system

Abstract

We provide the system. [Solution] A means of inputting and storing users' personal information in a database, A means for collecting product information from retailers using a product information acquisition device, A means of creating an optimized meal plan based on user information and product information using a generative model, A means of listing the ingredients needed for the meal plan, A means of sending the listed materials as an order to a delivery service, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Modern consumers spend a lot of time and effort in making a meal plan considering health maintenance and nutritional balance. However, in busy daily life, it is difficult to devise a menu according to individual health conditions and eating habits and to effectively utilize special offers. Also, it is inefficient to manually collect special offer information and reflect it in daily shopping, and physical shopping is also time-consuming. Furthermore, there is a need for means to simplify a series of processes for planning meals based on this information and purchasing necessary food ingredients.

Means for Solving the Problems

[0005] This invention provides a system that proposes an optimized meal plan using a generative model based on the user's personal information, incorporates sale information in real time, and enables an economical and healthy diet. Specifically, this system includes a function to input the user's eating habits and health information and store it in a database, a function to obtain the latest sale information from retailers, a function to construct an optimal meal menu based on this information using a generative model, and a function to list necessary ingredients and automatically send an order to a delivery service based on the user's selection. Furthermore, this generative model makes suggestions while considering nutritional information, thus supporting the user's health management. This makes it possible to reduce the user's time and effort, and to realize convenient and efficient ingredient procurement and a healthy diet.

[0006] A "user" is an individual or group that uses the system to plan their personal meals or order groceries.

[0007] "Personal information" refers to data about a user's eating habits, health status, and food preferences.

[0008] A "database" is a structured data storage system used to store and manage users' personal information and information on special offers.

[0009] A "product information acquisition device" is a device or software used to collect product information, such as sale items, from retailers.

[0010] A "retail store" refers to a shop or online store that handles ingredients and food products.

[0011] A "generative model" is an algorithm or AI system that proposes an appropriate meal plan based on input data.

[0012] A "meal plan" is a daily menu suggested based on the user's health status and information on special offers.

[0013] A "materials list" is a table that describes the ingredients and their quantities needed for the generated meal plan.

[0014] A "delivery service" is a service that delivers groceries ordered by the user to their home or a designated location.

[0015] An "algorithm" is a set of computational steps or data processing techniques that a generative model uses to create a meal plan. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0019] In the following embodiments, a processor with a reference numeral (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, a RAM (Random Access Memory) with a reference numeral is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system that efficiently supports users' meal planning, providing daily meal menu suggestions based on the user's personal information and enabling the purchase of ingredients. This system functions through the coordinated operation of a server, terminals, and users.

[0038] (User information input)

[0039] Users access a dedicated application or website and log in to their account. Here, users enter detailed information such as their eating habits, health status, and allergy information, and register their dietary preferences. This personal information is transmitted to a server via the device and stored in a database.

[0040] (Collecting information on special offers)

[0041] The server accesses the APIs of partner retailers via the internet to periodically retrieve the latest sale information. This ensures that the server is ready to provide users with the most up-to-date product prices and inventory information.

[0042] (Generating the optimal menu)

[0043] When a user sends a request to the application, a generative model on the server is activated. Based on user information and special offer information stored on the server, the generative model suggests several optimal daily menus that are nutritionally balanced. For example, if a user requests a low-fat, high-protein diet and chicken breast is on sale, healthy dishes using chicken breast will be suggested.

[0044] (Creating and verifying the ingredient list)

[0045] The terminal lists the necessary ingredients and their quantities based on the generated menu. This list is displayed to the user, who can then select the ingredients to purchase. Using sale items allows for economically efficient purchasing.

[0046] (Ordering and delivery of ingredients)

[0047] Once a user confirms their order by selecting ingredients from a list, this information is sent to the server via their device. The server automatically processes the order using the API of a partner delivery service and arranges delivery. The user is also notified of details such as the scheduled delivery date and time, ensuring they can receive their order with peace of mind.

[0048] The system of this invention allows users to effectively utilize sale items while leading a healthy and efficient diet. Furthermore, the automation of cumbersome shopping procedures contributes to saving users time and effort.

[0049] The following describes the processing flow.

[0050] Step 1:

[0051] Users log in to an application or website and enter personal information such as eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0052] Step 2:

[0053] The server, through scheduled tasks, accesses the APIs of partner retailers to automatically retrieve information on special offers. This information is then analyzed and stored in a database as the most up-to-date version.

[0054] Step 3:

[0055] When a user submits a meal plan request from the application, the device relays this request to the server. The request includes a link to the user's personal information.

[0056] Step 4:

[0057] The server launches a generative model, inputting saved user information and sale item information to generate optimal daily meal menus. The model considers nutritional balance and the use of sale items, and proposes multiple menu options.

[0058] Step 5:

[0059] The terminal displays the generated menu on the user's screen, listing the required ingredients and their quantities. The user can review the list and add or remove items.

[0060] Step 6:

[0061] Once the user confirms their order, the terminal sends the selected ingredient information to the server. The server then sends the order data to the API of a partner delivery service, which automatically arranges delivery.

[0062] Step 7:

[0063] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the scheduled delivery date, time, and delivery location.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] Modern consumers are expected to create meal plans tailored to their individual nutritional needs for health management purposes. However, efficiently determining what ingredients to buy and where to obtain them is not easy. Furthermore, the process from creating shopping lists to purchasing goods and delivery is a time-consuming and cumbersome one for consumers.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for inputting the user's personal attributes and storing them in a recording device, means for aggregating product information from suppliers using an information acquisition device, and means for generating optimized meal suggestions based on the user attributes and product information using a generation AI model. This enables the user to efficiently create a healthy meal plan and acquire ingredients.

[0069] "User personal attributes" refer to information related to an individual user's dietary habits, such as eating habits, health status, allergy information, and food preferences.

[0070] A "recording device" is a device such as a database or server used to store digital information.

[0071] An "information acquisition device" is a device that collects product information from a vendor's system via the internet.

[0072] A "vendor" refers to a retailer or wholesaler that provides goods.

[0073] A "generative AI model" is an artificial intelligence model that generates optimized meal suggestions based on input user attributes and product information.

[0074] "Meal suggestions" refer to suggestions for nutritionally balanced meal menus and recipes that are tailored to the user's needs.

[0075] "Items" refers to the ingredients and related consumables listed based on the meal proposal.

[0076] A "delivery company" is a company that provides a service of transporting food or products to a designated location after purchase.

[0077] "Request submission" is the procedure of requesting a delivery company to arrange delivery based on information about the purchased items.

[0078] This invention is a system designed to support users in maintaining a healthy diet, and it functions through the coordinated efforts of the user, terminal, and server.

[0079] Users access their accounts using a dedicated application or website and input personal attributes such as eating habits, health status, allergy information, and food preferences. Based on this information, it is possible to provide personalized meal suggestions to the user.

[0080] The terminal transmits the above user information to the server and securely stores it in a recording device (database). The stored information is processed using a generative AI model. This model operates on the server and generates nutritionally balanced meal suggestions based on user attributes and product information collected from vendors. This process is achieved by the information acquisition device accessing the vendor's API via the internet and transmitting product information to the server.

[0081] For example, if a user requests a health-conscious, low-fat, high-protein menu, the server will suggest healthy recipes using chicken breast, which has been entered as a special offer. An example of a prompt message the user might enter would be: "Please generate this week's meal menu. I would like low-fat, high-protein dishes. Please let me know if you have any recipes using chicken breast."

[0082] The server creates a list of necessary items based on the generated meal suggestions. This list is presented to the user via a terminal, allowing the user to select suitable ingredients and confirm their purchase. Finally, the terminal sends this information back to the server, which automatically places an order with the delivery company. This allows the user to efficiently obtain the necessary ingredients.

[0083] As described above, this system efficiently supports users' healthy eating habits by combining generative AI models and communication technologies.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user accesses the application or website and logs into their account. After logging in, they enter personal attributes such as eating habits, health status, allergy information, and food preferences. The entered information is transmitted to the server via the device and stored on the recording device. In this step, the user's personal attributes are the input data, and the transmission to the server and storage are the output. Specifically, this involves the user filling out information in a form on the screen, approving it, and submitting it.

[0087] Step 2:

[0088] The server uses an information acquisition device to access the vendor's API and collect product information. This includes data such as sale information, product name, price, and inventory status. The collected data is sent to the server to prepare for future processing. The input for this step is the product information obtained from the vendor's API, and the output is the storage of the collected product information on the server. Specifically, the server periodically accesses the API and queries the data.

[0089] Step 3:

[0090] The user enters a prompt message in the application that includes their desired dietary style (e.g., low-fat, high-protein) and submits a request for a meal menu. The generative AI model uses user attributes and product information stored on the server to generate optimized meal suggestions. Specifically, it analyzes the user's request to create a nutritionally balanced menu. In this step, the prompt message is the input and the meal suggestions are the output. This includes the actions of the generative AI model in processing the request.

[0091] Step 4:

[0092] The server creates a list of necessary items based on the generated meal suggestions. This list is then provided to the user via a terminal. The user reviews the list and selects the items they wish to purchase. The input for this step is the meal suggestion, and the output is the item list. The specific operation primarily involves analyzing the suggested menu and creating the list.

[0093] Step 5:

[0094] Once the user confirms their purchase, the terminal sends this information back to the server. The server automatically processes the order and arranges delivery using the delivery company's API. The user is then notified of the delivery date, time, and order details. This step is an input where the purchase confirmation information is received, and an output where the delivery arrangement is completed. Specifically, this involves the server sending the order information to the delivery company and coordinating the delivery schedule.

[0095] (Application Example 1)

[0096] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0097] In today's busy lifestyles, efficiently managing meal plans and appropriately selecting ingredients and dishes to meet individual health goals is a challenging task. Furthermore, there is a need to purchase ingredients economically and efficiently by utilizing market sale information and to have them delivered quickly. Existing systems are not adequately addressing these challenges.

[0098] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0099] In this invention, the server includes means for inputting the user's biometric information and storing it in an information processing device, means for collecting product information from suppliers using a communication device, and means for generating an optimized meal menu based on user information and product information using a generative model. This makes it possible for users to easily select ingredients and dishes according to their health goals, obtain ingredients economically and efficiently by utilizing market sale information, and maintain healthy lifestyle habits.

[0100] "User biometric information" refers to personalized information such as each user's health status, eating habits, and allergy information.

[0101] An "information processing device" is a technological device for receiving, storing, and processing data.

[0102] A "communication device" is a technical means for exchanging data with suppliers or servers located in remote locations.

[0103] A "supplier" is a business or store that supplies goods or ingredients and provides information.

[0104] A "generative model" is a technology that includes algorithms that use artificial intelligence to generate or optimize data based on specific goals.

[0105] A "meal plan" is a daily meal plan designed based on nutritional balance and individual health goals.

[0106] A "health goal" is an individual objective set to achieve or maintain a specific state of health.

[0107] "Special offer information" refers to information regarding the price or supply conditions of goods or services offered in the market for a certain period of time.

[0108] "Ingredients" refer to food products or goods that are necessary for making a meal.

[0109] The system implementing this invention primarily functions through the coordinated operation of a server, information terminal, and user.

[0110] The server receives personal information from users, including biometric data, from information terminals and stores it in an internal database. The information terminals provide an interface for users to input detailed information such as their health status, eating habits, and specific health goals through a dedicated application. The server also collects product information from suppliers via communication devices, stores it in the database as special offer information, and plays a role in reflecting the latest prices and inventory status.

[0111] Using a generative model installed on the server, the system generates meal menus tailored to the user's health goals based on stored user and product information. This generative model utilizes nutritional data to select optimal ingredients and suggest nutritionally balanced meals. The server also automatically places orders for the generated ingredient list from a delivery service based on the user's selections.

[0112] For example, if a user is aiming for a low-carbohydrate diet, they can enter this information into the application, and the system will suggest meal menus using low-carbohydrate discounted products based on that information. The user can easily complete an order by selecting their desired ingredients from the menu through the application, and the selected ingredients will be delivered to their home via a delivery service.

[0113] Examples of input prompts for the generative AI model are as follows:

[0114] "User Profile: {Age: 35, Gender: Female, Health Goal: Low Carb, Preference: Japanese Food} Special Offer: {Chicken Breast: In Stock, On Sale} Generate a nutritionally balanced menu."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] Users use an information terminal to input personal information such as their biometric data, health goals, and eating habits through a dedicated application. The entered data is temporarily stored on the information terminal and then sent to a server. The server receives this data and stores it in a database.

