotions" is an engine that uses sensors such as a camera and microphone to analyze the user's facial expressions and tone of voice, and recognizes emotions in real time.

[0401] The "server means for recommending the most suitable application based on the emotion analysis engine means" is a server having a function for recommending the most suitable AI application for the user's state based on the results of the user's emotion analysis.

[0402] To implement this invention, it is necessary to build a system that uses a database server that manages various application data, a server that receives requests from users, a server that processes lists and installation requests, an emotion analysis engine, and a server with recommendation functions.

[0403] Specifically, the server manages a database and stores information about available AI applications. Application data includes the application's ID, name, description, etc. When a user accesses the application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves the application information from the database, and returns it to the user's device in a structured data format. This allows the user to view a list of available applications on their device.

[0404] Furthermore, if a user wishes to install an application, the request will be sent to the server, which will analyze the user ID and application ID, check the database, update the user data if it exists, and return a message indicating successful installation to the device, allowing the user to smoothly install the AI ​​application.

[0405] The system also features an emotion analysis engine that recognizes the user's emotions. It uses a camera and microphone to collect the user's facial expressions and tone of voice, and analyzes their emotions in real time. Based on this emotion data, the server has the function of recommending the most appropriate AI application to the user. For example, if stress is detected from the user's emotion analysis, it can recommend a relaxation application. This function promotes the use of the most appropriate application tailored to the user's situation.

[0406] A specific example of application in factories is to introduce this system to automated robots working in factories. For example, if the emotion analysis engine detects stress from the tone of an operator's voice, a "predictive maintenance AI" can be installed to prevent the robot from breaking down.

[0407] An example prompt is, "User detected with high stress levels through voice analysis. Recommend installing preventive maintenance AI application to ensure smooth operation of factory robots."

[0408] In this way, this invention allows users to intuitively search for, install, and use AI applications, and by recommending optimal applications based on emotion analysis data, it is possible to improve the operation of automated robots in factories, perform predictive maintenance, manage and supply parts, and increase efficiency.

[0409] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0410] Step 1:

[0411] A user accesses the application market from a terminal. The input is the user's access request, and the terminal sends a request to the server to obtain an application list. The server receives this request. The output is the terminal receiving the request for the application list.

[0412] Step 2:

[0413] The server retrieves application information from the database. The input is the request received in step 1, and the server retrieves information such as application ID, name, description, etc. from the database. The output is the retrieved application list.

[0414] Step 3:

[0415] The server returns the acquired application information to the device in a structured data format (e.g., JSON format). The input is the data acquired in step 2, which the server converts into a structured data format. The output is a JSON-formatted application list that is sent to the device.

[0416] Step 4:

[0417] The terminal displays the received application list in the user interface. The input is the JSON-formatted data sent in step 3, and the terminal displays this to the user as a visually easy-to-read list. The output is the application list that the user views.

[0418] Step 5:

[0419] A user clicks a button to install a specific application. The input is the user's click, and the terminal sends an installation request to the server. The output is an installation request to the server.

[0420] Step 6:

[0421] The server parses the received installation request to obtain the user ID and application ID. The input is the request sent in step 5, which the server parses to extract the required IDs. The output is the parsed user ID and application ID.

[0422] Step 7:

[0423] The server checks the existence of the user ID and application ID in the database. The input is the ID obtained in step 6, and the server checks whether these IDs exist in the database. The output is the result of the existence check.

[0424] Step 8:

[0425] If the existence check is successful, the server adds the application ID to the user data and updates the database. The input is the check result from step 7, and the server updates the user data. The output is the updated database.

[0426] Step 9:

[0427] The server returns a message to the user terminal indicating that the installation was successful. The input is the data updated in step 8, and the server generates a message indicating that the installation was successful. The output is the success message sent to the user terminal.

[0428] Step 10:

[0429] The user's device uses an emotion analysis engine to analyze the user's emotional state. The input is data on the user's facial expressions and voice collected from a camera or microphone, which the device analyzes using the emotion analysis engine. The output is emotional data as the analysis result.

[0430] Step 11:

[0431] If the emotion analysis engine detects emotions such as stress or anxiety, the server will recommend the most appropriate application based on that. The input is the emotion data from step 10, and the server selects and recommends the most appropriate application from the database based on that data. The output is the recommendation result for the user.

[0432] Step 12:

[0433] The recommended applications are displayed on the user's device, and the user can install or use them as needed. The input is the recommendation result from step 11, which the device displays on the user interface. The output is the displayed recommendation result.

[0434] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating 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.

[0435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0436] 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.

[0437] [Second embodiment]

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

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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."

[0450] The present invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications. Specific embodiments of the system are described below.

[0451] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[0452] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0453] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0454] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[0455] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0456] As described above, this system allows users to intuitively search for, install, and use AI applications. Furthermore, by establishing a mechanism for providing appropriate rewards to developers, the system will improve the quality and diversity of applications and contribute to the development of AI.

[0457] The processing flow will be explained below.

[0458] Step 1:

[0459] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[0460] Step 2:

[0461] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[0462] Step 3:

[0463] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[0464] Step 4:

[0465] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[0466] Step 5:

[0467] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[0468] Step 6:

[0469] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[0470] Step 7:

[0471] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[0472] Step 8:

[0473] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[0474] Step 9:

[0475] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[0476] Step 10:

[0477] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[0478] Step 11:

[0479] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[0480] Step 12:

[0481] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[0482] Step 13:

[0483] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[0484] Example 1

[0485] 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."

[0486] In conventional systems, it has been difficult for users to search for, easily install, and use artificial intelligence (AI) applications. It has also been cumbersome for users to manage installed applications. Due to these issues, there is a demand for improved user convenience and efficiency.

[0487] 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.

[0488] In this invention, the server includes information processing means for managing an application database, information processing means for receiving requests from a user's terminal, information processing means for returning an application list to the user's terminal, information processing means for processing a user's request to install a specific application and updating user data, information processing means for obtaining a list of the user's installed applications and returning it to the user's terminal, information display means for allowing a user to access an application market from their terminal, select an application from the list, and request installation, information generation means for the server to generate a message indicating successful installation and return it to the terminal, information display means for the terminal to render the application list received from the server on the screen and display it to the user, and communication processing means for the terminal to send an HTTP request to the server to request a list of available applications. This enables users to easily search for, install, and use AI applications.

[0489] An "application database" is a collective data storage used to manage information about artificial intelligence applications.

[0490] "Information processing means" refers to a functional module that enables a computer system or server to perform specific data processing.

[0491] "User's device" refers to a computing device used by a user, such as a smartphone, tablet, or PC.

[0492] A "request" refers to an operation or the content of an operation in which a user requests specific information or service through a terminal.

[0493] An "application list" is a list of information about multiple artificial intelligence applications.

[0494] "User Data" means a data set containing identifying information and activity records relating to a user.

[0495] "Information display means" refers to a function or module that enables a terminal to display visual information to a user.

[0496] "Information generation means" refers to a function or module that allows the server to generate specific information and transmit that information to users or other systems.

[0497] "Communication processing means" refers to the function for performing data communication between the terminal and the server.

[0498] The present invention provides a system for assisting users in easily searching for, installing, and using artificial intelligence (AI) applications. Detailed embodiments are described below.

[0499] The server first manages the application database. Specifically, the server uses an Amazon Web Services (AWS) EC2 instance and the database uses Amazon RDS (Relational Database Service). The application data includes information such as the application ID, name, and description.

[0500] When a user accesses the application market using a terminal, the terminal sends an HTTP request to the server to request a list of available applications. This request is performed using the HTTP GET method.

[0501] The server receives this request, retrieves all application information from the application database, and returns it to the device as a structured response in JSON format. This process uses Node.js on the server side. The device renders the received JSON-formatted application list on the screen and provides it to the user as a selection. The processing on the device side is implemented using React (a front-end library).

[0502] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request uses the HTTP POST method, and the body contains the user ID and application ID.

[0503] The server receives the request and analyzes the user ID and application ID based on it. It checks the database to see if the user and application exist, and if they do, it adds the application ID to the user data and updates the database. Through this series of operations, the user data is changed using an UPDATE query. The server then generates a message indicating that the installation was successful and sends it back to the terminal.

[0504] The user will then receive a message on their device indicating successful installation, and will be able to use the selected application. If the user wishes to check the list of their installed applications, they can send a request to the server from their device. The server will retrieve the list of installed applications from the user database and send a response structured in JSON format back to the device. The device will then display this on the screen, allowing the user to check the currently installed applications.

[0505] As a concrete example, the process for a user to install an application named "Image Classification AI" is shown below.

[0506] 1. The user accesses the URL "https: / / ai-market.com".

[0507] 2. The device sends a request "GET / api / applications" to the server.

[0508] 3. The server retrieves the application information from the database and returns it in JSON format.

[0509] 4. The device parses this JSON data and displays an application called "Image Classification AI" on the screen.

[0510] 5. When the user clicks the install button for "Image Classification AI," the device sends a "POST / api / install" request to the server. The body contains { userId: "user1", appId: "app1"}.

[0511] 6. The server receives the request, updates the database, and adds "app1" to the user data.

[0512] 7. The server generates a message indicating that the installation was successful and returns it to the terminal.

[0513] 8. The device displays the message "Installation successful" to the user.

[0514] This series of processes allows users to easily install and use the AI ​​applications they need without any complicated work.

[0515] Example prompts to input to a generative AI model:

[0516] "Please explain in a way that the Generative AI model can understand how a user accesses the AI ​​App Market and installs a specific application. Please provide a detailed explanation of the entire process, with particular emphasis on submitting and processing the install request."

[0517] This system will improve user convenience by making it easier for users to intuitively search for, install, and use AI applications. It will also establish an appropriate reward system for developers, improving the quality and diversity of applications and contributing to the development of AI technology.

[0518] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0519] Step 1: User visits the App Market

[0520] Specific operation: The user opens the browser on their device and enters the URL of the AI ​​application market (e.g., https: / / ai-market.com) to access it.

[0521] Input: A user types a market URL into the browser's address bar.

[0522] Output: The terminal displays the initial Market screen.

[0523] Step 2: The device requests an application list from the server.

[0524] Specific operation: The device sends an HTTP GET request to the server to request a list of available applications.

[0525] Input: HTTP GET request sent by the device: "GET / api / applications"

[0526] Output: The server receives the request.

[0527] Step 3: The server retrieves all application information from the application database

[0528] What it does: The server queries the database to get application information and structures it in JSON format.

[0529] Input: HTTP GET request received by the server and application information from the database

[0530] Output: Application information structured in JSON format

[0531] Step 4: The server returns the application information to the device.

[0532] Specific operation: The server returns application information structured in JSON format to the terminal as an HTTP response.

[0533] Input: Application information in JSON format

[0534] Output: The HTTP response received by the device

[0535] Step 5: Display the list of applications retrieved by the device on the screen.

[0536] Specific operation: The device parses the received JSON data, renders the application list on the screen, and displays it to the user.

[0537] Input: JSON format application information received by the device

[0538] Output: Application list displayed on the device screen

[0539] Step 6: User selects specific application and submits installation request

[0540] Specific behavior: The user selects a specific application from the list and clicks the install button, which causes the device to send an HTTP POST request to the server.

[0541] Input: User selected application

[0542] Output: HTTP POST request "POST / api / install" sent by the device. The body contains the user ID and application ID.

[0543] Step 7: The server receives the install request and parses the user ID and application ID.

[0544] Specific operation: The server receives the installation request and analyzes the user ID and application ID in the request.

[0545] Input: HTTP POST request sent by the device

[0546] Output: Parsed user ID and application ID

[0547] Step 8: Server checks database for user and application existence

[0548] What happens: The server queries the database and verifies that the user ID and application ID exist.

[0549] Input: Parsed user ID and application ID

[0550] Output: User and application existence check results

[0551] Step 9: The server adds the application ID to the user data and updates the database

[0552] Specific operation: The server adds the application ID to the user data and updates the database.

[0553] Input: User data and verified application ID

[0554] Output: Updated user data

[0555] Step 10: The server sends a message back to the device confirming the installation was successful.

[0556] Specific operation: The server generates a message indicating that the installation was successful and sends it back to the terminal.

[0557] Input: Updated user data

[0558] Output: Installation successful message

[0559] Step 11: The terminal displays a successful installation message to the user

[0560] Specific operation: The device displays the installation success message to the user.

[0561] Input: Installation success message received from the server

[0562] Output: A successful installation message that is displayed to the user.

[0563] (Application example 1)

[0564] 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."

[0565] Modern consumers are trying to live comfortable lives by utilizing a wide variety of AI applications, but searching for and installing the appropriate applications from the vast number of available ones requires a great deal of effort and time. Online shopping sites, in particular, are required to quickly and accurately predict and recommend the product categories consumers desire, but current systems do not adequately meet this need. Therefore, there is a need for a system that allows consumers to easily search for and install the AI ​​applications they need, and also has the ability to predict and recommend product categories.

