System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting currently available ingredients; means for inputting budget information; means for inputting user location information; means for inputting cooking preferences; means for inputting health goals; means for generating an optimal menu based on the above information; means for presenting cooking methods associated with the generated menu; and means for performing cost assessment within the budget.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, it has become difficult for busy modern people to find time to cook at home or to plan an appropriate menu. Students and office workers living alone, in particular, face the challenge of eating healthy meals on a limited budget. Furthermore, if you lack cooking knowledge, it is even more difficult to prepare nutritionally balanced meals. For this reason, there is a need for methods that can simultaneously save on food costs and improve health. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for inputting currently available ingredients, budget information, user location information, cooking preferences, and health goals, a means for generating an optimal menu based on this information, a means for presenting cooking methods related to the generated menu, and a means for evaluating costs within the budget. The system also includes a means for receiving feedback from the user regarding the optimal menu and cooking methods and reflecting this in the next menu proposal, and a means for evaluating the nutritional value of the menu based on the user's health goals and measuring its health benefits. In this way, it is possible to achieve both food cost savings and health improvement.

[0006] A "user" is an individual or entity that utilizes the system to input currently available ingredients, budget information, location information, cooking preferences, health goals, and the like.

[0007] "Ingredients" are specific types of food that the user currently owns and that will be used when creating a menu.

[0008] A "budget" is the maximum amount a user can spend on a single meal or on meals within a certain period of time.

[0009] "Location" refers to the geographic information of the place where the user lives or is currently staying, and is necessary for creating menus based on a specific region or environment.

[0010] "Cuisine preferences" refers to the type or style of cuisine that the user particularly likes (for example, Japanese, Chinese, Italian, etc.), and is an important factor when proposing a menu.

[0011] "Health Goal" means a specific health or fitness objective that a user wishes to achieve (e.g., losing weight, gaining muscle, etc.).

[0012] "Menu" refers to a specific food combination or meal plan generated by the system based on information entered by the user.

[0013] "Cooking method" refers to detailed instructions such as steps, tools, cooking time, etc. for actually cooking the generated menu.

[0014] "Cost evaluation" is the process of calculating the cost of ingredients and materials needed for a menu and evaluating the economic savings by comparing it with the budget entered by the user.

[0015] "Feedback" refers to the opinions and impressions provided by the user after cooking, and is information used to improve the next menu suggestion.

[0016] "Nutritional value" refers to the amount and balance of nutritional elements such as protein, fat, carbohydrates, vitamins, and minerals provided by ingredients and menu items.

[0017] "Health effect" is an index for evaluating the extent to which the generated menu contributes to the user's health goals.

[0018] The "system" refers to an integrated mechanism of software and hardware that incorporates the above means, and provides a service that suggests optimal menus to users and reduces various burdens. [Brief explanation of the drawings]

[0019] [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

[0020] 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.

[0021] First, the terms used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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."

[0027] [First embodiment]

[0028] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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."

[0040] The present invention is a system that provides optimized menus and cooking methods based on information input by a user. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0041] User registration and initial settings

[0042] Device: The user installs the application and creates an account. When creating an account, they enter required information such as an email address and password. In addition, the user enters information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0043] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[0044] Data analysis and menu generation

[0045] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[0046] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0047] Menu and cooking instructions

[0048] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[0049] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0050] Measuring costs and health benefits

[0051] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0052] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0053] User Feedback and Improvements

[0054] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0055] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[0056] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0057] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals that are within their budget.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] A user installs the application and creates an account. The user enters an email address and password and receives a confirmation email.

[0061] Step 2:

[0062] The user inputs initial information into the device, including currently available ingredients, budget, location, cooking preferences, and health goals. This information is entered in detail.

[0063] Step 3:

[0064] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[0065] Step 4:

[0066] The server analyzes the user's input information and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). The server then prepares to generate the optimal menu based on the user information.

[0067] Step 5:

[0068] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[0069] Step 6:

[0070] The server generates optimal menus, selecting nutritionally balanced recipes based on the user's health goals, and creating optimal menus that include specific recipes, ingredient lists, and cooking instructions.

[0071] Step 7:

[0072] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[0073] Step 8:

[0074] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[0075] Step 9:

[0076] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[0077] Step 10:

[0078] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[0079] Step 11:

[0080] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[0081] Step 12:

[0082] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[0083] The above are the specific processing steps of the system.

[0084] Example 1

[0085] 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."