[0118] Step 2:

[0119] The server periodically retrieves product information from suppliers via communication devices. This information includes product prices, inventory status, and special offer information. The server processes this data and stores it in a database, keeping the special offer information up-to-date.

[0120] Step 3:

[0121] The server operates an AI model using the user's personal information and collected product information. By providing the user's health goals, eating habits, and special offer information as input, the program generates an optimal meal plan based on nutritional management. Multiple menu options are presented to the user.

[0122] Step 4:

[0123] The user selects their preferred menu from the suggested meal options. Based on the selected menu, the server creates a list of necessary ingredients and organizes this list as order data for the delivery service.

[0124] Step 5:

[0125] The server uses the delivery service API to send order data organized based on user selections in the database. The transmitted information is used by the delivery service to process the order and deliver the selected ingredients to the address specified by the user.

[0126] Step 6:

[0127] Detailed information such as the delivery progress and estimated delivery time for the transportation service is returned to the server. The server processes this information and notifies the user via their information terminal. The user can then check the delivery status in the application and prepare for receipt.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention provides a more personalized service by combining an emotion engine with a system that proposes optimized meal plans based on the user's personal health information and information on special offers. This system functions through the mutual cooperation of the user, terminal, and server.

[0130] First, the user logs into the application or website and enters their eating habits, health status, allergy information, and food preferences. This information is transmitted to the server via the device and securely stored in a database. Furthermore, the device is equipped with a camera and sensors that detect the user's facial expressions and movements in real time.

[0131] The server periodically retrieves information on sale items through APIs from partner retailers. This allows the server to provide users with the latest price information. After this information is integrated, a generative model is activated to create a nutritionally balanced meal menu based on the user's input and the sale item information. The emotion engine estimates the user's emotions from their facial expressions and actions, and adjusts the meal choices based on those emotions. For example, if the user is feeling stressed, foods with relaxing effects will be suggested.

[0132] The generated meal menu and list of required ingredients are displayed on the terminal, allowing the user to review and select them. Once the ingredient selection is complete, the terminal sends the order information to the server, which processes the order and arranges delivery using the API of a partnered delivery service. At this stage, an emotion engine is used to adjust the order so that the most suitable ingredients for the user's current state are ordered.

[0133] This invention enables users to receive flexible meal suggestions tailored to their individual emotions and preferences, thereby improving the quality of their eating habits. By using an emotion engine, more context-aware personalization is achieved, increasing user satisfaction and improving shopping efficiency.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] Users log in to the application or website and enter information such as their dietary preferences, eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0137] Step 2:

[0138] The device uses cameras and sensors to detect the user's facial expressions and movements in real time and collect emotional data. This information is sent to an emotion engine to estimate the user's current emotional state.

[0139] Step 3:

[0140] The server connects via API to partner retailers to retrieve special offer information and updates the latest prices and stock availability. This information is stored in a database.

[0141] Step 4:

[0142] The server combines the user's personal information, emotional data from the emotion engine, and special offer information to create an optimal meal plan using a generative model. The generative model suggests menus tailored to the user's nutritional balance and emotional state.

[0143] Step 5:

[0144] The terminal displays a generated meal menu and a list of required ingredients to the user. The user can review the provided menu and make selections according to their preferences.

[0145] Step 6:

[0146] Once the user confirms their ingredient selection, the device sends this information to the server. The server uses the selected ingredient list to process the order via the API of a partner delivery service and arranges for the ingredients to be delivered.

[0147] Step 7:

[0148] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the delivery date, time, and delivery location details and make adjustments as needed.

[0149] This processing flow allows users to efficiently plan and procure healthy and economical meals while taking their individual emotional states into consideration.

[0150] (Example 2)

[0151] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0152] Modern consumers desire to consistently consume healthy foods, but often lack the knowledge and time to create proper meal plans. Furthermore, emotional fluctuations can influence food choices, making standard meal suggestions insufficient to fully address individual needs. Additionally, there is a need for quick and efficient means of purchasing and obtaining suggested meal menus.

[0153] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0154] In this invention, the server includes a device for inputting and storing the user's personal information in a database, a device for collecting product information from commercial facilities using an information acquisition device, and a device for creating an optimized nutritional intake plan based on user information and product information using a generation module. This enables healthy and personalized meal suggestions for individual users, and allows for the rapid and appropriate acquisition of ingredients based on those suggestions.

[0155] "User personal information" refers to individual information including the user's health status, eating habits, allergy information, and food preferences.

[0156] A "database" is an information storage system used to efficiently store and manage data handled by a system, such as users' personal information and product information.

[0157] An "information acquisition device" is a hardware or software mechanism for collecting product information from commercial facilities or other information sources.

[0158] A "generation module" is a software unit that implements an algorithm for creating a nutritional intake plan based on the user's personal information and product information.

[0159] A "nutritional intake plan" is a suggestion of a balanced meal menu based on the user's health information and available product information.

[0160] "Commercial facilities" is a broad concept that refers to retailers that sell goods, stores that provide food ingredients, and so on.

[0161] A "sensor" is a device used to detect data on user actions and the environment.

[0162] A "camera" is a device used to capture images and analyze a user's facial expressions and gestures.

[0163] "Delivery method" refers to a service or system for delivering listed goods to a specified destination.

[0164] A "request" is a formal request to purchase or deliver a list of items.

[0165] This invention is a system in which a user, a terminal, and a server work in cooperation with each other. The user first uses an application or website and inputs personal information such as eating habits, health status, allergy information, and food preferences via the terminal. The terminal is equipped with a camera and sensors, which can detect the user's facial expressions and movements in real time.

[0166] The terminal sends the collected information to the server via the internet. The server first stores the user's personal information in a database. Next, it periodically calls the commercial facility's API using an information acquisition device to retrieve the latest information such as special offers and new products. This process typically uses the Python requests library.

[0167] The server integrates product information obtained from commercial facilities with the user's personal information and activates a generation module. This module uses machine learning frameworks such as TENSORFLOW® to generate a nutritional intake plan tailored to the user's needs. The prompt used at this time is "Please create an optimal nutritional intake plan based on user information and product information."

[0168] Furthermore, the server analyzes the user's facial expression data sent from the terminal to obtain emotional information. This allows the system to adjust the menu to include foods with relaxing effects if the user is experiencing stress. An emotional analysis service is used for this emotional analysis.

[0169] The generated nutritional intake plan and list of necessary items are sent from the server to the terminal and displayed on the user's screen. The user selects the most suitable option from these menus and confirms the information on the selected items.

[0170] Finally, the selected item list is sent from the terminal to the server. Based on this information, the server confirms the order using the shipping method's API and executes optimized delivery. In this process, it is common to use a web framework such as Django to interact with the API.

[0171] This invention provides a personalized meal plan tailored to the user's individual needs and emotional state, and further enables the rapid and efficient procurement of ingredients based on that plan. As a result, it can contribute to maintaining a healthy diet.

[0172] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0173] Step 1:

[0174] Users enter their eating habits, health status, allergy information, and dietary preferences using an application or website. The entered data is sent to the device and formatted in JSON format. The device then sends this to the server using the HTTPS protocol. By processing the input data, the server generates an individual user profile and stores it in a database.

[0175] Step 2:

[0176] The server periodically calls the commercial facility's API using an information acquisition device to retrieve product information. This data is received in JSON format and stored in the product database. When calling the API and retrieving product information using the Python requests library, the data is filtered and formatted to extract the necessary list of product information.

[0177] Step 3:

[0178] The server uses a generation module to create an optimized nutrition plan based on the user's personal information and product information. It takes user profile and product information as input and processes it with an AI model. The generation AI model uses TensorFlow, and the prompt is "Create an optimal nutrition plan based on user and product information." As a result, a list of meal menu options is output.

[0179] Step 4:

[0180] The device receives the nutritional intake plan transmitted from the server and adjusts the displayed meal menu using data from the user's facial expression sensor. During this process, the device analyzes the user's emotional state in real time and displays the adjusted menu on the screen. Emotional analysis software is used to make adjustments such as adding foods with relaxing effects to the menu.

[0181] Step 5:

[0182] The user makes a selection from the meal menu displayed on the terminal. Once the selection is confirmed, the terminal generates a list of selected items and sends it to the server. The server uses the item information based on the selected menu as input data for the next order processing.

[0183] Step 6:

[0184] The server processes the order by calling the shipping API based on the received list of items. It uses the Django framework to generate API requests, determine the best shipping option, and confirm the order. Finally, the order information is sent to the shipping service, and the output includes a delivery schedule and confirmation information.

[0185] (Application Example 2)

[0186] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0187] In today's world, optimizing individual meal plans based on health information, product pricing, and personal emotions is challenging. Traditional systems have failed to adequately consider user emotional states, resulting in a lack of convenience and satisfaction. Therefore, there is a need for a system that provides personalized meal suggestions based on user emotions and personal information, and efficiently procures ingredients based on that plan.

[0188] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0189] In this invention, the server includes means for storing information in a database based on the user's personal health information and dietary preferences, means for collecting product information from distributors, means for creating an optimized meal plan using a generative model and sentiment evaluation, and means for adjusting meal options according to the user's emotional state. This makes it possible to suggest meals that are tailored to each user's health condition and emotions, thereby providing a highly satisfying diet.

[0190] "Personal health information" refers to information related to an individual's body, such as the user's health status, dietary preferences, and allergy information.

[0191] "Product information" refers to information obtained from distributors, such as the product name, price, and special sale status.

[0192] A "generative model" is an algorithm or program that generates an optimal meal plan based on input data.

[0193] "Emotional assessment" is a technique or algorithm used to estimate a user's emotional state based on their facial expressions and actions.

[0194] A "meal plan" is a suggestion of optimized meal content and menus that take into account the user's health information and emotional state.

[0195] A "food ingredient list" is a list of all the ingredients needed for a meal plan, and is used when ordering or having food delivered.

[0196] To implement this invention, a system is constructed in which a server, terminal, and user work in cooperation with each other. The server has the function of receiving personal health information and dietary preferences provided by the user and securely storing them in a database. It also periodically collects product information and special offer information through APIs of distributors. Based on this data, the server uses a generative AI model to create an optimal meal plan. The generative model is developed using machine learning frameworks such as Python and TensorFlow.

[0197] The device is equipped with cameras and sensors that detect the user's facial expressions and movements in real time. This allows the system to estimate the user's emotional state and send that information to a server. The server then performs an emotional assessment and adjusts the meal options according to the user's emotions. Specifically, it has a function to generate menus that prioritize ingredients with relaxing effects.

[0198] The user reviews this information on their device and lists the necessary ingredients based on their selected meal plan. The listed ingredients are then ordered using the delivery service's API. Once the user completes their selection, the server receives the order information and arranges for the ingredients to be delivered through the partner delivery service.

[0199] This system allows users to receive personalized, healthy, and economical meal suggestions. For example, a user experiencing stress might be recommended chamomile tea or foods with massage-like effects. The generating AI model can be made more appropriate by inputting prompts such as, "Generate the optimal meal menu for when the user's emotional state is determined to be stressed."

[0200] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0201] Step 1:

[0202] Users input their eating habits, health status, allergy information, and food preferences through their terminal. The entered information is sent directly to the server and stored in the database. Here, the process of registering the user's individual information in digital format into the database takes place.

[0203] Step 2:

[0204] The device uses cameras and sensors to detect the user's facial expressions and movements in real time. The detected data is used as input to estimate the user's emotional state. This allows the user's current emotions to be categorized as "relaxed" or "stressed," and then sent to the server.

[0205] Step 3:

[0206] The server collects product information via APIs from partner distributors. This information includes product names, prices, and special offer information, and is used to update the price information database.

[0207] Step 4:

[0208] The server uses a generative AI model to integrate the user's health information and product information to generate an optimized meal plan. This process uses TensorFlow to analyze the input data and output a menu that considers nutritional balance. The prompt used is, "Generate the optimal meal menu when the user's emotional state is determined to be stressed."

[0209] Step 5:

[0210] The meal plan received from the server is displayed to the user on the terminal. The user reviews the suggested menu and selects the necessary ingredients. The selected ingredients are sent to the server as an ingredient list.