[0566] 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.

[0567] In this invention, the server includes means for managing an application database, means for receiving requests from a user's terminal, means for returning an application list to the user's terminal, means for processing a user's request to install a specific application and updating user data, means for obtaining a list of the user's installed applications and returning it to the user's terminal, and means for including a generative AI model that predicts and recommends product categories searched for by the user. This enables users to easily search for and install the AI ​​applications they need, and enables the prediction and recommendation of appropriate product categories on online shopping sites.

[0568] An "application database" is a database that holds information about available applications managed within the system.

[0569] "Server means" refers to the functions and devices of a server that manages an application database, receives and processes requests from users, and returns responses.

[0570] A "user device" is an electronic device used by a user to discover, install, and use applications.

[0571] A "request" is request data sent from a user's terminal to a server.

[0572] An "application list" is a list of available applications that is returned from the server to the user's terminal.

[0573] An "installation request" is a request made by a user to install a particular application on a terminal in order to use the application.

[0574] "User Data" is data in a database that contains user-specific information.

[0575] A "generative AI model" is a type of artificial intelligence that uses machine learning algorithms to perform a specific task, such as predicting product categories.

[0576] A "prompt" is input text that gives specific instructions to an AI.

[0577] The present invention relates to a system that enables users to easily search for, install, and use AI applications. Specific embodiments of the system are described below.

[0578] The server first manages an application database, which stores information about available applications. Application data includes the application's ID, name, description, etc.

[0579] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0580] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0581] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0582] Furthermore, this invention uses a generative AI model to predict and recommend the product category a user is searching for. Specifically, when a user accesses the application market or searches for a specific product category, the generative AI model analyzes product images and text data to predict and recommend the appropriate category. This function allows users to intuitively find the applications and products they need.

[0583] The hardware used includes smartphones and servers (virtual or physical), and the software used includes Flask, which is used to create API endpoints on the server side, requests, which is used to make HTTP requests, and the JSON format, which is used to structure and parse the data.

[0584] As a concrete example, consider the process in which a user installs an application called "Image Classification AI" and uses that AI to predict product categories on an online shopping website. The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request is sent from the device to the server stating, "User 1 installs App 1." The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user data, and returns a message to the device indicating successful installation.

[0585] An example of a prompt is as follows:

[0586] "Predict the product category from this image."

[0587] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0588] Step 1:

[0589] A user accesses the application market from a smartphone device.

[0590] Input: User action (access to the market).

[0591] Output: The request is sent to the server.

[0592] Specific operation: The user taps the application market icon on the smartphone, launching the market app, which then sends a GET request to the server.

[0593] Step 2:

[0594] The server generates an application list in JSON format and returns it to the device.

[0595] Input: A request from the user's terminal.

[0596] Output: A list of applications in JSON format.

[0597] Specific operation: The server accesses the application database to obtain all available application information, structures the obtained information in JSON format, and returns it to the user device.

[0598] Step 3:

[0599] The terminal displays the received application list on the user interface.

[0600] Input: A list of applications in JSON format.

[0601] Output: The application list displayed on the screen.

[0602] Specific operation: The device parses the JSON data received from the server and visually displays the application list in the user interface.

[0603] Step 4:

[0604] The user selects a particular application and submits an installation request.

[0605] Input: User's choice (Application ID).

[0606] Output: The installation request sent to the server.

[0607] Specific operation: The user taps the application they want to install, and the device sends a POST request to the server containing the application ID and the user ID.

[0608] Step 5:

[0609] The server receives the installation request and parses and verifies the user ID and application ID.

[0610] Input: The user ID and application ID in the install request.

[0611] Output: User database updated and installation successful message.

[0612] Specific operation: The server accesses the database and checks the existence of the user ID and application ID. After checking, it adds the application ID to the user data and generates a message indicating successful installation and returns it to the user device.

[0613] Step 6:

[0614] The user submits a request to see a list of installed applications.

[0615] Input: User action (submitting a confirmation request).

[0616] Output: A confirmation request sent to the server.

[0617] Specific operation: The user taps the confirmation button, and the device sends a GET request to the server.

[0618] Step 7:

[0619] The server obtains a list of the user's installed applications and returns it to the device in JSON format.

[0620] Input: User confirmation request.

[0621] Output: A list of installed applications in JSON format.

[0622] Specific operation: The server retrieves information about installed applications from the user database, structures it in JSON format, and sends it back to the user's device.

[0623] Step 8:

[0624] The terminal displays the acquired list of installed applications on a user interface.

[0625] Input: A list of installed applications in JSON format.

[0626] Output: A list of installed applications displayed on the screen.

[0627] Specific operation: The device parses the received JSON data and visually displays a list of installed applications in the user interface.

[0628] Step 9:

[0629] The user enters a prompt sentence to predict the product category using the generative AI model.

[0630] Input: The prompt text entered by the user.

[0631] Output: A request to the generative AI model.

[0632] Specific operation: The user enters the prompt "Please predict the product category from this image" into the input field of the device and taps the send button. The device then sends the prompt and the product image to the generative AI model.

[0633] Step 10:

[0634] The generative AI model predicts the product category and returns the prediction results to the terminal.

[0635] Input: Prompt text and product image.

[0636] Output: Product category prediction results.

[0637] Specific operation: The generative AI model analyzes the prompt text and product image to predict the product category, and returns the prediction result to the user's device.

[0638] Step 11:

[0639] The product category prediction result received by the terminal is displayed on a user interface.

[0640] Input: Product category prediction results.

[0641] Output: Product category prediction results displayed on the screen.

[0642] Specific operation: The device analyzes the prediction results received and displays them on the user interface.

[0643] 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.

[0644] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, and also provides a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[0645] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[0646] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0647] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect information such as the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time.

[0648] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0649] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[0650] The system also has the ability to recommend applications suitable for users based on their emotional data. For example, if the emotion engine detects that a user is stressed, it can recommend applications that help with relaxation. This recommendation function allows users to easily find the application that best suits their condition.

[0651] Furthermore, to check the applications installed by the user, the device can send a request to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0652] As described above, this system allows users to intuitively search for, install, and use AI applications, and also has the ability to recognize users' emotions in real time and recommend optimal applications based on that data, improving the user experience and promoting the use of AI applications.

[0653] The processing flow will be explained below.

[0654] Step 1:

[0655] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[0656] Step 2:

[0657] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[0658] Step 3:

[0659] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[0660] Step 4:

[0661] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[0662] Step 5:

[0663] The user's device uses an emotion engine to collect data from cameras, microphones, etc. to recognize the user's emotions. The device sends the collected data to the emotion engine, which then analyzes the emotions.

[0664] Step 6:

[0665] The emotion engine analyzes the user's emotions and sends the results to the server, which receives the emotion data and determines which applications to recommend based on the user's emotional state.

[0666] Step 7:

[0667] The server structures a list of suitable applications in JSON format based on the user's emotional state, and then sends the structured list of recommendations back to the device as an HTTP response.

[0668] Step 8:

[0669] The device analyzes the recommendation list received from the server and displays it on the screen. The user can then review the recommended applications and select them as needed.

[0670] Step 9:

[0671] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[0672] Step 10:

[0673] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[0674] Step 11:

[0675] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[0676] Step 12:

[0677] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[0678] Step 13:

[0679] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[0680] Step 14:

[0681] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[0682] Step 15:

[0683] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[0684] Step 16:

[0685] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[0686] Step 17:

[0687] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[0688] Example 2

[0689] 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."

[0690] Conventional systems require users to go through complicated procedures when installing AI applications, resulting in a poor user experience. Furthermore, the lack of a function to recommend appropriate applications based on user sentiment makes it difficult for users to find the application that best suits them. This does not promote the use of AI applications and reduces convenience for users.

[0691] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0692] In this invention, the server includes computer system means for managing an application database, computer system means for receiving requests from a user's computer device, computer system means for returning an application list to the user's computer device, computer system means for processing a user's request to install a specific application and updating user information, computer system means for obtaining the user's installed application list and returning it to the user's computer device, and emotion analysis means for recognizing the user's emotions and recommending appropriate applications based on that data. This allows users to intuitively and easily search for, install, and use AI applications, and further improves convenience by recommending optimal applications based on the user's emotions.

[0693] An "application database" is a database that manages information about multiple applications available to users.

[0694] "Computer system means" refers to the software and hardware running on a server or user's computing device that is used to provide a particular function or service.

[0695] A "request" refers to a request made from a user's computing device to a server, and includes operations such as retrieving or updating data.

[0696] A "structured language format" is a description format for representing data in an organized and consistent manner, and examples include JSON and XML.

[0697] "User information" refers to data about users managed within the system, including information such as user IDs and installed applications.

[0698] An "emotion analysis means" is a mechanism that recognizes emotions by analyzing data such as the user's facial expressions and voice, and recommends appropriate applications based on the results.

[0699] "User's computing device" refers to the electronic device used by the user to access the system, including smartphones, tablets, and personal computers.

[0700] MODE FOR CARRYING OUT THE INVENTION

[0701] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, as well as a system that combines an emotion engine that recognizes the user's emotions.

[0702] Configuration and Hardware / Software Used

[0703] The server provides the core functionality of the system using the following hardware and software:

[0704] Hardware: High-performance server machine

[0705] Software: Apache HTTP Server, MySQL database, Python (backend)

[0706] A terminal is a computing device used by a user (e.g., a smartphone) that has the following components:

[0707] Hardware: Smartphone (iOS or Android)

[0708] Software: Dedicated application (front end), sensors such as cameras and microphones

[0709] The emotion engine is a component for recognizing user emotions in real time, using:

[0710] Software: Python, OpenCV, Google Cloud Speech-to-Text API, deep learning framework (e.g., TensorFlow or PyTorch)

[0711] Program processing

[0712] The server manages an application database that contains information about available applications, such as application IDs, names, and descriptions.

[0713] When a user accesses the AI ​​application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns it to the device in a structured language (JSON) format. The device then displays the received application list on the screen and allows the user to make a selection.

[0714] When a user wants to install a specific application (e.g., "Image Classification AI"), they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database. If the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database. The server then sends a message back to the device indicating that the installation was successful.

[0715] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time. If the emotion engine detects that the user is stressed, it can recommend applications that will help with relaxation.

[0716] Furthermore, the user can check their installed applications by sending a request from the device to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0717] Specific examples

[0718] For example, consider the process of a user installing an application named "Image Classification AI." The user accesses the market, retrieves the application list, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user information, and returns a message to the device indicating successful installation.

[0719] This series of processes allows users to easily install and use the necessary applications without having to go through complicated procedures.

[0720] Prompt Sentence Examples

[0721] "User 1 sends a request to the server to install app 1. The server checks the user database and application database for the existence of user 1 and app 1, and adds app 1's information to the user information. The server then sends a message that the installation was successful."

[0722] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0723] Step 1:

[0724] The user accesses the AI ​​application market from their device.

[0725] Input: None

[0726] Output: None

[0727] Specific operation: The user launches the "AI App Market" app on their smartphone.

[0728] Step 2:

[0729] The terminal sends a request to the server for a list of currently available applications.

[0730] Input: User access request

[0731] Output: HTTP request to the server

[0732] Specific operation: The device sends an HTTP request to the server in the format "GET / api / applications".

[0733] Step 3:

[0734] The server retrieves all application information from the application database.

[0735] Input: Request from terminal

[0736] Output: Application information

[0737] Specific operation: The server executes the MySQL query "SELECT FROM applications" to retrieve the data.

[0738] Step 4:

[0739] The server converts the acquired application information into a structured language (JSON) format and returns it to the terminal.

[0740] Input: Application Information

[0741] Output: HTTP response to the terminal (JSON format)

[0742] Specific operation: The server uses a Python library to convert the data into JSON format and returns it as an HTTP response.

[0743] Step 5:

[0744] The terminal displays the received application list on the screen and provides the user with a selection.

[0745] Input: Application list from the server (JSON format)

[0746] Output: Application list displayed on screen

[0747] Specific behavior: The device's app UI displays the application name and description in a list format.

[0748] Step 6:

[0749] The user selects the application they wish to install and clicks the install icon.

[0750] Input: Application list displayed on the screen

[0751] Output: Clicking the installation icon

[0752] Specific operation: The user selects "Image Classification AI" and clicks the install button.

[0753] Step 7:

[0754] The device sends a request to the server to install a specific application, which includes the user ID and the application ID.

[0755] Input: User ID, Application ID

[0756] Output: HTTP POST request to the server

[0757] Specific operation: The device sends an HTTP POST request "POST / api / install" and includes the user ID and application ID in the request body.

[0758] Step 8:

[0759] The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database.

