system

Abstract

Provide a system. A method for receiving information about a user's dietary habits; A means for automatically generating a menu using a generation AI based on the received information; means for displaying the generated menu to a user; A means for creating an ingredient usage plan based on the generated menu; means for displaying the ingredient usage plan to a user; A system including:

Description

[Technical Field]

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

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

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

[0004] In modern society, planning a menu for daily meals at home can be a burden for many people. Maintaining a healthy diet while minimizing food waste is also a difficult task. Planning optimal menus based on dietary preferences, allergies, and budgets is particularly time-consuming, and addressing the issue of product loss is even more complicated. A system that solves these problems is needed. [Means for solving the problem]

[0005] The present invention provides a system including a means for receiving information about a user's dietary habits, a means for automatically generating a menu using a generation AI based on the received information, a means for displaying the generated menu to the user, a means for creating an ingredient usage plan based on the generated menu, and a means for displaying the ingredient usage plan to the user. The generation AI generates a menu based on the user's dietary preferences, allergy information, budget, and a list of ingredients on hand. The generated menu and ingredient usage plan are also designed to promote a healthy diet and minimize product waste. This system allows users to efficiently create menus, reducing product waste while maintaining a healthy diet.

[0006] "User" refers to an individual or group who uses this system to plan their daily meals and cook at home.

[0007] "Dietary information" refers to a series of data related to home cooking, such as the user's food preferences, allergy information, budget, list of ingredients they have, and number of meals they eat.

[0008] "Generative AI" refers to algorithms or programs that use artificial intelligence technology to generate optimal menus based on information received from users.

[0009] A "meal plan" refers to a list or menu that plans the meals a user will eat over a specific period of time.

[0010] "Display means" refers to a device or software interface for visually presenting the generated menu and ingredient usage plan to the user.

[0011] "Ingredient usage plan" refers to a plan or schedule that is presented to the user to plan how to use ingredients efficiently.

[0012] "Healthy diet" refers to eating habits that aim to maintain physical health by consuming a nutritionally balanced diet.

[0013] "Product waste" refers to ensuring that all purchased ingredients and meals are used effectively, without any waste. [Brief explanation of the drawings]

[0014] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0015] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0018] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0019] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0020] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0034] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0035] The present invention provides a system that allows users to easily plan their daily meals at home, promotes healthy eating habits, and prevents product waste. An embodiment of the system will now be described in detail.

[0036] This system consists of three main components: users, terminals, and servers.

[0037] User operations

[0038] Users access the system through applications.

[0039] Users input information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients they currently have (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[0040] Device operation

[0041] The terminal transmits the information entered by the user to the server.

[0042] The terminal receives the generated menu and ingredient usage plan sent from the server and displays them to the user.

[0043] Server Processing

[0044] The server analyzes the user information received from the terminal.

[0045] This analysis includes validating ingredient lists and filtering allergy information.

[0046] The server uses generative AI to automatically generate the optimal menu.

[0047] The AI ​​generates a menu that is appropriate for the user based on information such as the user's preferences, allergy information, budget, list of ingredients they have, and number of meals.

[0048] Based on the generated menu, the server creates a plan for using ingredients to minimize product waste while maintaining a healthy diet.

[0049] Specifically, this includes a detailed plan of how many servings of a particular ingredient should be used and which ingredients should be prioritized.

[0050] User Feedback

[0051] The server transmits the generated menu and ingredient usage plan to the terminal.

[0052] The terminal displays this in an easy-to-understand manner to the user.

[0053] For example, we suggest chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0054] It also provides specific advice on planning how to use ingredients, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0055] Specific examples

[0056] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[0057] 1. The user enters information.

[0058] 2. The device sends the information to the server.

[0059] 3. The server analyzes the received information, and the AI ​​generates the following menu:

[0060] Breakfast: Chicken rice balls and carrot miso soup

[0061] Lunch: Stir-fried cabbage and carrots, rolled egg

[0062] Dinner: Chicken and cabbage hotpot

[0063] 4. The server will create a plan for using ingredients based on this.

[0064] 5. The server sends the generated menu and usage plan to the terminal.

[0065] 6. The device displays the menu and provides a food plan to the user.

[0066] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] Users open the application and enter information about their diet, such as food preferences, allergy information, daily budget, a list of ingredients they have on hand, and the number of meals they eat per day.

[0070] Step 2:

[0071] The terminal stores the information about the dietary habits entered by the user in a database and transmits it to the server.

[0072] Step 3:

[0073] The server analyzes the user information received from the device, including validating the ingredient list (e.g., checking inventory) and filtering allergy information (excluding risky ingredients).

[0074] Step 4:

[0075] The server uses the analyzed data and passes it to the generation AI, which receives the user's preferences, allergy information, budget, list of ingredients they have, and number of meals as input parameters.

[0076] Step 5:

[0077] The AI ​​on the server generates the optimal menu based on these input parameters. For example, if a user likes Japanese food but has a dairy allergy, the AI ​​will suggest a Japanese menu that does not include dairy products.

[0078] Step 6:

[0079] The server creates a plan for using ingredients based on the generated menu, for example, planning to use cabbage for breakfast and dinner.

[0080] Step 7:

[0081] The server sends the generated menu and ingredient usage plan to the terminal.

[0082] Step 8:

[0083] The terminal displays the generated menu and ingredient usage plan received from the server to the user. For example, a menu of chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hotpot for dinner may be displayed.

[0084] Step 9:

[0085] The user reviews the displayed menu and ingredient usage plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[0086] This series of steps allows users to efficiently create menus and achieve a healthy, lean diet.

[0087] Example 1

[0088] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0089] In today's busy society, it is difficult to manage one's eating habits, especially maintaining a healthy diet and minimizing food waste. Furthermore, creating a menu for home cooking requires time and effort, and it is even more difficult to create a menu that takes into account allergies and food preferences. As a result, many people suffer from unhealthy eating habits and food waste.

[0090] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0091] In this invention, the server includes means for receiving information about a user's dietary habits from a user, means for transmitting the received information to the server, means for automatically generating a menu using a generative AI model based on the received information, means for creating an ingredient usage plan based on the generated menu, means for transmitting the generated menu and ingredient usage plan from the server to a terminal, and means for displaying the generated menu and ingredient usage plan to the user. This allows the user to efficiently create menus and enjoy a healthy and lean diet.

[0092] "User" refers to a person who uses the system to provide information about their own eating habits.

[0093] "Dietary information" refers to information that a user inputs into the system, such as dietary preferences, allergy information, budget, and a list of ingredients that the user has on hand.

[0094] "Terminal" refers to a device that allows a user to input information and display menus and ingredient usage plans sent from the server.

[0095] "Server" refers to a computer system that analyzes information received from users, automatically generates menus using generative AI models, and creates ingredient usage plans.

[0096] A "generative AI model" refers to an artificial intelligence model that automatically generates the optimal menu based on input information.

[0097] A "prompt sentence" is a sentence used to input information into a generative AI model, and contains information about the user's diet.

[0098] "Menu" refers to a specific meal menu automatically generated by a generative AI model based on the user's dietary information.

[0099] "Ingredient usage plan" refers to the specific usage schedule of ingredients to be used based on the generated menu to promote healthy eating habits and minimize food waste.

[0100] The present invention is a system for supporting a user's dietary management, and is mainly composed of three elements: a user, a terminal, and a server. Specific embodiments of the present invention will be described below.

[0101] User operations

[0102] Users access this system using devices such as smartphones or PCs. They enter the following information into the application:

[0103] Food preferences (e.g., Japanese food, Western food)

[0104] Allergy information (e.g. dairy, nuts)

[0105] Daily budget (e.g. 500 yen)

[0106] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0107] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0108] As a specific example, a user inputs information such as "Japanese food," "dairy allergy," "500 yen," "chicken, cabbage, carrots, eggs, rice," and "breakfast, lunch, dinner" into the application.

[0109] Device operation

[0110] The terminal sends the entered information to the server. This process is usually done using the HTTPS protocol. When the user presses the "Submit" button, the terminal sends this information to the server.

[0111] Processing on the server

[0112] The server analyzes the user information received from the terminal. The specific analysis process includes the following steps:

[0113] Validating an ingredient list (e.g., checking that the ingredients you have are actually available)

[0114] Allergy filtering (e.g., excluding ingredients that cause allergies)

[0115] Checking the budget (e.g., checking whether a menu can be created within the entered budget)

[0116] Menu generation

[0117] The server automatically generates the optimal menu using a generative AI model (e.g., a general-purpose artificial intelligence model) based on the analyzed information. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0118] "The user likes Japanese food and has a dairy allergy. Their budget is 500 yen, and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Please generate a menu based on this."

[0119] The generative AI model generates appropriate menu suggestions, such as "chicken rice balls and carrot miso soup for breakfast," "cabbage and carrot stir-fry with omelet for lunch," and "chicken and cabbage hot pot for dinner."

[0120] Creating an ingredient usage plan

[0121] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste. Specifically, the server plans how many meals to use the ingredients it has and which ingredients to prioritize. For example, it creates a specific usage plan, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0122] User Feedback

[0123] The server sends the generated menu and ingredient usage plan to the terminal. The terminal receives it and displays the generated menu and ingredient usage plan on the application screen in a visually easy-to-understand manner. For example, it may display chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0124] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[0125] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0126] Step 1: Enter your information

[0127] Users access the system using terminals.

[0128] Input: The user enters the following dietary information into the application:

[0129] Food preferences (e.g., Japanese food, Western food)

[0130] Allergy information (e.g. dairy, nuts)

[0131] Daily budget (e.g. 500 yen)

[0132] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0133] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0134] What happens: The user enters information and clicks the submit button.

[0135] Output: The entered information is saved on the device and ready to be sent to the server.

[0136] Step 2: Send information

[0137] The terminal transmits the input information to the server.

[0138] Input: Information entered after the user hits submit.

[0139] Specific operation: The terminal uses the HTTPS protocol to send information to the server.

[0140] Output: The user information is sent to the server.

[0141] Step 3: Analyzing information on the server

[0142] The server analyzes the user information received from the terminal.

[0143] Input: Information about the user's diet.

[0144] Specific behavior:

[0145] Ingredient list validation (check whether the ingredients you have are actually available)

[0146] Allergy information filtering (excluding ingredients that cause allergies)

[0147] Check whether it is possible to create a menu within your budget

[0148] Output: The parsed information is saved on the server.

[0149] Step 4: Menu generation

[0150] The server automatically generates the optimal menu using a generative AI model based on the analyzed information.

[0151] Input: Parsed user information.

[0152] Specific behavior:

[0153] The server generates a prompt sentence for the generative AI model and inputs it into the model.

[0154] Example prompt: "The user prefers Japanese food and has a dairy allergy. Their budget is 500 yen and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Generate a menu based on this."

[0155] A generative AI model analyzes this information and generates an optimal menu.

[0156] Output: The generated menu.

[0157] Step 5: Create an ingredient usage plan

[0158] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste.

[0159] Input: The generated menu.

[0160] Specific behavior:

[0161] Plan how many servings of a particular ingredient you will use.

[0162] Decide which ingredients to prioritize.

[0163] For example, create a specific plan for using cabbage at breakfast and dinner, and carrots at breakfast and lunch.

[0164] Output: Ingredient usage plan.

[0165] Step 6: Sending information (from server to device)

[0166] The server transmits the generated menu and ingredient usage plan to the terminal.

[0167] Input: Generated menu and ingredient usage plan.

[0168] Specific operation: The server uses the HTTPS protocol to send information to the terminal.

[0169] Output: The menu and ingredient plan are sent to the terminal.

[0170] Step 7: View your menu and spending plan

[0171] The terminal displays the information received from the server to the user.

[0172] Input: Menu and ingredient plan sent from the server.

[0173] Specific operation: The generated menu and ingredient usage plan are displayed visually and clearly on the application screen.

[0174] For example, it might say that breakfast is rice balls with chicken and carrot miso soup, lunch is stir-fried cabbage and carrots and tamagoyaki, and dinner is chicken and cabbage hot pot.

[0175] Output: A visual menu and ingredient plan for the user.

[0176] (Application example 1)

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

[0178] Today's hectic lifestyles make meal preparation and planning difficult. This calls for ways to minimize food waste while maintaining healthy eating habits. There is also a need for a system that not only provides personalized meal plans to users, but also comprehensive delivery options for ingredients based on those plans.

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

[0180] In this invention, the server includes means for receiving information about a user's dietary habits, means for automatically generating a menu using a generation AI based on the received information, means for displaying the generated menu to the user, means for creating an ingredient usage plan based on the generated menu, means for displaying the ingredient usage plan to the user, means for providing an ingredient list and delivery options for food delivery based on the generated menu and usage plan, and means for displaying the provided ingredient list and delivery options to the user, thereby enabling the user to efficiently plan and execute a healthy and lean diet and appropriately procure the necessary ingredients.

[0181] A "user" is an individual who uses the system to provide information about their eating habits and receive services such as menu suggestions and food delivery.

[0182] "Dietary information" refers to detailed data about the user's diet, such as the user's food preferences, allergy information, budget, number of meals per day, and a list of ingredients currently on hand.

[0183] "Generative AI" is an artificial intelligence that automatically generates optimal menus based on information input by the user.

[0184] A "menu" is a plan that shows the menu for each meal within a certain period of time based on the user's eating habits.

[0185] The "ingredient usage plan" is a plan that indicates the specific amount and timing of ingredients to be used for each meal based on the generated menu.

[0186] "Food delivery ingredient list" means a list of ingredients provided by a food delivery service based on the generated menu and usage plan.

[0187] "Delivery options" are options for food delivery provided to the user, including delivery date and time, delivery method, etc.

[0188] The present invention is a system that collects information about a user's eating habits, automatically generates menus based on that information, and provides a food delivery ingredient list and delivery options tailored to the user. An embodiment of the system is described in detail below.

[0189] System Configuration

[0190] This system consists of three main components: users, terminals, and servers.

[0191] User operations

[0192] 1. User: Accesses the system and inputs information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients currently on hand (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals eaten per day (e.g., breakfast, lunch, dinner).

[0193] Device operation

[0194] 2. Terminal: Sends the information entered by the user to the server, and receives the generated menu and ingredient usage plan, as well as the ingredient list and delivery options for food delivery, sent from the server, and displays them to the user.

[0195] Server Processing

[0196] 3. Server: Analyzes the user information received from the device and automatically generates the optimal menu using generative AI. This generative AI model uses GPT-3 (registered trademark).5, which utilizes Hugging Face's transformers library. Specific prompts are as follows:

[0197] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[0198] 4. Generative AI model: Generates the following menu based on user input information.

[0199] Breakfast: Chicken rice balls and carrot miso soup

[0200] Lunch: Stir-fried cabbage and carrots, rolled egg

[0201] Dinner: Chicken and cabbage hotpot

[0202] 5. Create a usage plan: Based on the generated menu, create a usage plan for ingredients to maintain a healthy diet and minimize food waste. For example, use cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0203] 6. Providing ingredient list and delivery options for food delivery: Based on the usage plan created, the required ingredient list and delivery options are generated and provided to the user.

[0204] User Feedback

[0205] 7. Feedback: The server sends the generated menu, ingredient plan, food delivery ingredient list and delivery options to the terminal, which displays them in an easy-to-understand manner for the user.

[0206] Specific examples

[0207] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[0208] 1. The user enters information.

[0209] 2. The device sends the information to the server.

[0210] 3. The server analyzes the received information, and the generation AI generates the menu shown above.

[0211] 4. The server will create a plan for using ingredients based on this.

[0212] 5. The server sends the generated menu, usage plan, ingredient list and delivery options to the device.

[0213] 6. The device displays the menu and provides a food plan to the user.

[0214] This system allows users to efficiently create menus and enjoy a healthy, lean diet. It also allows them to appropriately procure the ingredients they need through delivery services, improving the convenience of their lives.

[0215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0216] Step 1:

[0217] The user accesses the system and inputs information about their diet, such as their food preferences, allergies, daily budget, a list of ingredients they currently have, and the number of meals they eat per day, and this information is then sent to the device.

[0218] Input: Food preferences, allergy information, budget, list of ingredients you have, number of meals

[0219] Output: Detailed information about the user's diet

[0220] Step 2:

[0221] The device sends the information received from the user to the server, which then converts the information into an appropriate format and sends it to the server-side API.

[0222] Input: Detailed information about the user's diet

[0223] Output: API request sent to the server

[0224] Step 3:

[0225] The server analyzes the user information received from the device, and performs tasks such as checking the validity of the ingredient list and filtering allergy information.

[0226] Input: User information sent from the device

[0227] Output: Parsed user information

[0228] Step 4:

[0229] The server automatically generates the optimal menu using generative AI. Specifically, the generative AI model inputs user information as prompts and generates an appropriate menu. For generation, GPT-3.5 with Hugging Face's transformers library is used.

[0230] Input: Parsed user information, prompt text

[0231] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[0232] Output: Generated menu

[0233] Step 5:

[0234] The server creates an ingredient usage plan based on the generated menu, which helps maintain a healthy diet and minimize food waste.

[0235] Input: Generated menu

[0236] Output: Ingredient usage plan

[0237] Step 6:

[0238] The server provides the ingredient list and delivery options for food delivery. Based on the generated menu and usage plan, the server generates an appropriate ingredient list and its delivery options.

[0239] Input: Generated menu, ingredient usage plan

[0240] Output: Food delivery ingredients list, delivery options

[0241] Step 7:

[0242] The server sends the generated menu, ingredient usage plan, ingredient list for food delivery, and delivery options to the terminal.

[0243] Input: Generated menu, ingredient usage plan, ingredient list, delivery options

[0244] Output: Data sent to the terminal

[0245] Step 8:

[0246] The device displays the data received from the server to the user. Specifically, the generated menu, ingredient usage plan, food delivery ingredient list, and delivery options are displayed on the screen. Based on this, the user can plan their own meal and order the necessary ingredients via a delivery service.

[0247] Input: Data sent from the server

[0248] Output: Specific meal plan, usage plan, ingredient list, and delivery options displayed to the user

[0249] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0250] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using generative AI. It also combines an emotion engine that recognizes the user's emotions to suggest more personalized menus. This system can promote healthy eating habits and minimize product waste.

[0251] System Components

[0252] The system consists of the following main components:

[0253] 1. User: Provides information about dietary habits and accepts the system's menu suggestions.