[0211] Step 6:

[0212] The server processes orders via the delivery service's API based on the ingredient list. The API is used to send order data to the delivery service, arranging for the ingredients to be delivered to the user's address. The order status is also fed back to the user's device in real time.

[0213] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0214] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0215] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0216] [Second Embodiment]

[0217] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0218] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0219] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0220] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0221] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0222] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0223] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0224] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0225] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0226] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0227] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0228] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0229] This invention is a system that efficiently supports users' meal planning, providing daily meal menu suggestions based on the user's personal information and enabling the purchase of ingredients. This system functions through the coordinated operation of a server, terminals, and users.

[0230] (User information input)

[0231] Users access a dedicated application or website and log in to their account. Here, users enter detailed information such as their eating habits, health status, and allergy information, and register their dietary preferences. This personal information is transmitted to a server via the device and stored in a database.

[0232] (Collecting information on special offers)

[0233] The server accesses the APIs of partner retailers via the internet to periodically retrieve the latest sale information. This ensures that the server is ready to provide users with the most up-to-date product prices and inventory information.

[0234] (Generating the optimal menu)

[0235] When a user sends a request to the application, a generative model on the server is activated. Based on user information and special offer information stored on the server, the generative model suggests several optimal daily menus that are nutritionally balanced. For example, if a user requests a low-fat, high-protein diet and chicken breast is on sale, healthy dishes using chicken breast will be suggested.

[0236] (Creating and verifying the ingredient list)

[0237] The terminal lists the necessary ingredients and their quantities based on the generated menu. This list is displayed to the user, who can then select the ingredients to purchase. Using sale items allows for economically efficient purchasing.

[0238] (Ordering and delivery of ingredients)

[0239] Once a user confirms their order by selecting ingredients from a list, this information is sent to the server via their device. The server automatically processes the order using the API of a partner delivery service and arranges delivery. The user is also notified of details such as the scheduled delivery date and time, ensuring they can receive their order with peace of mind.

[0240] The system of this invention allows users to effectively utilize sale items while leading a healthy and efficient diet. Furthermore, the automation of cumbersome shopping procedures contributes to saving users time and effort.

[0241] The following describes the processing flow.

[0242] Step 1:

[0243] Users log in to an application or website and enter personal information such as eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0244] Step 2:

[0245] The server, through scheduled tasks, accesses the APIs of partner retailers to automatically retrieve information on special offers. This information is then analyzed and stored in a database as the most up-to-date version.

[0246] Step 3:

[0247] When a user submits a meal plan request from the application, the device relays this request to the server. The request includes a link to the user's personal information.

[0248] Step 4:

[0249] The server launches a generative model, inputting saved user information and sale item information to generate optimal daily meal menus. The model considers nutritional balance and the use of sale items, and proposes multiple menu options.

[0250] Step 5:

[0251] The terminal displays the generated menu on the user's screen, listing the required ingredients and their quantities. The user can review the list and add or remove items as needed.

[0252] Step 6:

[0253] Once the user confirms their order, the terminal sends the selected ingredient information to the server. The server then sends the order data to the API of a partner delivery service, which automatically arranges delivery.

[0254] Step 7:

[0255] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the scheduled delivery date, time, and delivery location.

[0256] (Example 1)

[0257] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0258] Modern consumers are expected to create meal plans tailored to their individual nutritional needs for health management purposes. However, efficiently determining what ingredients to buy and where to obtain them is not easy. Furthermore, the process from creating shopping lists to purchasing goods and delivery is a time-consuming and cumbersome one for consumers.

[0259] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0260] In this invention, the server includes means for inputting the user's personal attributes and storing them in a recording device, means for aggregating product information from suppliers using an information acquisition device, and means for generating optimized meal suggestions based on the user attributes and product information using a generation AI model. This enables the user to efficiently create a healthy meal plan and acquire ingredients.

[0261] "User personal attributes" refer to information related to an individual user's dietary habits, such as eating habits, health status, allergy information, and food preferences.

[0262] A "recording device" is a device such as a database or server used to store digital information.

[0263] An "information acquisition device" is a device that collects product information from a vendor's system via the internet.

[0264] A "vendor" refers to a retailer or wholesaler that provides goods.

[0265] A "generative AI model" is an artificial intelligence model that generates optimized meal suggestions based on input user attributes and product information.

[0266] "Meal suggestions" refer to suggestions for nutritionally balanced meal menus and recipes that are tailored to the user's needs.

[0267] "Items" refers to the ingredients and related consumables listed based on the meal proposal.

[0268] A "delivery company" is a company that provides a service of transporting food or products to a designated location after purchase.

[0269] "Request submission" is the procedure of requesting a delivery company to arrange delivery based on information about the purchased items.

[0270] This invention is a system designed to support users in maintaining a healthy diet, and it functions through the coordinated efforts of the user, terminal, and server.

[0271] Users access their accounts using a dedicated application or website and input personal attributes such as eating habits, health status, allergy information, and food preferences. Based on this information, it is possible to provide personalized meal suggestions to the user.

[0272] The terminal transmits the above user information to the server and securely stores it in a recording device (database). The stored information is processed using a generative AI model. This model operates on the server and generates nutritionally balanced meal suggestions based on user attributes and product information collected from vendors. This process is achieved by the information acquisition device accessing the vendor's API via the internet and transmitting product information to the server.

[0273] For example, if a user requests a health-conscious, low-fat, high-protein menu, the server will suggest healthy recipes using chicken breast, which has been entered as a special offer. An example of a prompt message the user might enter would be: "Please generate this week's meal menu. I would like low-fat, high-protein dishes. Please let me know if you have any recipes using chicken breast."

[0274] The server creates a list of necessary items based on the generated meal suggestions. This list is presented to the user via a terminal, allowing the user to select suitable ingredients and confirm their purchase. Finally, the terminal sends this information back to the server, which automatically places an order with the delivery company. This allows the user to efficiently obtain the necessary ingredients.

[0275] As described above, this system efficiently supports users' healthy eating habits by combining generative AI models and communication technologies.

[0276] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0277] Step 1:

[0278] The user accesses the application or website and logs into their account. After logging in, they enter personal attributes such as eating habits, health status, allergy information, and food preferences. The entered information is transmitted to the server via the device and stored on the recording device. In this step, the user's personal attributes are the input data, and the transmission to the server and storage are the output. Specifically, this involves the user filling out information in a form on the screen, approving it, and submitting it.

[0279] Step 2:

[0280] The server uses an information acquisition device to access the vendor's API and collect product information. This includes data such as sale information, product name, price, and inventory status. The collected data is sent to the server to prepare for future processing. The input for this step is the product information obtained from the vendor's API, and the output is the storage of the collected product information on the server. Specifically, the server periodically accesses the API and queries the data.

[0281] Step 3:

[0282] The user enters a prompt message in the application that includes their desired dietary style (e.g., low-fat, high-protein) and submits a request for a meal menu. The generative AI model uses user attributes and product information stored on the server to generate optimized meal suggestions. Specifically, it analyzes the user's request to create a nutritionally balanced menu. In this step, the prompt message is the input and the meal suggestions are the output. This includes the actions of the generative AI model in processing the request.

[0283] Step 4:

[0284] The server performs the task of listing the necessary items based on the generated meal suggestions. The listed data is provided to the user through the terminal. The user checks the list and selects the items they want to purchase. The input for this step is the meal suggestion, and the output is the item list. The specific operation mainly involves analyzing the proposed menu and creating the list.

[0285] Step 5:

[0286] When the user confirms the purchase, the terminal sends this information back to the server. The server automatically processes the order and arranges the delivery using the API of the delivery provider. The delivery date and time and order details are notified to the user again. This step takes the purchase confirmation information as the input and the implementation of the delivery arrangement as the output. The specific operations include the server sending the order information to the delivery provider and adjusting the delivery schedule.

[0287] (Application Example 1)

[0288] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0289] In modern times, efficiently managing meal plans and appropriately selecting ingredients and dishes according to personal health goals is a difficult task in a busy lifestyle. Also, it is required to purchase ingredients economically and efficiently using market special offer information and deliver them quickly. These issues cannot be fully addressed by existing systems.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0291] In this invention, the server includes means for inputting the user's biometric information and storing it in an information processing device, means for collecting product information from suppliers using a communication device, and means for generating an optimized meal menu based on user information and product information using a generative model. This makes it possible for users to easily select ingredients and dishes according to their health goals, obtain ingredients economically and efficiently by utilizing market sale information, and maintain healthy lifestyle habits.

[0292] "User biometric information" refers to personalized information such as each user's health status, eating habits, and allergy information.

[0293] An "information processing device" is a technological device for receiving, storing, and processing data.

[0294] A "communication device" is a technical means for exchanging data with suppliers or servers located in remote locations.

[0295] A "supplier" is a business or store that supplies goods or ingredients and provides information.

[0296] A "generative model" is a technology that includes algorithms that use artificial intelligence to generate or optimize data based on specific goals.

[0297] A "meal menu" refers to a daily meal plan designed based on nutritional balance and individual health goals.

[0298] A "health goal" is an individual objective set to achieve or maintain a specific state of health.

[0299] "Special offer information" refers to information regarding the price or supply conditions of goods or services offered in the market for a certain period of time.

[0300] "Ingredients" refer to food products or goods that are necessary for making a meal.

[0301] The system for implementing this invention mainly functions through the cooperation of a server, an information terminal, and a user.

[0302] The server receives the personal information of the user including biometric information from the information terminal and stores it in an internal database. The information terminal provides an interface for the user to input details such as health status, eating habits, and specific health goals through a dedicated application. Also, the server collects product information from suppliers via a communication device, accumulates it in the database as special sale information, and is responsible for reflecting the latest prices and inventory status.

[0303] Using the generation model installed on the server, a diet menu suitable for the user's health goals is generated based on the stored user information and product information. This generation model utilizes data related to nutrition science to provide diet proposals with optimal ingredient selection and balanced nutrition. Also, the server executes procedures to automatically order the generated ingredient list to a transportation service based on the user's selection.

[0304] As a specific example, when a user aims for a diet with limited carbohydrate intake and inputs that information into the application, the system proposes a diet menu that utilizes special sale products with low carbohydrates based on that information. The user can easily complete the order by selecting favorite ingredients from the menu through the application, and the selected ingredients will be delivered to their home through a transportation service.

[0305] Examples of input prompts for the generation AI model are as follows:

[0306] "User profile: {age: 35, gender: female, health goal: carbohydrate restriction, preference: Japanese cuisine} Special sale items: {chicken breast: in stock, on sale} Generate a nutritionally balanced menu."

[0307] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0308] Step 1:

[0309] Users use an information terminal to input personal information such as their biometric data, health goals, and eating habits through a dedicated application. The entered data is temporarily stored on the information terminal and then sent to a server. The server receives this data and stores it in a database.

[0310] Step 2:

[0311] The server periodically retrieves product information from suppliers via communication devices. This information includes product prices, inventory status, and special offer information. The server processes this data and stores it in a database, keeping the special offer information up-to-date.

[0312] Step 3:

[0313] The server operates an AI model using the user's personal information and collected product information. By providing the user's health goals, eating habits, and special offer information as input, the program generates optimal meal plans based on nutritional management. Multiple menus are presented to the user.

[0314] Step 4:

[0315] The user selects their preferred menu from the suggested meal options. Based on the selected menu, the server creates a list of necessary ingredients and organizes this list as order data for the delivery service.

[0316] Step 5:

[0317] The server uses the delivery service API to send order data organized based on user selections in the database. The transmitted information is used by the delivery service to process the order and deliver the selected ingredients to the address specified by the user.

[0318] Step 6:

[0319] Detailed information such as the delivery progress and estimated delivery time for the transportation service is returned to the server. The server processes this information and notifies the user via their information terminal. The user can then check the delivery status in the application and prepare for receipt.

[0320] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0321] This invention provides a more personalized service by combining an emotion engine with a system that proposes optimized meal plans based on the user's personal health information and information on special offers. This system functions through the mutual cooperation of the user, terminal, and server.

[0322] First, the user logs into the application or website and enters their eating habits, health status, allergy information, and food preferences. This information is transmitted to the server via the device and securely stored in a database. Furthermore, the device is equipped with a camera and sensors that detect the user's facial expressions and movements in real time.