[0760] Input: Installation request (user ID, application ID)

[0761] Output: User and application records retrieved from the database

[0762] Specific operation: The server executes the MySQL queries "SELECT FROM users WHERE id="user ID"" and "SELECT FROM applications WHERE id="application ID"".

[0763] Step 9:

[0764] After the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database.

[0765] Input: User and application records

[0766] Output: Updated user information

[0767] Specific operation: The server executes the MySQL query "INSERT INTO user_apps (user_id, app_id) VALUES ('user ID', 'application ID')".

[0768] Step 10:

[0769] The server will return a message to the terminal indicating that the installation was successful.

[0770] Input: Updated user information

[0771] Output: Installation successful message (JSON format)

[0772] Specific operation: The server returns an "Installation successful" message in JSON format in the HTTP response.

[0773] Step 11:

[0774] The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice.

[0775] Input: User's facial expression, tone of voice

[0776] Output: Collected emotion data

[0777] Specific operation: The device activates the camera to capture the user's face and collects audio data using the microphone.

[0778] Step 12:

[0779] The device sends the collected data to the emotion engine.

[0780] Input: Collected emotion data

[0781] Output: Input data to the emotion engine

[0782] Specific operation: Camera image data is analyzed using the OpenCV library, and audio data is processed using the Google Cloud Speech-to-Text API.

[0783] Step 13:

[0784] The emotion engine analyzes the user's emotions and recommends appropriate applications.

[0785] Input: Parsed emotion data

[0786] Output: A list of recommended applications

[0787] How it works: The emotion engine uses deep learning models (TensorFlow and PyTorch) to recognize emotions and recommends relaxation apps when stress is detected.

[0788] Step 14:

[0789] A user sends a request from the terminal to the server to check the installed applications.

[0790] Input: User verification request

[0791] Output: HTTP request to the server

[0792] What happens: The user accesses the "My Apps" section of their device.

[0793] Step 15:

[0794] The server retrieves a list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format.

[0795] Input: User request

[0796] Output: List of installed applications (JSON format)

[0797] Specific operation: The server executes the MySQL query "SELECT FROM user_apps WHERE user_id='User ID'" and returns the results in JSON format.

[0798] Step 16:

[0799] The terminal displays the acquired information and allows the user to check the currently installed applications.

[0800] Input: JSON response from the server

[0801] Output: A list of installed applications displayed on the screen.

[0802] Specific behavior: The device's app UI displays a list of installed applications.

[0803] (Application example 2)

[0804] 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."

[0805] The process of searching, installing, and using existing AI applications is complicated and unintuitive for users. Furthermore, it does not recommend optimal applications based on the user's emotional state. Therefore, a more efficient and user-friendly system is needed. In particular, it is essential to manage applications suitable for automation robots in factories and to provide optimal recommendations based on real-time emotional analysis.

[0806] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0807] In this invention, the server includes a database server means for managing application data, a server means for receiving requests from a user terminal, a server means for returning an application list to the user terminal, a server means for processing a user's request to install a specific application and updating user data, a server means for acquiring a list of the user's installed applications and returning it to the user terminal, an emotion analysis engine means for recognizing the user's emotions, and a server means for recommending optimal applications based on the emotion analysis engine means. This allows users to intuitively search for, install, and use AI applications, and the recommendation of optimal applications based on emotional states can improve the operation of automated robots in factories, achieve predictive maintenance, parts management and supply, and increase efficiency.

[0808] "Database server means for managing application data" refers to a server that centrally manages information such as the ID, name, and description of various AI applications.

[0809] The "server means for receiving requests from user terminals" refers to a server that has the function of receiving requests that users send to the server from their own terminals.

[0810] "Server means for returning an application list to the user terminal" refers to the function of the server sending a list of AI applications to the user terminal in response to a user request.

[0811] The "server means for processing requests from users to install specific applications and updating user data" refers to a server that processes requests to install AI applications selected by users and updates user data.

[0812] The "server means for acquiring a list of applications already installed by the user and returning it to the user terminal" is a server having the function of acquiring a list of applications already installed and sending it to the user terminal.

[0813] The "emotion analysis engine means for recognizing the user's emotions" is an engine that uses sensors such as a camera and microphone to analyze the user's facial expressions and tone of voice, and recognizes emotions in real time.

[0814] The "server means for recommending the most suitable application based on the emotion analysis engine means" is a server having a function for recommending the most suitable AI application for the user's state based on the results of the user's emotion analysis.

[0815] To implement this invention, it is necessary to build a system that uses a database server that manages various application data, a server that receives requests from users, a server that processes lists and installation requests, an emotion analysis engine, and a server with recommendation functions.

[0816] Specifically, the server manages a database and stores information about available AI applications. Application data includes the application's ID, name, description, etc. When a user accesses the application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves the application information from the database, and returns it to the user's device in a structured data format. This allows the user to view a list of available applications on their device.

[0817] Furthermore, if a user wishes to install an application, the request will be sent to the server, which will analyze the user ID and application ID, check the database, update the user data if it exists, and return a message indicating successful installation to the device, allowing the user to smoothly install the AI ​​application.

[0818] The system also features an emotion analysis engine that recognizes the user's emotions. It uses a camera and microphone to collect the user's facial expressions and tone of voice, and analyzes their emotions in real time. Based on this emotion data, the server has the function of recommending the most appropriate AI application to the user. For example, if stress is detected from the user's emotion analysis, it can recommend a relaxation application. This function promotes the use of the most appropriate application tailored to the user's situation.

[0819] A specific example of application in factories is to introduce this system to automated robots working in factories. For example, if the emotion analysis engine detects stress from the tone of an operator's voice, a "predictive maintenance AI" can be installed to prevent the robot from breaking down.

[0820] An example prompt is, "User detected with high stress levels through voice analysis. Recommend installing preventive maintenance AI application to ensure smooth operation of factory robots."

[0821] In this way, this invention allows users to intuitively search for, install, and use AI applications, and by recommending optimal applications based on emotion analysis data, it is possible to improve the operation of automated robots in factories, perform predictive maintenance, manage and supply parts, and increase efficiency.

[0822] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0823] Step 1:

[0824] A user accesses the application market from a terminal. The input is the user's access request, and the terminal sends a request to the server to obtain an application list. The server receives this request. The output is the terminal receiving the request for the application list.

[0825] Step 2:

[0826] The server retrieves application information from the database. The input is the request received in step 1, and the server retrieves information such as application ID, name, description, etc. from the database. The output is the retrieved application list.

[0827] Step 3:

[0828] The server returns the acquired application information to the device in a structured data format (e.g., JSON format). The input is the data acquired in step 2, which the server converts into a structured data format. The output is a JSON-formatted application list that is sent to the device.

[0829] Step 4:

[0830] The terminal displays the received application list in the user interface. The input is the JSON-formatted data sent in step 3, and the terminal displays this to the user as a visually easy-to-read list. The output is the application list that the user views.

[0831] Step 5:

[0832] A user clicks a button to install a specific application. The input is the user's click, and the terminal sends an installation request to the server. The output is an installation request to the server.

[0833] Step 6:

[0834] The server parses the received installation request to obtain the user ID and application ID. The input is the request sent in step 5, which the server parses to extract the required IDs. The output is the parsed user ID and application ID.

[0835] Step 7:

[0836] The server checks the existence of the user ID and application ID in the database. The input is the ID obtained in step 6, and the server checks whether these IDs exist in the database. The output is the result of the existence check.

[0837] Step 8:

[0838] If the existence check is successful, the server adds the application ID to the user data and updates the database. The input is the check result from step 7, and the server updates the user data. The output is the updated database.

[0839] Step 9:

[0840] The server returns a message to the user terminal indicating that the installation was successful. The input is the data updated in step 8, and the server generates a message indicating that the installation was successful. The output is the success message sent to the user terminal.

[0841] Step 10:

[0842] The user's device uses an emotion analysis engine to analyze the user's emotional state. The input is data on the user's facial expressions and voice collected from a camera or microphone, which the device analyzes using the emotion analysis engine. The output is emotional data as the analysis result.

[0843] Step 11:

[0844] If the emotion analysis engine detects emotions such as stress or anxiety, the server will recommend the most appropriate application based on that. The input is the emotion data from step 10, and the server selects and recommends the most appropriate application from the database based on that data. The output is the recommendation result for the user.

[0845] Step 12:

[0846] The recommended applications are displayed on the user's device, and the user can install or use them as needed. The input is the recommendation result from step 11, which the device displays on the user interface. The output is the displayed recommendation result.

[0847] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating 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.

[0848] 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.

[0849] 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.

[0850] [Third embodiment]

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

[0852] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0853] 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).

[0854] 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.

[0855] 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.

[0856] 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).

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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."

[0863] The present invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications. Specific embodiments of the system are described below.

[0864] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[0865] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0866] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0867] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[0868] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0869] As described above, this system allows users to intuitively search for, install, and use AI applications. Furthermore, by establishing a mechanism for providing appropriate rewards to developers, the system will improve the quality and diversity of applications and contribute to the development of AI.

[0870] The processing flow will be explained below.

[0871] Step 1:

[0872] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[0873] Step 2:

[0874] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[0875] Step 3:

[0876] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[0877] Step 4:

[0878] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[0879] Step 5:

[0880] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[0881] Step 6:

[0882] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[0883] Step 7:

[0884] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[0885] Step 8:

[0886] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[0887] Step 9:

[0888] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[0889] Step 10:

[0890] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[0891] Step 11:

[0892] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[0893] Step 12:

[0894] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[0895] Step 13:

[0896] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[0897] Example 1

[0898] 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."

[0899] In conventional systems, it has been difficult for users to search for, easily install, and use artificial intelligence (AI) applications. It has also been cumbersome for users to manage installed applications. Due to these issues, there is a demand for improved user convenience and efficiency.

[0900] 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.

[0901] In this invention, the server includes information processing means for managing an application database, information processing means for receiving requests from a user's terminal, information processing means for returning an application list to the user's terminal, information processing means for processing a user's request to install a specific application and updating user data, information processing means for obtaining a list of the user's installed applications and returning it to the user's terminal, information display means for allowing a user to access an application market from their terminal, select an application from the list, and request installation, information generation means for the server to generate a message indicating successful installation and return it to the terminal, information display means for the terminal to render the application list received from the server on the screen and display it to the user, and communication processing means for the terminal to send an HTTP request to the server to request a list of available applications. This enables users to easily search for, install, and use AI applications.

[0902] An "application database" is a collective data storage used to manage information about artificial intelligence applications.

[0903] "Information processing means" refers to a functional module that enables a computer system or server to perform specific data processing.

[0904] "User's device" refers to a computing device used by a user, such as a smartphone, tablet, or PC.

[0905] A "request" refers to an operation or the content of an operation in which a user requests specific information or service through a terminal.

[0906] An "application list" is a list of information about multiple artificial intelligence applications.

[0907] "User Data" means a data set containing identifying information and activity records relating to a user.

[0908] "Information display means" refers to a function or module that enables a terminal to display visual information to a user.

[0909] "Information generation means" refers to a function or module that allows the server to generate specific information and transmit that information to users or other systems.

[0910] "Communication processing means" refers to the function for performing data communication between the terminal and the server.

[0911] The present invention provides a system for assisting users in easily searching for, installing, and using artificial intelligence (AI) applications. Detailed embodiments are described below.

[0912] The server first manages the application database. Specifically, the server uses an Amazon Web Services (AWS) EC2 instance and the database uses Amazon RDS (Relational Database Service). The application data includes information such as the application ID, name, and description.

[0913] When a user accesses the application market using a terminal, the terminal sends an HTTP request to the server to request a list of available applications. This request is performed using the HTTP GET method.

[0914] The server receives this request, retrieves all application information from the application database, and returns it to the device as a structured response in JSON format. This process uses Node.js on the server side. The device renders the received JSON-formatted application list on the screen and provides it to the user as a selection. The processing on the device side is implemented using React (a front-end library).

[0915] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request uses the HTTP POST method, and the body contains the user ID and application ID.

[0916] The server receives the request and analyzes the user ID and application ID based on it. It checks the database to see if the user and application exist, and if they do, it adds the application ID to the user data and updates the database. Through this series of operations, the user data is changed using an UPDATE query. The server then generates a message indicating that the installation was successful and sends it back to the terminal.

[0917] The user will then receive a message on their device indicating successful installation, and will be able to use the selected application. If the user wishes to check the list of their installed applications, they can send a request to the server from their device. The server will retrieve the list of installed applications from the user database and send a response structured in JSON format back to the device. The device will then display this on the screen, allowing the user to check the currently installed applications.

[0918] As a concrete example, the process for a user to install an application named "Image Classification AI" is shown below.

[0919] 1. The user accesses the URL "https: / / ai-market.com".

[0920] 2. The device sends a request "GET / api / applications" to the server.