[0086] In today's busy world, consumers need easy ways to prepare healthy and economical meals. However, coming up with optimal menus with limited ingredients and a limited budget is a challenge for many people. Furthermore, there are few systems that suggest menus that meet individual health goals and culinary preferences. Therefore, a user-friendly menu suggestion system is needed.

[0087] 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.

[0088] In this invention, the server includes a means for inputting currently available ingredients, a means for inputting budget information, a means for inputting user location information, a means for inputting cooking preferences, a means for inputting health goals, a means for analyzing the above information and deriving evaluation data based on variables, a means for generating an optimal menu by referencing a database based on the evaluation data, a means for presenting cooking methods related to the generated menu, a means for evaluating costs within the budget, a means for storing and analyzing user feedback in a database, and a means for reflecting the feedback in the next menu proposal. This allows users to easily obtain optimal menus and cooking methods tailored to their individual requirements. Furthermore, the generated menu can be evaluated to see whether it is within budget and how much it contributes to health goals, allowing users to easily achieve an economical and healthy diet. Furthermore, by reflecting user feedback in the next proposal, more personalized menu proposals are possible.

[0089] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[0090] "Budget information" is data indicating the upper limit of the cost that a user is willing to spend on a single meal.

[0091] "User location information" is information about the user's residential area or current location, and is a factor that affects the ingredients and cooking methods available depending on the area.

[0092] "Cooking preferences" is information that indicates the genres, styles, and seasonings of cooking that the user particularly likes.

[0093] "Health goals" are health conditions and weight management goals that a user aims for, and include dieting and improving nutritional balance.

[0094] "Means for deriving evaluation data" refers to a function that analyzes various information entered by the user and calculates specific evaluation values ​​and indicators.

[0095] The "means for generating the optimal menu by referring to the database" is a function that selects the optimal menu from a database of saved recipes and ingredient information based on the analyzed evaluation data.

[0096] The "means for presenting cooking methods" is a function that provides the user with detailed information such as the steps to prepare the dish, the necessary tools, and cooking time based on the generated menu.

[0097] The "means for performing cost evaluation" is a function that calculates the cost of ingredients required for the generated menu and compares this with the user's budget to perform an economic evaluation.

[0098] "Means for saving and analyzing feedback in a database" is a function for saving evaluations and opinions provided by users in a database, analyzing them, and reflecting them in the next proposal.

[0099] The present invention is a system that provides optimized menus and cooking methods based on information entered by a user. The system aims to improve health and reduce food costs, and specific embodiments are described below.

[0100] User registration and initial settings

[0101] On the device: The user installs the application and creates an account, entering basic information such as an email address and password, as well as details such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0102] Server: The server stores the entered information in a database and generates a user profile, which is used for subsequent menu suggestions.

[0103] Data analysis and menu generation

[0104] Server: Analyzes the information entered by the user (ingredients, budget, location, preferences, and health goals) and derives evaluation data. This analysis is performed using data analysis libraries such as Python's pandas and scikit-learn. Based on the analyzed data, the optimal menu is generated by referencing the ingredient database, recipe database, budget analysis, and health database.

[0105] Example: If a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server uses this information to search a Japanese food recipe database for low-calorie recipes that fit within the user's budget and generate the optimal menu. It suggests "stir-fried chicken breast and vegetables."

[0106] Menu and cooking instructions

[0107] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[0108] On the device: The user is notified and shown detailed cooking instructions. The app UI provides step-by-step instructions and allows users to track their progress.

[0109] Measuring costs and health benefits

[0110] Server: Calculates the cost of ingredients needed for the generated menu. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. This evaluates the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0111] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[0112] User Feedback and Improvements

[0113] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[0114] User: Fill out the feedback form and click the "Submit" button.

[0115] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal. For analysis using AI models, generative AI models such as TENSORFLOW (registered trademark) and PyTorch are used.

[0116] Example prompt sentence:

[0117] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[0118] This system allows users to easily enjoy healthy meals within their budget, and by incorporating user feedback, it is possible to provide more personalized menu suggestions.

[0119] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0120] Step 1: Install the app and create an account

[0121] Device: The user installs and opens the application. The account creation screen appears.

[0122] User: Enter your email address, password, and other required information and click the "Register" button.

[0123] Input: Email address, password, and other personal information.

[0124] Server: Receives the entered information and stores it in a database. It creates a user profile and sends a message to the terminal indicating successful registration.

[0125] Output: Registration successful message.

[0126] Step 2: Enter the initial configuration information

[0127] Terminal: Displays an input form for the user to enter information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0128] User: Enter the current ingredients (e.g., "chicken breast," "carrots," and "potatoes"), budget (e.g., 500 yen), location (e.g., Tokyo), preferences (e.g., Japanese food), and health goals (e.g., weight loss), then press the "Save" button.