[0323] The server periodically retrieves information on sale items through APIs from partner retailers. This allows the server to provide users with the latest price information. After this information is integrated, a generative model is activated to create a nutritionally balanced meal menu based on the user's input and the sale item information. The emotion engine estimates the user's emotions from their facial expressions and actions, and adjusts the meal choices based on those emotions. For example, if the user is feeling stressed, foods with relaxing effects will be suggested.

[0324] The generated meal menu and list of required ingredients are displayed on the terminal, allowing the user to review and select them. Once the ingredient selection is complete, the terminal sends the order information to the server, which processes the order and arranges delivery using the API of a partnered delivery service. At this stage, an emotion engine is used to adjust the order so that the most suitable ingredients for the user's current state are ordered.

[0325] This invention enables users to receive flexible meal suggestions tailored to their individual emotions and preferences, thereby improving the quality of their eating habits. By using an emotion engine, more context-aware personalization is achieved, increasing user satisfaction and improving shopping efficiency.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] Users log in to the application or website and enter information such as their dietary preferences, eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0329] Step 2:

[0330] The device uses cameras and sensors to detect the user's facial expressions and movements in real time and collect emotional data. This information is sent to an emotion engine to estimate the user's current emotional state.

[0331] Step 3:

[0332] The server connects via API to partner retailers to retrieve special offer information and updates the latest prices and stock availability. This information is stored in a database.

[0333] Step 4:

[0334] The server combines the user's personal information, emotional data from the emotion engine, and special offer information to create an optimal meal plan using a generative model. The generative model suggests menus tailored to the user's nutritional balance and emotional state.

[0335] Step 5:

[0336] The terminal displays a generated meal menu and a list of required ingredients to the user. The user can review the provided menu and make selections according to their preferences.

[0337] Step 6:

[0338] Once the user confirms their ingredient selection, the device sends this information to the server. The server uses the selected ingredient list to process the order via the API of a partner delivery service and arranges for the ingredients to be delivered.

[0339] Step 7:

[0340] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the delivery date, time, and delivery location details and make adjustments as needed.

[0341] This processing flow allows users to efficiently plan and procure healthy and economical meals while taking their individual emotional states into consideration.

[0342] (Example 2)

[0343] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0344] Modern consumers desire to consistently consume healthy foods, but often lack the knowledge and time to create proper meal plans. Furthermore, emotional fluctuations can influence food choices, making standard meal suggestions insufficient to fully address individual needs. Additionally, there is a need for quick and efficient means of purchasing and obtaining suggested meal menus.

[0345] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0346] In this invention, the server includes a device for inputting and storing the user's personal information in a database, a device for collecting product information from commercial facilities using an information acquisition device, and a device for creating an optimized nutritional intake plan based on user information and product information using a generation module. This enables healthy and personalized meal suggestions for individual users, and allows for the rapid and appropriate acquisition of ingredients based on those suggestions.

[0347] "User personal information" refers to individual information including the user's health status, eating habits, allergy information, and food preferences.

[0348] A "database" is an information storage system used to efficiently store and manage data handled by a system, such as users' personal information and product information.

[0349] An "information acquisition device" is a hardware or software mechanism for collecting product information from commercial facilities or other information sources.

[0350] A "generation module" is a software unit that implements an algorithm for creating a nutritional intake plan based on the user's personal information and product information.

[0351] A "nutritional intake plan" is a suggestion of a balanced meal menu based on the user's health information and available product information.

[0352] "Commercial facilities" is a broad concept that refers to retailers that sell goods, stores that provide food ingredients, and so on.

[0353] A "sensor" is a device used to detect data on user actions and the environment.

[0354] A "camera" is a device used to capture images and analyze a user's facial expressions and gestures.

[0355] "Delivery method" refers to a service or system for delivering listed goods to a specified destination.

[0356] A "request" is a formal request to purchase or deliver a list of items.

[0357] This invention is a system in which a user, a terminal, and a server work in cooperation with each other. The user first uses an application or website and inputs personal information such as eating habits, health status, allergy information, and food preferences via the terminal. The terminal is equipped with a camera and sensors, which can detect the user's facial expressions and movements in real time.

[0358] The terminal sends the collected information to the server via the internet. The server first stores the user's personal information in a database. Next, it periodically calls the commercial facility's API using an information acquisition device to retrieve the latest information such as special offers and new products. This process typically uses the Python requests library.

[0359] The server integrates product information obtained from commercial facilities with the user's personal information and launches a generation module. This module uses a machine learning framework such as TensorFlow to generate a nutritional intake plan tailored to the user's needs. The prompt used during this process is "Please create an optimal nutritional intake plan based on user information and product information."

[0360] Furthermore, the server analyzes the user's facial expression data sent from the terminal to obtain emotional information. This allows the system to adjust the menu to include foods with relaxing effects if the user is experiencing stress. An emotional analysis service is used for this emotional analysis.

[0361] The generated nutritional intake plan and list of necessary items are sent from the server to the terminal and displayed on the user's screen. The user selects the most suitable option from these menus and confirms the information on the selected items.

[0362] Finally, the selected item list is sent from the terminal to the server. Based on this information, the server confirms the order using the shipping method's API and executes optimized delivery. In this process, it is common to use a web framework such as Django to interact with the API.

[0363] This invention provides a personalized meal plan tailored to the user's individual needs and emotional state, and further realizes a system that enables the rapid and efficient procurement of ingredients based on that plan. As a result, it can contribute to maintaining a healthy diet.

[0364] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0365] Step 1:

[0366] Users enter their eating habits, health status, allergy information, and dietary preferences using an application or website. The entered data is sent to the device and formatted in JSON format. The device then sends this to the server using the HTTPS protocol. By processing the input data, the server generates an individual user profile and stores it in a database.

[0367] Step 2:

[0368] The server periodically calls the commercial facility's API using an information acquisition device to retrieve product information. This data is received in JSON format and stored in the product database. When calling the API and retrieving product information using the Python requests library, the data is filtered and formatted to extract the necessary list of product information.

[0369] Step 3:

[0370] The server uses a generation module to create an optimized nutrition plan based on the user's personal information and product information. It takes user profile and product information as input and processes it with an AI model. The generation AI model uses TensorFlow, and the prompt is "Create an optimal nutrition plan based on user and product information." As a result, a list of meal menu options is output.

[0371] Step 4:

[0372] The device receives the nutritional intake plan transmitted from the server and adjusts the displayed meal menu using data from the user's facial expression sensor. During this process, the device analyzes the user's emotional state in real time and displays the adjusted menu on the screen. Emotional analysis software is used to make adjustments such as adding foods with relaxing effects to the menu.

[0373] Step 5:

[0374] The user makes a selection from the meal menu displayed on the terminal. Once the selection is confirmed, the terminal generates a list of selected items and sends it to the server. The server uses the item information based on the selected menu as input data for the next order processing.

[0375] Step 6:

[0376] The server processes the order by calling the shipping API based on the received list of items. It uses the Django framework to generate API requests, determine the best shipping option, and confirm the order. Finally, the order information is sent to the shipping service, and the output includes a delivery schedule and confirmation information.

[0377] (Application Example 2)

[0378] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0379] In today's world, optimizing individual meal plans based on health information, product pricing, and personal emotions is challenging. Traditional systems have failed to adequately consider user emotional states, resulting in a lack of convenience and satisfaction. Therefore, there is a need for a system that provides personalized meal suggestions based on user emotions and personal information, and efficiently procures ingredients based on that plan.

[0380] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0381] In this invention, the server includes means for storing information in a database based on the user's personal health information and dietary preferences, means for collecting product information from distributors, means for creating an optimized meal plan using a generative model and sentiment evaluation, and means for adjusting meal options according to the user's emotional state. This makes it possible to suggest meals that are tailored to each user's health condition and emotions, thereby providing a highly satisfying diet.

[0382] "Personal health information" refers to information related to an individual's body, such as the user's health status, dietary preferences, and allergy information.

[0383] "Product information" refers to information obtained from distributors, such as the product name, price, and special sale status.

[0384] A "generative model" is an algorithm or program that generates an optimal meal plan based on input data.

[0385] "Emotional assessment" is a technique or algorithm used to estimate a user's emotional state based on their facial expressions and actions.

[0386] A "meal plan" is a suggestion of optimized meal content and menus that take into account the user's health information and emotional state.

[0387] A "food ingredient list" is a list of all the ingredients needed for a meal plan, and is used when ordering or having food delivered.

[0388] To implement this invention, a system is constructed in which a server, terminal, and user work in cooperation with each other. The server has the function of receiving personal health information and dietary preferences provided by the user and securely storing them in a database. It also periodically collects product information and special offer information through APIs of distributors. Based on this data, the server uses a generative AI model to create an optimal meal plan. The generative model is developed using machine learning frameworks such as Python and TensorFlow.

[0389] The device is equipped with cameras and sensors that detect the user's facial expressions and movements in real time. This allows the system to estimate the user's emotional state and send that information to a server. The server then performs an emotional assessment and adjusts the meal options according to the user's emotions. Specifically, it has a function to generate menus that prioritize ingredients with relaxing effects.

[0390] The user reviews this information on their device and lists the necessary ingredients based on their selected meal plan. The listed ingredients are then ordered using the delivery service's API. Once the user completes their selection, the server receives the order information and arranges for the ingredients to be delivered through the partner delivery service.

[0391] This system allows users to receive personalized, healthy, and economical meal suggestions. For example, a user experiencing stress might be recommended chamomile tea or foods with massage-like effects. The generating AI model can be made more appropriate by inputting prompts such as, "Generate the optimal meal menu for when the user's emotional state is determined to be stressed."

[0392] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0393] Step 1:

[0394] Users input their eating habits, health status, allergy information, and food preferences through their terminal. The entered information is sent directly to the server and stored in the database. Here, the process of registering the user's individual information in digital format into the database takes place.

[0395] Step 2:

[0396] The device uses cameras and sensors to detect the user's facial expressions and movements in real time. The detected data is used as input to estimate the user's emotional state. This allows the user's current emotions to be categorized as "relaxed" or "stressed," and then sent to the server.

[0397] Step 3:

[0398] The server collects product information via APIs from partner distributors. This information includes product names, prices, and special offer information, and is used to update the price information database.

[0399] Step 4:

[0400] The server uses a generative AI model to integrate the user's health information and product information to generate an optimized meal plan. This process uses TensorFlow to analyze the input data and output a menu that considers nutritional balance. The prompt used is, "Generate the optimal meal menu when the user's emotional state is determined to be stressed."

[0401] Step 5:

[0402] The meal plan received from the server is displayed to the user on the terminal. The user reviews the suggested menu and selects the necessary ingredients. The selected ingredients are sent to the server as an ingredient list.

[0403] Step 6:

[0404] The server processes orders via the delivery service's API based on the ingredient list. The API is used to send order data to the delivery service, which then arranges for the ingredients to be delivered to the user's address. The order status is also fed back to the user's device in real time.

[0405] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0406] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0407] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0408] [Third Embodiment]

[0409] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0410] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0411] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0412] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0413] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0414] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0415] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0416] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0417] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0418] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0419] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0420] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0421] This invention is a system that efficiently supports users' meal planning, providing daily meal menu suggestions based on the user's personal information and enabling the purchase of ingredients. This system functions through the coordinated operation of a server, terminals, and users.

[0422] (User information input)

[0423] Users access a dedicated application or website and log in to their account. Here, users enter detailed information such as their eating habits, health status, and allergy information, and register their dietary preferences. This personal information is transmitted to a server via the device and stored in a database.

[0424] (Collecting information on special offers)

[0425] The server accesses the APIs of partner retailers via the internet to periodically retrieve the latest sale information. This ensures that the server is ready to provide users with the most up-to-date product prices and inventory information.

[0426] (Generating the optimal menu)

[0427] When a user sends a request to the application, a generative model on the server is activated. Based on user information and special offer information stored on the server, the generative model suggests several optimal daily menus that are nutritionally balanced. For example, if a user requests a low-fat, high-protein diet and chicken breast is on sale, healthy dishes using chicken breast will be suggested.

[0428] (Creating and verifying the ingredient list)

[0429] The terminal lists the necessary ingredients and their quantities based on the generated menu. This list is displayed to the user, who can then select the ingredients to purchase. Using sale items allows for economically efficient purchasing.