[0921] 3. The server retrieves the application information from the database and returns it in JSON format.

[0922] 4. The device parses this JSON data and displays an application called "Image Classification AI" on the screen.

[0923] 5. When the user clicks the install button for "Image Classification AI," the device sends a "POST / api / install" request to the server. The body contains { userId: "user1", appId: "app1"}.

[0924] 6. The server receives the request, updates the database, and adds "app1" to the user data.

[0925] 7. The server generates a message indicating that the installation was successful and returns it to the terminal.

[0926] 8. The device displays the message "Installation successful" to the user.

[0927] This series of processes allows users to easily install and use the AI ​​applications they need without any complicated work.

[0928] Example prompts to input to a generative AI model:

[0929] "Please explain in a way that the Generative AI model can understand how a user accesses the AI ​​App Market and installs a specific application. Please provide a detailed explanation of the entire process, with particular emphasis on submitting and processing the install request."

[0930] This system will improve user convenience by making it easier for users to intuitively search for, install, and use AI applications. It will also establish an appropriate reward system for developers, improving the quality and diversity of applications and contributing to the development of AI technology.

[0931] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0932] Step 1: User visits the App Market

[0933] Specific operation: The user opens the browser on their device and enters the URL of the AI ​​application market (e.g., https: / / ai-market.com) to access it.

[0934] Input: A user types a market URL into the browser's address bar.

[0935] Output: The terminal displays the initial Market screen.

[0936] Step 2: The device requests an application list from the server.

[0937] Specific operation: The device sends an HTTP GET request to the server to request a list of available applications.

[0938] Input: HTTP GET request sent by the device: "GET / api / applications"

[0939] Output: The server receives the request.

[0940] Step 3: The server retrieves all application information from the application database

[0941] What it does: The server queries the database to get application information and structures it in JSON format.

[0942] Input: HTTP GET request received by the server and application information from the database

[0943] Output: Application information structured in JSON format

[0944] Step 4: The server returns the application information to the device.

[0945] Specific operation: The server returns application information structured in JSON format to the terminal as an HTTP response.

[0946] Input: Application information in JSON format

[0947] Output: The HTTP response received by the device

[0948] Step 5: Display the list of applications retrieved by the device on the screen.

[0949] Specific operation: The device parses the received JSON data, renders the application list on the screen, and displays it to the user.

[0950] Input: JSON format application information received by the device

[0951] Output: Application list displayed on the device screen

[0952] Step 6: User selects specific application and submits installation request

[0953] Specific behavior: The user selects a specific application from the list and clicks the install button, which causes the device to send an HTTP POST request to the server.

[0954] Input: User selected application

[0955] Output: HTTP POST request "POST / api / install" sent by the device. The body contains the user ID and application ID.

[0956] Step 7: The server receives the install request and parses the user ID and application ID.

[0957] Specific operation: The server receives the installation request and analyzes the user ID and application ID in the request.

[0958] Input: HTTP POST request sent by the device

[0959] Output: Parsed user ID and application ID

[0960] Step 8: Server checks database for user and application existence

[0961] What happens: The server queries the database and verifies that the user ID and application ID exist.

[0962] Input: Parsed user ID and application ID

[0963] Output: User and application existence check results

[0964] Step 9: The server adds the application ID to the user data and updates the database

[0965] Specific operation: The server adds the application ID to the user data and updates the database.

[0966] Input: User data and verified application ID

[0967] Output: Updated user data

[0968] Step 10: The server sends a message back to the device confirming the installation was successful.

[0969] Specific operation: The server generates a message indicating that the installation was successful and sends it back to the terminal.

[0970] Input: Updated user data

[0971] Output: Installation successful message

[0972] Step 11: The terminal displays a successful installation message to the user

[0973] Specific operation: The device displays the installation success message to the user.

[0974] Input: Installation success message received from the server

[0975] Output: A successful installation message that is displayed to the user.

[0976] (Application example 1)

[0977] 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."

[0978] Modern consumers are trying to live comfortable lives by utilizing a wide variety of AI applications, but searching for and installing the appropriate applications from the vast number of available ones requires a great deal of effort and time. Online shopping sites, in particular, are required to quickly and accurately predict and recommend the product categories consumers desire, but current systems do not adequately meet this need. Therefore, there is a need for a system that allows consumers to easily search for and install the AI ​​applications they need, and also has the ability to predict and recommend product categories.

[0979] 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.

[0980] In this invention, the server includes means for managing an application database, means for receiving requests from a user's terminal, means for returning an application list to the user's terminal, means for processing a user's request to install a specific application and updating user data, means for obtaining a list of the user's installed applications and returning it to the user's terminal, and means for including a generative AI model that predicts and recommends product categories searched for by the user. This enables users to easily search for and install the AI ​​applications they need, and enables the prediction and recommendation of appropriate product categories on online shopping sites.

[0981] An "application database" is a database that holds information about available applications managed within the system.

[0982] "Server means" refers to the functions and devices of a server that manages an application database, receives and processes requests from users, and returns responses.

[0983] A "user device" is an electronic device used by a user to discover, install, and use applications.

[0984] A "request" is request data sent from a user's terminal to a server.

[0985] An "application list" is a list of available applications that is returned from the server to the user's terminal.

[0986] An "installation request" is a request made by a user to install a particular application on a terminal in order to use the application.

[0987] "User Data" is data in a database that contains user-specific information.

[0988] A "generative AI model" is a type of artificial intelligence that uses machine learning algorithms to perform a specific task, such as predicting product categories.

[0989] A "prompt" is input text that gives specific instructions to an AI.

[0990] The present invention relates to a system that enables users to easily search for, install, and use AI applications. Specific embodiments of the system are described below.

[0991] The server first manages an application database, which stores information about available applications. Application data includes the application's ID, name, description, etc.

[0992] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[0993] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[0994] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[0995] Furthermore, this invention uses a generative AI model to predict and recommend the product category a user is searching for. Specifically, when a user accesses the application market or searches for a specific product category, the generative AI model analyzes product images and text data to predict and recommend the appropriate category. This function allows users to intuitively find the applications and products they need.

[0996] The hardware used includes smartphones and servers (virtual or physical), and the software used includes Flask, which is used to create API endpoints on the server side, requests, which is used to make HTTP requests, and the JSON format, which is used to structure and parse the data.

[0997] As a concrete example, consider the process in which a user installs an application called "Image Classification AI" and uses that AI to predict product categories on an online shopping website. The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request is sent from the device to the server stating, "User 1 installs App 1." The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user data, and returns a message to the device indicating successful installation.

[0998] An example of a prompt is as follows:

[0999] "Predict the product category from this image."

[1000] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1001] Step 1:

[1002] A user accesses the application market from a smartphone device.

[1003] Input: User action (access to the market).

[1004] Output: The request is sent to the server.

[1005] Specific operation: The user taps the application market icon on the smartphone, launching the market app, which then sends a GET request to the server.

[1006] Step 2:

[1007] The server generates an application list in JSON format and returns it to the device.

[1008] Input: A request from the user's terminal.

[1009] Output: A list of applications in JSON format.

[1010] Specific operation: The server accesses the application database to obtain all available application information, structures the obtained information in JSON format, and returns it to the user device.

[1011] Step 3:

[1012] The terminal displays the received application list on the user interface.

[1013] Input: A list of applications in JSON format.

[1014] Output: The application list displayed on the screen.

[1015] Specific operation: The device parses the JSON data received from the server and visually displays the application list in the user interface.

[1016] Step 4:

[1017] The user selects a particular application and submits an installation request.

[1018] Input: User's choice (Application ID).

[1019] Output: The installation request sent to the server.

[1020] Specific operation: The user taps the application they want to install, and the device sends a POST request to the server containing the application ID and the user ID.

[1021] Step 5:

[1022] The server receives the installation request and parses and verifies the user ID and application ID.

[1023] Input: The user ID and application ID in the install request.

[1024] Output: User database updated and installation successful message.

[1025] Specific operation: The server accesses the database and checks the existence of the user ID and application ID. After checking, it adds the application ID to the user data and generates a message indicating successful installation and returns it to the user device.

[1026] Step 6:

[1027] The user submits a request to see a list of installed applications.

[1028] Input: User action (submitting a confirmation request).

[1029] Output: A confirmation request sent to the server.

[1030] Specific operation: The user taps the confirmation button, and the device sends a GET request to the server.

[1031] Step 7:

[1032] The server obtains a list of the user's installed applications and returns it to the device in JSON format.

[1033] Input: User confirmation request.

[1034] Output: A list of installed applications in JSON format.

[1035] Specific operation: The server retrieves information about installed applications from the user database, structures it in JSON format, and sends it back to the user's device.

[1036] Step 8:

[1037] The terminal displays the acquired list of installed applications on a user interface.

[1038] Input: A list of installed applications in JSON format.

[1039] Output: A list of installed applications displayed on the screen.

[1040] Specific operation: The device parses the received JSON data and visually displays a list of installed applications in the user interface.

[1041] Step 9:

[1042] The user enters a prompt sentence to predict the product category using the generative AI model.

[1043] Input: The prompt text entered by the user.

[1044] Output: A request to the generative AI model.

[1045] Specific operation: The user enters the prompt "Please predict the product category from this image" into the input field of the device and taps the send button. The device then sends the prompt and the product image to the generative AI model.

[1046] Step 10:

[1047] The generative AI model predicts the product category and returns the prediction results to the terminal.

[1048] Input: Prompt text and product image.

[1049] Output: Product category prediction results.

[1050] Specific operation: The generative AI model analyzes the prompt text and product image to predict the product category, and returns the prediction result to the user's device.

[1051] Step 11:

[1052] The product category prediction result received by the terminal is displayed on a user interface.

[1053] Input: Product category prediction results.

[1054] Output: Product category prediction results displayed on the screen.

[1055] Specific operation: The device analyzes the prediction results received and displays them on the user interface.

[1056] 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.

[1057] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, and also provides a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[1058] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[1059] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[1060] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect information such as the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time.

[1061] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[1062] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[1063] The system also has the ability to recommend applications suitable for users based on their emotional data. For example, if the emotion engine detects that a user is stressed, it can recommend applications that help with relaxation. This recommendation function allows users to easily find the application that best suits their condition.

[1064] Furthermore, to check the applications installed by the user, the device can send a request to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1065] As described above, this system allows users to intuitively search for, install, and use AI applications, and also has the ability to recognize users' emotions in real time and recommend optimal applications based on that data, improving the user experience and promoting the use of AI applications.

[1066] The processing flow will be explained below.

[1067] Step 1:

[1068] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[1069] Step 2:

[1070] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[1071] Step 3:

[1072] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[1073] Step 4:

[1074] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[1075] Step 5:

[1076] The user's device uses an emotion engine to collect data from cameras, microphones, etc. to recognize the user's emotions. The device sends the collected data to the emotion engine, which then analyzes the emotions.

[1077] Step 6:

[1078] The emotion engine analyzes the user's emotions and sends the results to the server, which receives the emotion data and determines which applications to recommend based on the user's emotional state.

[1079] Step 7:

[1080] The server structures a list of suitable applications in JSON format based on the user's emotional state, and then sends the structured list of recommendations back to the device as an HTTP response.

[1081] Step 8:

[1082] The device analyzes the recommendation list received from the server and displays it on the screen. The user can then review the recommended applications and select them as needed.

[1083] Step 9:

[1084] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[1085] Step 10:

[1086] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[1087] Step 11:

[1088] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[1089] Step 12:

[1090] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[1091] Step 13:

[1092] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[1093] Step 14:

[1094] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[1095] Step 15:

[1096] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[1097] Step 16:

[1098] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[1099] Step 17:

[1100] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[1101] Example 2

[1102] 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."

[1103] Conventional systems require users to go through complicated procedures when installing AI applications, resulting in a poor user experience. Furthermore, the lack of a function to recommend appropriate applications based on user sentiment makes it difficult for users to find the application that best suits them. This does not promote the use of AI applications and reduces convenience for users.

[1104] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1105] In this invention, the server includes computer system means for managing an application database, computer system means for receiving requests from a user's computer device, computer system means for returning an application list to the user's computer device, computer system means for processing a user's request to install a specific application and updating user information, computer system means for obtaining the user's installed application list and returning it to the user's computer device, and emotion analysis means for recognizing the user's emotions and recommending appropriate applications based on that data. This allows users to intuitively and easily search for, install, and use AI applications, and further improves convenience by recommending optimal applications based on the user's emotions.

[1106] An "application database" is a database that manages information about multiple applications available to users.

[1107] "Computer system means" refers to the software and hardware running on a server or user's computing device that is used to provide a particular function or service.

[1108] A "request" refers to a request made from a user's computing device to a server, and includes operations such as retrieving or updating data.

[1109] A "structured language format" is a description format for representing data in an organized and consistent manner, and examples include JSON and XML.