[0254] 2. Terminal: Collects data from the user, sends it to the server, and displays the information from the server to the user.

[0255] 3. Server: Performs data analysis, menu generation using generative AI, ingredient usage planning, and emotion analysis using an emotion engine.

[0256] Program processing flow

[0257] 1. User Action:

[0258] Users open the application and enter information about their diet, including food preferences, allergy information, budget, a list of ingredients they have on hand, and meal frequency.

[0259] Emotions are provided to the system through the user's facial expressions, voice, and text input.

[0260] 2. Terminal operation:

[0261] The terminal transmits the user's input information and emotion data to the server.

[0262] 3. Server Processing:

[0263] The server analyzes the received information. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user is feeling stressed, it will suggest a meal plan that takes into account ingredients that help reduce stress.

[0264] Next, the analyzed emotional data and dietary information are input into a generation AI to generate the optimal menu.

[0265] Ingredients and menus are considered to address specific health and emotional states, and emotional analysis is used to select foods that have a relaxing effect or enhance your mood.

[0266] 4. Generative AI and ingredient planning:

[0267] The server uses AI to generate menus based on user information. For example, if the server detects that the user is tired, it will suggest a menu using ingredients that are good for replenishing energy.

[0268] The server then creates an ingredient usage plan based on the generated menu, for example, a plan for efficiently using ingredients across multiple meals.

[0269] 5. Feedback:

[0270] The server transmits the generated menu and ingredient usage plan to the terminal.

[0271] The device will display this to the user, suggesting, for example, stress-reducing herbal tea and fruit salad for breakfast, an energizing chicken and vegetable stir-fry for lunch, and a relaxing soup for dinner.

[0272] Specific examples

[0273] For example, let's assume that a user likes Western food, has no allergies, has a daily budget of 1,000 yen, and has chicken, tomatoes, cabbage, eggs, and bread. Furthermore, the following example shows the case where the user's emotions are analyzed as being stressed.

[0274] 1. User Action:

[0275] The user inputs this information and sends it, including emotion data, to the terminal.

[0276] 2. Terminal operation:

[0277] The device transmits this information and emotion data to the server.

[0278] 3. Server Processing:

[0279] The server uses an emotion engine to analyze stress and adjusts the menu based on the analysis results.

[0280] The generative AI generates the following menu:

[0281] Breakfast: Toast and tomato salad

[0282] Lunch: Stir-fried chicken and cabbage

[0283] Dinner: Vegetable soup and omelet

[0284] 4. Feedback:

[0285] The server sends the generated menu and ingredient usage plan to the terminal.

[0286] The terminal is displayed to the user.

[0287] The system allows users to efficiently plan meals, enjoy healthy and lean eating habits, and receive personalized suggestions tailored to their emotional state.

[0288] The processing flow will be explained below.

[0289] Step 1:

[0290] Users open the application and enter information about their diet, including food preferences (e.g., Japanese, Western), allergies (e.g., dairy, nuts), budget (e.g., 1,000 yen per day), ingredients they have (e.g., chicken, tomatoes, cabbage, eggs, bread), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[0291] Step 2:

[0292] The user provides their emotions to the system through their terminal. Emotion data is acquired through facial expression recognition, voice recognition, or text input.

[0293] Step 3:

[0294] The terminal transmits the information about the eating habits and emotion data collected from the user to the server in a lump sum.

[0295] Step 4:

[0296] The server analyzes all information received from the device. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user sends emotional data such as "I'm tired" or "I'm stressed," the server extracts the analysis results.

[0297] Step 5:

[0298] The server inputs the analysis results into a generation AI that adjusts the menu based on the emotional data. The generation AI generates an optimal menu based on the user's dietary preferences, allergy information, budget, available ingredients, and emotional state. For example, it may suggest a menu that includes foods that have a stress-reducing effect.

[0299] Step 6:

[0300] Based on the generated menu, the server creates an ingredient plan to efficiently use the ingredients available. Specifically, it plans how many meals a particular ingredient will be used and how. For example, it can plan to use cabbage for breakfast and dinner separately.

[0301] Step 7:

[0302] The server transmits the generated menu and ingredient usage plan to the terminal.

[0303] Step 8:

[0304] The terminal displays the information received from the server to the user, including a suggested menu (e.g., toast and tomato salad for breakfast, stir-fried chicken and cabbage for lunch, vegetable soup and omelet for dinner) and a plan for using the ingredients.

[0305] Step 9:

[0306] The user reviews the proposed menu and ingredient plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[0307] This series of steps allows users to efficiently plan meals, achieve a healthy and lean diet, and receive personalized suggestions based on their emotional state.

[0308] Example 2

[0309] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0310] While conventional menu generation systems can automatically generate menus based on information about a user's eating habits, they have difficulty making personalized suggestions that take the user's emotional state into account. Furthermore, they often fail to efficiently plan ingredient usage, resulting in food waste. Therefore, there is a need for a system that can efficiently plan ingredient usage while taking the user's emotional state into account.

[0311] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0312] In this invention, the server includes means for receiving information about the user's dietary habits, means for transmitting data including the received information and the user's emotional data to the server, means for analyzing the user's emotional state using an emotional analysis engine and inputting prompt sentences into a generative AI model based on the analysis results to automatically generate an optimal menu, means for creating an ingredient usage plan based on the generated menu, and means for feeding back the generated menu and ingredient usage plan to the user and displaying them on the user terminal. This enables personalized menu suggestions and efficient ingredient usage plans that take the user's emotional state into consideration.

[0313] "User" refers to an individual who uses this system and provides information about their diet and emotional data.

[0314] "Information about dietary habits" refers to information about the user's eating habits, such as food preferences, allergy information, budget, a list of ingredients in the user's possession, and the number of meals eaten.

[0315] "Emotional data" refers to information about a user's emotional state, collected through the user's facial expressions, voice, text input, etc.

[0316] A "terminal" is a device used by a user to input information, and specifically refers to a smartphone, PC, tablet, etc.

[0317] "Server" refers to a computer system that analyzes information sent by users, generates menus using generative AI and a sentiment analysis engine, and provides feedback.

[0318] "Emotion analysis engine" refers to software or hardware for analyzing a user's emotional data and identifying the user's emotional state.

[0319] A "generative AI model" refers to an artificial intelligence model that automatically generates optimal menus based on information about the user's eating habits and emotional state.

[0320] A "prompt sentence" is an instruction sentence input to a generative AI model that instructs the model to generate a specific menu based on the user's information and situation.

[0321] "Menu" refers to a list of meal suggestions that are automatically generated based on the user's eating habits.

[0322] The "ingredient usage plan" refers to a plan for efficiently using ingredients based on the generated menu.

[0323] "Feedback" refers to returning the generated menu and ingredient usage plan to the user and displaying it on the user terminal.

[0324] "JSON format" is an abbreviation for JavaScript (registered trademark) Object Notation, and refers to a lightweight data exchange format for exchanging structured data.

[0325] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using a generative AI model. Furthermore, this system incorporates an emotion analysis engine that can analyze the user's emotional state and suggest more personalized menus. The hardware and software configurations for implementing this system, as well as the data processing flow, are described below.

[0326] Main components of the system

[0327] User: Provides information about their diet and receives suggestions from the system.

[0328] Terminal: Collects data from the user and sends it to the server. It also displays information from the server to the user. Specific examples include smartphones (iPhone (registered trademark), ANDROID (registered trademark)) and PCs (Windows, Mac).

[0329] Server: Performs data analysis, menu generation using a generative AI model, ingredient planning, and sentiment analysis using a sentiment analysis engine. Software used includes programs written in Python and Java (registered trademark), sentiment analysis engines such as Microsoft (registered trademark) Azure (registered trademark) Emotion API, and generative AI models such as OpenAI (registered trademark) GPT-4 (registered trademark).

[0330] Specific explanation of the system's operation

[0331] 1. User Operation

[0332] Users open the application using their smartphone or PC and enter information about their dietary habits into the designated fields. This information includes food preferences, allergies, budget, list of ingredients on hand, and number of meals. Emotional data is also provided through facial expressions and voice. For example, users can enter "Western food," "no allergies," "budget 1,000 yen," "chicken, tomato, cabbage, egg, bread," and "number of meals three times," and then the camera scans their facial expressions.

[0333] 2. Terminal operation

[0334] The device temporarily stores the input data in its internal storage, and then sends the data (in JSON format) to the server using the HTTPS protocol. Specific examples of data include "Western food, no allergies, 1,000 yen, chicken, tomato, cabbage, egg, bread, and facial expression data."

[0335] 3. Server Processing

[0336] The server analyzes the received data. First, it uses an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, it adjusts the menu based on the analysis results. The emotional data and dietary information are then input into a generative AI model to generate an optimal menu. An example of a specific prompt could be, "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these."

[0337] 4. Menu generation using generative AI

[0338] The generative AI model generates a menu based on the prompt sentence, taking into account the user information. For example, the following menu is generated:

[0339] Breakfast: Toast and tomato salad

[0340] Lunch: Stir-fried chicken and cabbage

[0341] Dinner: Vegetable soup and omelet

[0342] 5. Create an ingredient usage plan

[0343] Based on the generated menu, the server creates an efficient ingredient usage plan, for example, using tomatoes in a breakfast salad and a stir-fry for lunch, and cabbage for lunch and dinner.

[0344] 6. Feedback

[0345] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol. The terminal receives this data and displays it on the user interface. Specifically, the menu screen displays options such as "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[0346] This system efficiently proposes personalized menus to users, helping them to lead a healthy and lean diet.It also makes suggestions based on the user's emotional state, thereby increasing user satisfaction.

[0347] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0348] Step 1:

[0349] User Input Processing

[0350] Users access the application using a smartphone or PC and input information about their dietary habits, including food preferences, allergies, budget, a list of ingredients they have on hand, and the number of meals they eat. Users also use a camera and microphone to provide emotional data such as facial expressions and voice.

[0351] Input: Dietary information (e.g., Western food, no allergies, budget 1,000 yen, chicken, tomato, cabbage, egg, bread), emotional data (facial expression, voice)

[0352] Output: Input data storage to the device

[0353] Step 2:

[0354] Data transmission by the terminal

[0355] The device temporarily stores the dietary information and emotion data entered by the user in its internal storage and transmits them to the server using the HTTPS protocol.

[0356] Input: User information and emotion data stored in internal storage

[0357] Output: Send data to the server

[0358] Step 3:

[0359] Data reception and analysis by the server

[0360] The server receives and analyzes the data sent from the device. First, it uses an emotion analysis engine to analyze the emotion data and identify the user's emotional state. From the analysis results, it extracts the user's emotional state (e.g., stress level).

[0361] Input: User information and emotion data sent via HTTPS

[0362] Output: User's emotional state (e.g., stress state)

[0363] Step 4:

[0364] Prompt input and menu generation using generative AI

[0365] The server inputs a prompt into the generative AI model based on the analyzed emotional data and the user's dietary information. A specific instruction is generated: "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these." The generative AI model then automatically generates the optimal menu based on this.

[0366] Input: User information, analysis results, prompt text

[0367] Output: Generated menu (e.g. Breakfast: Toast and tomato salad, Lunch: Stir-fried chicken and cabbage, Dinner: Vegetable soup and omelet)

[0368] Step 5:

[0369] Creating an ingredient usage plan

[0370] The server creates an efficient ingredient plan based on the generated menu, for example, using tomatoes in a breakfast salad and a lunch stir-fry, and using cabbage for lunch and dinner, thereby minimizing food waste.

[0371] Input: Generated menu

[0372] Output: Ingredient usage plan (e.g., tomatoes for breakfast and lunch, cabbage for lunch and dinner)

[0373] Step 6:

[0374] Server feedback

[0375] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol.

[0376] Input: Generated menu and ingredient plan

[0377] Output: Sending data to the terminal

[0378] Step 7:

[0379] Displaying data on a terminal

[0380] The device receives the data sent from the server and displays it on the user interface. Specifically, the menu screen of the application displays "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[0381] Input: Menu and ingredient usage plan sent from the server

[0382] Output: Display of menu and ingredient plan to user

[0383] (Application example 2)

[0384] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0385] In modern society, eating a healthy diet is important, but achieving it in a busy daily life is not easy. The lack of personalized menu suggestions that take into account the user's emotional state is a further challenge. Furthermore, a system that utilizes food delivery services and proposes efficient and waste-free ingredient usage plans is needed.

[0386] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for adjusting a menu based on the emotional state, and means for ordering ingredients and dishes from a food delivery service based on the menu. This makes it possible to provide a personalized menu taking into account the emotional state of the user, and to efficiently use food delivery services.

[0387] "User" means an individual user of the system.

[0388] "Dietary information" refers to data such as the user's dietary preferences, allergy information, budget, and a list of ingredients they own.

[0389] "Generative AI" is a technology that uses artificial intelligence to automatically generate menus based on specific data.

[0390] A "menu" is a meal combination or cooking plan suggested for a user to consume.

[0391] "Ingredient usage plan" refers to a plan for efficiently using ingredients based on the proposed menu.

[0392] "Emotional state" is data that indicates a user's current psychological or emotional state.

[0393] A "food delivery service" is a service that delivers ingredients and meals to a user's home or designated location based on the user's order.

[0394] A "server" is a central processing unit that processes and analyzes data and provides feedback to the user interface.

[0395] A "terminal" is a device through which a user accesses the system and inputs or receives information.

[0396] "Analysis" is the process of examining data in detail to reveal its meaning and structure.

[0397] This invention is a system that analyzes a user's dietary information and emotional state, proposes personalized menus using generative AI, and then efficiently provides ingredients and dishes using a food delivery service. Specific embodiments of the system are described below.

[0398] System Components

[0399] The system consists of the following main components:

[0400] 1. User: An individual user of the system.

[0401] 2. Terminal: A device, such as a smartphone, through which a user inputs information and interfaces with the system.

[0402] 3. Server: A central processing unit that receives, analyzes, and generates data. It generates menus using AI, analyzes emotions using an emotion engine, and connects with food delivery services.

[0403] System Operation

[0404] 1. User interaction and data entry

[0405] The user opens the food delivery app on their smartphone and enters the following information:

[0406] Food preferences

[0407] Allergy Information

[0408] Daily Budget

[0409] List of ingredients you have

[0410] Number of meals

[0411] The app also uses the camera and microphone to capture the user's facial expressions and voice and record them as emotional data.

[0412] 2. Data transmission

[0413] The terminal transmits the user's input information and emotion data to the server.

[0414] 3. Data analysis and menu generation on the server

[0415] The server analyzes the received data. First, it uses an emotion engine to analyze the user's emotional state. For emotion analysis, it uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API.

[0416] Next, a generative AI generates an optimal menu based on dietary information and emotional data. This uses a generative AI such as OpenAI's GPT model. A specific example of a prompt is as follows:

[0417] Prompt Sentence Examples

[0418] User preference: Japanese food

[0419] Allergy Information: Dairy allergy

[0420] Budget: 1,500 yen

[0421] Ingredients I have: Chicken, potatoes, carrots

[0422] Emotional state: Fatigue

[0423] Based on this, please suggest the best menu.

[0424] 4. Creation and collaboration of ingredient use plans

[0425] The server creates an efficient ingredient usage plan based on the generated menu, which allows for efficient consumption of ingredients across multiple meals.

[0426] 5. Integration with food delivery services

[0427] The user confirms the proposed menu, and the server coordinates with a food delivery service to arrange for the necessary ingredients and dishes to be delivered to the user's designated location.

[0428] Specific examples

[0429] For example, if a user prefers Japanese food, has a dairy allergy, has a daily budget of 1500 yen, has chicken, potatoes, and carrots, and is in a "fatigued" emotional state, the following menu will be generated:

[0430] Breakfast: Rice balls and miso soup

[0431] Lunch: Chicken and potato stew

[0432] Dinner: Carrot and spinach salad

[0433] Based on this, the system orders additional ingredients and dishes from a food delivery service and delivers them to the user, enabling users to lead a healthy and efficient diet without any hassle.

[0434] The above is an embodiment of the present invention. This system enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[0435] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0436] Step 1:

[0437] The user opens a food delivery app on their smartphone. There, they input information about their diet. Specifically, they input their food preferences, allergy information, budget, list of ingredients they have, number of meals, etc. They also provide facial and voice data using a camera and microphone. This information is then captured by the device. The input data is the user's food preferences, allergy information, budget, list of ingredients they have, number of meals, and emotional data.

[0438] Step 2:

[0439] The device sends the data entered by the user and emotion data to the server. The device then uploads the acquired data to the server as a JSON format request. The data sent is dietary information and emotion data, and is sent to the server's API endpoint.

[0440] Step 3:

[0441] The server analyzes the received dietary information and emotional data. First, the emotion engine analyzes the emotional data and evaluates the user's emotional state. This analysis uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API. The input is emotional data, and the output is the user's emotional state as a result of the analysis.

[0442] Step 4:

[0443] The server uses a generative AI to generate an optimal menu based on the analyzed emotional state and dietary information. The generative AI uses, for example, OpenAI's GPT model. This AI generates a personalized menu based on the user's preferences, allergy information, budget, ingredients available, emotional state, etc. The input is dietary information and emotional state, and the output is the generated menu.

[0444] Step 5:

[0445] The server creates an ingredient usage plan based on the generated menu. Based on the generated menu, a plan is created to use ingredients without waste. This ingredient usage plan includes a method for efficiently allocating ingredients to multiple meals. The input is the generated menu, and the output is an ingredient usage plan.

[0446] Step 6:

[0447] The server sends the generated menu and ingredient usage plan to the terminal. The server returns this data to the terminal and displays it on the user's smartphone. The transmitted data is the generated menu and ingredient usage plan.

[0448] Step 7:

[0449] Users can check the menu and ingredient usage plan displayed on their smartphone. If they like it, they can order ingredients and dishes from a food delivery service with just one tap. The order information is sent to the food delivery service, and the required ingredients and dishes are delivered to the user.

[0450] This concludes the processing flow of the system program that realizes this application example. This processing enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[0451] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0452] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0453] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0454] [Second embodiment]

[0455] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0456] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0457] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0458] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0459] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0460] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0461] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0462] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0463] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0464] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0465] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0466] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0467] The present invention provides a system that allows users to easily plan their daily meals at home, promotes healthy eating habits, and prevents product waste. An embodiment of the system will now be described in detail.