[0430] (Ordering and delivery of ingredients)

[0431] Once a user confirms their order by selecting ingredients from a list, this information is sent to the server via their device. The server automatically processes the order using the API of a partner delivery service and arranges delivery. The user is also notified of details such as the scheduled delivery date and time, ensuring they can receive their order with peace of mind.

[0432] The system of this invention allows users to effectively utilize sale items while leading a healthy and efficient diet. Furthermore, the automation of cumbersome shopping procedures contributes to saving users time and effort.

[0433] The following describes the processing flow.

[0434] Step 1:

[0435] Users log in to an application or website and enter personal information such as eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0436] Step 2:

[0437] The server, through scheduled tasks, accesses the APIs of partner retailers to automatically retrieve information on special offers. This information is then analyzed and stored in a database as the most up-to-date version.

[0438] Step 3:

[0439] When a user submits a meal plan request from the application, the device relays this request to the server. The request includes a link to the user's personal information.

[0440] Step 4:

[0441] The server launches a generative model, inputting saved user information and sale item information to generate optimal daily meal menus. The model considers nutritional balance and the use of sale items, and proposes multiple menu options.

[0442] Step 5:

[0443] The terminal displays the generated menu on the user's screen, listing the required ingredients and their quantities. The user can review the list and add or remove items as needed.

[0444] Step 6:

[0445] Once the user confirms their order, the terminal sends the selected ingredient information to the server. The server then sends the order data to the API of a partner delivery service, which automatically arranges delivery.

[0446] Step 7:

[0447] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the scheduled delivery date, time, and delivery location.

[0448] (Example 1)

[0449] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0450] Modern consumers are expected to create meal plans tailored to their individual nutritional needs for health management purposes. However, efficiently determining what ingredients to buy and where to obtain them is not easy. Furthermore, the process from creating shopping lists to purchasing goods and delivery is a time-consuming and cumbersome one for consumers.

[0451] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0452] In this invention, the server includes means for inputting the user's personal attributes and storing them in a recording device, means for aggregating product information from suppliers using an information acquisition device, and means for generating optimized meal suggestions based on the user attributes and product information using a generation AI model. This enables the user to efficiently create a healthy meal plan and acquire ingredients.

[0453] "User personal attributes" refer to information related to an individual user's dietary habits, such as eating habits, health status, allergy information, and food preferences.

[0454] A "recording device" is a device such as a database or server used to store digital information.

[0455] An "information acquisition device" is a device that collects product information from a vendor's system via the internet.

[0456] A "vendor" refers to a retailer or wholesaler that provides goods.

[0457] A "generative AI model" is an artificial intelligence model that generates optimized meal suggestions based on input user attributes and product information.

[0458] "Meal suggestions" refer to suggestions for nutritionally balanced meal menus and recipes that are tailored to the user's needs.

[0459] "Items" refers to the ingredients and related consumables listed based on the meal proposal.

[0460] A "delivery company" is a company that provides a service of transporting food or products to a designated location after purchase.

[0461] "Request submission" is the procedure of requesting a delivery company to arrange delivery based on information about the purchased items.

[0462] This invention is a system designed to support users in maintaining a healthy diet, and it functions through the coordinated efforts of the user, terminal, and server.

[0463] Users access their accounts using a dedicated application or website and input personal attributes such as eating habits, health status, allergy information, and food preferences. Based on this information, it is possible to provide personalized meal suggestions to the user.

[0464] The terminal transmits the above user information to the server and securely stores it in a recording device (database). The stored information is processed using a generative AI model. This model operates on the server and generates nutritionally balanced meal suggestions based on user attributes and product information collected from vendors. This process is achieved by the information acquisition device accessing the vendor's API via the internet and transmitting product information to the server.

[0465] For example, if a user requests a health-conscious, low-fat, high-protein menu, the server will suggest healthy recipes using chicken breast, which has been entered as a special offer. An example of a prompt message the user might enter would be: "Please generate this week's meal menu. I would like low-fat, high-protein dishes. Please let me know if you have any recipes using chicken breast."

[0466] The server creates a list of necessary items based on the generated meal suggestions. This list is presented to the user via a terminal, allowing the user to select suitable ingredients and confirm their purchase. Finally, the terminal sends this information back to the server, which automatically places an order with the delivery company. This allows the user to efficiently obtain the necessary ingredients.

[0467] As described above, this system efficiently supports users' healthy eating habits by combining generative AI models and communication technologies.

[0468] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0469] Step 1:

[0470] The user accesses the application or website and logs into their account. After logging in, they enter personal attributes such as eating habits, health status, allergy information, and food preferences. The entered information is transmitted to the server via the device and stored on the recording device. In this step, the user's personal attributes are the input data, and the transmission to the server and storage are the output. Specifically, this involves the user filling out information in a form on the screen, approving it, and submitting it.

[0471] Step 2:

[0472] The server uses an information acquisition device to access the vendor's API and collect product information. This includes data such as sale information, product name, price, and inventory status. The collected data is sent to the server to prepare for future processing. The input for this step is the product information obtained from the vendor's API, and the output is the storage of the collected product information on the server. Specifically, the server periodically accesses the API and queries the data.

[0473] Step 3:

[0474] The user enters a prompt message in the application that includes their desired dietary style (e.g., low-fat, high-protein) and submits a request for a meal menu. The generative AI model uses user attributes and product information stored on the server to generate optimized meal suggestions. Specifically, it analyzes the user's request to create a nutritionally balanced menu. In this step, the prompt message is the input and the meal suggestions are the output. This includes the actions of the generative AI model in processing the request.

[0475] Step 4:

[0476] The server creates a list of necessary items based on the generated meal suggestions. This list is then provided to the user via a terminal. The user reviews the list and selects the items they wish to purchase. The input for this step is the meal suggestion, and the output is the item list. The specific operation primarily involves analyzing the suggested menu and creating the list.

[0477] Step 5:

[0478] Once the user confirms their purchase, the terminal sends this information back to the server. The server automatically processes the order and arranges delivery using the delivery company's API. The user is then notified of the delivery date, time, and order details. This step is an input where the purchase confirmation information is received, and an output where the delivery arrangement is completed. Specifically, this involves the server sending the order information to the delivery company and coordinating the delivery schedule.

[0479] (Application Example 1)

[0480] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0481] In today's busy lifestyles, efficiently managing meal plans and appropriately selecting ingredients and dishes to meet individual health goals is a challenging task. Furthermore, there is a need to purchase ingredients economically and efficiently by utilizing market sale information and to have them delivered quickly. Existing systems are not adequately addressing these challenges.

[0482] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0483] In this invention, the server includes means for inputting the user's biometric information and storing it in an information processing device, means for collecting product information from suppliers using a communication device, and means for generating an optimized meal menu based on user information and product information using a generative model. This makes it possible for users to easily select ingredients and dishes according to their health goals, obtain ingredients economically and efficiently by utilizing market sale information, and maintain healthy lifestyle habits.

[0484] "User biometric information" refers to personalized information such as each user's health status, eating habits, and allergy information.

[0485] An "information processing device" is a technological device for receiving, storing, and processing data.

[0486] A "communication device" is a technical means for exchanging data with suppliers or servers located in remote locations.

[0487] A "supplier" is a business or store that supplies goods or ingredients and provides information.

[0488] A "generative model" is a technology that includes algorithms that use artificial intelligence to generate or optimize data based on specific goals.

[0489] A "meal menu" refers to a daily meal plan designed based on nutritional balance and individual health goals.

[0490] A "health goal" is an individual objective set to achieve or maintain a specific state of health.

[0491] "Special offer information" refers to information regarding the price or supply conditions of goods or services offered in the market for a certain period of time.

[0492] "Ingredients" refer to food products or goods that are necessary for making a meal.

[0493] The system implementing this invention primarily functions through the coordinated operation of a server, information terminal, and user.

[0494] The server receives personal information from users, including biometric data, from information terminals and stores it in an internal database. The information terminals provide an interface for users to input detailed information such as their health status, eating habits, and specific health goals through a dedicated application. The server also collects product information from suppliers via communication devices, stores it in the database as special offer information, and plays a role in reflecting the latest prices and inventory status.

[0495] Using a generative model installed on the server, the system generates meal menus tailored to the user's health goals based on stored user and product information. This generative model utilizes nutritional data to select optimal ingredients and suggest nutritionally balanced meals. The server also automatically places orders for the generated ingredient list from a delivery service based on the user's selections.

[0496] For example, if a user is aiming for a low-carbohydrate diet, they can enter this information into the application, and the system will suggest meal menus using low-carbohydrate discounted products based on that information. The user can easily complete an order by selecting their desired ingredients from the menu through the application, and the selected ingredients will be delivered to their home via a delivery service.

[0497] Examples of input prompts for the generative AI model are as follows:

[0498] "User Profile: {Age: 35, Gender: Female, Health Goal: Low Carb, Preference: Japanese Food} Special Offer: {Chicken Breast: In Stock, On Sale} Generate a nutritionally balanced menu."

[0499] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0500] Step 1:

[0501] Users use an information terminal to input personal information such as their biometric data, health goals, and eating habits through a dedicated application. The entered data is temporarily stored on the information terminal and then sent to a server. The server receives this data and stores it in a database.

[0502] Step 2:

[0503] The server periodically retrieves product information from suppliers via communication devices. This information includes product prices, inventory status, and special offer information. The server processes this data and stores it in a database, keeping the special offer information up-to-date.

[0504] Step 3:

[0505] The server operates an AI model using the user's personal information and collected product information. By providing the user's health goals, eating habits, and special offer information as input, the program generates optimal meal plans based on nutritional management. Multiple menus are presented to the user.

[0506] Step 4:

[0507] The user selects their preferred menu from the suggested meal options. Based on the selected menu, the server creates a list of necessary ingredients and organizes this list as order data for the delivery service.

[0508] Step 5:

[0509] The server uses the delivery service API to send order data organized based on user selections in the database. The transmitted information is used by the delivery service to process the order and deliver the selected ingredients to the address specified by the user.

[0510] Step 6:

[0511] Detailed information such as the delivery progress and estimated delivery time for the transportation service is returned to the server. The server processes this information and notifies the user via their information terminal. The user can then check the delivery status in the application and prepare for receipt.

[0512] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0513] This invention provides a more personalized service by combining an emotion engine with a system that proposes optimized meal plans based on the user's personal health information and information on special offers. This system functions through the mutual cooperation of the user, terminal, and server.

[0514] First, the user logs into the application or website and enters their eating habits, health status, allergy information, and food preferences. This information is transmitted to the server via the device and securely stored in a database. Furthermore, the device is equipped with a camera and sensors that detect the user's facial expressions and movements in real time.

[0515] The server periodically retrieves information on sale items through APIs from partner retailers. This allows the server to provide users with the latest price information. After this information is integrated, a generative model is activated to create a nutritionally balanced meal menu based on the user's input and the sale item information. The emotion engine estimates the user's emotions from their facial expressions and actions, and adjusts the meal choices based on those emotions. For example, if the user is feeling stressed, foods with relaxing effects will be suggested.

[0516] The generated meal menu and list of required ingredients are displayed on the terminal, allowing the user to review and select them. Once the ingredient selection is complete, the terminal sends the order information to the server, which processes the order and arranges delivery using the API of a partnered delivery service. At this stage, an emotion engine is used to adjust the order so that the most suitable ingredients for the user's current state are ordered.

[0517] This invention enables users to receive flexible meal suggestions tailored to their individual emotions and preferences, thereby improving the quality of their eating habits. By using an emotion engine, more context-aware personalization is achieved, increasing user satisfaction and improving shopping efficiency.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] Users log in to the application or website and enter information such as their dietary preferences, eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0521] Step 2:

[0522] The device uses cameras and sensors to detect the user's facial expressions and movements in real time and collect emotional data. This information is sent to an emotion engine to estimate the user's current emotional state.

[0523] Step 3:

[0524] The server connects via API to partner retailers to retrieve special offer information and updates the latest prices and stock availability. This information is stored in a database.

[0525] Step 4:

[0526] The server combines the user's personal information, emotional data from the emotion engine, and special offer information to create an optimal meal plan using a generative model. The generative model suggests menus tailored to the user's nutritional balance and emotional state.

[0527] Step 5:

[0528] The terminal displays a generated meal menu and a list of required ingredients to the user. The user can review the provided menu and make selections according to their preferences.