[1110] "User information" refers to data about users managed within the system, including information such as user IDs and installed applications.

[1111] An "emotion analysis means" is a mechanism that recognizes emotions by analyzing data such as the user's facial expressions and voice, and recommends appropriate applications based on the results.

[1112] "User's computing device" refers to the electronic device used by the user to access the system, including smartphones, tablets, and personal computers.

[1113] MODE FOR CARRYING OUT THE INVENTION

[1114] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, as well as a system that combines an emotion engine that recognizes the user's emotions.

[1115] Configuration and Hardware / Software Used

[1116] The server provides the core functionality of the system using the following hardware and software:

[1117] Hardware: High-performance server machine

[1118] Software: Apache HTTP Server, MySQL database, Python (backend)

[1119] A terminal is a computing device used by a user (e.g., a smartphone) that has the following components:

[1120] Hardware: Smartphone (iOS or Android)

[1121] Software: Dedicated application (front end), sensors such as cameras and microphones

[1122] The emotion engine is a component for recognizing user emotions in real time, using:

[1123] Software: Python, OpenCV, Google Cloud Speech-to-Text API, deep learning framework (e.g., TensorFlow or PyTorch)

[1124] Program processing

[1125] The server manages an application database that contains information about available applications, such as application IDs, names, and descriptions.

[1126] When a user accesses the AI ​​application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns it to the device in a structured language (JSON) format. The device then displays the received application list on the screen and allows the user to make a selection.

[1127] When a user wants to install a specific application (e.g., "Image Classification AI"), they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database. If the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database. The server then sends a message back to the device indicating that the installation was successful.

[1128] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time. If the emotion engine detects that the user is stressed, it can recommend applications that will help with relaxation.

[1129] Furthermore, the user can check their installed applications by sending a request from the device to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1130] Specific examples

[1131] For example, consider the process of a user installing an application named "Image Classification AI." The user accesses the market, retrieves the application list, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user information, and returns a message to the device indicating successful installation.

[1132] This series of processes allows users to easily install and use the necessary applications without having to go through complicated procedures.

[1133] Prompt Sentence Examples

[1134] "User 1 sends a request to the server to install app 1. The server checks the user database and application database for the existence of user 1 and app 1, and adds app 1's information to the user information. The server then sends a message that the installation was successful."

[1135] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1136] Step 1:

[1137] The user accesses the AI ​​application market from their device.

[1138] Input: None

[1139] Output: None

[1140] Specific operation: The user launches the "AI App Market" app on their smartphone.

[1141] Step 2:

[1142] The terminal sends a request to the server for a list of currently available applications.

[1143] Input: User access request

[1144] Output: HTTP request to the server

[1145] Specific operation: The device sends an HTTP request to the server in the format "GET / api / applications".

[1146] Step 3:

[1147] The server retrieves all application information from the application database.

[1148] Input: Request from terminal

[1149] Output: Application information

[1150] Specific operation: The server executes the MySQL query "SELECT FROM applications" to retrieve the data.

[1151] Step 4:

[1152] The server converts the acquired application information into a structured language (JSON) format and returns it to the terminal.

[1153] Input: Application Information

[1154] Output: HTTP response to the terminal (JSON format)

[1155] Specific operation: The server uses a Python library to convert the data into JSON format and returns it as an HTTP response.

[1156] Step 5:

[1157] The terminal displays the received application list on the screen and provides the user with a selection.

[1158] Input: Application list from the server (JSON format)

[1159] Output: Application list displayed on screen

[1160] Specific behavior: The device's app UI displays the application name and description in a list format.

[1161] Step 6:

[1162] The user selects the application they wish to install and clicks the install icon.

[1163] Input: Application list displayed on the screen

[1164] Output: Clicking the installation icon

[1165] Specific operation: The user selects "Image Classification AI" and clicks the install button.

[1166] Step 7:

[1167] The device sends a request to the server to install a specific application, which includes the user ID and the application ID.

[1168] Input: User ID, Application ID

[1169] Output: HTTP POST request to the server

[1170] Specific operation: The device sends an HTTP POST request "POST / api / install" and includes the user ID and application ID in the request body.

[1171] Step 8:

[1172] The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database.

[1173] Input: Installation request (user ID, application ID)

[1174] Output: User and application records retrieved from the database

[1175] Specific operation: The server executes the MySQL queries "SELECT FROM users WHERE id="user ID"" and "SELECT FROM applications WHERE id="application ID"".

[1176] Step 9:

[1177] After the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database.

[1178] Input: User and application records

[1179] Output: Updated user information

[1180] Specific operation: The server executes the MySQL query "INSERT INTO user_apps (user_id, app_id) VALUES ('user ID', 'application ID')".

[1181] Step 10:

[1182] The server will return a message to the terminal indicating that the installation was successful.

[1183] Input: Updated user information

[1184] Output: Installation successful message (JSON format)

[1185] Specific operation: The server returns an "Installation successful" message in JSON format in the HTTP response.

[1186] Step 11:

[1187] The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice.

[1188] Input: User's facial expression, tone of voice

[1189] Output: Collected emotion data

[1190] Specific operation: The device activates the camera to capture the user's face and collects audio data using the microphone.

[1191] Step 12:

[1192] The device sends the collected data to the emotion engine.

[1193] Input: Collected emotion data

[1194] Output: Input data to the emotion engine

[1195] Specific operation: Camera image data is analyzed using the OpenCV library, and audio data is processed using the Google Cloud Speech-to-Text API.

[1196] Step 13:

[1197] The emotion engine analyzes the user's emotions and recommends appropriate applications.

[1198] Input: Parsed emotion data

[1199] Output: A list of recommended applications

[1200] How it works: The emotion engine uses deep learning models (TensorFlow and PyTorch) to recognize emotions and recommends relaxation apps when stress is detected.

[1201] Step 14:

[1202] A user sends a request from the terminal to the server to check the installed applications.

[1203] Input: User verification request

[1204] Output: HTTP request to the server

[1205] What happens: The user accesses the "My Apps" section of their device.

[1206] Step 15:

[1207] The server retrieves a list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format.

[1208] Input: User request

[1209] Output: List of installed applications (JSON format)

[1210] Specific operation: The server executes the MySQL query "SELECT FROM user_apps WHERE user_id='User ID'" and returns the results in JSON format.

[1211] Step 16:

[1212] The terminal displays the acquired information and allows the user to check the currently installed applications.

[1213] Input: JSON response from the server

[1214] Output: A list of installed applications displayed on the screen.

[1215] Specific behavior: The device's app UI displays a list of installed applications.

[1216] (Application example 2)

[1217] 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."

[1218] The process of searching, installing, and using existing AI applications is complicated and unintuitive for users. Furthermore, it does not recommend optimal applications based on the user's emotional state. Therefore, a more efficient and user-friendly system is needed. In particular, it is essential to manage applications suitable for automation robots in factories and to provide optimal recommendations based on real-time emotional analysis.

[1219] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1220] In this invention, the server includes a database server means for managing application data, a server means for receiving requests from a user terminal, a server means for returning an application list to the user terminal, a server means for processing a user's request to install a specific application and updating user data, a server means for acquiring a list of the user's installed applications and returning it to the user terminal, an emotion analysis engine means for recognizing the user's emotions, and a server means for recommending optimal applications based on the emotion analysis engine means. This allows users to intuitively search for, install, and use AI applications, and the recommendation of optimal applications based on emotional states can improve the operation of automated robots in factories, achieve predictive maintenance, parts management and supply, and increase efficiency.

[1221] "Database server means for managing application data" refers to a server that centrally manages information such as the ID, name, and description of various AI applications.

[1222] The "server means for receiving requests from user terminals" refers to a server that has the function of receiving requests that users send to the server from their own terminals.

[1223] "Server means for returning an application list to the user terminal" refers to the function of the server sending a list of AI applications to the user terminal in response to a user request.

[1224] The "server means for processing requests from users to install specific applications and updating user data" refers to a server that processes requests to install AI applications selected by users and updates user data.

[1225] The "server means for acquiring a list of applications already installed by the user and returning it to the user terminal" is a server having the function of acquiring a list of applications already installed and sending it to the user terminal.

[1226] The "emotion analysis engine means for recognizing the user's emotions" is an engine that uses sensors such as a camera and microphone to analyze the user's facial expressions and tone of voice, and recognizes emotions in real time.

[1227] The "server means for recommending the most suitable application based on the emotion analysis engine means" is a server having a function for recommending the most suitable AI application for the user's state based on the results of the user's emotion analysis.

[1228] To implement this invention, it is necessary to build a system that uses a database server that manages various application data, a server that receives requests from users, a server that processes lists and installation requests, an emotion analysis engine, and a server with recommendation functions.

[1229] Specifically, the server manages a database and stores information about available AI applications. Application data includes the application's ID, name, description, etc. When a user accesses the application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves the application information from the database, and returns it to the user's device in a structured data format. This allows the user to view a list of available applications on their device.

[1230] Furthermore, if a user wishes to install an application, the request will be sent to the server, which will analyze the user ID and application ID, check the database, update the user data if it exists, and return a message indicating successful installation to the device, allowing the user to smoothly install the AI ​​application.

[1231] The system also features an emotion analysis engine that recognizes the user's emotions. It uses a camera and microphone to collect the user's facial expressions and tone of voice, and analyzes their emotions in real time. Based on this emotion data, the server has the function of recommending the most appropriate AI application to the user. For example, if stress is detected from the user's emotion analysis, it can recommend a relaxation application. This function promotes the use of the most appropriate application tailored to the user's situation.

[1232] A specific example of application in factories is to introduce this system to automated robots working in factories. For example, if the emotion analysis engine detects stress from the tone of an operator's voice, a "predictive maintenance AI" can be installed to prevent the robot from breaking down.

[1233] An example prompt is, "User detected with high stress levels through voice analysis. Recommend installing preventive maintenance AI application to ensure smooth operation of factory robots."

[1234] In this way, this invention allows users to intuitively search for, install, and use AI applications, and by recommending optimal applications based on emotion analysis data, it is possible to improve the operation of automated robots in factories, perform predictive maintenance, manage and supply parts, and increase efficiency.

[1235] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1236] Step 1:

[1237] A user accesses the application market from a terminal. The input is the user's access request, and the terminal sends a request to the server to obtain an application list. The server receives this request. The output is the terminal receiving the request for the application list.

[1238] Step 2:

[1239] The server retrieves application information from the database. The input is the request received in step 1, and the server retrieves information such as application ID, name, description, etc. from the database. The output is the retrieved application list.

[1240] Step 3:

[1241] The server returns the acquired application information to the device in a structured data format (e.g., JSON format). The input is the data acquired in step 2, which the server converts into a structured data format. The output is a JSON-formatted application list that is sent to the device.

[1242] Step 4:

[1243] The terminal displays the received application list in the user interface. The input is the JSON-formatted data sent in step 3, and the terminal displays this to the user as a visually easy-to-read list. The output is the application list that the user views.

[1244] Step 5:

[1245] A user clicks a button to install a specific application. The input is the user's click, and the terminal sends an installation request to the server. The output is an installation request to the server.

[1246] Step 6:

[1247] The server parses the received installation request to obtain the user ID and application ID. The input is the request sent in step 5, which the server parses to extract the required IDs. The output is the parsed user ID and application ID.

[1248] Step 7:

[1249] The server checks the existence of the user ID and application ID in the database. The input is the ID obtained in step 6, and the server checks whether these IDs exist in the database. The output is the result of the existence check.

[1250] Step 8:

[1251] If the existence check is successful, the server adds the application ID to the user data and updates the database. The input is the check result from step 7, and the server updates the user data. The output is the updated database.

[1252] Step 9:

[1253] The server returns a message to the user terminal indicating that the installation was successful. The input is the data updated in step 8, and the server generates a message indicating that the installation was successful. The output is the success message sent to the user terminal.

[1254] Step 10:

[1255] The user's device uses an emotion analysis engine to analyze the user's emotional state. The input is data on the user's facial expressions and voice collected from a camera or microphone, which the device analyzes using the emotion analysis engine. The output is emotional data as the analysis result.

[1256] Step 11:

[1257] If the emotion analysis engine detects emotions such as stress or anxiety, the server will recommend the most appropriate application based on that. The input is the emotion data from step 10, and the server selects and recommends the most appropriate application from the database based on that data. The output is the recommendation result for the user.

[1258] Step 12:

[1259] The recommended applications are displayed on the user's device, and the user can install or use them as needed. The input is the recommendation result from step 11, which the device displays on the user interface. The output is the displayed recommendation result.

[1260] 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.

[1261] 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.

[1262] 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.

[1263] [Fourth embodiment]

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

[1265] 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.

[1266] 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).

[1267] 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.

[1268] 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.

[1269] 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).

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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.

[1275] 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.