[0468] This system consists of three main components: users, terminals, and servers.

[0469] User operations

[0470] Users access the system through applications.

[0471] Users input information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients they currently have (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[0472] Device operation

[0473] The terminal transmits the information entered by the user to the server.

[0474] The terminal receives the generated menu and ingredient usage plan sent from the server and displays them to the user.

[0475] Server Processing

[0476] The server analyzes the user information received from the terminal.

[0477] This analysis includes validating ingredient lists and filtering allergy information.

[0478] The server uses generative AI to automatically generate the optimal menu.

[0479] The AI ​​generates a menu that is appropriate for the user based on information such as the user's preferences, allergy information, budget, list of ingredients they have, and number of meals.

[0480] Based on the generated menu, the server creates a plan for using ingredients to minimize product waste while maintaining a healthy diet.

[0481] Specifically, this includes a detailed plan of how many servings of a particular ingredient should be used and which ingredients should be prioritized.

[0482] User Feedback

[0483] The server transmits the generated menu and ingredient usage plan to the terminal.

[0484] The terminal displays this in an easy-to-understand manner to the user.

[0485] For example, we suggest chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0486] It also provides specific advice on planning how to use ingredients, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0487] Specific examples

[0488] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[0489] 1. The user enters information.

[0490] 2. The device sends the information to the server.

[0491] 3. The server analyzes the received information, and the AI ​​generates the following menu:

[0492] Breakfast: Chicken rice balls and carrot miso soup

[0493] Lunch: Stir-fried cabbage and carrots, rolled egg

[0494] Dinner: Chicken and cabbage hotpot

[0495] 4. The server will create a plan for using ingredients based on this.

[0496] 5. The server sends the generated menu and usage plan to the terminal.

[0497] 6. The device displays the menu and provides a food plan to the user.

[0498] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[0499] The processing flow will be explained below.

[0500] Step 1:

[0501] Users open the application and enter information about their diet, such as food preferences, allergy information, daily budget, a list of ingredients they have on hand, and the number of meals they eat per day.

[0502] Step 2:

[0503] The terminal stores the information about the dietary habits entered by the user in a database and transmits it to the server.

[0504] Step 3:

[0505] The server analyzes the user information received from the device, including validating the ingredient list (e.g., checking inventory) and filtering allergy information (excluding risky ingredients).

[0506] Step 4:

[0507] The server uses the analyzed data and passes it to the generation AI, which receives the user's preferences, allergy information, budget, list of ingredients they have, and number of meals as input parameters.

[0508] Step 5:

[0509] The AI ​​on the server generates the optimal menu based on these input parameters. For example, if a user likes Japanese food but has a dairy allergy, the AI ​​will suggest a Japanese menu that does not include dairy products.

[0510] Step 6:

[0511] The server creates a plan for using ingredients based on the generated menu, for example, planning to use cabbage for breakfast and dinner.

[0512] Step 7:

[0513] The server sends the generated menu and ingredient usage plan to the terminal.

[0514] Step 8:

[0515] The terminal displays the generated menu and ingredient usage plan received from the server to the user. For example, a menu of chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hotpot for dinner may be displayed.

[0516] Step 9:

[0517] The user reviews the displayed menu and ingredient usage plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[0518] This series of steps allows users to efficiently create menus and achieve a healthy, lean diet.

[0519] Example 1

[0520] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0521] In today's busy society, it is difficult to manage one's eating habits, especially maintaining a healthy diet and minimizing food waste. Furthermore, creating a menu for home cooking requires time and effort, and it is even more difficult to create a menu that takes into account allergies and food preferences. As a result, many people suffer from unhealthy eating habits and food waste.

[0522] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0523] In this invention, the server includes means for receiving information about a user's dietary habits from a user, means for transmitting the received information to the server, means for automatically generating a menu using a generative AI model based on the received information, means for creating an ingredient usage plan based on the generated menu, means for transmitting the generated menu and ingredient usage plan from the server to a terminal, and means for displaying the generated menu and ingredient usage plan to the user. This allows the user to efficiently create menus and enjoy a healthy and lean diet.

[0524] "User" refers to a person who uses the system to provide information about their own eating habits.

[0525] "Dietary information" refers to information that a user inputs into the system, such as dietary preferences, allergy information, budget, and a list of ingredients that the user has on hand.

[0526] "Terminal" refers to a device that allows a user to input information and display menus and ingredient usage plans sent from the server.

[0527] "Server" refers to a computer system that analyzes information received from users, automatically generates menus using generative AI models, and creates ingredient usage plans.

[0528] A "generative AI model" refers to an artificial intelligence model that automatically generates the optimal menu based on input information.

[0529] A "prompt sentence" is a sentence used to input information into a generative AI model, and contains information about the user's diet.

[0530] "Menu" refers to a specific meal menu automatically generated by a generative AI model based on the user's dietary information.

[0531] "Ingredient usage plan" refers to the specific usage schedule of ingredients to be used based on the generated menu to promote healthy eating habits and minimize food waste.

[0532] The present invention is a system for supporting a user's dietary management, and is mainly composed of three elements: a user, a terminal, and a server. Specific embodiments of the present invention will be described below.

[0533] User operations

[0534] Users access this system using devices such as smartphones or PCs. They enter the following information into the application:

[0535] Food preferences (e.g., Japanese food, Western food)

[0536] Allergy information (e.g. dairy, nuts)

[0537] Daily budget (e.g. 500 yen)

[0538] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0539] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0540] As a specific example, a user inputs information such as "Japanese food," "dairy allergy," "500 yen," "chicken, cabbage, carrots, eggs, rice," and "breakfast, lunch, dinner" into the application.

[0541] Device operation

[0542] The terminal sends the entered information to the server. This process is usually done using the HTTPS protocol. When the user presses the "Submit" button, the terminal sends this information to the server.

[0543] Processing on the server

[0544] The server analyzes the user information received from the terminal. The specific analysis process includes the following steps:

[0545] Validating an ingredient list (e.g., checking that the ingredients you have are actually available)

[0546] Allergy filtering (e.g., excluding ingredients that cause allergies)

[0547] Checking the budget (e.g., checking whether a menu can be created within the entered budget)

[0548] Menu generation

[0549] The server automatically generates the optimal menu using a generative AI model (e.g., a general-purpose artificial intelligence model) based on the analyzed information. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0550] "The user likes Japanese food and has a dairy allergy. Their budget is 500 yen, and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Please generate a menu based on this."

[0551] The generative AI model generates appropriate menu suggestions, such as "chicken rice balls and carrot miso soup for breakfast," "cabbage and carrot stir-fry with omelet for lunch," and "chicken and cabbage hot pot for dinner."

[0552] Creating an ingredient usage plan

[0553] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste. Specifically, the server plans how many meals to use the ingredients it has and which ingredients to prioritize. For example, it creates a specific usage plan, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0554] User Feedback

[0555] The server sends the generated menu and ingredient usage plan to the terminal. The terminal receives it and displays the generated menu and ingredient usage plan on the application screen in a visually easy-to-understand manner. For example, it may display chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0556] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[0557] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0558] Step 1: Enter your information

[0559] Users access the system using terminals.

[0560] Input: The user enters the following dietary information into the application:

[0561] Food preferences (e.g., Japanese food, Western food)

[0562] Allergy information (e.g. dairy, nuts)

[0563] Daily budget (e.g. 500 yen)

[0564] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0565] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0566] What happens: The user enters information and clicks the submit button.

[0567] Output: The entered information is saved on the device and ready to be sent to the server.

[0568] Step 2: Send information

[0569] The terminal transmits the input information to the server.

[0570] Input: Information entered after the user hits submit.

[0571] Specific operation: The terminal uses the HTTPS protocol to send information to the server.

[0572] Output: The user information is sent to the server.

[0573] Step 3: Analyzing information on the server

[0574] The server analyzes the user information received from the terminal.

[0575] Input: Information about the user's diet.

[0576] Specific behavior:

[0577] Ingredient list validation (check whether the ingredients you have are actually available)

[0578] Allergy information filtering (excluding ingredients that cause allergies)

[0579] Check whether it is possible to create a menu within your budget

[0580] Output: The parsed information is saved on the server.

[0581] Step 4: Menu generation

[0582] The server automatically generates the optimal menu using a generative AI model based on the analyzed information.

[0583] Input: Parsed user information.

[0584] Specific behavior:

[0585] The server generates a prompt sentence for the generative AI model and inputs it into the model.

[0586] Example prompt: "The user prefers Japanese food and has a dairy allergy. Their budget is 500 yen and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Generate a menu based on this."

[0587] A generative AI model analyzes this information and generates an optimal menu.

[0588] Output: The generated menu.

[0589] Step 5: Create an ingredient usage plan

[0590] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste.

[0591] Input: The generated menu.

[0592] Specific behavior:

[0593] Plan how many servings of a particular ingredient you will use.

[0594] Decide which ingredients to prioritize.

[0595] For example, create a specific plan for using cabbage at breakfast and dinner, and carrots at breakfast and lunch.

[0596] Output: Ingredient usage plan.

[0597] Step 6: Sending information (from server to device)

[0598] The server transmits the generated menu and ingredient usage plan to the terminal.

[0599] Input: Generated menu and ingredient usage plan.

[0600] Specific operation: The server uses the HTTPS protocol to send information to the terminal.

[0601] Output: The menu and ingredient plan are sent to the terminal.

[0602] Step 7: View your menu and spending plan

[0603] The terminal displays the information received from the server to the user.

[0604] Input: Menu and ingredient plan sent from the server.

[0605] Specific operation: The generated menu and ingredient usage plan are displayed visually and clearly on the application screen.

[0606] For example, it might say that breakfast is rice balls with chicken and carrot miso soup, lunch is stir-fried cabbage and carrots and tamagoyaki, and dinner is chicken and cabbage hot pot.

[0607] Output: A visual menu and ingredient plan for the user.

[0608] (Application example 1)

[0609] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0610] Today's hectic lifestyles make meal preparation and planning difficult. This calls for ways to minimize food waste while maintaining healthy eating habits. There is also a need for a system that not only provides personalized meal plans to users, but also comprehensive delivery options for ingredients based on those plans.

[0611] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0612] In this invention, the server includes means for receiving information about a user's dietary habits, means for automatically generating a menu using a generation AI based on the received information, means for displaying the generated menu to the user, means for creating an ingredient usage plan based on the generated menu, means for displaying the ingredient usage plan to the user, means for providing an ingredient list and delivery options for food delivery based on the generated menu and usage plan, and means for displaying the provided ingredient list and delivery options to the user, thereby enabling the user to efficiently plan and execute a healthy and lean diet and appropriately procure the necessary ingredients.

[0613] A "user" is an individual who uses the system to provide information about their eating habits and receive services such as menu suggestions and food delivery.

[0614] "Dietary information" refers to detailed data about the user's diet, such as the user's food preferences, allergy information, budget, number of meals per day, and a list of ingredients currently on hand.

[0615] "Generative AI" is an artificial intelligence that automatically generates optimal menus based on information input by the user.

[0616] A "menu" is a plan that shows the menu for each meal within a certain period of time based on the user's eating habits.

[0617] The "ingredient usage plan" is a plan that indicates the specific amount and timing of ingredients to be used for each meal based on the generated menu.

[0618] "Food delivery ingredient list" means a list of ingredients provided by a food delivery service based on the generated menu and usage plan.

[0619] "Delivery options" are options for food delivery provided to the user, including delivery date and time, delivery method, etc.

[0620] The present invention is a system that collects information about a user's eating habits, automatically generates menus based on that information, and provides a food delivery ingredient list and delivery options tailored to the user. An embodiment of the system is described in detail below.

[0621] System Configuration

[0622] This system consists of three main components: users, terminals, and servers.

[0623] User operations

[0624] 1. User: Accesses the system and inputs information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients currently on hand (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals eaten per day (e.g., breakfast, lunch, dinner).

[0625] Device operation

[0626] 2. Terminal: Sends the information entered by the user to the server, and receives the generated menu and ingredient usage plan, as well as the ingredient list and delivery options for food delivery, sent from the server, and displays them to the user.

[0627] Server Processing

[0628] 3. Server: Analyzes the user information received from the device and automatically generates the optimal menu using generative AI. This generative AI model uses GPT-3.5, which utilizes the Hugging Face transformers library. Specific prompts are as follows:

[0629] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[0630] 4. Generative AI model: Generates the following menu based on user input information.

[0631] Breakfast: Chicken rice balls and carrot miso soup

[0632] Lunch: Stir-fried cabbage and carrots, rolled egg

[0633] Dinner: Chicken and cabbage hotpot

[0634] 5. Create a usage plan: Based on the generated menu, create a usage plan for ingredients to maintain a healthy diet and minimize food waste. For example, use cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0635] 6. Providing ingredient lists and delivery options for food delivery: Based on the usage plan created, the required ingredient lists and delivery options are generated and provided to the user.

[0636] User Feedback

[0637] 7. Feedback: The server sends the generated menu, ingredient plan, food delivery ingredient list and delivery options to the terminal, which displays them in an easy-to-understand manner for the user.

[0638] Specific examples

[0639] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[0640] 1. The user enters information.

[0641] 2. The device sends the information to the server.

[0642] 3. The server analyzes the received information, and the generation AI generates the menu shown above.

[0643] 4. The server will create a plan for using ingredients based on this.

[0644] 5. The server sends the generated menu, usage plan, ingredient list and delivery options to the device.

[0645] 6. The device displays the menu and provides a food plan to the user.

[0646] This system allows users to efficiently create menus and enjoy a healthy, lean diet. It also allows them to appropriately procure the ingredients they need through delivery services, improving the convenience of their lives.

[0647] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0648] Step 1:

[0649] The user accesses the system and inputs information about their diet, such as their food preferences, allergies, daily budget, a list of ingredients they currently have, and the number of meals they eat per day, and this information is then sent to the device.

[0650] Input: Food preferences, allergy information, budget, list of ingredients you have, number of meals

[0651] Output: Detailed information about the user's diet

[0652] Step 2:

[0653] The device sends the information received from the user to the server, which then converts the information into an appropriate format and sends it to the server-side API.

[0654] Input: Detailed information about the user's diet

[0655] Output: API request sent to the server

[0656] Step 3:

[0657] The server analyzes the user information received from the device, and performs tasks such as checking the validity of the ingredient list and filtering allergy information.

[0658] Input: User information sent from the device

[0659] Output: Parsed user information

[0660] Step 4:

[0661] The server automatically generates the optimal menu using generative AI. Specifically, the generative AI model inputs user information as prompts and generates an appropriate menu. For generation, GPT-3.5 with Hugging Face's transformers library is used.

[0662] Input: Parsed user information, prompt text

[0663] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[0664] Output: Generated menu

[0665] Step 5:

[0666] The server creates an ingredient usage plan based on the generated menu, which helps maintain a healthy diet and minimize food waste.

[0667] Input: Generated menu

[0668] Output: Ingredient usage plan

[0669] Step 6:

[0670] The server provides the ingredient list and delivery options for food delivery. Based on the generated menu and usage plan, the server generates an appropriate ingredient list and its delivery options.

[0671] Input: Generated menu, ingredient usage plan

[0672] Output: Food delivery ingredients list, delivery options

[0673] Step 7:

[0674] The server sends the generated menu, ingredient usage plan, ingredient list for food delivery, and delivery options to the terminal.

[0675] Input: Generated menu, ingredient usage plan, ingredient list, delivery options

[0676] Output: Data sent to the terminal

[0677] Step 8:

[0678] The device displays the data received from the server to the user. Specifically, the generated menu, ingredient usage plan, food delivery ingredient list, and delivery options are displayed on the screen. Based on this, the user can plan their own meal and order the necessary ingredients via a delivery service.

[0679] Input: Data sent from the server

[0680] Output: Specific meal plan, usage plan, ingredient list, and delivery options displayed to the user

[0681] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0682] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using generative AI. It also combines an emotion engine that recognizes the user's emotions to suggest more personalized menus. This system can promote healthy eating habits and minimize product waste.

[0683] System Components

[0684] The system consists of the following main components:

[0685] 1. User: Provides information about dietary habits and accepts the system's menu suggestions.

[0686] 2. Terminal: Collects data from the user, sends it to the server, and displays the information from the server to the user.

[0687] 3. Server: Performs data analysis, menu generation using generative AI, ingredient usage planning, and emotion analysis using an emotion engine.

[0688] Program processing flow

[0689] 1. User Action:

[0690] Users open the application and enter information about their diet, including food preferences, allergy information, budget, a list of ingredients they have on hand, and meal frequency.

[0691] Emotions are provided to the system through the user's facial expressions, voice, and text input.

[0692] 2. Terminal operation:

[0693] The terminal transmits the user's input information and emotion data to the server.

[0694] 3. Server Processing:

[0695] The server analyzes the received information. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user is feeling stressed, it will suggest a meal plan that takes into account ingredients that help reduce stress.

[0696] Next, the analyzed emotional data and dietary information are input into a generation AI to generate the optimal menu.

[0697] Ingredients and menus are considered to address specific health and emotional states, and emotional analysis is used to select foods that have a relaxing effect or enhance your mood.

[0698] 4. Generative AI and ingredient planning:

[0699] The server uses AI to generate menus based on user information. For example, if the server detects that the user is tired, it will suggest a menu using ingredients that are good for replenishing energy.

[0700] The server then creates an ingredient usage plan based on the generated menu, for example, a plan for efficiently using ingredients across multiple meals.

[0701] 5. Feedback:

[0702] The server transmits the generated menu and ingredient usage plan to the terminal.

[0703] The device will display this to the user, suggesting, for example, stress-reducing herbal tea and fruit salad for breakfast, an energizing chicken and vegetable stir-fry for lunch, and a relaxing soup for dinner.

[0704] Specific examples

[0705] For example, let's assume that a user likes Western food, has no allergies, has a daily budget of 1,000 yen, and has chicken, tomatoes, cabbage, eggs, and bread. Furthermore, the following example shows the case where the user's emotions are analyzed as being stressed.

[0706] 1. User Action:

[0707] The user inputs this information and sends it, including emotion data, to the terminal.

[0708] 2. Terminal operation:

[0709] The device transmits this information and emotion data to the server.

[0710] 3. Server Processing:

[0711] The server uses an emotion engine to analyze stress and adjusts the menu based on the analysis results.