[0529] Step 6:

[0530] Once the user confirms their ingredient selection, the device sends this information to the server. The server uses the selected ingredient list to process the order via the API of a partner delivery service and arranges for the ingredients to be delivered.

[0531] Step 7:

[0532] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the delivery date, time, and delivery location details and make adjustments as needed.

[0533] This processing flow allows users to efficiently plan and procure healthy and economical meals while taking their individual emotional states into consideration.

[0534] (Example 2)

[0535] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0536] Modern consumers desire to consistently consume healthy foods, but often lack the knowledge and time to create proper meal plans. Furthermore, emotional fluctuations can influence food choices, making standard meal suggestions insufficient to fully address individual needs. Additionally, there is a need for quick and efficient means of purchasing and obtaining suggested meal menus.

[0537] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0538] In this invention, the server includes a device for inputting and storing the user's personal information in a database, a device for collecting product information from commercial facilities using an information acquisition device, and a device for creating an optimized nutritional intake plan based on user information and product information using a generation module. This enables healthy and personalized meal suggestions for individual users, and allows for the rapid and appropriate acquisition of ingredients based on those suggestions.

[0539] "User personal information" refers to individual information including the user's health status, eating habits, allergy information, and food preferences.

[0540] A "database" is an information storage system used to efficiently store and manage data handled by a system, such as users' personal information and product information.

[0541] An "information acquisition device" is a hardware or software mechanism for collecting product information from commercial facilities or other information sources.

[0542] A "generation module" is a software unit that implements an algorithm for creating a nutritional intake plan based on the user's personal information and product information.

[0543] A "nutritional intake plan" is a suggestion of a balanced meal menu based on the user's health information and available product information.

[0544] "Commercial facilities" is a broad concept that refers to retailers that sell goods, stores that provide food ingredients, and so on.

[0545] A "sensor" is a device used to detect data on user actions and the environment.

[0546] A "camera" is a device used to capture images and analyze a user's facial expressions and gestures.

[0547] "Delivery method" refers to a service or system for delivering listed goods to a specified destination.

[0548] A "request" is a formal request to purchase or deliver a list of items.

[0549] This invention is a system in which a user, a terminal, and a server work in cooperation with each other. The user first uses an application or website and inputs personal information such as eating habits, health status, allergy information, and food preferences via the terminal. The terminal is equipped with a camera and sensors, which can detect the user's facial expressions and movements in real time.

[0550] The terminal sends the collected information to the server via the internet. The server first stores the user's personal information in a database. Next, it periodically calls the commercial facility's API using an information acquisition device to retrieve the latest information such as special offers and new products. This process typically uses the Python requests library.

[0551] The server integrates product information obtained from commercial facilities with the user's personal information and launches a generation module. This module uses a machine learning framework such as TensorFlow to generate a nutritional intake plan tailored to the user's needs. The prompt used during this process is "Please create an optimal nutritional intake plan based on user information and product information."

[0552] Furthermore, the server analyzes the user's facial expression data sent from the terminal to obtain emotional information. This allows the system to adjust the menu to include foods with relaxing effects if the user is experiencing stress. An emotional analysis service is used for this emotional analysis.

[0553] The generated nutritional intake plan and list of necessary items are sent from the server to the terminal and displayed on the user's screen. The user selects the most suitable option from these menus and confirms the information on the selected items.

[0554] Finally, the selected item list is sent from the terminal to the server. Based on this information, the server confirms the order using the shipping method's API and executes optimized delivery. In this process, it is common to use a web framework such as Django to interact with the API.

[0555] This invention provides a personalized meal plan tailored to the user's individual needs and emotional state, and further realizes a system that enables the rapid and efficient procurement of ingredients based on that plan. As a result, it can contribute to maintaining a healthy diet.

[0556] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0557] Step 1:

[0558] Users enter their eating habits, health status, allergy information, and dietary preferences using an application or website. The entered data is sent to the device and formatted in JSON format. The device then sends this to the server using the HTTPS protocol. By processing the input data, the server generates an individual user profile and stores it in a database.

[0559] Step 2:

[0560] The server periodically calls the commercial facility's API using an information acquisition device to retrieve product information. This data is received in JSON format and stored in the product database. When calling the API and retrieving product information using the Python requests library, the data is filtered and formatted to extract the necessary list of product information.

[0561] Step 3:

[0562] The server uses a generation module to create an optimized nutrition plan based on the user's personal information and product information. It takes user profile and product information as input and processes it with an AI model. The generation AI model uses TensorFlow, and the prompt is "Create an optimal nutrition plan based on user and product information." As a result, a list of meal menu options is output.

[0563] Step 4:

[0564] The device receives the nutritional intake plan transmitted from the server and adjusts the displayed meal menu using data from the user's facial expression sensor. During this process, the device analyzes the user's emotional state in real time and displays the adjusted menu on the screen. Emotional analysis software is used to make adjustments such as adding foods with relaxing effects to the menu.

[0565] Step 5:

[0566] The user makes a selection from the meal menu displayed on the terminal. Once the selection is confirmed, the terminal generates a list of selected items and sends it to the server. The server uses the item information based on the selected menu as input data for the next order processing.

[0567] Step 6:

[0568] The server processes the order by calling the shipping API based on the received list of items. It uses the Django framework to generate API requests, determine the best shipping option, and confirm the order. Finally, the order information is sent to the shipping service, and the output includes a delivery schedule and confirmation information.

[0569] (Application Example 2)

[0570] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0571] In today's world, optimizing individual meal plans based on health information, product pricing, and personal emotions is challenging. Traditional systems have failed to adequately consider user emotional states, resulting in a lack of convenience and satisfaction. Therefore, there is a need for a system that provides personalized meal suggestions based on user emotions and personal information, and efficiently procures ingredients based on that plan.

[0572] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0573] In this invention, the server includes means for storing information in a database based on the user's personal health information and dietary preferences, means for collecting product information from distributors, means for creating an optimized meal plan using a generative model and sentiment evaluation, and means for adjusting meal options according to the user's emotional state. This makes it possible to suggest meals that are tailored to each user's health condition and emotions, thereby providing a highly satisfying diet.

[0574] "Personal health information" refers to information related to an individual's body, such as the user's health status, dietary preferences, and allergy information.

[0575] "Product information" refers to information obtained from distributors, such as the product name, price, and special sale status.

[0576] A "generative model" is an algorithm or program that generates an optimal meal plan based on input data.

[0577] "Emotional assessment" is a technique or algorithm used to estimate a user's emotional state based on their facial expressions and actions.

[0578] A "meal plan" is a suggestion of optimized meal content and menus that take into account the user's health information and emotional state.

[0579] A "food ingredient list" is a list of all the ingredients needed for a meal plan, and is used when ordering or having food delivered.

[0580] To implement this invention, a system is constructed in which a server, terminal, and user work in cooperation with each other. The server has the function of receiving personal health information and dietary preferences provided by the user and securely storing them in a database. It also periodically collects product information and special offer information through APIs of distributors. Based on this data, the server uses a generative AI model to create an optimal meal plan. The generative model is developed using machine learning frameworks such as Python and TensorFlow.

[0581] The device is equipped with cameras and sensors that detect the user's facial expressions and movements in real time. This allows the system to estimate the user's emotional state and send that information to a server. The server then performs an emotional assessment and adjusts the meal options according to the user's emotions. Specifically, it has a function to generate menus that prioritize ingredients with relaxing effects.

[0582] The user reviews this information on their device and lists the necessary ingredients based on their selected meal plan. The listed ingredients are then ordered using the delivery service's API. Once the user completes their selection, the server receives the order information and arranges for the ingredients to be delivered through the partner delivery service.

[0583] This system allows users to receive personalized, healthy, and economical meal suggestions. For example, a user experiencing stress might be recommended chamomile tea or foods with massage-like effects. The generating AI model can be made more appropriate by inputting prompts such as, "Generate the optimal meal menu for when the user's emotional state is determined to be stressed."

[0584] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0585] Step 1:

[0586] Users input their eating habits, health status, allergy information, and food preferences through their terminal. The entered information is sent directly to the server and stored in the database. Here, the process of registering the user's individual information in digital format into the database takes place.

[0587] Step 2:

[0588] The device uses cameras and sensors to detect the user's facial expressions and movements in real time. The detected data is used as input to estimate the user's emotional state. This allows the user's current emotions to be categorized as "relaxed" or "stressed," and then sent to the server.

[0589] Step 3:

[0590] The server collects product information via APIs from partner distributors. This information includes product names, prices, and special offer information, and is used to update the price information database.

[0591] Step 4:

[0592] The server uses a generative AI model to integrate the user's health information and product information to generate an optimized meal plan. This process uses TensorFlow to analyze the input data and output a menu that considers nutritional balance. The prompt used is, "Generate the optimal meal menu when the user's emotional state is determined to be stressed."

[0593] Step 5:

[0594] The meal plan received from the server is displayed to the user on the terminal. The user reviews the suggested menu and selects the necessary ingredients. The selected ingredients are sent to the server as an ingredient list.

[0595] Step 6:

[0596] The server processes orders via the delivery service's API based on the ingredient list. The API is used to send order data to the delivery service, which then arranges for the ingredients to be delivered to the user's address. The order status is also fed back to the user's device in real time.

[0597] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0598] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0599] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0600] [Fourth Embodiment]

[0601] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0602] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0603] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0604] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0605] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0606] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0607] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0608] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0609] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0610] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0611] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0612] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0613] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0614] This invention is a system that efficiently supports users' meal planning, providing daily meal menu suggestions based on the user's personal information and enabling the purchase of ingredients. This system functions through the coordinated operation of a server, terminals, and users.

[0615] (User information input)

[0616] Users access a dedicated application or website and log in to their account. Here, users enter detailed information such as their eating habits, health status, and allergy information, and register their dietary preferences. This personal information is transmitted to a server via the device and stored in a database.

[0617] (Collecting information on special offers)

[0618] The server accesses the APIs of partner retailers via the internet to periodically retrieve the latest sale information. This ensures that the server is ready to provide users with the most up-to-date product prices and inventory information.

[0619] (Generating the optimal menu)

[0620] When a user sends a request to the application, a generative model on the server is activated. Based on user information and special offer information stored on the server, the generative model suggests several optimal daily menus that are nutritionally balanced. For example, if a user requests a low-fat, high-protein diet and chicken breast is on sale, healthy dishes using chicken breast will be suggested.

[0621] (Creating and verifying the ingredient list)

[0622] The terminal lists the necessary ingredients and their quantities based on the generated menu. This list is displayed to the user, who can then select the ingredients to purchase. Using sale items allows for economically efficient purchasing.

[0623] (Ordering and delivery of ingredients)

[0624] Once a user confirms their order by selecting ingredients from a list, this information is sent to the server via their device. The server automatically processes the order using the API of a partner delivery service and arranges delivery. The user is also notified of details such as the scheduled delivery date and time, ensuring they can receive their order with peace of mind.

[0625] The system of this invention allows users to effectively utilize sale items while leading a healthy and efficient diet. Furthermore, the automation of cumbersome shopping procedures contributes to saving users time and effort.

[0626] The following describes the processing flow.

[0627] Step 1:

[0628] Users log in to an application or website and enter personal information such as eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0629] Step 2:

[0630] The server, through scheduled tasks, accesses the APIs of partner retailers to automatically retrieve information on special offers. This information is then analyzed and stored in a database as the most up-to-date version.

[0631] Step 3:

[0632] When a user submits a meal plan request from the application, the device relays this request to the server. The request includes a link to the user's personal information.

[0633] Step 4:

[0634] The server launches a generative model, inputting saved user information and sale item information to generate optimal daily meal menus. The model considers nutritional balance and the use of sale items, and proposes multiple menu options.

[0635] Step 5:

[0636] The terminal displays the generated menu on the user's screen, listing the required ingredients and their quantities. The user can review the list and add or remove items as needed.

[0637] Step 6:

[0638] Once the user confirms their order, the terminal sends the selected ingredient information to the server. The server then sends the order data to the API of a partner delivery service, which automatically arranges delivery.

[0639] Step 7:

[0640] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the scheduled delivery date, time, and delivery location.