[1276] 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."

[1277] The present invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications. Specific embodiments of the system are described below.

[1278] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[1279] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[1280] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[1281] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[1282] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1283] As described above, this system allows users to intuitively search for, install, and use AI applications. Furthermore, by establishing a mechanism for providing appropriate rewards to developers, the system will improve the quality and diversity of applications and contribute to the development of AI.

[1284] The processing flow will be explained below.

[1285] Step 1:

[1286] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[1287] Step 2:

[1288] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[1289] Step 3:

[1290] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[1291] Step 4:

[1292] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[1293] Step 5:

[1294] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[1295] Step 6:

[1296] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[1297] Step 7:

[1298] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[1299] Step 8:

[1300] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[1301] Step 9:

[1302] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[1303] Step 10:

[1304] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[1305] Step 11:

[1306] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[1307] Step 12:

[1308] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[1309] Step 13:

[1310] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[1311] Example 1

[1312] 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."

[1313] In conventional systems, it has been difficult for users to search for, easily install, and use artificial intelligence (AI) applications. It has also been cumbersome for users to manage installed applications. Due to these issues, there is a demand for improved user convenience and efficiency.

[1314] 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.

[1315] In this invention, the server includes information processing means for managing an application database, information processing means for receiving requests from a user's terminal, information processing means for returning an application list to the user's terminal, information processing means for processing a user's request to install a specific application and updating user data, information processing means for obtaining a list of the user's installed applications and returning it to the user's terminal, information display means for allowing a user to access an application market from their terminal, select an application from the list, and request installation, information generation means for the server to generate a message indicating successful installation and return it to the terminal, information display means for the terminal to render the application list received from the server on the screen and display it to the user, and communication processing means for the terminal to send an HTTP request to the server to request a list of available applications. This enables users to easily search for, install, and use AI applications.

[1316] An "application database" is a collective data storage used to manage information about artificial intelligence applications.

[1317] "Information processing means" refers to a functional module that enables a computer system or server to perform specific data processing.

[1318] "User's device" refers to a computing device used by a user, such as a smartphone, tablet, or PC.

[1319] A "request" refers to an operation or the content of an operation in which a user requests specific information or service through a terminal.

[1320] An "application list" is a list of information about multiple artificial intelligence applications.

[1321] "User Data" means a data set containing identifying information and activity records relating to a user.

[1322] "Information display means" refers to a function or module that enables a terminal to display visual information to a user.

[1323] "Information generation means" refers to a function or module that allows the server to generate specific information and transmit that information to users or other systems.

[1324] "Communication processing means" refers to the function for performing data communication between the terminal and the server.

[1325] The present invention provides a system for assisting users in easily searching for, installing, and using artificial intelligence (AI) applications. Detailed embodiments are described below.

[1326] The server first manages the application database. Specifically, the server uses an Amazon Web Services (AWS) EC2 instance and the database uses Amazon RDS (Relational Database Service). The application data includes information such as the application ID, name, and description.

[1327] When a user accesses the application market using a terminal, the terminal sends an HTTP request to the server to request a list of available applications. This request is performed using the HTTP GET method.

[1328] The server receives this request, retrieves all application information from the application database, and returns it to the device as a structured response in JSON format. This process uses Node.js on the server side. The device renders the received JSON-formatted application list on the screen and provides it to the user as a selection. The processing on the device side is implemented using React (a front-end library).

[1329] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request uses the HTTP POST method, and the body contains the user ID and application ID.

[1330] The server receives the request and analyzes the user ID and application ID based on it. It checks the database to see if the user and application exist, and if they do, it adds the application ID to the user data and updates the database. Through this series of operations, the user data is changed using an UPDATE query. The server then generates a message indicating that the installation was successful and sends it back to the terminal.

[1331] The user will then receive a message on their device indicating successful installation, and will be able to use the selected application. If the user wishes to check the list of their installed applications, they can send a request to the server from their device. The server will retrieve the list of installed applications from the user database and send a response structured in JSON format back to the device. The device will then display this on the screen, allowing the user to check the currently installed applications.

[1332] As a concrete example, the process for a user to install an application named "Image Classification AI" is shown below.

[1333] 1. The user accesses the URL "https: / / ai-market.com".

[1334] 2. The device sends a request "GET / api / applications" to the server.

[1335] 3. The server retrieves the application information from the database and returns it in JSON format.

[1336] 4. The device parses this JSON data and displays an application called "Image Classification AI" on the screen.

[1337] 5. When the user clicks the install button for "Image Classification AI," the device sends a "POST / api / install" request to the server. The body contains { userId: "user1", appId: "app1"}.

[1338] 6. The server receives the request, updates the database, and adds "app1" to the user data.

[1339] 7. The server generates a message indicating that the installation was successful and returns it to the terminal.

[1340] 8. The device displays the message "Installation successful" to the user.

[1341] This series of processes allows users to easily install and use the AI ​​applications they need without any complicated work.

[1342] Example prompts to input to a generative AI model:

[1343] "Please explain in a way that the Generative AI model can understand how a user accesses the AI ​​App Market and installs a specific application. Please provide a detailed explanation of the entire process, with particular emphasis on submitting and processing the install request."

[1344] This system will improve user convenience by making it easier for users to intuitively search for, install, and use AI applications. It will also establish an appropriate reward system for developers, improving the quality and diversity of applications and contributing to the development of AI technology.

[1345] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1346] Step 1: User visits the App Market

[1347] Specific operation: The user opens the browser on their device and enters the URL of the AI ​​application market (e.g., https: / / ai-market.com) to access it.

[1348] Input: A user types a market URL into the browser's address bar.

[1349] Output: The terminal displays the initial Market screen.

[1350] Step 2: The device requests an application list from the server.

[1351] Specific operation: The device sends an HTTP GET request to the server to request a list of available applications.

[1352] Input: HTTP GET request sent by the device: "GET / api / applications"

[1353] Output: The server receives the request.

[1354] Step 3: The server retrieves all application information from the application database

[1355] What it does: The server queries the database to get application information and structures it in JSON format.

[1356] Input: HTTP GET request received by the server and application information from the database

[1357] Output: Application information structured in JSON format

[1358] Step 4: The server returns the application information to the device.

[1359] Specific operation: The server returns application information structured in JSON format to the terminal as an HTTP response.

[1360] Input: Application information in JSON format

[1361] Output: The HTTP response received by the device

[1362] Step 5: Display the list of applications retrieved by the device on the screen.

[1363] Specific operation: The device parses the received JSON data, renders the application list on the screen, and displays it to the user.

[1364] Input: JSON format application information received by the device

[1365] Output: Application list displayed on the device screen

[1366] Step 6: User selects specific application and submits installation request

[1367] Specific behavior: The user selects a specific application from the list and clicks the install button, which causes the device to send an HTTP POST request to the server.

[1368] Input: User selected application

[1369] Output: HTTP POST request "POST / api / install" sent by the device. The body contains the user ID and application ID.

[1370] Step 7: The server receives the install request and parses the user ID and application ID.

[1371] Specific operation: The server receives the installation request and analyzes the user ID and application ID in the request.

[1372] Input: HTTP POST request sent by the device

[1373] Output: Parsed user ID and application ID

[1374] Step 8: Server checks database for user and application existence

[1375] What happens: The server queries the database and verifies that the user ID and application ID exist.

[1376] Input: Parsed user ID and application ID

[1377] Output: User and application existence check results

[1378] Step 9: The server adds the application ID to the user data and updates the database

[1379] Specific operation: The server adds the application ID to the user data and updates the database.

[1380] Input: User data and verified application ID

[1381] Output: Updated user data

[1382] Step 10: The server sends a message back to the device confirming the installation was successful.

[1383] Specific operation: The server generates a message indicating that the installation was successful and sends it back to the terminal.

[1384] Input: Updated user data

[1385] Output: Installation successful message

[1386] Step 11: The terminal displays a successful installation message to the user

[1387] Specific operation: The device displays the installation success message to the user.

[1388] Input: Installation success message received from the server

[1389] Output: A successful installation message that is displayed to the user.

[1390] (Application example 1)

[1391] 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."

[1392] Modern consumers are trying to live comfortable lives by utilizing a wide variety of AI applications, but searching for and installing the appropriate applications from the vast number of available ones requires a great deal of effort and time. Online shopping sites, in particular, are required to quickly and accurately predict and recommend the product categories consumers desire, but current systems do not adequately meet this need. Therefore, there is a need for a system that allows consumers to easily search for and install the AI ​​applications they need, and also has the ability to predict and recommend product categories.

[1393] 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.

[1394] In this invention, the server includes means for managing an application database, means for receiving requests from a user's terminal, means for returning an application list to the user's terminal, means for processing a user's request to install a specific application and updating user data, means for obtaining a list of the user's installed applications and returning it to the user's terminal, and means for including a generative AI model that predicts and recommends product categories searched for by the user. This enables users to easily search for and install the AI ​​applications they need, and enables the prediction and recommendation of appropriate product categories on online shopping sites.

[1395] An "application database" is a database that holds information about available applications managed within the system.

[1396] "Server means" refers to the functions and devices of a server that manages an application database, receives and processes requests from users, and returns responses.

[1397] A "user device" is an electronic device used by a user to discover, install, and use applications.

[1398] A "request" is request data sent from a user's terminal to a server.

[1399] An "application list" is a list of available applications that is returned from the server to the user's terminal.

[1400] An "installation request" is a request made by a user to install a particular application on a terminal in order to use the application.

[1401] "User Data" is data in a database that contains user-specific information.

[1402] A "generative AI model" is a type of artificial intelligence that uses machine learning algorithms to perform a specific task, such as predicting product categories.

[1403] A "prompt" is input text that gives specific instructions to an AI.

[1404] The present invention relates to a system that enables users to easily search for, install, and use AI applications. Specific embodiments of the system are described below.

[1405] The server first manages an application database, which stores information about available applications. Application data includes the application's ID, name, description, etc.

[1406] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[1407] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[1408] In addition, a user can send a request from the device to the server to check their installed applications. The server retrieves a list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1409] Furthermore, this invention uses a generative AI model to predict and recommend the product category a user is searching for. Specifically, when a user accesses the application market or searches for a specific product category, the generative AI model analyzes product images and text data to predict and recommend the appropriate category. This function allows users to intuitively find the applications and products they need.

[1410] The hardware used includes smartphones and servers (virtual or physical), and the software used includes Flask, which is used to create API endpoints on the server side, requests, which is used to make HTTP requests, and the JSON format, which is used to structure and parse the data.

[1411] As a concrete example, consider the process in which a user installs an application called "Image Classification AI" and uses that AI to predict product categories on an online shopping website. The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request is sent from the device to the server stating, "User 1 installs App 1." The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user data, and returns a message to the device indicating successful installation.

[1412] An example of a prompt is as follows:

[1413] "Predict the product category from this image."

[1414] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1415] Step 1:

[1416] A user accesses the application market from a smartphone device.

[1417] Input: User action (access to the market).

[1418] Output: The request is sent to the server.

[1419] Specific operation: The user taps the application market icon on the smartphone, launching the market app, which then sends a GET request to the server.

[1420] Step 2:

[1421] The server generates an application list in JSON format and returns it to the device.

[1422] Input: A request from the user's terminal.

[1423] Output: A list of applications in JSON format.

[1424] Specific operation: The server accesses the application database to obtain all available application information, structures the obtained information in JSON format, and returns it to the user device.

[1425] Step 3:

[1426] The terminal displays the received application list on the user interface.

[1427] Input: A list of applications in JSON format.

[1428] Output: The application list displayed on the screen.

[1429] Specific operation: The device parses the JSON data received from the server and visually displays the application list in the user interface.

[1430] Step 4:

[1431] The user selects a particular application and submits an installation request.

[1432] Input: User's choice (Application ID).

[1433] Output: The installation request sent to the server.

[1434] Specific operation: The user taps the application they want to install, and the device sends a POST request to the server containing the application ID and the user ID.

[1435] Step 5:

[1436] The server receives the installation request and parses and verifies the user ID and application ID.

[1437] Input: The user ID and application ID in the install request.

[1438] Output: User database updated and installation successful message.

[1439] Specific operation: The server accesses the database and checks the existence of the user ID and application ID. After checking, it adds the application ID to the user data and generates a message indicating successful installation and returns it to the user device.

[1440] Step 6:

[1441] The user submits a request to see a list of installed applications.

[1442] Input: User action (submitting a confirmation request).

[1443] Output: A confirmation request sent to the server.

[1444] Specific operation: The user taps the confirmation button, and the device sends a GET request to the server.

[1445] Step 7:

[1446] The server obtains a list of the user's installed applications and returns it to the device in JSON format.

[1447] Input: User confirmation request.

[1448] Output: A list of installed applications in JSON format.