[0712] The generative AI generates the following menu:

[0713] Breakfast: Toast and tomato salad

[0714] Lunch: Stir-fried chicken and cabbage

[0715] Dinner: Vegetable soup and omelet

[0716] 4. Feedback:

[0717] The server sends the generated menu and ingredient usage plan to the terminal.

[0718] The terminal is displayed to the user.

[0719] The system allows users to efficiently plan meals, enjoy healthy and lean eating habits, and receive personalized suggestions tailored to their emotional state.

[0720] The processing flow will be explained below.

[0721] Step 1:

[0722] Users open the application and enter information about their diet, including food preferences (e.g., Japanese, Western), allergies (e.g., dairy, nuts), budget (e.g., 1,000 yen per day), ingredients they have (e.g., chicken, tomatoes, cabbage, eggs, bread), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[0723] Step 2:

[0724] The user provides their emotions to the system through their terminal. Emotion data is acquired through facial expression recognition, voice recognition, or text input.

[0725] Step 3:

[0726] The terminal transmits the information about the eating habits and emotion data collected from the user to the server in a lump sum.

[0727] Step 4:

[0728] The server analyzes all information received from the device. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user sends emotional data such as "I'm tired" or "I'm stressed," the server extracts the analysis results.

[0729] Step 5:

[0730] The server inputs the analysis results into a generation AI that adjusts the menu based on the emotional data. The generation AI generates an optimal menu based on the user's dietary preferences, allergy information, budget, available ingredients, and emotional state. For example, it may suggest a menu that includes foods that have a stress-reducing effect.

[0731] Step 6:

[0732] Based on the generated menu, the server creates an ingredient plan to efficiently use the ingredients available. Specifically, it plans how many meals a particular ingredient will be used and how. For example, it can plan to use cabbage for breakfast and dinner separately.

[0733] Step 7:

[0734] The server transmits the generated menu and ingredient usage plan to the terminal.

[0735] Step 8:

[0736] The terminal displays the information received from the server to the user, including a suggested menu (e.g., toast and tomato salad for breakfast, stir-fried chicken and cabbage for lunch, vegetable soup and omelet for dinner) and a plan for using the ingredients.

[0737] Step 9:

[0738] The user reviews the proposed menu and ingredient plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[0739] This series of steps allows users to efficiently plan meals, achieve a healthy and lean diet, and receive personalized suggestions based on their emotional state.

[0740] Example 2

[0741] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0742] While conventional menu generation systems can automatically generate menus based on information about a user's eating habits, they have difficulty making personalized suggestions that take the user's emotional state into account. Furthermore, they often fail to efficiently plan ingredient usage, resulting in food waste. Therefore, there is a need for a system that can efficiently plan ingredient usage while taking the user's emotional state into account.

[0743] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0744] In this invention, the server includes means for receiving information about the user's dietary habits, means for transmitting data including the received information and the user's emotional data to the server, means for analyzing the user's emotional state using an emotional analysis engine and inputting prompt sentences into a generative AI model based on the analysis results to automatically generate an optimal menu, means for creating an ingredient usage plan based on the generated menu, and means for feeding back the generated menu and ingredient usage plan to the user and displaying them on the user terminal. This enables personalized menu suggestions and efficient ingredient usage plans that take the user's emotional state into consideration.

[0745] "User" refers to an individual who uses this system and provides information about their diet and emotional data.

[0746] "Information about dietary habits" refers to information about the user's eating habits, such as food preferences, allergy information, budget, a list of ingredients in the user's possession, and the number of meals eaten.

[0747] "Emotional data" refers to information about a user's emotional state, collected through the user's facial expressions, voice, text input, etc.

[0748] A "terminal" is a device used by a user to input information, and specifically refers to a smartphone, PC, tablet, etc.

[0749] "Server" refers to a computer system that analyzes information sent by users, generates menus using generative AI and a sentiment analysis engine, and provides feedback.

[0750] "Emotion analysis engine" refers to software or hardware for analyzing a user's emotional data and identifying the user's emotional state.

[0751] A "generative AI model" refers to an artificial intelligence model that automatically generates optimal menus based on information about the user's eating habits and emotional state.

[0752] A "prompt sentence" is an instruction sentence input to a generative AI model that instructs the model to generate a specific menu based on the user's information and situation.

[0753] "Menu" refers to a list of meal suggestions that are automatically generated based on the user's eating habits.

[0754] The "ingredient usage plan" refers to a plan for efficiently using ingredients based on the generated menu.

[0755] "Feedback" refers to returning the generated menu and ingredient usage plan to the user and displaying it on the user terminal.

[0756] "JSON format" stands for JavaScript Object Notation and refers to a lightweight data exchange format for exchanging structured data.

[0757] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using a generative AI model. Furthermore, this system incorporates an emotion analysis engine that can analyze the user's emotional state and suggest more personalized menus. The hardware and software configurations for implementing this system, as well as the data processing flow, are described below.

[0758] Main components of the system

[0759] User: Provides information about their diet and receives suggestions from the system.

[0760] Terminal: Collects data from the user and sends it to the server. It also displays information from the server to the user. Specific examples include smartphones (iPhone, Android) and PCs (Windows, Mac).

[0761] Server: Performs data analysis, menu generation using a generative AI model, ingredient planning, and sentiment analysis using an emotion analysis engine. Software used includes programs written in Python and Java, the Microsoft Azure Emotion API as the sentiment analysis engine, and OpenAI GPT-4 as the generative AI model.

[0762] Specific explanation of the system's operation

[0763] 1. User Operation

[0764] Users open the application using their smartphone or PC and enter information about their dietary habits into the designated fields. This information includes food preferences, allergies, budget, list of ingredients on hand, and number of meals. Emotional data is also provided through facial expressions and voice. For example, users can enter "Western food," "no allergies," "budget 1,000 yen," "chicken, tomato, cabbage, egg, bread," and "number of meals three times," and then the camera scans their facial expressions.

[0765] 2. Terminal operation

[0766] The device temporarily stores the input data in its internal storage, and then sends the data (in JSON format) to the server using the HTTPS protocol. Specific examples of data include "Western food, no allergies, 1,000 yen, chicken, tomato, cabbage, egg, bread, and facial expression data."

[0767] 3. Server Processing

[0768] The server analyzes the received data. First, it uses an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, it adjusts the menu based on the analysis results. The emotional data and dietary information are then input into a generative AI model to generate an optimal menu. An example of a specific prompt could be, "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these."

[0769] 4. Menu generation using generative AI

[0770] The generative AI model generates a menu based on the prompt sentence, taking into account the user information. For example, the following menu is generated:

[0771] Breakfast: Toast and tomato salad

[0772] Lunch: Stir-fried chicken and cabbage

[0773] Dinner: Vegetable soup and omelet

[0774] 5. Create an ingredient usage plan

[0775] Based on the generated menu, the server creates an efficient ingredient usage plan, for example, using tomatoes in a breakfast salad and a stir-fry for lunch, and cabbage for lunch and dinner.

[0776] 6. Feedback

[0777] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol. The terminal receives this data and displays it on the user interface. Specifically, the menu screen displays options such as "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[0778] This system efficiently proposes personalized menus to users, helping them to lead a healthy and lean diet.It also makes suggestions based on the user's emotional state, thereby increasing user satisfaction.

[0779] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0780] Step 1:

[0781] User Input Processing

[0782] Users access the application using a smartphone or PC and input information about their dietary habits, including food preferences, allergies, budget, a list of ingredients they have on hand, and the number of meals they eat. Users also use a camera and microphone to provide emotional data such as facial expressions and voice.

[0783] Input: Dietary information (e.g., Western food, no allergies, budget 1,000 yen, chicken, tomato, cabbage, egg, bread), emotional data (facial expression, voice)

[0784] Output: Input data storage to the device

[0785] Step 2:

[0786] Data transmission by the terminal

[0787] The device temporarily stores the dietary information and emotion data entered by the user in its internal storage and transmits them to the server using the HTTPS protocol.

[0788] Input: User information and emotion data stored in internal storage

[0789] Output: Send data to the server

[0790] Step 3:

[0791] Data reception and analysis by the server

[0792] The server receives and analyzes the data sent from the device. First, it uses an emotion analysis engine to analyze the emotion data and identify the user's emotional state. From the analysis results, it extracts the user's emotional state (e.g., stress level).

[0793] Input: User information and emotion data sent via HTTPS

[0794] Output: User's emotional state (e.g., stress state)

[0795] Step 4:

[0796] Prompt input and menu generation using generative AI

[0797] The server inputs a prompt into the generative AI model based on the analyzed emotional data and the user's dietary information. A specific instruction is generated: "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these." The generative AI model then automatically generates the optimal menu based on this.

[0798] Input: User information, analysis results, prompt text

[0799] Output: Generated menu (e.g. Breakfast: Toast and tomato salad, Lunch: Stir-fried chicken and cabbage, Dinner: Vegetable soup and omelet)

[0800] Step 5:

[0801] Creating an ingredient usage plan

[0802] The server creates an efficient ingredient plan based on the generated menu, for example, using tomatoes in a breakfast salad and a lunch stir-fry, and using cabbage for lunch and dinner, thereby minimizing food waste.

[0803] Input: Generated menu

[0804] Output: Ingredient usage plan (e.g., tomatoes for breakfast and lunch, cabbage for lunch and dinner)

[0805] Step 6:

[0806] Server feedback

[0807] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol.

[0808] Input: Generated menu and ingredient plan

[0809] Output: Sending data to the terminal

[0810] Step 7:

[0811] Displaying data on a terminal

[0812] The device receives the data sent from the server and displays it on the user interface. Specifically, the menu screen of the application displays "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[0813] Input: Menu and ingredient usage plan sent from the server

[0814] Output: Display of menu and ingredient plan to user

[0815] (Application example 2)

[0816] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0817] In modern society, eating a healthy diet is important, but achieving it in a busy daily life is not easy. The lack of personalized menu suggestions that take into account the user's emotional state is a further challenge. Furthermore, a system that utilizes food delivery services and proposes efficient and waste-free ingredient usage plans is needed.

[0818] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for adjusting a menu based on the emotional state, and means for ordering ingredients and dishes from a food delivery service based on the menu. This makes it possible to provide a personalized menu taking into account the emotional state of the user, and to efficiently use food delivery services.

[0819] "User" means an individual user of the system.

[0820] "Dietary information" refers to data such as the user's dietary preferences, allergy information, budget, and a list of ingredients they own.

[0821] "Generative AI" is a technology that uses artificial intelligence to automatically generate menus based on specific data.

[0822] A "menu" is a meal combination or cooking plan suggested for a user to consume.

[0823] "Ingredient usage plan" refers to a plan for efficiently using ingredients based on the proposed menu.

[0824] "Emotional state" is data that indicates a user's current psychological or emotional state.

[0825] A "food delivery service" is a service that delivers ingredients and meals to a user's home or designated location based on the user's order.

[0826] A "server" is a central processing unit that processes and analyzes data and provides feedback to the user interface.

[0827] A "terminal" is a device through which a user accesses the system and inputs or receives information.

[0828] "Analysis" is the process of examining data in detail to reveal its meaning and structure.

[0829] This invention is a system that analyzes a user's dietary information and emotional state, proposes personalized menus using generative AI, and then efficiently provides ingredients and dishes using a food delivery service. Specific embodiments of the system are described below.

[0830] System Components

[0831] The system consists of the following main components:

[0832] 1. User: An individual user of the system.

[0833] 2. Terminal: A device, such as a smartphone, through which a user inputs information and interfaces with the system.

[0834] 3. Server: A central processing unit that receives, analyzes, and generates data. It generates menus using AI, analyzes emotions using an emotion engine, and connects with food delivery services.

[0835] System Operation

[0836] 1. User interaction and data entry

[0837] The user opens the food delivery app on their smartphone and enters the following information:

[0838] Food preferences

[0839] Allergy Information

[0840] Daily Budget

[0841] List of ingredients you have

[0842] Number of meals

[0843] The app also uses the camera and microphone to capture the user's facial expressions and voice and record them as emotional data.

[0844] 2. Data transmission

[0845] The terminal transmits the user's input information and emotion data to the server.

[0846] 3. Data analysis and menu generation on the server

[0847] The server analyzes the received data. First, it uses an emotion engine to analyze the user's emotional state. For emotion analysis, it uses Microsoft Azure's Emotion API or Google Cloud's Natural Language API, for example.

[0848] Next, a generative AI generates an optimal menu based on dietary information and emotional data. This uses a generative AI such as OpenAI's GPT model. A specific example of a prompt is as follows:

[0849] Prompt Sentence Examples

[0850] User preference: Japanese food

[0851] Allergy Information: Dairy allergy

[0852] Budget: 1,500 yen

[0853] Ingredients I have: Chicken, potatoes, carrots

[0854] Emotional state: Fatigue

[0855] Based on this, please suggest the best menu.

[0856] 4. Creation and collaboration of ingredient use plans

[0857] The server creates an efficient ingredient usage plan based on the generated menu, which allows for efficient consumption of ingredients across multiple meals.

[0858] 5. Integration with food delivery services

[0859] The user confirms the proposed menu, and the server coordinates with a food delivery service to arrange for the necessary ingredients and dishes to be delivered to the user's designated location.

[0860] Specific examples

[0861] For example, if a user prefers Japanese food, has a dairy allergy, has a daily budget of 1500 yen, has chicken, potatoes, and carrots, and is in a "fatigued" emotional state, the following menu will be generated:

[0862] Breakfast: Rice balls and miso soup

[0863] Lunch: Chicken and potato stew

[0864] Dinner: Carrot and spinach salad

[0865] Based on this, the system orders additional ingredients and dishes from a food delivery service and delivers them to the user, enabling users to lead a healthy and efficient diet without any hassle.

[0866] The above is an embodiment of the present invention. This system enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[0867] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0868] Step 1:

[0869] The user opens a food delivery app on their smartphone. There, they input information about their diet. Specifically, they input their food preferences, allergy information, budget, list of ingredients they have, number of meals, etc. They also provide facial and voice data using a camera and microphone. This information is then captured by the device. The input data is the user's food preferences, allergy information, budget, list of ingredients they have, number of meals, and emotional data.

[0870] Step 2:

[0871] The device sends the data entered by the user and emotion data to the server. The device then uploads the acquired data to the server as a JSON format request. The data sent is dietary information and emotion data, and is sent to the server's API endpoint.

[0872] Step 3:

[0873] The server analyzes the received dietary information and emotional data. First, the emotion engine analyzes the emotional data and evaluates the user's emotional state. This analysis uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API. The input is emotional data, and the output is the user's emotional state as a result of the analysis.

[0874] Step 4:

[0875] The server uses a generative AI to generate an optimal menu based on the analyzed emotional state and dietary information. The generative AI uses, for example, OpenAI's GPT model. This AI generates a personalized menu based on the user's preferences, allergy information, budget, ingredients available, emotional state, etc. The input is dietary information and emotional state, and the output is the generated menu.

[0876] Step 5:

[0877] The server creates an ingredient usage plan based on the generated menu. Based on the generated menu, a plan is created to use ingredients without waste. This ingredient usage plan includes a method for efficiently allocating ingredients to multiple meals. The input is the generated menu, and the output is an ingredient usage plan.

[0878] Step 6:

[0879] The server sends the generated menu and ingredient usage plan to the terminal. The server returns this data to the terminal and displays it on the user's smartphone. The transmitted data is the generated menu and ingredient usage plan.

[0880] Step 7:

[0881] Users can check the menu and ingredient usage plan displayed on their smartphone. If they like it, they can order ingredients and dishes from a food delivery service with just one tap. The order information is sent to the food delivery service, and the required ingredients and dishes are delivered to the user.

[0882] This concludes the processing flow of the system program that realizes this application example. This processing enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[0883] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0884] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0885] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0886] [Third embodiment]

[0887] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0888] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0889] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0890] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0891] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0892] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0893] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0894] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0895] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0896] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0897] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0898] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0899] The present invention provides a system that allows users to easily plan their daily meals at home, promotes healthy eating habits, and prevents product waste. An embodiment of the system will now be described in detail.

[0900] This system consists of three main components: users, terminals, and servers.

[0901] User operations

[0902] Users access the system through applications.

[0903] Users input information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients they currently have (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[0904] Device operation

[0905] The terminal transmits the information entered by the user to the server.

[0906] The terminal receives the generated menu and ingredient usage plan sent from the server and displays them to the user.

[0907] Server Processing

[0908] The server analyzes the user information received from the terminal.

[0909] This analysis includes validating ingredient lists and filtering allergy information.

[0910] The server uses generative AI to automatically generate the optimal menu.

[0911] The AI ​​generates a menu that is appropriate for the user based on information such as the user's preferences, allergy information, budget, list of ingredients they have, and number of meals.

[0912] Based on the generated menu, the server creates a plan for using ingredients to minimize product waste while maintaining a healthy diet.

[0913] Specifically, this includes a detailed plan of how many servings of a particular ingredient should be used and which ingredients should be prioritized.

[0914] User Feedback

[0915] The server transmits the generated menu and ingredient usage plan to the terminal.

[0916] The terminal displays this in an easy-to-understand manner to the user.

[0917] For example, we suggest chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0918] It also provides specific advice on planning how to use ingredients, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0919] Specific examples

[0920] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[0921] 1. The user enters information.

[0922] 2. The device sends the information to the server.

[0923] 3. The server analyzes the received information, and the AI ​​generates the following menu:

[0924] Breakfast: Chicken rice balls and carrot miso soup

[0925] Lunch: Stir-fried cabbage and carrots, rolled egg

[0926] Dinner: Chicken and cabbage hotpot

[0927] 4. The server will create a plan for using ingredients based on this.

[0928] 5. The server sends the generated menu and usage plan to the terminal.

[0929] 6. The device displays the menu and provides a food plan to the user.

[0930] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[0931] The processing flow will be explained below.

[0932] Step 1:

[0933] Users open the application and enter information about their diet, such as food preferences, allergy information, daily budget, a list of ingredients they have on hand, and the number of meals they eat per day.

[0934] Step 2:

[0935] The terminal stores the information about the dietary habits entered by the user in a database and transmits it to the server.

[0936] Step 3:

[0937] The server analyzes the user information received from the device, including validating the ingredient list (e.g., checking inventory) and filtering allergy information (excluding risky ingredients).