[0641] (Example 1)

[0642] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0643] Modern consumers are expected to create meal plans tailored to their individual nutritional needs for health management purposes. However, efficiently determining what ingredients to buy and where to obtain them is not easy. Furthermore, the process from creating shopping lists to purchasing goods and delivery is a time-consuming and cumbersome one for consumers.

[0644] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0645] In this invention, the server includes means for inputting the user's personal attributes and storing them in a recording device, means for aggregating product information from suppliers using an information acquisition device, and means for generating optimized meal suggestions based on the user attributes and product information using a generation AI model. This enables the user to efficiently create a healthy meal plan and acquire ingredients.

[0646] "User personal attributes" refer to information related to an individual user's dietary habits, such as eating habits, health status, allergy information, and food preferences.

[0647] A "recording device" is a device such as a database or server used to store digital information.

[0648] An "information acquisition device" is a device that collects product information from a vendor's system via the internet.

[0649] A "vendor" refers to a retailer or wholesaler that provides goods.

[0650] A "generative AI model" is an artificial intelligence model that generates optimized meal suggestions based on input user attributes and product information.

[0651] "Meal suggestions" refer to suggestions for nutritionally balanced meal menus and recipes that are tailored to the user's needs.

[0652] "Items" refers to the ingredients and related consumables listed based on the meal proposal.

[0653] A "delivery company" is a company that provides a service of transporting food or products to a designated location after purchase.

[0654] "Request submission" is the procedure of requesting a delivery company to arrange delivery based on information about the purchased items.

[0655] This invention is a system designed to support users in maintaining a healthy diet, and it functions through the coordinated efforts of the user, terminal, and server.

[0656] Users access their accounts using a dedicated application or website and input personal attributes such as eating habits, health status, allergy information, and food preferences. Based on this information, it is possible to provide personalized meal suggestions to the user.

[0657] The terminal transmits the above user information to the server and securely stores it in a recording device (database). The stored information is processed using a generative AI model. This model operates on the server and generates nutritionally balanced meal suggestions based on user attributes and product information collected from vendors. This process is achieved by the information acquisition device accessing the vendor's API via the internet and transmitting product information to the server.

[0658] For example, if a user requests a health-conscious, low-fat, high-protein menu, the server will suggest healthy recipes using chicken breast, which has been entered as a special offer. An example of a prompt message the user might enter would be: "Please generate this week's meal menu. I would like low-fat, high-protein dishes. Please let me know if you have any recipes using chicken breast."

[0659] The server creates a list of necessary items based on the generated meal suggestions. This list is presented to the user via a terminal, allowing the user to select suitable ingredients and confirm their purchase. Finally, the terminal sends this information back to the server, which automatically places an order with the delivery company. This allows the user to efficiently obtain the necessary ingredients.

[0660] As described above, this system efficiently supports users' healthy eating habits by combining generative AI models and communication technologies.

[0661] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0662] Step 1:

[0663] The user accesses the application or website and logs into their account. After logging in, they enter personal attributes such as eating habits, health status, allergy information, and food preferences. The entered information is transmitted to the server via the device and stored on the recording device. In this step, the user's personal attributes are the input data, and the transmission to the server and storage are the output. Specifically, this involves the user filling out information in a form on the screen, approving it, and submitting it.

[0664] Step 2:

[0665] The server uses an information acquisition device to access the vendor's API and collect product information. This includes data such as sale information, product name, price, and inventory status. The collected data is sent to the server to prepare for future processing. The input for this step is the product information obtained from the vendor's API, and the output is the storage of the collected product information on the server. Specifically, the server periodically accesses the API and queries the data.

[0666] Step 3:

[0667] The user enters a prompt message in the application that includes their desired dietary style (e.g., low-fat, high-protein) and submits a request for a meal menu. The generative AI model uses user attributes and product information stored on the server to generate optimized meal suggestions. Specifically, it analyzes the user's request to create a nutritionally balanced menu. In this step, the prompt message is the input and the meal suggestions are the output. This includes the actions of the generative AI model in processing the request.

[0668] Step 4:

[0669] The server creates a list of necessary items based on the generated meal suggestions. This list is then provided to the user via a terminal. The user reviews the list and selects the items they wish to purchase. The input for this step is the meal suggestion, and the output is the item list. The specific operation primarily involves analyzing the suggested menu and creating the list.

[0670] Step 5:

[0671] Once the user confirms their purchase, the terminal sends this information back to the server. The server automatically processes the order and arranges delivery using the delivery company's API. The user is then notified of the delivery date, time, and order details. This step is an input where the purchase confirmation information is received, and an output where the delivery arrangement is completed. Specifically, this involves the server sending the order information to the delivery company and coordinating the delivery schedule.

[0672] (Application Example 1)

[0673] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] In today's busy lifestyles, efficiently managing meal plans and appropriately selecting ingredients and dishes to meet individual health goals is a challenging task. Furthermore, there is a need to purchase ingredients economically and efficiently by utilizing market sale information and to have them delivered quickly. Existing systems are not adequately addressing these challenges.

[0675] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0676] In this invention, the server includes means for inputting the user's biometric information and storing it in an information processing device, means for collecting product information from suppliers using a communication device, and means for generating an optimized meal menu based on user information and product information using a generative model. This makes it possible for users to easily select ingredients and dishes according to their health goals, obtain ingredients economically and efficiently by utilizing market sale information, and maintain healthy lifestyle habits.

[0677] "User biometric information" refers to personalized information such as each user's health status, eating habits, and allergy information.

[0678] An "information processing device" is a technological device for receiving, storing, and processing data.

[0679] A "communication device" is a technical means for exchanging data with suppliers or servers located in remote locations.

[0680] A "supplier" is a business or store that supplies goods or ingredients and provides information.

[0681] A "generative model" is a technology that includes algorithms that use artificial intelligence to generate or optimize data based on specific goals.

[0682] A "meal menu" refers to a daily meal plan designed based on nutritional balance and individual health goals.

[0683] A "health goal" is an individual objective set to achieve or maintain a specific state of health.

[0684] "Special offer information" refers to information regarding the price or supply conditions of goods or services offered in the market for a certain period of time.

[0685] "Ingredients" refer to food products or goods that are necessary for making a meal.

[0686] The system implementing this invention primarily functions through the coordinated operation of a server, information terminal, and user.

[0687] The server receives personal information from users, including biometric data, from information terminals and stores it in an internal database. The information terminals provide an interface for users to input detailed information such as their health status, eating habits, and specific health goals through a dedicated application. The server also collects product information from suppliers via communication devices, stores it in the database as special offer information, and plays a role in reflecting the latest prices and inventory status.

[0688] Using a generative model installed on the server, the system generates meal menus tailored to the user's health goals based on stored user and product information. This generative model utilizes nutritional data to select optimal ingredients and suggest nutritionally balanced meals. The server also automatically places orders for the generated ingredient list from a delivery service based on the user's selections.

[0689] For example, if a user is aiming for a low-carbohydrate diet, they can enter this information into the application, and the system will suggest meal menus using low-carbohydrate discounted products based on that information. The user can easily complete an order by selecting their desired ingredients from the menu through the application, and the selected ingredients will be delivered to their home via a delivery service.

[0690] Examples of input prompts for the generative AI model are as follows:

[0691] "User Profile: {Age: 35, Gender: Female, Health Goal: Low Carb, Preference: Japanese Food} Special Offer: {Chicken Breast: In Stock, On Sale} Generate a nutritionally balanced menu."

[0692] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0693] Step 1:

[0694] Users use an information terminal to input personal information such as their biometric data, health goals, and eating habits through a dedicated application. The entered data is temporarily stored on the information terminal and then sent to a server. The server receives this data and stores it in a database.

[0695] Step 2:

[0696] The server periodically retrieves product information from suppliers via communication devices. This information includes product prices, inventory status, and special offer information. The server processes this data and stores it in a database, keeping the special offer information up-to-date.

[0697] Step 3:

[0698] The server operates an AI model using the user's personal information and collected product information. By providing the user's health goals, eating habits, and special offer information as input, the program generates optimal meal plans based on nutritional management. Multiple menus are presented to the user.

[0699] Step 4:

[0700] The user selects their preferred menu from the suggested meal options. Based on the selected menu, the server creates a list of necessary ingredients and organizes this list as order data for the delivery service.

[0701] Step 5:

[0702] The server uses the delivery service API to send order data organized based on user selections in the database. The transmitted information is used by the delivery service to process the order and deliver the selected ingredients to the address specified by the user.

[0703] Step 6:

[0704] Detailed information such as the delivery progress and estimated delivery time for the transportation service is returned to the server. The server processes this information and notifies the user via their information terminal. The user can then check the delivery status in the application and prepare for receipt.

[0705] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0706] This invention provides a more personalized service by combining an emotion engine with a system that proposes optimized meal plans based on the user's personal health information and information on special offers. This system functions through the mutual cooperation of the user, terminal, and server.

[0707] First, the user logs into the application or website and enters their eating habits, health status, allergy information, and food preferences. This information is transmitted to the server via the device and securely stored in a database. Furthermore, the device is equipped with a camera and sensors that detect the user's facial expressions and movements in real time.

[0708] The server periodically retrieves information on sale items through APIs from partner retailers. This allows the server to provide users with the latest price information. After this information is integrated, a generative model is activated to create a nutritionally balanced meal menu based on the user's input and the sale item information. The emotion engine estimates the user's emotions from their facial expressions and actions, and adjusts the meal choices based on those emotions. For example, if the user is feeling stressed, foods with relaxing effects will be suggested.

[0709] The generated meal menu and list of required ingredients are displayed on the terminal, allowing the user to review and select them. Once the ingredient selection is complete, the terminal sends the order information to the server, which processes the order and arranges delivery using the API of a partnered delivery service. At this stage, an emotion engine is used to adjust the order so that the most suitable ingredients for the user's current state are ordered.

[0710] This invention enables users to receive flexible meal suggestions tailored to their individual emotions and preferences, thereby improving the quality of their eating habits. By using an emotion engine, more context-aware personalization is achieved, increasing user satisfaction and improving shopping efficiency.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] Users log in to the application or website and enter information such as their dietary preferences, eating habits, health status, and allergy information. This information is transmitted to the server via the device and stored in a database.

[0714] Step 2:

[0715] The device uses cameras and sensors to detect the user's facial expressions and movements in real time and collect emotional data. This information is sent to an emotion engine to estimate the user's current emotional state.

[0716] Step 3:

[0717] The server connects via API to partner retailers to retrieve special offer information and updates the latest prices and stock availability. This information is stored in a database.

[0718] Step 4:

[0719] The server combines the user's personal information, emotional data from the emotion engine, and special offer information to create an optimal meal plan using a generative model. The generative model suggests menus tailored to the user's nutritional balance and emotional state.

[0720] Step 5:

[0721] The terminal displays a generated meal menu and a list of required ingredients to the user. The user can review the provided menu and make selections according to their preferences.

[0722] Step 6:

[0723] Once the user confirms their ingredient selection, the device sends this information to the server. The server uses the selected ingredient list to process the order via the API of a partner delivery service and arranges for the ingredients to be delivered.

[0724] Step 7:

[0725] The server receives delivery confirmation information from the delivery service and notifies the user. The user can then check the delivery date, time, and delivery location details and make adjustments as needed.

[0726] This processing flow allows users to efficiently plan and procure healthy and economical meals while taking their individual emotional states into consideration.

[0727] (Example 2)

[0728] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0729] Modern consumers desire to consistently consume healthy foods, but often lack the knowledge and time to create proper meal plans. Furthermore, emotional fluctuations can influence food choices, making standard meal suggestions insufficient to fully address individual needs. Additionally, there is a need for quick and efficient means of purchasing and obtaining suggested meal menus.

[0730] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0731] In this invention, the server includes a device for inputting and storing the user's personal information in a database, a device for collecting product information from commercial facilities using an information acquisition device, and a device for creating an optimized nutritional intake plan based on user information and product information using a generation module. This enables healthy and personalized meal suggestions for individual users, and allows for the rapid and appropriate acquisition of ingredients based on those suggestions.

[0732] "User personal information" refers to individual information including the user's health status, eating habits, allergy information, and food preferences.

[0733] A "database" is an information storage system used to efficiently store and manage data handled by a system, such as users' personal information and product information.

[0734] An "information acquisition device" is a hardware or software mechanism for collecting product information from commercial facilities or other information sources.