[1449] Specific operation: The server retrieves information about installed applications from the user database, structures it in JSON format, and sends it back to the user's device.

[1450] Step 8:

[1451] The terminal displays the acquired list of installed applications on a user interface.

[1452] Input: A list of installed applications in JSON format.

[1453] Output: A list of installed applications displayed on the screen.

[1454] Specific operation: The device parses the received JSON data and visually displays a list of installed applications in the user interface.

[1455] Step 9:

[1456] The user enters a prompt sentence to predict the product category using the generative AI model.

[1457] Input: The prompt text entered by the user.

[1458] Output: A request to the generative AI model.

[1459] Specific operation: The user enters the prompt "Please predict the product category from this image" into the input field of the device and taps the send button. The device then sends the prompt and the product image to the generative AI model.

[1460] Step 10:

[1461] The generative AI model predicts the product category and returns the prediction results to the terminal.

[1462] Input: Prompt text and product image.

[1463] Output: Product category prediction results.

[1464] Specific operation: The generative AI model analyzes the prompt text and product image to predict the product category, and returns the prediction result to the user's device.

[1465] Step 11:

[1466] The product category prediction result received by the terminal is displayed on a user interface.

[1467] Input: Product category prediction results.

[1468] Output: Product category prediction results displayed on the screen.

[1469] Specific operation: The device analyzes the prediction results received and displays them on the user interface.

[1470] 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.

[1471] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, and also provides a system that combines an emotion engine that recognizes the user's emotions. Specific embodiments of the system are described below.

[1472] The server first manages an application database, which stores information about available applications. Application data includes the application ID, name, description, etc.

[1473] When a user accesses the application market from a device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns a structured response in JSON format to the device. The device then displays the received application list on the screen and allows the user to make a selection.

[1474] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect information such as the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time.

[1475] When a user wants to install a specific application, they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID based on the request, and searches for the respective records in the database. If the server confirms that the user and application exist, it adds the application ID to the user data and updates the database. The server then returns a message to the user indicating that the installation was successful.

[1476] As a concrete example, consider the process of a user installing an application called "Image Classification AI." The user accesses the market, retrieves a list of applications, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1 information to the user data, and returns a message to the device indicating successful installation. This series of processes allows the user to easily install and use the necessary applications without having to go through complicated procedures.

[1477] The system also has the ability to recommend applications suitable for users based on their emotional data. For example, if the emotion engine detects that a user is stressed, it can recommend applications that help with relaxation. This recommendation function allows users to easily find the application that best suits their condition.

[1478] Furthermore, to check the applications installed by the user, the device can send a request to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device as a structured response in JSON format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1479] As described above, this system allows users to intuitively search for, install, and use AI applications, and also has the ability to recognize users' emotions in real time and recommend optimal applications based on that data, improving the user experience and promoting the use of AI applications.

[1480] The processing flow will be explained below.

[1481] Step 1:

[1482] A user opens the application market web page from their device, and the device sends an HTTP GET request to the server requesting a list of applications.

[1483] Step 2:

[1484] The server receives a request for an application list. The server queries the application database and retrieves all application information.

[1485] Step 3:

[1486] The server structures the acquired application information in JSON format, and then returns the structured data to the device as an HTTP response.

[1487] Step 4:

[1488] The device analyzes the response received from the server and displays a list of applications on the screen, from which the user can select a specific application.

[1489] Step 5:

[1490] The user's device uses an emotion engine to collect data from cameras, microphones, etc. to recognize the user's emotions. The device sends the collected data to the emotion engine, which then analyzes the emotions.

[1491] Step 6:

[1492] The emotion engine analyzes the user's emotions and sends the results to the server, which receives the emotion data and determines which applications to recommend based on the user's emotional state.

[1493] Step 7:

[1494] The server structures a list of suitable applications in JSON format based on the user's emotional state, and then sends the structured list of recommendations back to the device as an HTTP response.

[1495] Step 8:

[1496] The device analyzes the recommendation list received from the server and displays it on the screen. The user can then review the recommended applications and select them as needed.

[1497] Step 9:

[1498] The user clicks the install button for a specific application. The device sends an HTTP POST request to the server requesting application installation. This request includes the user ID and application ID.

[1499] Step 10:

[1500] The server receives the installation request, analyzes the user ID and application ID in the request, and searches for the respective records in the database.

[1501] Step 11:

[1502] The server checks the search results, and if the user and application exist, adds the application ID to the user database and updates the database after the addition.

[1503] Step 12:

[1504] The server structures the results of the installation process in JSON format and returns them to the device as an HTTP response, which includes a message indicating that the installation was successful.

[1505] Step 13:

[1506] The device analyzes the response received from the server and displays a message indicating successful installation to the user, allowing the user to check the installed application.

[1507] Step 14:

[1508] A user sends an HTTP GET request from their device to the server to check the list of installed applications.

[1509] Step 15:

[1510] The server receives a request for a list of installed applications. The server queries the user database to retrieve the installed applications for that user.

[1511] Step 16:

[1512] The server structures the installed application information it obtains in JSON format and returns it to the device as an HTTP response.

[1513] Step 17:

[1514] The device analyzes the response received from the server and displays a list of installed applications on the screen, allowing the user to check the currently installed applications.

[1515] Example 2

[1516] 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."

[1517] Conventional systems require users to go through complicated procedures when installing AI applications, resulting in a poor user experience. Furthermore, the lack of a function to recommend appropriate applications based on user sentiment makes it difficult for users to find the application that best suits them. This does not promote the use of AI applications and reduces convenience for users.

[1518] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1519] In this invention, the server includes computer system means for managing an application database, computer system means for receiving requests from a user's computer device, computer system means for returning an application list to the user's computer device, computer system means for processing a user's request to install a specific application and updating user information, computer system means for obtaining the user's installed application list and returning it to the user's computer device, and emotion analysis means for recognizing the user's emotions and recommending appropriate applications based on that data. This allows users to intuitively and easily search for, install, and use AI applications, and further improves convenience by recommending optimal applications based on the user's emotions.

[1520] An "application database" is a database that manages information about multiple applications available to users.

[1521] "Computer system means" refers to the software and hardware running on a server or user's computing device that is used to provide a particular function or service.

[1522] A "request" refers to a request made from a user's computing device to a server, and includes operations such as retrieving or updating data.

[1523] A "structured language format" is a description format for representing data in an organized and consistent manner, and examples include JSON and XML.

[1524] "User information" refers to data about users managed within the system, including information such as user IDs and installed applications.

[1525] An "emotion analysis means" is a mechanism that recognizes emotions by analyzing data such as the user's facial expressions and voice, and recommends appropriate applications based on the results.

[1526] "User's computing device" refers to the electronic device used by the user to access the system, including smartphones, tablets, and personal computers.

[1527] MODE FOR CARRYING OUT THE INVENTION

[1528] This invention provides a system that helps users easily search for, install, and use artificial intelligence (AI) applications, as well as a system that combines an emotion engine that recognizes the user's emotions.

[1529] Configuration and Hardware / Software Used

[1530] The server provides the core functionality of the system using the following hardware and software:

[1531] Hardware: High-performance server machine

[1532] Software: Apache HTTP Server, MySQL database, Python (backend)

[1533] A terminal is a computing device used by a user (e.g., a smartphone) that has the following components:

[1534] Hardware: Smartphone (iOS or Android)

[1535] Software: Dedicated application (front end), sensors such as cameras and microphones

[1536] The emotion engine is a component for recognizing user emotions in real time, using:

[1537] Software: Python, OpenCV, Google Cloud Speech-to-Text API, deep learning framework (e.g., TensorFlow or PyTorch)

[1538] Program processing

[1539] The server manages an application database that contains information about available applications, such as application IDs, names, and descriptions.

[1540] When a user accesses the AI ​​application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves all application information from the application database, and returns it to the device in a structured language (JSON) format. The device then displays the received application list on the screen and allows the user to make a selection.

[1541] When a user wants to install a specific application (e.g., "Image Classification AI"), they click the install icon. This action causes the device to send a request to the server to install the specific application. This request includes the user ID and application ID. The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database. If the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database. The server then sends a message back to the device indicating that the installation was successful.

[1542] In addition, the system is equipped with an emotion engine that recognizes the user's emotions. The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice. The emotion engine analyzes this data and recognizes the user's emotions in real time. If the emotion engine detects that the user is stressed, it can recommend applications that will help with relaxation.

[1543] Furthermore, the user can check their installed applications by sending a request from the device to the server. The server retrieves the list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format. The device displays the retrieved information and allows the user to check the currently installed applications.

[1544] Specific examples

[1545] For example, consider the process of a user installing an application named "Image Classification AI." The user accesses the market, retrieves the application list, and selects "Image Classification AI." When the user clicks the install button, a request "User 1 installs App 1" is sent from the device to the server. The server receives this request, confirms the existence of User 1 and App 1 in the user database and application database, adds App 1's information to the user information, and returns a message to the device indicating successful installation.

[1546] This series of processes allows users to easily install and use the necessary applications without having to go through complicated procedures.

[1547] Prompt Sentence Examples

[1548] "User 1 sends a request to the server to install app 1. The server checks the user database and application database for the existence of user 1 and app 1, and adds app 1's information to the user information. The server then sends a message that the installation was successful."

[1549] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1550] Step 1:

[1551] The user accesses the AI ​​application market from their device.

[1552] Input: None

[1553] Output: None

[1554] Specific operation: The user launches the "AI App Market" app on their smartphone.

[1555] Step 2:

[1556] The terminal sends a request to the server for a list of currently available applications.

[1557] Input: User access request

[1558] Output: HTTP request to the server

[1559] Specific operation: The device sends an HTTP request to the server in the format "GET / api / applications".

[1560] Step 3:

[1561] The server retrieves all application information from the application database.

[1562] Input: Request from terminal

[1563] Output: Application information

[1564] Specific operation: The server executes the MySQL query "SELECT FROM applications" to retrieve the data.

[1565] Step 4:

[1566] The server converts the acquired application information into a structured language (JSON) format and returns it to the terminal.

[1567] Input: Application Information

[1568] Output: HTTP response to the terminal (JSON format)

[1569] Specific operation: The server uses a Python library to convert the data into JSON format and returns it as an HTTP response.

[1570] Step 5:

[1571] The terminal displays the received application list on the screen and provides the user with a selection.

[1572] Input: Application list from the server (JSON format)

[1573] Output: Application list displayed on screen

[1574] Specific behavior: The device's app UI displays the application name and description in a list format.

[1575] Step 6:

[1576] The user selects the application they wish to install and clicks the install icon.

[1577] Input: Application list displayed on the screen

[1578] Output: Clicking the installation icon

[1579] Specific operation: The user selects "Image Classification AI" and clicks the install button.

[1580] Step 7:

[1581] The device sends a request to the server to install a specific application, which includes the user ID and the application ID.

[1582] Input: User ID, Application ID

[1583] Output: HTTP POST request to the server

[1584] Specific operation: The device sends an HTTP POST request "POST / api / install" and includes the user ID and application ID in the request body.

[1585] Step 8:

[1586] The server receives the request, analyzes the user ID and application ID, and searches for the respective records in the database.

[1587] Input: Installation request (user ID, application ID)

[1588] Output: User and application records retrieved from the database

[1589] Specific operation: The server executes the MySQL queries "SELECT FROM users WHERE id="user ID"" and "SELECT FROM applications WHERE id="application ID"".

[1590] Step 9:

[1591] After the server confirms the existence of the user and application, it adds the application ID to the user information and updates the database.

[1592] Input: User and application records

[1593] Output: Updated user information

[1594] Specific operation: The server executes the MySQL query "INSERT INTO user_apps (user_id, app_id) VALUES ('user ID', 'application ID')".

[1595] Step 10:

[1596] The server will return a message to the terminal indicating that the installation was successful.

[1597] Input: Updated user information

[1598] Output: Installation successful message (JSON format)

[1599] Specific operation: The server returns an "Installation successful" message in JSON format in the HTTP response.

[1600] Step 11:

[1601] The user's device uses sensors such as a camera and microphone to collect the user's facial expressions and tone of voice.

[1602] Input: User's facial expression, tone of voice

[1603] Output: Collected emotion data

[1604] Specific operation: The device activates the camera to capture the user's face and collects audio data using the microphone.

[1605] Step 12:

[1606] The device sends the collected data to the emotion engine.

[1607] Input: Collected emotion data

[1608] Output: Input data to the emotion engine

[1609] Specific operation: Camera image data is analyzed using the OpenCV library, and audio data is processed using the Google Cloud Speech-to-Text API.

[1610] Step 13:

[1611] The emotion engine analyzes the user's emotions and recommends appropriate applications.

[1612] Input: Parsed emotion data

[1613] Output: A list of recommended applications

[1614] How it works: The emotion engine uses deep learning models (TensorFlow and PyTorch) to recognize emotions and recommends relaxation apps when stress is detected.