[0938] Step 4:

[0939] The server uses the analyzed data and passes it to the generation AI, which receives the user's preferences, allergy information, budget, list of ingredients they have, and number of meals as input parameters.

[0940] Step 5:

[0941] The AI ​​on the server generates the optimal menu based on these input parameters. For example, if a user likes Japanese food but has a dairy allergy, the AI ​​will suggest a Japanese menu that does not include dairy products.

[0942] Step 6:

[0943] The server creates a plan for using ingredients based on the generated menu, for example, planning to use cabbage for breakfast and dinner.

[0944] Step 7:

[0945] The server sends the generated menu and ingredient usage plan to the terminal.

[0946] Step 8:

[0947] The terminal displays the generated menu and ingredient usage plan received from the server to the user. For example, a menu of chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hotpot for dinner may be displayed.

[0948] Step 9:

[0949] The user reviews the displayed menu and ingredient usage plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[0950] This series of steps allows users to efficiently create menus and achieve a healthy, lean diet.

[0951] Example 1

[0952] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0953] In today's busy society, it is difficult to manage one's eating habits, especially maintaining a healthy diet and minimizing food waste. Furthermore, creating a menu for home cooking requires time and effort, and it is even more difficult to create a menu that takes into account allergies and food preferences. As a result, many people suffer from unhealthy eating habits and food waste.

[0954] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0955] In this invention, the server includes means for receiving information about a user's dietary habits from a user, means for transmitting the received information to the server, means for automatically generating a menu using a generative AI model based on the received information, means for creating an ingredient usage plan based on the generated menu, means for transmitting the generated menu and ingredient usage plan from the server to a terminal, and means for displaying the generated menu and ingredient usage plan to the user. This allows the user to efficiently create menus and enjoy a healthy and lean diet.

[0956] "User" refers to a person who uses the system to provide information about their own eating habits.

[0957] "Dietary information" refers to information that a user inputs into the system, such as dietary preferences, allergy information, budget, and a list of ingredients that the user has on hand.

[0958] "Terminal" refers to a device that allows a user to input information and display menus and ingredient usage plans sent from the server.

[0959] "Server" refers to a computer system that analyzes information received from users, automatically generates menus using generative AI models, and creates ingredient usage plans.

[0960] A "generative AI model" refers to an artificial intelligence model that automatically generates the optimal menu based on input information.

[0961] A "prompt sentence" is a sentence used to input information into a generative AI model, and contains information about the user's diet.

[0962] "Menu" refers to a specific meal menu automatically generated by a generative AI model based on the user's dietary information.

[0963] "Ingredient usage plan" refers to the specific usage schedule of ingredients to be used based on the generated menu to promote healthy eating habits and minimize food waste.

[0964] The present invention is a system for supporting a user's dietary management, and is mainly composed of three elements: a user, a terminal, and a server. Specific embodiments of the present invention will be described below.

[0965] User operations

[0966] Users access this system using devices such as smartphones or PCs. They enter the following information into the application:

[0967] Food preferences (e.g., Japanese food, Western food)

[0968] Allergy information (e.g. dairy, nuts)

[0969] Daily budget (e.g. 500 yen)

[0970] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0971] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0972] As a specific example, a user inputs information such as "Japanese food," "dairy allergy," "500 yen," "chicken, cabbage, carrots, eggs, rice," and "breakfast, lunch, dinner" into the application.

[0973] Device operation

[0974] The terminal sends the entered information to the server. This process is usually done using the HTTPS protocol. When the user presses the "Submit" button, the terminal sends this information to the server.

[0975] Processing on the server

[0976] The server analyzes the user information received from the terminal. The specific analysis process includes the following steps:

[0977] Validating an ingredient list (e.g., checking that the ingredients you have are actually available)

[0978] Allergy filtering (e.g., excluding ingredients that cause allergies)

[0979] Checking the budget (e.g., checking whether a menu can be created within the entered budget)

[0980] Menu generation

[0981] The server automatically generates the optimal menu using a generative AI model (e.g., a general-purpose artificial intelligence model) based on the analyzed information. Specifically, the server inputs the following prompt sentence into the generative AI model:

[0982] "The user likes Japanese food and has a dairy allergy. Their budget is 500 yen, and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Please generate a menu based on this."

[0983] The generative AI model generates appropriate menu suggestions, such as "chicken rice balls and carrot miso soup for breakfast," "cabbage and carrot stir-fry with omelet for lunch," and "chicken and cabbage hot pot for dinner."

[0984] Creating an ingredient usage plan

[0985] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste. Specifically, the server plans how many meals to use the ingredients it has and which ingredients to prioritize. For example, it creates a specific usage plan, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[0986] User Feedback

[0987] The server sends the generated menu and ingredient usage plan to the terminal. The terminal receives it and displays the generated menu and ingredient usage plan on the application screen in a visually easy-to-understand manner. For example, it may display chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[0988] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

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

[0990] Step 1: Enter your information

[0991] Users access the system using terminals.

[0992] Input: The user enters the following dietary information into the application:

[0993] Food preferences (e.g., Japanese food, Western food)

[0994] Allergy information (e.g. dairy, nuts)

[0995] Daily budget (e.g. 500 yen)

[0996] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[0997] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[0998] What happens: The user enters information and clicks the submit button.

[0999] Output: The entered information is saved on the device and ready to be sent to the server.

[1000] Step 2: Send information

[1001] The terminal transmits the input information to the server.

[1002] Input: Information entered after the user hits submit.

[1003] Specific operation: The terminal uses the HTTPS protocol to send information to the server.

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

[1005] Step 3: Analyzing information on the server

[1006] The server analyzes the user information received from the terminal.

[1007] Input: Information about the user's diet.

[1008] Specific behavior:

[1009] Ingredient list validation (check whether the ingredients you have are actually available)

[1010] Allergy information filtering (excluding ingredients that cause allergies)

[1011] Check whether it is possible to create a menu within your budget

[1012] Output: The parsed information is saved on the server.

[1013] Step 4: Menu generation

[1014] The server automatically generates the optimal menu using a generative AI model based on the analyzed information.

[1015] Input: Parsed user information.

[1016] Specific behavior:

[1017] The server generates a prompt sentence for the generative AI model and inputs it into the model.

[1018] Example prompt: "The user prefers Japanese food and has a dairy allergy. Their budget is 500 yen and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Generate a menu based on this."

[1019] A generative AI model analyzes this information and generates an optimal menu.

[1020] Output: The generated menu.

[1021] Step 5: Create an ingredient usage plan

[1022] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste.

[1023] Input: The generated menu.

[1024] Specific behavior:

[1025] Plan how many servings of a particular ingredient you will use.

[1026] Decide which ingredients to prioritize.

[1027] For example, create a specific plan for using cabbage at breakfast and dinner, and carrots at breakfast and lunch.

[1028] Output: Ingredient usage plan.

[1029] Step 6: Sending information (from server to device)

[1030] The server transmits the generated menu and ingredient usage plan to the terminal.

[1031] Input: Generated menu and ingredient usage plan.

[1032] Specific operation: The server uses the HTTPS protocol to send information to the terminal.

[1033] Output: The menu and ingredient plan are sent to the terminal.

[1034] Step 7: View your menu and spending plan

[1035] The terminal displays the information received from the server to the user.

[1036] Input: Menu and ingredient plan sent from the server.

[1037] Specific operation: The generated menu and ingredient usage plan are displayed visually and clearly on the application screen.

[1038] For example, it might say that breakfast is rice balls with chicken and carrot miso soup, lunch is stir-fried cabbage and carrots and tamagoyaki, and dinner is chicken and cabbage hot pot.

[1039] Output: A visual menu and ingredient plan for the user.

[1040] (Application example 1)

[1041] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1042] Today's hectic lifestyles make meal preparation and planning difficult. This calls for ways to minimize food waste while maintaining healthy eating habits. There is also a need for a system that not only provides personalized meal plans to users, but also comprehensive delivery options for ingredients based on those plans.

[1043] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1044] In this invention, the server includes means for receiving information about a user's dietary habits, means for automatically generating a menu using a generation AI based on the received information, means for displaying the generated menu to the user, means for creating an ingredient usage plan based on the generated menu, means for displaying the ingredient usage plan to the user, means for providing an ingredient list and delivery options for food delivery based on the generated menu and usage plan, and means for displaying the provided ingredient list and delivery options to the user, thereby enabling the user to efficiently plan and execute a healthy and lean diet and appropriately procure the necessary ingredients.

[1045] A "user" is an individual who uses the system to provide information about their eating habits and receive services such as menu suggestions and food delivery.

[1046] "Dietary information" refers to detailed data about the user's diet, such as the user's food preferences, allergy information, budget, number of meals per day, and a list of ingredients currently on hand.

[1047] "Generative AI" is an artificial intelligence that automatically generates optimal menus based on information input by the user.

[1048] A "menu" is a plan that shows the menu for each meal within a certain period of time based on the user's eating habits.

[1049] The "ingredient usage plan" is a plan that indicates the specific amount and timing of ingredients to be used for each meal based on the generated menu.

[1050] "Food delivery ingredient list" means a list of ingredients provided by a food delivery service based on the generated menu and usage plan.

[1051] "Delivery options" are options for food delivery provided to the user, including delivery date and time, delivery method, etc.

[1052] The present invention is a system that collects information about a user's eating habits, automatically generates menus based on that information, and provides a food delivery ingredient list and delivery options tailored to the user. An embodiment of the system is described in detail below.

[1053] System Configuration

[1054] This system consists of three main components: users, terminals, and servers.

[1055] User operations

[1056] 1. User: Accesses the system and inputs information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients currently on hand (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals eaten per day (e.g., breakfast, lunch, dinner).

[1057] Device operation

[1058] 2. Terminal: Sends the information entered by the user to the server, and receives the generated menu and ingredient usage plan, as well as the ingredient list and delivery options for food delivery, sent from the server, and displays them to the user.

[1059] Server Processing

[1060] 3. Server: Analyzes the user information received from the device and automatically generates the optimal menu using generative AI. This generative AI model uses GPT-3.5, which utilizes the Hugging Face transformers library. Specific prompts are as follows:

[1061] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[1062] 4. Generative AI model: Generates the following menu based on user input information.

[1063] Breakfast: Chicken rice balls and carrot miso soup

[1064] Lunch: Stir-fried cabbage and carrots, rolled egg

[1065] Dinner: Chicken and cabbage hotpot

[1066] 5. Create a usage plan: Based on the generated menu, create a usage plan for ingredients to maintain a healthy diet and minimize food waste. For example, use cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[1067] 6. Providing ingredient lists and delivery options for food delivery: Based on the usage plan created, the required ingredient lists and delivery options are generated and provided to the user.

[1068] User Feedback

[1069] 7. Feedback: The server sends the generated menu, ingredient plan, food delivery ingredient list and delivery options to the terminal, which displays them in an easy-to-understand manner for the user.

[1070] Specific examples

[1071] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[1072] 1. The user enters information.

[1073] 2. The device sends the information to the server.

[1074] 3. The server analyzes the received information, and the generation AI generates the menu shown above.

[1075] 4. The server will create a plan for using ingredients based on this.

[1076] 5. The server sends the generated menu, usage plan, ingredient list and delivery options to the device.

[1077] 6. The device displays the menu and provides a food plan to the user.

[1078] This system allows users to efficiently create menus and enjoy a healthy, lean diet. It also allows them to appropriately procure the ingredients they need through delivery services, improving the convenience of their lives.

[1079] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1080] Step 1:

[1081] The user accesses the system and inputs information about their diet, such as their food preferences, allergies, daily budget, a list of ingredients they currently have, and the number of meals they eat per day, and this information is then sent to the device.

[1082] Input: Food preferences, allergy information, budget, list of ingredients you have, number of meals

[1083] Output: Detailed information about the user's diet

[1084] Step 2:

[1085] The device sends the information received from the user to the server, which then converts the information into an appropriate format and sends it to the server-side API.

[1086] Input: Detailed information about the user's diet

[1087] Output: API request sent to the server

[1088] Step 3:

[1089] The server analyzes the user information received from the device, and performs tasks such as checking the validity of the ingredient list and filtering allergy information.

[1090] Input: User information sent from the device

[1091] Output: Parsed user information

[1092] Step 4:

[1093] The server automatically generates the optimal menu using generative AI. Specifically, the generative AI model inputs user information as prompts and generates an appropriate menu. For generation, GPT-3.5 with Hugging Face's transformers library is used.

[1094] Input: Parsed user information, prompt text

[1095] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[1096] Output: Generated menu

[1097] Step 5:

[1098] The server creates an ingredient usage plan based on the generated menu, which helps maintain a healthy diet and minimize food waste.

[1099] Input: Generated menu

[1100] Output: Ingredient usage plan

[1101] Step 6:

[1102] The server provides the ingredient list and delivery options for food delivery. Based on the generated menu and usage plan, the server generates an appropriate ingredient list and its delivery options.

[1103] Input: Generated menu, ingredient usage plan

[1104] Output: Food delivery ingredients list, delivery options

[1105] Step 7:

[1106] The server sends the generated menu, ingredient usage plan, ingredient list for food delivery, and delivery options to the terminal.

[1107] Input: Generated menu, ingredient usage plan, ingredient list, delivery options

[1108] Output: Data sent to the terminal

[1109] Step 8:

[1110] The device displays the data received from the server to the user. Specifically, the generated menu, ingredient usage plan, food delivery ingredient list, and delivery options are displayed on the screen. Based on this, the user can plan their own meal and order the necessary ingredients via a delivery service.

[1111] Input: Data sent from the server

[1112] Output: Specific meal plan, usage plan, ingredient list, and delivery options displayed to the user

[1113] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1114] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using generative AI. It also combines an emotion engine that recognizes the user's emotions to suggest more personalized menus. This system can promote healthy eating habits and minimize product waste.

[1115] System Components

[1116] The system consists of the following main components:

[1117] 1. User: Provides information about dietary habits and accepts the system's menu suggestions.

[1118] 2. Terminal: Collects data from the user, sends it to the server, and displays the information from the server to the user.

[1119] 3. Server: Performs data analysis, menu generation using generative AI, ingredient usage planning, and emotion analysis using an emotion engine.

[1120] Program processing flow

[1121] 1. User Action:

[1122] Users open the application and enter information about their diet, including food preferences, allergy information, budget, a list of ingredients they have on hand, and meal frequency.

[1123] Emotions are provided to the system through the user's facial expressions, voice, and text input.

[1124] 2. Terminal operation:

[1125] The terminal transmits the user's input information and emotion data to the server.

[1126] 3. Server Processing:

[1127] The server analyzes the received information. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user is feeling stressed, it will suggest a meal plan that takes into account ingredients that help reduce stress.

[1128] Next, the analyzed emotional data and dietary information are input into a generation AI to generate the optimal menu.

[1129] Ingredients and menus are considered to address specific health and emotional states, and emotional analysis is used to select foods that have a relaxing effect or enhance your mood.

[1130] 4. Generative AI and ingredient planning:

[1131] The server uses AI to generate menus based on user information. For example, if the server detects that the user is tired, it will suggest a menu using ingredients that are good for replenishing energy.

[1132] The server then creates an ingredient usage plan based on the generated menu, for example, a plan for efficiently using ingredients across multiple meals.

[1133] 5. Feedback:

[1134] The server transmits the generated menu and ingredient usage plan to the terminal.

[1135] The device will display this to the user, suggesting, for example, stress-reducing herbal tea and fruit salad for breakfast, an energizing chicken and vegetable stir-fry for lunch, and a relaxing soup for dinner.

[1136] Specific examples

[1137] For example, let's assume that a user likes Western food, has no allergies, has a daily budget of 1,000 yen, and has chicken, tomatoes, cabbage, eggs, and bread. Furthermore, the following example shows the case where the user's emotions are analyzed as being stressed.

[1138] 1. User Action:

[1139] The user inputs this information and sends it, including emotion data, to the terminal.

[1140] 2. Terminal operation:

[1141] The device transmits this information and emotion data to the server.

[1142] 3. Server Processing:

[1143] The server uses an emotion engine to analyze stress and adjusts the menu based on the analysis results.

[1144] The generative AI generates the following menu:

[1145] Breakfast: Toast and tomato salad

[1146] Lunch: Stir-fried chicken and cabbage

[1147] Dinner: Vegetable soup and omelet

[1148] 4. Feedback:

[1149] The server sends the generated menu and ingredient usage plan to the terminal.

[1150] The terminal is displayed to the user.

[1151] The system allows users to efficiently plan meals, enjoy healthy and lean eating habits, and receive personalized suggestions tailored to their emotional state.

[1152] The processing flow will be explained below.

[1153] Step 1:

[1154] Users open the application and enter information about their diet, including food preferences (e.g., Japanese, Western), allergies (e.g., dairy, nuts), budget (e.g., 1,000 yen per day), ingredients they have (e.g., chicken, tomatoes, cabbage, eggs, bread), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[1155] Step 2:

[1156] The user provides their emotions to the system through their terminal. Emotion data is acquired through facial expression recognition, voice recognition, or text input.

[1157] Step 3:

[1158] The terminal transmits the information about the eating habits and emotion data collected from the user to the server in a lump sum.

[1159] Step 4:

[1160] The server analyzes all information received from the device. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user sends emotional data such as "I'm tired" or "I'm stressed," the server extracts the analysis results.

[1161] Step 5:

[1162] The server inputs the analysis results into a generation AI that adjusts the menu based on the emotional data. The generation AI generates an optimal menu based on the user's dietary preferences, allergy information, budget, available ingredients, and emotional state. For example, it may suggest a menu that includes foods that have a stress-reducing effect.

[1163] Step 6:

[1164] Based on the generated menu, the server creates an ingredient plan to efficiently use the ingredients available. Specifically, it plans how many meals a particular ingredient will be used and how. For example, it can plan to use cabbage for breakfast and dinner separately.

[1165] Step 7:

[1166] The server transmits the generated menu and ingredient usage plan to the terminal.

[1167] Step 8:

[1168] The terminal displays the information received from the server to the user, including a suggested menu (e.g., toast and tomato salad for breakfast, stir-fried chicken and cabbage for lunch, vegetable soup and omelet for dinner) and a plan for using the ingredients.

[1169] Step 9:

[1170] The user reviews the proposed menu and ingredient plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[1171] This series of steps allows users to efficiently plan meals, achieve a healthy and lean diet, and receive personalized suggestions based on their emotional state.