[0735] A "generation module" is a software unit that implements an algorithm for creating a nutritional intake plan based on the user's personal information and product information.

[0736] A "nutritional intake plan" is a suggestion of a balanced meal menu based on the user's health information and available product information.

[0737] "Commercial facilities" is a broad concept that refers to retailers that sell goods, stores that provide food ingredients, and so on.

[0738] A "sensor" is a device used to detect data on user actions and the environment.

[0739] A "camera" is a device used to capture images and analyze a user's facial expressions and gestures.

[0740] "Delivery method" refers to a service or system for delivering listed goods to a specified destination.

[0741] A "request" is a formal request to purchase or deliver a list of items.

[0742] This invention is a system in which a user, a terminal, and a server work in cooperation with each other. The user first uses an application or website and inputs personal information such as eating habits, health status, allergy information, and food preferences via the terminal. The terminal is equipped with a camera and sensors, which can detect the user's facial expressions and movements in real time.

[0743] The terminal sends the collected information to the server via the internet. The server first stores the user's personal information in a database. Next, it periodically calls the commercial facility's API using an information acquisition device to retrieve the latest information such as special offers and new products. This process typically uses the Python requests library.

[0744] The server integrates product information obtained from commercial facilities with the user's personal information and launches a generation module. This module uses a machine learning framework such as TensorFlow to generate a nutritional intake plan tailored to the user's needs. The prompt used during this process is "Please create an optimal nutritional intake plan based on user information and product information."

[0745] Furthermore, the server analyzes the user's facial expression data sent from the terminal to obtain emotional information. This allows the system to adjust the menu to include foods with relaxing effects if the user is experiencing stress. An emotional analysis service is used for this emotional analysis.

[0746] The generated nutritional intake plan and list of necessary items are sent from the server to the terminal and displayed on the user's screen. The user selects the most suitable option from these menus and confirms the information on the selected items.

[0747] Finally, the selected item list is sent from the terminal to the server. Based on this information, the server confirms the order using the shipping method's API and executes optimized delivery. In this process, it is common to use a web framework such as Django to interact with the API.

[0748] This invention provides a personalized meal plan tailored to the user's individual needs and emotional state, and further realizes a system that enables the rapid and efficient procurement of ingredients based on that plan. As a result, it can contribute to maintaining a healthy diet.

[0749] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0750] Step 1:

[0751] Users enter their eating habits, health status, allergy information, and dietary preferences using an application or website. The entered data is sent to the device and formatted in JSON format. The device then sends this to the server using the HTTPS protocol. By processing the input data, the server generates an individual user profile and stores it in a database.

[0752] Step 2:

[0753] The server periodically calls the commercial facility's API using an information acquisition device to retrieve product information. This data is received in JSON format and stored in the product database. When calling the API and retrieving product information using the Python requests library, the data is filtered and formatted to extract the necessary list of product information.

[0754] Step 3:

[0755] The server uses a generation module to create an optimized nutrition plan based on the user's personal information and product information. It takes user profile and product information as input and processes it with an AI model. The generation AI model uses TensorFlow, and the prompt is "Create an optimal nutrition plan based on user and product information." As a result, a list of meal menu options is output.

[0756] Step 4:

[0757] The device receives the nutritional intake plan transmitted from the server and adjusts the displayed meal menu using data from the user's facial expression sensor. During this process, the device analyzes the user's emotional state in real time and displays the adjusted menu on the screen. Emotional analysis software is used to make adjustments such as adding foods with relaxing effects to the menu.

[0758] Step 5:

[0759] The user makes a selection from the meal menu displayed on the terminal. Once the selection is confirmed, the terminal generates a list of selected items and sends it to the server. The server uses the item information based on the selected menu as input data for the next order processing.

[0760] Step 6:

[0761] The server processes the order by calling the shipping API based on the received list of items. It uses the Django framework to generate API requests, determine the best shipping option, and confirm the order. Finally, the order information is sent to the shipping service, and the output includes a delivery schedule and confirmation information.

[0762] (Application Example 2)

[0763] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0764] In today's world, optimizing individual meal plans based on health information, product pricing, and personal emotions is challenging. Traditional systems have failed to adequately consider user emotional states, resulting in a lack of convenience and satisfaction. Therefore, there is a need for a system that provides personalized meal suggestions based on user emotions and personal information, and efficiently procures ingredients based on that plan.

[0765] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0766] In this invention, the server includes means for storing information in a database based on the user's personal health information and dietary preferences, means for collecting product information from distributors, means for creating an optimized meal plan using a generative model and sentiment evaluation, and means for adjusting meal options according to the user's emotional state. This makes it possible to suggest meals that are tailored to each user's health condition and emotions, thereby providing a highly satisfying diet.

[0767] "Personal health information" refers to information related to an individual's body, such as the user's health status, dietary preferences, and allergy information.

[0768] "Product information" refers to information obtained from distributors, such as the product name, price, and special sale status.

[0769] A "generative model" is an algorithm or program that generates an optimal meal plan based on input data.

[0770] "Emotional assessment" is a technique or algorithm used to estimate a user's emotional state based on their facial expressions and actions.

[0771] A "meal plan" is a suggestion of optimized meal content and menus that take into account the user's health information and emotional state.

[0772] A "food ingredient list" is a list of all the ingredients needed for a meal plan, and is used when ordering or having food delivered.

[0773] To implement this invention, a system is constructed in which a server, terminal, and user work in cooperation with each other. The server has the function of receiving personal health information and dietary preferences provided by the user and securely storing them in a database. It also periodically collects product information and special offer information through APIs of distributors. Based on this data, the server uses a generative AI model to create an optimal meal plan. The generative model is developed using machine learning frameworks such as Python and TensorFlow.

[0774] The device is equipped with cameras and sensors that detect the user's facial expressions and movements in real time. This allows the system to estimate the user's emotional state and send that information to a server. The server then performs an emotional assessment and adjusts the meal options according to the user's emotions. Specifically, it has a function to generate menus that prioritize ingredients with relaxing effects.

[0775] The user reviews this information on their device and lists the necessary ingredients based on their selected meal plan. The listed ingredients are then ordered using the delivery service's API. Once the user completes their selection, the server receives the order information and arranges for the ingredients to be delivered through the partner delivery service.

[0776] This system allows users to receive personalized, healthy, and economical meal suggestions. For example, a user experiencing stress might be recommended chamomile tea or foods with massage-like effects. The generating AI model can be made more appropriate by inputting prompts such as, "Generate the optimal meal menu for when the user's emotional state is determined to be stressed."

[0777] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0778] Step 1:

[0779] Users input their eating habits, health status, allergy information, and food preferences through their terminal. The entered information is sent directly to the server and stored in the database. Here, the process of registering the user's individual information in digital format into the database takes place.

[0780] Step 2:

[0781] The device uses cameras and sensors to detect the user's facial expressions and movements in real time. The detected data is used as input to estimate the user's emotional state. This allows the user's current emotions to be categorized as "relaxed" or "stressed," and then sent to the server.

[0782] Step 3:

[0783] The server collects product information via APIs from partner distributors. This information includes product names, prices, and special offer information, and is used to update the price information database.

[0784] Step 4:

[0785] The server uses a generative AI model to integrate the user's health information and product information to generate an optimized meal plan. This process uses TensorFlow to analyze the input data and output a menu that considers nutritional balance. The prompt used is, "Generate the optimal meal menu when the user's emotional state is determined to be stressed."

[0786] Step 5:

[0787] The meal plan received from the server is displayed to the user on the terminal. The user reviews the suggested menu and selects the necessary ingredients. The selected ingredients are sent to the server as an ingredient list.

[0788] Step 6:

[0789] The server processes orders via the delivery service's API based on the ingredient list. The API is used to send order data to the delivery service, which then arranges for the ingredients to be delivered to the user's address. The order status is also fed back to the user's device in real time.

[0790] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0791] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0792] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0793] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0794] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0795] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0796] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0797] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0798] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0799] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0800] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0801] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0802] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0803] 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.

[0804] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0805] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0806] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0807] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0808] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0809] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0810] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0811] The following is further disclosed regarding the embodiments described above.

[0812] (Claim 1)

[0813] A means of inputting and storing users' personal information in a database,

[0814] A means for collecting product information from retailers using a product information acquisition device,

[0815] A means of creating an optimized meal plan based on user information and product information using a generative model,

[0816] A means of listing the ingredients needed for the meal plan,

[0817] A means of sending the listed materials as an order to a delivery service,

[0818] A system that includes this.

[0819] (Claim 2)

[0820] The system according to claim 1, characterized in that the generative model includes an algorithm that proposes a meal plan using data related to nutritional management.

[0821] (Claim 3)

[0822] The system according to claim 1, characterized in that the listing of the materials and the submission of orders are performed automatically based on the user's selection.

[0823] "Example 1"

[0824] (Claim 1)

[0825] A means for inputting the user's personal attributes and saving them to a recording device,

[0826] A means of collecting product information from vendors using an information acquisition device,

[0827] A means of generating optimized meal suggestions based on user attributes and product information using a generative AI model,

[0828] A means for listing the items necessary for the meal proposal,

[0829] A means of sending the listed items as a request to a delivery company,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The system according to claim 1, which includes an algorithm that creates meal suggestions using health management-related information in the generation AI model.

[0833] (Claim 3)

[0834] The system according to claim 1, wherein the listing of the aforementioned items and the transmission of the request are performed automatically based on the user's selection.

[0835] "Application Example 1"

[0836] (Claim 1)

[0837] A means for inputting a user's biometric information and storing it in an information processing device,

[0838] A means of collecting product information from suppliers using communication equipment,

[0839] A means for generating an optimized meal menu based on user information and product information using a generative model,

[0840] A means for listing the necessary resources based on the meal menu,

[0841] A means for sending the listed resources as a request for a transportation service,

[0842] A means to customize the menu according to the user's health goals,

[0843] A system that includes this.

[0844] (Claim 2)

[0845] The system according to claim 1 is characterized in that the generative model includes an algorithm that proposes a meal plan using nutritional data, and has a function to notify the user of the delivery date of the ordered resources.

[0846] (Claim 3)

[0847] The system according to claim 1, characterized in that the listing of materials and the submission of requests are performed automatically based on user specifications.

[0848] "Example 2 of combining an emotion engine"

[0849] (Claim 1)

[0850] A device that inputs and stores users' personal information in a database,

[0851] A device that collects product information from commercial facilities using an information acquisition device,

[0852] A device that uses a generation module to create an optimized nutritional intake plan based on user information and product information,

[0853] A device that analyzes the user's facial expressions and movements using sensors and cameras, and adjusts meal suggestions based on the results,

[0854] A device for listing the items necessary for the nutrition intake plan,

[0855] A device that transmits the listed items as a request to a delivery method,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, wherein the generation module includes an algorithm that proposes a nutritional intake plan using data related to nutritional management.

[0859] (Claim 3)

[0860] The system according to claim 1, wherein the listing of the items and the sending of the request are performed automatically based on the user's selection.

[0861] "Application example 2 when combining with an emotional engine"

[0862] (Claim 1)

[0863] A means of inputting users' personal health information and dietary preferences and saving them in a database,

[0864] A means of collecting product information from distributors using a product information acquisition device,

[0865] A means for creating an optimized meal plan based on user information and product information using generative models and sentiment evaluation,

[0866] A means of adjusting meal options according to the user's emotional state,

[0867] A means of listing the ingredients needed for the meal plan and sending it as an order to a delivery service,

[0868] A system that includes this.

[0869] (Claim 2)

[0870] The system according to claim 1, characterized in that the generative model includes an algorithm that proposes a meal plan using information on nutritional management and emotional state.

[0871] (Claim 3)

[0872] The system according to claim 1, characterized in that the listing of ingredients and the submission of orders are performed automatically based on the user's selection or emotional state. [Explanation of symbols]

[0873] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting and storing users' personal information in a database, A means for collecting product information from retailers using a product information acquisition device, A means of creating an optimized meal plan based on user information and product information using a generative model, A means of listing the ingredients needed for the meal plan, A means of sending the listed materials as an order to a delivery service, A system that includes this.

2. The system according to claim 1, characterized in that the generation model includes an algorithm that proposes a meal plan using data related to nutritional management.

3. The system according to claim 1, characterized in that the listing of the materials and the submission of the order are performed automatically based on the user's selection.

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