[1615] Step 14:

[1616] A user sends a request from the terminal to the server to check the installed applications.

[1617] Input: User verification request

[1618] Output: HTTP request to the server

[1619] What happens: The user accesses the "My Apps" section of their device.

[1620] Step 15:

[1621] The server retrieves a list of the user's installed applications from the database and returns it to the device in a structured language (JSON) format.

[1622] Input: User request

[1623] Output: List of installed applications (JSON format)

[1624] Specific operation: The server executes the MySQL query "SELECT FROM user_apps WHERE user_id='User ID'" and returns the results in JSON format.

[1625] Step 16:

[1626] The terminal displays the acquired information and allows the user to check the currently installed applications.

[1627] Input: JSON response from the server

[1628] Output: A list of installed applications displayed on the screen.

[1629] Specific behavior: The device's app UI displays a list of installed applications.

[1630] (Application example 2)

[1631] 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."

[1632] The process of searching, installing, and using existing AI applications is complicated and unintuitive for users. Furthermore, it does not recommend optimal applications based on the user's emotional state. Therefore, a more efficient and user-friendly system is needed. In particular, it is essential to manage applications suitable for automation robots in factories and to provide optimal recommendations based on real-time emotional analysis.

[1633] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1634] In this invention, the server includes a database server means for managing application data, a server means for receiving requests from a user terminal, a server means for returning an application list to the user terminal, a server means for processing a user's request to install a specific application and updating user data, a server means for acquiring a list of the user's installed applications and returning it to the user terminal, an emotion analysis engine means for recognizing the user's emotions, and a server means for recommending optimal applications based on the emotion analysis engine means. This allows users to intuitively search for, install, and use AI applications, and the recommendation of optimal applications based on emotional states can improve the operation of automated robots in factories, achieve predictive maintenance, parts management and supply, and increase efficiency.

[1635] "Database server means for managing application data" refers to a server that centrally manages information such as the ID, name, and description of various AI applications.

[1636] The "server means for receiving requests from user terminals" refers to a server that has the function of receiving requests that users send to the server from their own terminals.

[1637] "Server means for returning an application list to the user terminal" refers to the function of the server sending a list of AI applications to the user terminal in response to a user request.

[1638] The "server means for processing requests from users to install specific applications and updating user data" refers to a server that processes requests to install AI applications selected by users and updates user data.

[1639] The "server means for acquiring a list of applications already installed by the user and returning it to the user terminal" is a server having the function of acquiring a list of applications already installed and sending it to the user terminal.

[1640] The "emotion analysis engine means for recognizing the user's emotions" is an engine that uses sensors such as a camera and microphone to analyze the user's facial expressions and tone of voice, and recognizes emotions in real time.

[1641] The "server means for recommending the most suitable application based on the emotion analysis engine means" is a server having a function for recommending the most suitable AI application for the user's state based on the results of the user's emotion analysis.

[1642] To implement this invention, it is necessary to build a system that uses a database server that manages various application data, a server that receives requests from users, a server that processes lists and installation requests, an emotion analysis engine, and a server with recommendation functions.

[1643] Specifically, the server manages a database and stores information about available AI applications. Application data includes the application's ID, name, description, etc. When a user accesses the application market from their device, the device sends a request to the server for a list of applications. The server receives this request, retrieves the application information from the database, and returns it to the user's device in a structured data format. This allows the user to view a list of available applications on their device.

[1644] Furthermore, if a user wishes to install an application, the request will be sent to the server, which will analyze the user ID and application ID, check the database, update the user data if it exists, and return a message indicating successful installation to the device, allowing the user to smoothly install the AI ​​application.

[1645] The system also features an emotion analysis engine that recognizes the user's emotions. It uses a camera and microphone to collect the user's facial expressions and tone of voice, and analyzes their emotions in real time. Based on this emotion data, the server has the function of recommending the most appropriate AI application to the user. For example, if stress is detected from the user's emotion analysis, it can recommend a relaxation application. This function promotes the use of the most appropriate application tailored to the user's situation.

[1646] A specific example of application in factories is to introduce this system to automated robots working in factories. For example, if the emotion analysis engine detects stress from the tone of an operator's voice, a "predictive maintenance AI" can be installed to prevent the robot from breaking down.

[1647] An example prompt is, "User detected with high stress levels through voice analysis. Recommend installing preventive maintenance AI application to ensure smooth operation of factory robots."

[1648] In this way, this invention allows users to intuitively search for, install, and use AI applications, and by recommending optimal applications based on emotion analysis data, it is possible to improve the operation of automated robots in factories, perform predictive maintenance, manage and supply parts, and increase efficiency.

[1649] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1650] Step 1:

[1651] A user accesses the application market from a terminal. The input is the user's access request, and the terminal sends a request to the server to obtain an application list. The server receives this request. The output is the terminal receiving the request for the application list.

[1652] Step 2:

[1653] The server retrieves application information from the database. The input is the request received in step 1, and the server retrieves information such as application ID, name, description, etc. from the database. The output is the retrieved application list.

[1654] Step 3:

[1655] The server returns the acquired application information to the device in a structured data format (e.g., JSON format). The input is the data acquired in step 2, which the server converts into a structured data format. The output is a JSON-formatted application list that is sent to the device.

[1656] Step 4:

[1657] The terminal displays the received application list in the user interface. The input is the JSON-formatted data sent in step 3, and the terminal displays this to the user as a visually easy-to-read list. The output is the application list that the user views.

[1658] Step 5:

[1659] A user clicks a button to install a specific application. The input is the user's click, and the terminal sends an installation request to the server. The output is an installation request to the server.

[1660] Step 6:

[1661] The server parses the received installation request to obtain the user ID and application ID. The input is the request sent in step 5, which the server parses to extract the required IDs. The output is the parsed user ID and application ID.

[1662] Step 7:

[1663] The server checks the existence of the user ID and application ID in the database. The input is the ID obtained in step 6, and the server checks whether these IDs exist in the database. The output is the result of the existence check.

[1664] Step 8:

[1665] If the existence check is successful, the server adds the application ID to the user data and updates the database. The input is the check result from step 7, and the server updates the user data. The output is the updated database.

[1666] Step 9:

[1667] The server returns a message to the user terminal indicating that the installation was successful. The input is the data updated in step 8, and the server generates a message indicating that the installation was successful. The output is the success message sent to the user terminal.

[1668] Step 10:

[1669] The user's device uses an emotion analysis engine to analyze the user's emotional state. The input is data on the user's facial expressions and voice collected from a camera or microphone, which the device analyzes using the emotion analysis engine. The output is emotional data as the analysis result.

[1670] Step 11:

[1671] If the emotion analysis engine detects emotions such as stress or anxiety, the server will recommend the most appropriate application based on that. The input is the emotion data from step 10, and the server selects and recommends the most appropriate application from the database based on that data. The output is the recommendation result for the user.

[1672] Step 12:

[1673] The recommended applications are displayed on the user's device, and the user can install or use them as needed. The input is the recommendation result from step 11, which the device displays on the user interface. The output is the displayed recommendation result.

[1674] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the 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.

[1675] 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.

[1676] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1677] 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.

[1678] 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.

[1679] 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.

[1680] 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).

[1681] 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.

[1682] 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."

[1683] 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.

[1684] 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).

[1685] 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.

[1686] 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.

[1687] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1688] 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.

[1689] 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.

[1690] 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.

[1691] 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.

[1692] 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.

[1693] 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.

[1694] 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.

[1695] The following is further disclosed regarding the above embodiment.

[1696] (Claim 1)

[1697] a server means for managing an application database;

[1698] A server means for receiving a request from a user terminal;

[1699] a server means for returning an application list to the user's terminal;

[1700] server means for processing user requests to install specific applications and for updating user data;

[1701] a server means for acquiring a list of applications installed by the user and returning the list to the user's terminal;

[1702] A system including:

[1703] (Claim 2)

[1704] The system of claim 1, further comprising means for, when the user requests installation of an application from the terminal, the server means analyzes the user ID and application ID in the request, checks for existence in the database, and, if the application ID exists, adds the application ID to the user data and updates the database.

[1705] (Claim 3)

[1706] 2. The system of claim 1, wherein the server means comprises means for structuring the application data in a JSON format and returning the JSON format to the terminal.

[1707] "Example 1"

[1708] (Claim 1)

[1709] an information processing means for managing an application database;

[1710] an information processing means for receiving a request from a user terminal;

[1711] an information processing means for returning an application list to the user's terminal;

[1712] information processing means for processing user requests to install specific applications and for updating user data;

[1713] an information processing means for acquiring a list of applications installed by the user and returning the list to the user's terminal;

[1714] an information display means that allows a user to access the application market from a terminal, select an application from a list, and request installation of the application;

[1715] an information generating means for the server to generate a message indicating that installation has been successful and return the message to the terminal;

[1716] an information display means for displaying the application list received by the terminal from the server on a screen for the user;

[1717] a communication processing means for transmitting an HTTP request from the terminal to the server to request a list of available applications;

[1718] A system including:

[1719] (Claim 2)

[1720] The system of claim 1, further comprising means for, when the user requests installation of an application from the terminal, the information processing means analyzes the user ID and application ID in the request, checks for existence in the database, and, if the application ID exists, adds the application ID to the user data and updates the database.

[1721] (Claim 3)

[1722] 2. The system according to claim 1, wherein the information processing means comprises means for structuring the application data in a structured data format and returning the structured data to the terminal.

[1723] "Application Example 1"

[1724] (Claim 1)

[1725] a server means for managing an application database;

[1726] A server means for receiving a request from a user terminal;

[1727] a server means for returning an application list to the user's terminal;

[1728] server means for processing user requests to install specific applications and for updating user data;

[1729] a server means for acquiring a list of applications installed by the user and returning the list to the user's terminal;

[1730] A means including a generative AI model that predicts and recommends categories of products that a user explores;

[1731] A system including:

[1732] (Claim 2)

[1733] The system of claim 1, further comprising means for, when the user requests installation of an application from the terminal, the server means analyzes the user ID and application ID in the request, checks for existence in the database, and, if the application ID exists, adds the application ID to the user data and updates the database.

[1734] (Claim 3)

[1735] 2. The system of claim 1, wherein the server means comprises means for structuring the application data in a JSON format and returning the JSON format to the terminal.

[1736] "Example 2: Combining Emotion Engines"

[1737] (Claim 1)

[1738] a computer system means for managing an application database;

[1739] a computer system means for receiving a request from a user's computing device;

[1740] computer system means for returning the application list to the user's computing device;

[1741] computer system means for processing user requests to install specific applications and updating user information;

[1742] computer system means for obtaining and returning a list of installed applications to the user's computing device;

[1743] a sentiment analysis means for recognizing a user's sentiment and recommending appropriate applications based on the sentiment data;

[1744] A system including:

[1745] (Claim 2)

[1746] The system of claim 1, further comprising means for, when the user requests installation of an application from the computer device, analyzing the user ID and application ID in the request, checking the existence of the application ID in the database, and, if the application ID exists, adding the application ID to the user information and updating the database.

[1747] (Claim 3)

[1748] 10. The system of claim 1, wherein the computer system means comprises means for structuring the application data in a structured language format and returning it to the computer device.

[1749] "Application example 2 when combining emotion engines"

[1750] (Claim 1)

[1751] a database server means for managing application data;

[1752] A server means for receiving a request from a user terminal;

[1753] a server means for returning an application list to the user terminal;

[1754] server means for processing user requests to install specific applications and for updating user data;

[1755] a server means for acquiring a list of applications installed by the user and returning the list to the user terminal;

[1756] an emotion analysis engine means for recognizing the emotion of a user;

[1757] a server means for recommending an optimal application based on the sentiment analysis engine means;

[1758] A system including:

[1759] (Claim 2)

[1760] The system of claim 1, further comprising means for, when the user requests installation of an application from the terminal, the server means analyzes the user ID and application ID in the request, checks for existence in the database, and, if the application ID exists, adds the application ID to the user data and updates the database.

[1761] (Claim 3)

[1762] 2. The system according to claim 1, wherein said server means comprises means for structuring the application data into a structured data format and returning the structured data to the terminal. [Explanation of symbols]

[1763] 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 server means for managing an application database; A server means for receiving a request from a user terminal; a server means for returning an application list to the user's terminal; server means for processing user requests to install specific applications and for updating user data; a server means for acquiring a list of applications installed by the user and returning the list to the user's terminal; A system including:

2. The system according to claim 1, further comprising means for, when the user requests installation of an application from the terminal, the server means analyzes the user ID and application ID in the request, checks for existence in the database, and, if the application ID exists, adds the application ID to the user data and updates the database.

3. The system according to claim 1 , wherein the server means has means for structuring the application data in a JSON format and returning the JSON format to the terminal.

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