[1172] Example 2

[1173] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1174] While conventional menu generation systems can automatically generate menus based on information about a user's eating habits, they have difficulty making personalized suggestions that take the user's emotional state into account. Furthermore, they often fail to efficiently plan ingredient usage, resulting in food waste. Therefore, there is a need for a system that can efficiently plan ingredient usage while taking the user's emotional state into account.

[1175] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1176] In this invention, the server includes means for receiving information about the user's dietary habits, means for transmitting data including the received information and the user's emotional data to the server, means for analyzing the user's emotional state using an emotional analysis engine and inputting prompt sentences into a generative AI model based on the analysis results to automatically generate an optimal menu, means for creating an ingredient usage plan based on the generated menu, and means for feeding back the generated menu and ingredient usage plan to the user and displaying them on the user terminal. This enables personalized menu suggestions and efficient ingredient usage plans that take the user's emotional state into consideration.

[1177] "User" refers to an individual who uses this system and provides information about their diet and emotional data.

[1178] "Information about dietary habits" refers to information about the user's eating habits, such as food preferences, allergy information, budget, a list of ingredients in the user's possession, and the number of meals eaten.

[1179] "Emotional data" refers to information about a user's emotional state, collected through the user's facial expressions, voice, text input, etc.

[1180] A "terminal" is a device used by a user to input information, and specifically refers to a smartphone, PC, tablet, etc.

[1181] "Server" refers to a computer system that analyzes information sent by users, generates menus using generative AI and a sentiment analysis engine, and provides feedback.

[1182] "Emotion analysis engine" refers to software or hardware for analyzing a user's emotional data and identifying the user's emotional state.

[1183] A "generative AI model" refers to an artificial intelligence model that automatically generates optimal menus based on information about the user's eating habits and emotional state.

[1184] A "prompt sentence" is an instruction sentence input to a generative AI model that instructs the model to generate a specific menu based on the user's information and situation.

[1185] "Menu" refers to a list of meal suggestions that are automatically generated based on the user's eating habits.

[1186] The "ingredient usage plan" refers to a plan for efficiently using ingredients based on the generated menu.

[1187] "Feedback" refers to returning the generated menu and ingredient usage plan to the user and displaying it on the user terminal.

[1188] "JSON format" stands for JavaScript Object Notation and refers to a lightweight data exchange format for exchanging structured data.

[1189] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using a generative AI model. Furthermore, this system incorporates an emotion analysis engine that can analyze the user's emotional state and suggest more personalized menus. The hardware and software configurations for implementing this system, as well as the data processing flow, are described below.

[1190] Main components of the system

[1191] User: Provides information about their diet and receives suggestions from the system.

[1192] Terminal: Collects data from the user and sends it to the server. It also displays information from the server to the user. Specific examples include smartphones (iPhone, Android) and PCs (Windows, Mac).

[1193] Server: Performs data analysis, menu generation using a generative AI model, ingredient planning, and sentiment analysis using an emotion analysis engine. Software used includes programs written in Python and Java, the Microsoft Azure Emotion API as the sentiment analysis engine, and OpenAI GPT-4 as the generative AI model.

[1194] Specific explanation of the system's operation

[1195] 1. User Operation

[1196] Users open the application using their smartphone or PC and enter information about their dietary habits into the designated fields. This information includes food preferences, allergies, budget, list of ingredients on hand, and number of meals. Emotional data is also provided through facial expressions and voice. For example, users can enter "Western food," "no allergies," "budget 1,000 yen," "chicken, tomato, cabbage, egg, bread," and "number of meals three times," and then the camera scans their facial expressions.

[1197] 2. Terminal operation

[1198] The device temporarily stores the input data in its internal storage, and then sends the data (in JSON format) to the server using the HTTPS protocol. Specific examples of data include "Western food, no allergies, 1,000 yen, chicken, tomato, cabbage, egg, bread, and facial expression data."

[1199] 3. Server Processing

[1200] The server analyzes the received data. First, it uses an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, it adjusts the menu based on the analysis results. The emotional data and dietary information are then input into a generative AI model to generate an optimal menu. An example of a specific prompt could be, "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these."

[1201] 4. Menu generation using generative AI

[1202] The generative AI model generates a menu based on the prompt sentence, taking into account the user information. For example, the following menu is generated:

[1203] Breakfast: Toast and tomato salad

[1204] Lunch: Stir-fried chicken and cabbage

[1205] Dinner: Vegetable soup and omelet

[1206] 5. Create an ingredient usage plan

[1207] Based on the generated menu, the server creates an efficient ingredient usage plan, for example, using tomatoes in a breakfast salad and a stir-fry for lunch, and cabbage for lunch and dinner.

[1208] 6. Feedback

[1209] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol. The terminal receives this data and displays it on the user interface. Specifically, the menu screen displays options such as "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[1210] This system efficiently proposes personalized menus to users, helping them to lead a healthy and lean diet.It also makes suggestions based on the user's emotional state, thereby increasing user satisfaction.

[1211] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1212] Step 1:

[1213] User Input Processing

[1214] Users access the application using a smartphone or PC and input information about their dietary habits, including food preferences, allergies, budget, a list of ingredients they have on hand, and the number of meals they eat. Users also use a camera and microphone to provide emotional data such as facial expressions and voice.

[1215] Input: Dietary information (e.g., Western food, no allergies, budget 1,000 yen, chicken, tomato, cabbage, egg, bread), emotional data (facial expression, voice)

[1216] Output: Input data storage to the device

[1217] Step 2:

[1218] Data transmission by the terminal

[1219] The device temporarily stores the dietary information and emotion data entered by the user in its internal storage and transmits them to the server using the HTTPS protocol.

[1220] Input: User information and emotion data stored in internal storage

[1221] Output: Send data to the server

[1222] Step 3:

[1223] Data reception and analysis by the server

[1224] The server receives and analyzes the data sent from the device. First, it uses an emotion analysis engine to analyze the emotion data and identify the user's emotional state. From the analysis results, it extracts the user's emotional state (e.g., stress level).

[1225] Input: User information and emotion data sent via HTTPS

[1226] Output: User's emotional state (e.g., stress state)

[1227] Step 4:

[1228] Prompt input and menu generation using generative AI

[1229] The server inputs a prompt into the generative AI model based on the analyzed emotional data and the user's dietary information. A specific instruction is generated: "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these." The generative AI model then automatically generates the optimal menu based on this.

[1230] Input: User information, analysis results, prompt text

[1231] Output: Generated menu (e.g. Breakfast: Toast and tomato salad, Lunch: Stir-fried chicken and cabbage, Dinner: Vegetable soup and omelet)

[1232] Step 5:

[1233] Creating an ingredient usage plan

[1234] The server creates an efficient ingredient plan based on the generated menu, for example, using tomatoes in a breakfast salad and a lunch stir-fry, and using cabbage for lunch and dinner, thereby minimizing food waste.

[1235] Input: Generated menu

[1236] Output: Ingredient usage plan (e.g., tomatoes for breakfast and lunch, cabbage for lunch and dinner)

[1237] Step 6:

[1238] Server feedback

[1239] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol.

[1240] Input: Generated menu and ingredient plan

[1241] Output: Sending data to the terminal

[1242] Step 7:

[1243] Displaying data on a terminal

[1244] The device receives the data sent from the server and displays it on the user interface. Specifically, the menu screen of the application displays "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[1245] Input: Menu and ingredient usage plan sent from the server

[1246] Output: Display of menu and ingredient plan to user

[1247] (Application example 2)

[1248] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1249] In modern society, eating a healthy diet is important, but achieving it in a busy daily life is not easy. The lack of personalized menu suggestions that take into account the user's emotional state is a further challenge. Furthermore, a system that utilizes food delivery services and proposes efficient and waste-free ingredient usage plans is needed.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for adjusting a menu based on the emotional state, and means for ordering ingredients and dishes from a food delivery service based on the menu. This makes it possible to provide a personalized menu taking into account the emotional state of the user, and to efficiently use food delivery services.

[1251] "User" means an individual user of the system.

[1252] "Dietary information" refers to data such as the user's dietary preferences, allergy information, budget, and a list of ingredients they own.

[1253] "Generative AI" is a technology that uses artificial intelligence to automatically generate menus based on specific data.

[1254] A "menu" is a meal combination or cooking plan suggested for a user to consume.

[1255] "Ingredient usage plan" refers to a plan for efficiently using ingredients based on the proposed menu.

[1256] "Emotional state" is data that indicates a user's current psychological or emotional state.

[1257] A "food delivery service" is a service that delivers ingredients and meals to a user's home or designated location based on the user's order.

[1258] A "server" is a central processing unit that processes and analyzes data and provides feedback to the user interface.

[1259] A "terminal" is a device through which a user accesses the system and inputs or receives information.

[1260] "Analysis" is the process of examining data in detail to reveal its meaning and structure.

[1261] This invention is a system that analyzes a user's dietary information and emotional state, proposes personalized menus using generative AI, and then efficiently provides ingredients and dishes using a food delivery service. Specific embodiments of the system are described below.

[1262] System Components

[1263] The system consists of the following main components:

[1264] 1. User: An individual user of the system.

[1265] 2. Terminal: A device, such as a smartphone, through which a user inputs information and interfaces with the system.

[1266] 3. Server: A central processing unit that receives, analyzes, and generates data. It generates menus using AI, analyzes emotions using an emotion engine, and connects with food delivery services.

[1267] System Operation

[1268] 1. User interaction and data entry

[1269] The user opens the food delivery app on their smartphone and enters the following information:

[1270] Food preferences

[1271] Allergy Information

[1272] Daily Budget

[1273] List of ingredients you have

[1274] Number of meals

[1275] The app also uses the camera and microphone to capture the user's facial expressions and voice and record them as emotional data.

[1276] 2. Data transmission

[1277] The terminal transmits the user's input information and emotion data to the server.

[1278] 3. Data analysis and menu generation on the server

[1279] The server analyzes the received data. First, it uses an emotion engine to analyze the user's emotional state. For emotion analysis, it uses Microsoft Azure's Emotion API or Google Cloud's Natural Language API, for example.

[1280] Next, a generative AI generates an optimal menu based on dietary information and emotional data. This uses a generative AI such as OpenAI's GPT model. A specific example of a prompt is as follows:

[1281] Prompt Sentence Examples

[1282] User preference: Japanese food

[1283] Allergy Information: Dairy allergy

[1284] Budget: 1,500 yen

[1285] Ingredients I have: Chicken, potatoes, carrots

[1286] Emotional state: Fatigue

[1287] Based on this, please suggest the best menu.

[1288] 4. Creation and collaboration of ingredient use plans

[1289] The server creates an efficient ingredient usage plan based on the generated menu, which allows for efficient consumption of ingredients across multiple meals.

[1290] 5. Integration with food delivery services

[1291] The user confirms the proposed menu, and the server coordinates with a food delivery service to arrange for the necessary ingredients and dishes to be delivered to the user's designated location.

[1292] Specific examples

[1293] For example, if a user prefers Japanese food, has a dairy allergy, has a daily budget of 1500 yen, has chicken, potatoes, and carrots, and is in a "fatigued" emotional state, the following menu will be generated:

[1294] Breakfast: Rice balls and miso soup

[1295] Lunch: Chicken and potato stew

[1296] Dinner: Carrot and spinach salad

[1297] Based on this, the system orders additional ingredients and dishes from a food delivery service and delivers them to the user, enabling users to lead a healthy and efficient diet without any hassle.

[1298] The above is an embodiment of the present invention. This system enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[1299] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1300] Step 1:

[1301] The user opens a food delivery app on their smartphone. There, they input information about their diet. Specifically, they input their food preferences, allergy information, budget, list of ingredients they have, number of meals, etc. They also provide facial and voice data using a camera and microphone. This information is then captured by the device. The input data is the user's food preferences, allergy information, budget, list of ingredients they have, number of meals, and emotional data.

[1302] Step 2:

[1303] The device sends the data entered by the user and emotion data to the server. The device then uploads the acquired data to the server as a JSON format request. The data sent is dietary information and emotion data, and is sent to the server's API endpoint.

[1304] Step 3:

[1305] The server analyzes the received dietary information and emotional data. First, the emotion engine analyzes the emotional data and evaluates the user's emotional state. This analysis uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API. The input is emotional data, and the output is the user's emotional state as a result of the analysis.

[1306] Step 4:

[1307] The server uses a generative AI to generate an optimal menu based on the analyzed emotional state and dietary information. The generative AI uses, for example, OpenAI's GPT model. This AI generates a personalized menu based on the user's preferences, allergy information, budget, ingredients available, emotional state, etc. The input is dietary information and emotional state, and the output is the generated menu.

[1308] Step 5:

[1309] The server creates an ingredient usage plan based on the generated menu. Based on the generated menu, a plan is created to use ingredients without waste. This ingredient usage plan includes a method for efficiently allocating ingredients to multiple meals. The input is the generated menu, and the output is an ingredient usage plan.

[1310] Step 6:

[1311] The server sends the generated menu and ingredient usage plan to the terminal. The server returns this data to the terminal and displays it on the user's smartphone. The transmitted data is the generated menu and ingredient usage plan.

[1312] Step 7:

[1313] Users can check the menu and ingredient usage plan displayed on their smartphone. If they like it, they can order ingredients and dishes from a food delivery service with just one tap. The order information is sent to the food delivery service, and the required ingredients and dishes are delivered to the user.

[1314] This concludes the processing flow of the system program that realizes this application example. This processing enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[1315] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1316] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1317] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1318] [Fourth embodiment]

[1319] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1320] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1321] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1322] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1323] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1324] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1325] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1326] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1327] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1328] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1329] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1330] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1331] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1332] The present invention provides a system that allows users to easily plan their daily meals at home, promotes healthy eating habits, and prevents product waste. An embodiment of the system will now be described in detail.

[1333] This system consists of three main components: users, terminals, and servers.

[1334] User operations

[1335] Users access the system through applications.

[1336] Users input information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients they currently have (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[1337] Device operation

[1338] The terminal transmits the information entered by the user to the server.

[1339] The terminal receives the generated menu and ingredient usage plan sent from the server and displays them to the user.

[1340] Server Processing

[1341] The server analyzes the user information received from the terminal.

[1342] This analysis includes validating ingredient lists and filtering allergy information.

[1343] The server uses generative AI to automatically generate the optimal menu.

[1344] The AI ​​generates a menu that is appropriate for the user based on information such as the user's preferences, allergy information, budget, list of ingredients they have, and number of meals.

[1345] Based on the generated menu, the server creates a plan for using ingredients to minimize product waste while maintaining a healthy diet.

[1346] Specifically, this includes a detailed plan of how many servings of a particular ingredient should be used and which ingredients should be prioritized.

[1347] User Feedback

[1348] The server transmits the generated menu and ingredient usage plan to the terminal.

[1349] The terminal displays this in an easy-to-understand manner to the user.

[1350] For example, we suggest chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[1351] It also provides specific advice on planning how to use ingredients, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[1352] Specific examples

[1353] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[1354] 1. The user enters information.

[1355] 2. The device sends the information to the server.

[1356] 3. The server analyzes the received information, and the AI ​​generates the following menu:

[1357] Breakfast: Chicken rice balls and carrot miso soup

[1358] Lunch: Stir-fried cabbage and carrots, rolled egg

[1359] Dinner: Chicken and cabbage hotpot

[1360] 4. The server will create a plan for using ingredients based on this.

[1361] 5. The server sends the generated menu and usage plan to the terminal.

[1362] 6. The device displays the menu and provides a food plan to the user.

[1363] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[1364] The processing flow will be explained below.

[1365] Step 1:

[1366] Users open the application and enter information about their diet, such as food preferences, allergy information, daily budget, a list of ingredients they have on hand, and the number of meals they eat per day.

[1367] Step 2:

[1368] The terminal stores the information about the dietary habits entered by the user in a database and transmits it to the server.

[1369] Step 3:

[1370] The server analyzes the user information received from the device, including validating the ingredient list (e.g., checking inventory) and filtering allergy information (excluding risky ingredients).

[1371] Step 4:

[1372] The server uses the analyzed data and passes it to the generation AI, which receives the user's preferences, allergy information, budget, list of ingredients they have, and number of meals as input parameters.

[1373] Step 5:

[1374] The AI ​​on the server generates the optimal menu based on these input parameters. For example, if a user likes Japanese food but has a dairy allergy, the AI ​​will suggest a Japanese menu that does not include dairy products.

[1375] Step 6:

[1376] The server creates a plan for using ingredients based on the generated menu, for example, planning to use cabbage for breakfast and dinner.

[1377] Step 7:

[1378] The server sends the generated menu and ingredient usage plan to the terminal.

[1379] Step 8:

[1380] The terminal displays the generated menu and ingredient usage plan received from the server to the user. For example, a menu of chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hotpot for dinner may be displayed.

[1381] Step 9:

[1382] The user reviews the displayed menu and ingredient usage plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[1383] This series of steps allows users to efficiently create menus and achieve a healthy, lean diet.

[1384] Example 1

[1385] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1386] In today's busy society, it is difficult to manage one's eating habits, especially maintaining a healthy diet and minimizing food waste. Furthermore, creating a menu for home cooking requires time and effort, and it is even more difficult to create a menu that takes into account allergies and food preferences. As a result, many people suffer from unhealthy eating habits and food waste.

[1387] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1388] In this invention, the server includes means for receiving information about a user's dietary habits from a user, means for transmitting the received information to the server, means for automatically generating a menu using a generative AI model based on the received information, means for creating an ingredient usage plan based on the generated menu, means for transmitting the generated menu and ingredient usage plan from the server to a terminal, and means for displaying the generated menu and ingredient usage plan to the user. This allows the user to efficiently create menus and enjoy a healthy and lean diet.

[1389] "User" refers to a person who uses the system to provide information about their own eating habits.

[1390] "Dietary information" refers to information that a user inputs into the system, such as dietary preferences, allergy information, budget, and a list of ingredients that the user has on hand.

[1391] "Terminal" refers to a device that allows a user to input information and display menus and ingredient usage plans sent from the server.

[1392] "Server" refers to a computer system that analyzes information received from users, automatically generates menus using generative AI models, and creates ingredient usage plans.

[1393] A "generative AI model" refers to an artificial intelligence model that automatically generates the optimal menu based on input information.

[1394] A "prompt sentence" is a sentence used to input information into a generative AI model, and contains information about the user's diet.

[1395] "Menu" refers to a specific meal menu automatically generated by a generative AI model based on the user's dietary information.

[1396] "Ingredient usage plan" refers to the specific usage schedule of ingredients to be used based on the generated menu to promote healthy eating habits and minimize food waste.

[1397] The present invention is a system for supporting a user's dietary management, and is mainly composed of three elements: a user, a terminal, and a server. Specific embodiments of the present invention will be described below.

[1398] User operations

[1399] Users access this system using devices such as smartphones or PCs. They enter the following information into the application:

[1400] Food preferences (e.g., Japanese food, Western food)

[1401] Allergy information (e.g. dairy, nuts)

[1402] Daily budget (e.g. 500 yen)

[1403] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[1404] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[1405] As a specific example, a user inputs information such as "Japanese food," "dairy allergy," "500 yen," "chicken, cabbage, carrots, eggs, rice," and "breakfast, lunch, dinner" into the application.

[1406] Device operation

[1407] The terminal sends the entered information to the server. This process is usually done using the HTTPS protocol. When the user presses the "Submit" button, the terminal sends this information to the server.

[1408] Processing on the server

[1409] The server analyzes the user information received from the terminal. The specific analysis process includes the following steps:

[1410] Validating an ingredient list (e.g., checking that the ingredients you have are actually available)

[1411] Allergy filtering (e.g., excluding ingredients that cause allergies)

[1412] Checking the budget (e.g., checking whether a menu can be created within the entered budget)

[1413] Menu generation

[1414] The server automatically generates the optimal menu using a generative AI model (e.g., a general-purpose artificial intelligence model) based on the analyzed information. Specifically, the server inputs the following prompt sentence into the generative AI model:

[1415] "The user likes Japanese food and has a dairy allergy. Their budget is 500 yen, and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Please generate a menu based on this."

[1416] The generative AI model generates appropriate menu suggestions, such as "chicken rice balls and carrot miso soup for breakfast," "cabbage and carrot stir-fry with omelet for lunch," and "chicken and cabbage hot pot for dinner."

[1417] Creating an ingredient usage plan

[1418] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste. Specifically, the server plans how many meals to use the ingredients it has and which ingredients to prioritize. For example, it creates a specific usage plan, such as using cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[1419] User Feedback

[1420] The server sends the generated menu and ingredient usage plan to the terminal. The terminal receives it and displays the generated menu and ingredient usage plan on the application screen in a visually easy-to-understand manner. For example, it may display chicken rice balls and carrot miso soup for breakfast, stir-fried cabbage and carrots and tamagoyaki for lunch, and chicken and cabbage hot pot for dinner.

[1421] This system allows users to efficiently create menus and enjoy a healthy, lean diet.

[1422] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1423] Step 1: Enter your information

[1424] Users access the system using terminals.

[1425] Input: The user enters the following dietary information into the application:

[1426] Food preferences (e.g., Japanese food, Western food)

[1427] Allergy information (e.g. dairy, nuts)

[1428] Daily budget (e.g. 500 yen)

[1429] A list of ingredients you currently have (e.g. chicken, cabbage, carrots, eggs, rice)

[1430] Number of meals eaten per day (e.g., breakfast, lunch, dinner)

[1431] What happens: The user enters information and clicks the submit button.

[1432] Output: The entered information is saved on the device and ready to be sent to the server.

[1433] Step 2: Send information

[1434] The terminal transmits the input information to the server.

[1435] Input: Information entered after the user hits submit.

[1436] Specific operation: The terminal uses the HTTPS protocol to send information to the server.

[1437] Output: The user information is sent to the server.

[1438] Step 3: Analyzing information on the server

[1439] The server analyzes the user information received from the terminal.

[1440] Input: Information about the user's diet.

[1441] Specific behavior:

[1442] Ingredient list validation (check whether the ingredients you have are actually available)

[1443] Allergy information filtering (excluding ingredients that cause allergies)

[1444] Check whether it is possible to create a menu within your budget

[1445] Output: The parsed information is saved on the server.

[1446] Step 4: Menu generation

[1447] The server automatically generates the optimal menu using a generative AI model based on the analyzed information.

[1448] Input: Parsed user information.

[1449] Specific behavior:

[1450] The server generates a prompt sentence for the generative AI model and inputs it into the model.

[1451] Example prompt: "The user prefers Japanese food and has a dairy allergy. Their budget is 500 yen and they have chicken, cabbage, carrots, eggs, and rice. They eat three meals a day: breakfast, lunch, and dinner. Generate a menu based on this."

[1452] A generative AI model analyzes this information and generates an optimal menu.

[1453] Output: The generated menu.

[1454] Step 5: Create an ingredient usage plan

[1455] Based on the generated menu, the server creates an ingredient usage plan to minimize food waste.

[1456] Input: The generated menu.

[1457] Specific behavior:

[1458] Plan how many servings of a particular ingredient you will use.

[1459] Decide which ingredients to prioritize.

[1460] For example, create a specific plan for using cabbage at breakfast and dinner, and carrots at breakfast and lunch.

[1461] Output: Ingredient usage plan.

[1462] Step 6: Sending information (from server to device)

[1463] The server transmits the generated menu and ingredient usage plan to the terminal.

[1464] Input: Generated menu and ingredient usage plan.

[1465] Specific operation: The server uses the HTTPS protocol to send information to the terminal.

[1466] Output: The menu and ingredient plan are sent to the terminal.

[1467] Step 7: View your menu and spending plan

[1468] The terminal displays the information received from the server to the user.

[1469] Input: Menu and ingredient plan sent from the server.

[1470] Specific operation: The generated menu and ingredient usage plan are displayed visually and clearly on the application screen.

[1471] For example, it might say that breakfast is rice balls with chicken and carrot miso soup, lunch is stir-fried cabbage and carrots and tamagoyaki, and dinner is chicken and cabbage hot pot.

[1472] Output: A visual menu and ingredient plan for the user.

[1473] (Application example 1)

[1474] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1475] Today's hectic lifestyles make meal preparation and planning difficult. This calls for ways to minimize food waste while maintaining healthy eating habits. There is also a need for a system that not only provides personalized meal plans to users, but also comprehensive delivery options for ingredients based on those plans.

[1476] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1477] In this invention, the server includes means for receiving information about a user's dietary habits, means for automatically generating a menu using a generation AI based on the received information, means for displaying the generated menu to the user, means for creating an ingredient usage plan based on the generated menu, means for displaying the ingredient usage plan to the user, means for providing an ingredient list and delivery options for food delivery based on the generated menu and usage plan, and means for displaying the provided ingredient list and delivery options to the user, thereby enabling the user to efficiently plan and execute a healthy and lean diet and appropriately procure the necessary ingredients.

[1478] A "user" is an individual who uses the system to provide information about their eating habits and receive services such as menu suggestions and food delivery.

[1479] "Dietary information" refers to detailed data about the user's diet, such as the user's food preferences, allergy information, budget, number of meals per day, and a list of ingredients currently on hand.

[1480] "Generative AI" is an artificial intelligence that automatically generates optimal menus based on information input by the user.

[1481] A "menu" is a plan that shows the menu for each meal within a certain period of time based on the user's eating habits.

[1482] The "ingredient usage plan" is a plan that indicates the specific amount and timing of ingredients to be used for each meal based on the generated menu.

[1483] "Food delivery ingredient list" means a list of ingredients provided by a food delivery service based on the generated menu and usage plan.

[1484] "Delivery options" are options for food delivery provided to the user, including delivery date and time, delivery method, etc.

[1485] The present invention is a system that collects information about a user's eating habits, automatically generates menus based on that information, and provides a food delivery ingredient list and delivery options tailored to the user. An embodiment of the system is described in detail below.

[1486] System Configuration

[1487] This system consists of three main components: users, terminals, and servers.

[1488] User operations

[1489] 1. User: Accesses the system and inputs information about their diet, such as food preferences (e.g., Japanese food, Western food), allergy information (e.g., dairy products, nuts), daily budget (e.g., 500 yen), a list of ingredients currently on hand (e.g., chicken, cabbage, carrots, eggs, rice), and the number of meals eaten per day (e.g., breakfast, lunch, dinner).

[1490] Device operation

[1491] 2. Terminal: Sends the information entered by the user to the server, and receives the generated menu and ingredient usage plan, as well as the ingredient list and delivery options for food delivery, sent from the server, and displays them to the user.

[1492] Server Processing

[1493] 3. Server: Analyzes the user information received from the device and automatically generates the optimal menu using generative AI. This generative AI model uses GPT-3.5, which utilizes the Hugging Face transformers library. Specific prompts are as follows:

[1494] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[1495] 4. Generative AI model: Generates the following menu based on user input information.

[1496] Breakfast: Chicken rice balls and carrot miso soup

[1497] Lunch: Stir-fried cabbage and carrots, rolled egg

[1498] Dinner: Chicken and cabbage hotpot

[1499] 5. Create a usage plan: Based on the generated menu, create a usage plan for ingredients to maintain a healthy diet and minimize food waste. For example, use cabbage for breakfast and dinner, and carrots for breakfast and lunch.

[1500] 6. Providing ingredient lists and delivery options for food delivery: Based on the usage plan created, the required ingredient lists and delivery options are generated and provided to the user.

[1501] User Feedback

[1502] 7. Feedback: The server sends the generated menu, ingredient plan, food delivery ingredient list and delivery options to the terminal, which displays them in an easy-to-understand manner for the user.

[1503] Specific examples

[1504] For example, if a user likes Japanese food, has a dairy allergy, sets a daily budget of 500 yen, and has chicken, cabbage, carrots, eggs, and rice, the system will operate in the following sequence:

[1505] 1. The user enters information.

[1506] 2. The device sends the information to the server.

[1507] 3. The server analyzes the received information, and the generation AI generates the menu shown above.

[1508] 4. The server will create a plan for using ingredients based on this.

[1509] 5. The server sends the generated menu, usage plan, ingredient list and delivery options to the device.

[1510] 6. The device displays the menu and provides a food plan to the user.

[1511] This system allows users to efficiently create menus and enjoy a healthy, lean diet. It also allows them to appropriately procure the ingredients they need through delivery services, improving the convenience of their lives.

[1512] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1513] Step 1:

[1514] The user accesses the system and inputs information about their diet, such as their food preferences, allergies, daily budget, a list of ingredients they currently have, and the number of meals they eat per day, and this information is then sent to the device.

[1515] Input: Food preferences, allergy information, budget, list of ingredients you have, number of meals

[1516] Output: Detailed information about the user's diet

[1517] Step 2:

[1518] The device sends the information received from the user to the server, which then converts the information into an appropriate format and sends it to the server-side API.

[1519] Input: Detailed information about the user's diet

[1520] Output: API request sent to the server

[1521] Step 3:

[1522] The server analyzes the user information received from the device, and performs tasks such as checking the validity of the ingredient list and filtering allergy information.

[1523] Input: User information sent from the device

[1524] Output: Parsed user information

[1525] Step 4:

[1526] The server automatically generates the optimal menu using generative AI. Specifically, the generative AI model inputs user information as prompts and generates an appropriate menu. For generation, GPT-3.5 with Hugging Face's transformers library is used.

[1527] Input: Parsed user information, prompt text

[1528] User preferences: Japanese, Allergies: dairy, Budget: 500 yen, Ingredients: chicken, cabbage, carrot, egg, rice, Meals: breakfast, lunch, dinner.

[1529] Output: Generated menu

[1530] Step 5:

[1531] The server creates an ingredient usage plan based on the generated menu, which helps maintain a healthy diet and minimize food waste.

[1532] Input: Generated menu

[1533] Output: Ingredient usage plan

[1534] Step 6:

[1535] The server provides the ingredient list and delivery options for food delivery. Based on the generated menu and usage plan, the server generates an appropriate ingredient list and its delivery options.

[1536] Input: Generated menu, ingredient usage plan

[1537] Output: Food delivery ingredients list, delivery options

[1538] Step 7:

[1539] The server sends the generated menu, ingredient usage plan, ingredient list for food delivery, and delivery options to the terminal.

[1540] Input: Generated menu, ingredient usage plan, ingredient list, delivery options

[1541] Output: Data sent to the terminal

[1542] Step 8:

[1543] The device displays the data received from the server to the user. Specifically, the generated menu, ingredient usage plan, food delivery ingredient list, and delivery options are displayed on the screen. Based on this, the user can plan their own meal and order the necessary ingredients via a delivery service.

[1544] Input: Data sent from the server

[1545] Output: Specific meal plan, usage plan, ingredient list, and delivery options displayed to the user

[1546] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1547] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using generative AI. It also combines an emotion engine that recognizes the user's emotions to suggest more personalized menus. This system can promote healthy eating habits and minimize product waste.

[1548] System Components

[1549] The system consists of the following main components:

[1550] 1. User: Provides information about dietary habits and accepts the system's menu suggestions.

[1551] 2. Terminal: Collects data from the user, sends it to the server, and displays the information from the server to the user.

[1552] 3. Server: Performs data analysis, menu generation using generative AI, ingredient usage planning, and emotion analysis using an emotion engine.

[1553] Program processing flow

[1554] 1. User Action:

[1555] Users open the application and enter information about their diet, including food preferences, allergy information, budget, a list of ingredients they have on hand, and meal frequency.

[1556] Emotions are provided to the system through the user's facial expressions, voice, and text input.

[1557] 2. Terminal operation:

[1558] The terminal transmits the user's input information and emotion data to the server.

[1559] 3. Server Processing:

[1560] The server analyzes the received information. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user is feeling stressed, it will suggest a meal plan that takes into account ingredients that help reduce stress.

[1561] Next, the analyzed emotional data and dietary information are input into a generation AI to generate the optimal menu.

[1562] Ingredients and menus are considered to address specific health and emotional states, and emotional analysis is used to select foods that have a relaxing effect or enhance your mood.

[1563] 4. Generative AI and ingredient planning:

[1564] The server uses AI to generate menus based on user information. For example, if the server detects that the user is tired, it will suggest a menu using ingredients that are good for replenishing energy.

[1565] The server then creates an ingredient usage plan based on the generated menu, for example, a plan for efficiently using ingredients across multiple meals.

[1566] 5. Feedback:

[1567] The server transmits the generated menu and ingredient usage plan to the terminal.

[1568] The device will display this to the user, suggesting, for example, stress-reducing herbal tea and fruit salad for breakfast, an energizing chicken and vegetable stir-fry for lunch, and a relaxing soup for dinner.

[1569] Specific examples

[1570] For example, let's assume that a user likes Western food, has no allergies, has a daily budget of 1,000 yen, and has chicken, tomatoes, cabbage, eggs, and bread. Furthermore, the following example shows the case where the user's emotions are analyzed as being stressed.

[1571] 1. User Action:

[1572] The user inputs this information and sends it, including emotion data, to the terminal.

[1573] 2. Terminal operation:

[1574] The device transmits this information and emotion data to the server.

[1575] 3. Server Processing:

[1576] The server uses an emotion engine to analyze stress and adjusts the menu based on the analysis results.

[1577] The generative AI generates the following menu:

[1578] Breakfast: Toast and tomato salad

[1579] Lunch: Stir-fried chicken and cabbage

[1580] Dinner: Vegetable soup and omelet

[1581] 4. Feedback:

[1582] The server sends the generated menu and ingredient usage plan to the terminal.

[1583] The terminal is displayed to the user.

[1584] The system allows users to efficiently plan meals, enjoy healthy and lean eating habits, and receive personalized suggestions tailored to their emotional state.

[1585] The processing flow will be explained below.

[1586] Step 1:

[1587] Users open the application and enter information about their diet, including food preferences (e.g., Japanese, Western), allergies (e.g., dairy, nuts), budget (e.g., 1,000 yen per day), ingredients they have (e.g., chicken, tomatoes, cabbage, eggs, bread), and the number of meals they eat per day (e.g., breakfast, lunch, dinner).

[1588] Step 2:

[1589] The user provides their emotions to the system through their terminal. Emotion data is acquired through facial expression recognition, voice recognition, or text input.

[1590] Step 3:

[1591] The terminal transmits the information about the eating habits and emotion data collected from the user to the server in a lump sum.

[1592] Step 4:

[1593] The server analyzes all information received from the device. First, it uses an emotion engine to analyze the user's emotional state. For example, if the user sends emotional data such as "I'm tired" or "I'm stressed," the server extracts the analysis results.

[1594] Step 5:

[1595] The server inputs the analysis results into a generation AI that adjusts the menu based on the emotional data. The generation AI generates an optimal menu based on the user's dietary preferences, allergy information, budget, available ingredients, and emotional state. For example, it may suggest a menu that includes foods that have a stress-reducing effect.

[1596] Step 6:

[1597] Based on the generated menu, the server creates an ingredient plan to efficiently use the ingredients available. Specifically, it plans how many meals a particular ingredient will be used and how. For example, it can plan to use cabbage for breakfast and dinner separately.

[1598] Step 7:

[1599] The server transmits the generated menu and ingredient usage plan to the terminal.

[1600] Step 8:

[1601] The terminal displays the information received from the server to the user, including a suggested menu (e.g., toast and tomato salad for breakfast, stir-fried chicken and cabbage for lunch, vegetable soup and omelet for dinner) and a plan for using the ingredients.

[1602] Step 9:

[1603] The user reviews the proposed menu and ingredient plan, makes adjustments as needed, and then begins cooking according to the suggested recipe.

[1604] This series of steps allows users to efficiently plan meals, achieve a healthy and lean diet, and receive personalized suggestions based on their emotional state.

[1605] Example 2

[1606] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1607] While conventional menu generation systems can automatically generate menus based on information about a user's eating habits, they have difficulty making personalized suggestions that take the user's emotional state into account. Furthermore, they often fail to efficiently plan ingredient usage, resulting in food waste. Therefore, there is a need for a system that can efficiently plan ingredient usage while taking the user's emotional state into account.

[1608] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1609] In this invention, the server includes means for receiving information about the user's dietary habits, means for transmitting data including the received information and the user's emotional data to the server, means for analyzing the user's emotional state using an emotional analysis engine and inputting prompt sentences into a generative AI model based on the analysis results to automatically generate an optimal menu, means for creating an ingredient usage plan based on the generated menu, and means for feeding back the generated menu and ingredient usage plan to the user and displaying them on the user terminal. This enables personalized menu suggestions and efficient ingredient usage plans that take the user's emotional state into consideration.

[1610] "User" refers to an individual who uses this system and provides information about their diet and emotional data.

[1611] "Information about dietary habits" refers to information about the user's eating habits, such as food preferences, allergy information, budget, a list of ingredients in the user's possession, and the number of meals eaten.

[1612] "Emotional data" refers to information about a user's emotional state, collected through the user's facial expressions, voice, text input, etc.

[1613] A "terminal" is a device used by a user to input information, and specifically refers to a smartphone, PC, tablet, etc.

[1614] "Server" refers to a computer system that analyzes information sent by users, generates menus using generative AI and a sentiment analysis engine, and provides feedback.

[1615] "Emotion analysis engine" refers to software or hardware for analyzing a user's emotional data and identifying the user's emotional state.

[1616] A "generative AI model" refers to an artificial intelligence model that automatically generates optimal menus based on information about the user's eating habits and emotional state.

[1617] A "prompt sentence" is an instruction sentence input to a generative AI model that instructs the model to generate a specific menu based on the user's information and situation.

[1618] "Menu" refers to a list of meal suggestions that are automatically generated based on the user's eating habits.

[1619] The "ingredient usage plan" refers to a plan for efficiently using ingredients based on the generated menu.

[1620] "Feedback" refers to returning the generated menu and ingredient usage plan to the user and displaying it on the user terminal.

[1621] "JSON format" stands for JavaScript Object Notation and refers to a lightweight data exchange format for exchanging structured data.

[1622] This invention is a system that collects information about a user's eating habits and automatically generates optimal menus using a generative AI model. Furthermore, this system incorporates an emotion analysis engine that can analyze the user's emotional state and suggest more personalized menus. The hardware and software configurations for implementing this system, as well as the data processing flow, are described below.

[1623] Main components of the system

[1624] User: Provides information about their diet and receives suggestions from the system.

[1625] Terminal: Collects data from the user and sends it to the server. It also displays information from the server to the user. Specific examples include smartphones (iPhone, Android) and PCs (Windows, Mac).

[1626] Server: Performs data analysis, menu generation using a generative AI model, ingredient planning, and sentiment analysis using an emotion analysis engine. Software used includes programs written in Python and Java, the Microsoft Azure Emotion API as the sentiment analysis engine, and OpenAI GPT-4 as the generative AI model.

[1627] Specific explanation of the system's operation

[1628] 1. User Operation

[1629] Users open the application using their smartphone or PC and enter information about their dietary habits into the designated fields. This information includes food preferences, allergies, budget, list of ingredients on hand, and number of meals. Emotional data is also provided through facial expressions and voice. For example, users can enter "Western food," "no allergies," "budget 1,000 yen," "chicken, tomato, cabbage, egg, bread," and "number of meals three times," and then the camera scans their facial expressions.

[1630] 2. Terminal operation

[1631] The device temporarily stores the input data in its internal storage, and then sends the data (in JSON format) to the server using the HTTPS protocol. Specific examples of data include "Western food, no allergies, 1,000 yen, chicken, tomato, cabbage, egg, bread, and facial expression data."

[1632] 3. Server Processing

[1633] The server analyzes the received data. First, it uses an emotion analysis engine to analyze the user's emotional state. For example, if the user is feeling stressed, it adjusts the menu based on the analysis results. The emotional data and dietary information are then input into a generative AI model to generate an optimal menu. An example of a specific prompt could be, "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these."

[1634] 4. Menu generation using generative AI

[1635] The generative AI model generates a menu based on the prompt sentence, taking into account the user information. For example, the following menu is generated:

[1636] Breakfast: Toast and tomato salad

[1637] Lunch: Stir-fried chicken and cabbage

[1638] Dinner: Vegetable soup and omelet

[1639] 5. Create an ingredient usage plan

[1640] Based on the generated menu, the server creates an efficient ingredient usage plan, for example, using tomatoes in a breakfast salad and a stir-fry for lunch, and cabbage for lunch and dinner.

[1641] 6. Feedback

[1642] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol. The terminal receives this data and displays it on the user interface. Specifically, the menu screen displays options such as "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[1643] This system efficiently proposes personalized menus to users, helping them to lead a healthy and lean diet.It also makes suggestions based on the user's emotional state, thereby increasing user satisfaction.

[1644] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1645] Step 1:

[1646] User Input Processing

[1647] Users access the application using a smartphone or PC and input information about their dietary habits, including food preferences, allergies, budget, a list of ingredients they have on hand, and the number of meals they eat. Users also use a camera and microphone to provide emotional data such as facial expressions and voice.

[1648] Input: Dietary information (e.g., Western food, no allergies, budget 1,000 yen, chicken, tomato, cabbage, egg, bread), emotional data (facial expression, voice)

[1649] Output: Input data storage to the device

[1650] Step 2:

[1651] Data transmission by the terminal

[1652] The device temporarily stores the dietary information and emotion data entered by the user in its internal storage and transmits them to the server using the HTTPS protocol.

[1653] Input: User information and emotion data stored in internal storage

[1654] Output: Send data to the server

[1655] Step 3:

[1656] Data reception and analysis by the server

[1657] The server receives and analyzes the data sent from the device. First, it uses an emotion analysis engine to analyze the emotion data and identify the user's emotional state. From the analysis results, it extracts the user's emotional state (e.g., stress level).

[1658] Input: User information and emotion data sent via HTTPS

[1659] Output: User's emotional state (e.g., stress state)

[1660] Step 4:

[1661] Prompt input and menu generation using generative AI

[1662] The server inputs a prompt into the generative AI model based on the analyzed emotional data and the user's dietary information. A specific instruction is generated: "The user is feeling stressed and has chicken, tomatoes, cabbage, eggs, and bread. Please suggest a healthy menu using these." The generative AI model then automatically generates the optimal menu based on this.

[1663] Input: User information, analysis results, prompt text

[1664] Output: Generated menu (e.g. Breakfast: Toast and tomato salad, Lunch: Stir-fried chicken and cabbage, Dinner: Vegetable soup and omelet)

[1665] Step 5:

[1666] Creating an ingredient usage plan

[1667] The server creates an efficient ingredient plan based on the generated menu, for example, using tomatoes in a breakfast salad and a lunch stir-fry, and using cabbage for lunch and dinner, thereby minimizing food waste.

[1668] Input: Generated menu

[1669] Output: Ingredient usage plan (e.g., tomatoes for breakfast and lunch, cabbage for lunch and dinner)

[1670] Step 6:

[1671] Server feedback

[1672] The server sends the generated menu and ingredient usage plan to the terminal using the HTTPS protocol.

[1673] Input: Generated menu and ingredient plan

[1674] Output: Sending data to the terminal

[1675] Step 7:

[1676] Displaying data on a terminal

[1677] The device receives the data sent from the server and displays it on the user interface. Specifically, the menu screen of the application displays "Breakfast: Toast and tomato salad," "Lunch: Stir-fried chicken and cabbage," and "Dinner: Vegetable soup and omelet."

[1678] Input: Menu and ingredient usage plan sent from the server

[1679] Output: Display of menu and ingredient plan to user

[1680] (Application example 2)

[1681] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1682] In modern society, eating a healthy diet is important, but achieving it in a busy daily life is not easy. The lack of personalized menu suggestions that take into account the user's emotional state is a further challenge. Furthermore, a system that utilizes food delivery services and proposes efficient and waste-free ingredient usage plans is needed.

[1683] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for analyzing the emotional state of the user, means for adjusting a menu based on the emotional state, and means for ordering ingredients and dishes from a food delivery service based on the menu. This makes it possible to provide a personalized menu taking into account the emotional state of the user, and to efficiently use food delivery services.

[1684] "User" means an individual user of the system.

[1685] "Dietary information" refers to data such as the user's dietary preferences, allergy information, budget, and a list of ingredients they own.

[1686] "Generative AI" is a technology that uses artificial intelligence to automatically generate menus based on specific data.

[1687] A "menu" is a meal combination or cooking plan suggested for a user to consume.

[1688] "Ingredient usage plan" refers to a plan for efficiently using ingredients based on the proposed menu.

[1689] "Emotional state" is data that indicates a user's current psychological or emotional state.

[1690] A "food delivery service" is a service that delivers ingredients and meals to a user's home or designated location based on the user's order.

[1691] A "server" is a central processing unit that processes and analyzes data and provides feedback to the user interface.

[1692] A "terminal" is a device through which a user accesses the system and inputs or receives information.

[1693] "Analysis" is the process of examining data in detail to reveal its meaning and structure.

[1694] This invention is a system that analyzes a user's dietary information and emotional state, proposes personalized menus using generative AI, and then efficiently provides ingredients and dishes using a food delivery service. Specific embodiments of the system are described below.

[1695] System Components

[1696] The system consists of the following main components:

[1697] 1. User: An individual user of the system.

[1698] 2. Terminal: A device, such as a smartphone, through which a user inputs information and interfaces with the system.

[1699] 3. Server: A central processing unit that receives, analyzes, and generates data. It generates menus using AI, analyzes emotions using an emotion engine, and connects with food delivery services.

[1700] System Operation

[1701] 1. User interaction and data entry

[1702] The user opens the food delivery app on their smartphone and enters the following information:

[1703] Food preferences

[1704] Allergy Information

[1705] Daily Budget

[1706] List of ingredients you have

[1707] Number of meals

[1708] The app also uses the camera and microphone to capture the user's facial expressions and voice and record them as emotional data.

[1709] 2. Data transmission

[1710] The terminal transmits the user's input information and emotion data to the server.

[1711] 3. Data analysis and menu generation on the server

[1712] The server analyzes the received data. First, it uses an emotion engine to analyze the user's emotional state. For emotion analysis, it uses Microsoft Azure's Emotion API or Google Cloud's Natural Language API, for example.

[1713] Next, a generative AI generates an optimal menu based on dietary information and emotional data. This uses a generative AI such as OpenAI's GPT model. A specific example of a prompt is as follows:

[1714] Prompt Sentence Examples

[1715] User preference: Japanese food

[1716] Allergy Information: Dairy allergy

[1717] Budget: 1,500 yen

[1718] Ingredients I have: Chicken, potatoes, carrots

[1719] Emotional state: Fatigue

[1720] Based on this, please suggest the best menu.

[1721] 4. Creation and collaboration of ingredient use plans

[1722] The server creates an efficient ingredient usage plan based on the generated menu, which allows for efficient consumption of ingredients across multiple meals.

[1723] 5. Integration with food delivery services

[1724] The user confirms the proposed menu, and the server coordinates with a food delivery service to arrange for the necessary ingredients and dishes to be delivered to the user's designated location.

[1725] Specific examples

[1726] For example, if a user prefers Japanese food, has a dairy allergy, has a daily budget of 1500 yen, has chicken, potatoes, and carrots, and is in a "fatigued" emotional state, the following menu will be generated:

[1727] Breakfast: Rice balls and miso soup

[1728] Lunch: Chicken and potato stew

[1729] Dinner: Carrot and spinach salad

[1730] Based on this, the system orders additional ingredients and dishes from a food delivery service and delivers them to the user, enabling users to lead a healthy and efficient diet without any hassle.

[1731] The above is an embodiment of the present invention. This system enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[1732] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1733] Step 1:

[1734] The user opens a food delivery app on their smartphone. There, they input information about their diet. Specifically, they input their food preferences, allergy information, budget, list of ingredients they have, number of meals, etc. They also provide facial and voice data using a camera and microphone. This information is then captured by the device. The input data is the user's food preferences, allergy information, budget, list of ingredients they have, number of meals, and emotional data.

[1735] Step 2:

[1736] The device sends the data entered by the user and emotion data to the server. The device then uploads the acquired data to the server as a JSON format request. The data sent is dietary information and emotion data, and is sent to the server's API endpoint.

[1737] Step 3:

[1738] The server analyzes the received dietary information and emotional data. First, the emotion engine analyzes the emotional data and evaluates the user's emotional state. This analysis uses, for example, Microsoft Azure's Emotion API or Google Cloud's Natural Language API. The input is emotional data, and the output is the user's emotional state as a result of the analysis.

[1739] Step 4:

[1740] The server uses a generative AI to generate an optimal menu based on the analyzed emotional state and dietary information. The generative AI uses, for example, OpenAI's GPT model. This AI generates a personalized menu based on the user's preferences, allergy information, budget, ingredients available, emotional state, etc. The input is dietary information and emotional state, and the output is the generated menu.

[1741] Step 5:

[1742] The server creates an ingredient usage plan based on the generated menu. Based on the generated menu, a plan is created to use ingredients without waste. This ingredient usage plan includes a method for efficiently allocating ingredients to multiple meals. The input is the generated menu, and the output is an ingredient usage plan.

[1743] Step 6:

[1744] The server sends the generated menu and ingredient usage plan to the terminal. The server returns this data to the terminal and displays it on the user's smartphone. The transmitted data is the generated menu and ingredient usage plan.

[1745] Step 7:

[1746] Users can check the menu and ingredient usage plan displayed on their smartphone. If they like it, they can order ingredients and dishes from a food delivery service with just one tap. The order information is sent to the food delivery service, and the required ingredients and dishes are delivered to the user.

[1747] This concludes the processing flow of the system program that realizes this application example. This processing enables personalized menu suggestions that take into account the user's emotional state and efficient food delivery services.

[1748] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1749] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1750] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1751] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1752] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1753] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1754] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1755] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1756] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1757] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1758] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1759] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1760] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1761] 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.

[1762] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1763] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1764] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1765] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1766] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1767] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1768] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1769] The following is further disclosed regarding the above embodiment.

[1770] (Claim 1)

[1771] means for receiving information about dietary habits from a user;

[1772] A means for automatically generating a menu using a generation AI based on the received information;

[1773] means for displaying the generated menu to a user;

[1774] A means for creating an ingredient usage plan based on the generated menu;

[1775] means for displaying the ingredient usage plan to a user;

[1776] A system including:

[1777] (Claim 2)

[1778] 2. The system of claim 1, wherein the generation AI generates menus based on the user's dietary preferences, allergy information, budget, and a list of ingredients they have on hand.

[1779] (Claim 3)

[1780] 2. The system of claim 1, wherein the generated menu and ingredient usage plan are designed to promote healthy eating habits and minimize product waste.

[1781] "Example 1"

[1782] (Claim 1)

[1783] means for receiving information about dietary habits from a user;

[1784] means for transmitting the received information to a server;

[1785] A means for automatically generating a menu using a generative AI model based on the received information;

[1786] A means for creating an ingredient usage plan based on the generated menu;

[1787] means for transmitting the generated menu and ingredient usage plan from the server to the terminal;

[1788] A means for displaying the generated menu and ingredient usage plan to a user;

[1789] A system including:

[1790] (Claim 2)

[1791] 10. The system of claim 1, wherein the generative AI model uses prompts to generate menus based on the user's dietary preferences, allergy information, budget, and on-hand ingredient list.

[1792] (Claim 3)

[1793] The system of claim 1, wherein the menus and ingredient usage plans generated by the generative AI model are designed to promote healthy eating habits and minimize food waste.

[1794] "Application Example 1"

[1795] (Claim 1)

[1796] means for receiving information about dietary habits from a user;

[1797] A means for automatically generating a menu using a generation AI based on the received information;

[1798] means for displaying the generated menu to a user;

[1799] A means for creating an ingredient usage plan based on the generated menu;

[1800] means for displaying the ingredient usage plan to a user;

[1801] means for providing an ingredient list and delivery options for food delivery based on the generated menu and usage plan;

[1802] means for displaying the provided ingredient list and delivery options to a user;

[1803] A system including:

[1804] (Claim 2)

[1805] 2. The system of claim 1, wherein the generation AI generates menus based on the user's dietary preferences, allergy information, budget, and a list of ingredients they have on hand.

[1806] (Claim 3)

[1807] 2. The system of claim 1, wherein the generated menu and ingredient usage plan are designed to promote healthy eating habits and minimize product waste.

[1808] "Example 2: Combining Emotion Engines"

[1809] (Claim 1)

[1810] means for receiving information about dietary habits from a user;

[1811] means for transmitting data including the received information and user emotion data to a server;

[1812] The server uses an emotion analysis engine to analyze the user's emotional state, and inputs a prompt sentence into a generation AI model based on the analysis result to automatically generate an optimal menu.

[1813] A means for creating an ingredient usage plan based on the generated menu;

[1814] a means for feeding back the generated menu and ingredient use plan to a user and displaying it on a user terminal;

[1815] A system including:

[1816] (Claim 2)

[1817] 2. The system of claim 1, wherein the generative AI model generates menus based on the user's dietary preferences, allergy information, budget, list of ingredients on hand, and sentiment analysis results.

[1818] (Claim 3)

[1819] 2. The system of claim 1, wherein the generated menu and ingredient usage plan are designed to promote healthy eating habits and minimize food waste.

[1820] "Application example 2 when combining emotion engines"

[1821] (Claim 1)

[1822] means for receiving information about dietary habits from a user;

[1823] A means for automatically generating a menu using a generation AI based on the received information;

[1824] means for displaying the generated menu to a user;

[1825] A means for creating an ingredient usage plan based on the generated menu;

[1826] means for displaying the ingredient usage plan to a user;

[1827] means for analyzing the emotional state of a user;

[1828] means for adjusting a menu based on said emotional state;

[1829] A means to order ingredients and dishes from a food delivery service based on the menu,

[1830] A system including:

[1831] (Claim 2)

[1832] 2. The system of claim 1, wherein the generation AI generates menus based on the user's dietary preferences, allergy information, budget, and a list of ingredients they have on hand.

[1833] (Claim 3)

[1834] 2. The system of claim 1, wherein the generated menu and ingredient usage plan are designed to promote healthy eating habits and minimize product waste. [Explanation of symbols]

[1835] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving information about dietary habits from a user; A means for automatically generating a menu using a generation AI based on the received information; means for displaying the generated menu to a user; A means for creating an ingredient usage plan based on the generated menu; means for displaying the ingredient usage plan to a user; A system including:

2. The system of claim 1, wherein the generation AI generates menus based on the user's dietary preferences, allergy information, budget, and a list of ingredients that the user has on hand.

3. The system of claim 1 , wherein the generated menu and ingredient usage plan are designed to promote healthy eating habits and minimize product waste.

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