[0129] Input: ingredients, budget, location, preferences, health goals.

[0130] Server: Receives the entered information and stores it in a database. Updates the user profile based on this information.

[0131] Output: Initial configuration information stored in the database.

[0132] Step 3: Information analysis and evaluation data derivation

[0133] Server: Analyzes the information entered by the user and creates evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Data analysis libraries such as Python's pandas and scikit-learn are used for the analysis.

[0134] Input: Initial setup information (ingredients, budget, location, preferences, health goals).

[0135] Data processing / data calculation: Analyze numerical and categorical data using Python's pandas and scikit-learn to generate evaluation data.

[0136] Output: Evaluation data.

[0137] Step 4: Menu generation

[0138] Server: Based on the analyzed data, the server generates the optimal menu by referencing the food ingredient database, recipe database, budget analysis, and health database.

[0139] Input: Evaluation data, various databases.

[0140] Data processing / data calculation: Run queries against the database to extract the recipe that best suits the evaluation data.

[0141] Example: If the user inputs "chicken breast," "carrot," "potato," budget of 500 yen, location of "Tokyo," preference of "Japanese food," and health goal of "weight loss," the system will search a Japanese food recipe database for low-calorie recipes that fit within the budget and suggest "stir-fried chicken breast and vegetables."

[0142] Output: Optimal menu.

[0143] Step 5: Present the menu and cooking instructions

[0144] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[0145] Input: The generated menu.

[0146] On the device: The user is notified and shown detailed cooking instructions. The app UI displays step-by-step instructions and allows users to track their progress.

[0147] Output: Menu and cooking instructions displayed on the terminal.

[0148] Step 6: Cost and health assessment

[0149] Server: Calculates the cost of ingredients needed for the generated meal plan. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. Evaluates the financial savings. Also analyzes the nutritional value of the meal plan to measure its contribution to the user's health goals.

[0150] Input: Generated menu and price database.

[0151] Data processing / data calculation: Based on price data, the cost of ingredients is added up and evaluated to see if it is within the user's budget. Also, based on nutritional data, the degree of achievement toward health goals is calculated.

[0152] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[0153] Output: Cost assessment and health assessment results.

[0154] Step 7: Gather user feedback

[0155] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[0156] User: Fill out the feedback form and click the "Submit" button.

[0157] Input: User feedback.

[0158] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal.

[0159] Output: Feedback data.

[0160] Example prompt sentence:

[0161] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[0162] (Application example 1)

[0163] 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."

[0164] Conventional menu suggestion systems require users to purchase ingredients and cook the meals themselves based on the suggested menu, which is time-consuming, especially for busy modern people. Furthermore, there was a lack of an efficient way to obtain ingredients and meals, so integration with delivery services was required. Therefore, a system was needed that would allow users to easily secure healthy meals within their budget.

[0165] 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.

[0166] In this invention, the server includes means for inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting food preferences, means for inputting health goals, means for generating an optimal menu based on this information, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, means for coordinating ingredients and dishes required for the optimal menu with a delivery company and presenting ordering options, and means for contacting the delivery company and delivering the ingredients and dishes after the user confirms the order. This allows the user to automatically order and receive ingredients and dishes based on the menu suggestions, ensuring healthy and efficient meals with significantly less hassle.

[0167] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[0168] "Budget information" refers to the amount of money a user can spend on ingredients and dishes.

[0169] "User location information" refers to geographical information about the location where the user resides.

[0170] "Cooking preferences" refers to the user's preferences regarding the food and cooking styles they prefer to eat.

[0171] A "health goal" is a health-related goal that a user wants to achieve, such as losing weight or improving nutritional balance.

[0172] A "means for generating an optimal menu" is a method or system for deriving appropriate dish and meal combinations based on information entered by the user.

[0173] "Means for presenting cooking methods related to the generated menu" refers to a method or system for instructing the user on specific cooking methods and procedures for the menu generated by the system.

[0174] The "means for evaluating costs within a budget" refers to a method or system for evaluating whether the ingredients and dishes required for the generated menu fit within the user's budget.

[0175] "Means for coordinating with delivery companies the ingredients and dishes required for the optimal menu and presenting ordering options" refers to a method or system that works with a delivery service to coordinate the ingredients and dishes required for the generated menu and provides the user with ordering options.

[0176] "Means for contacting a delivery company to deliver ingredients or food after a user has confirmed an order" refers to a method or system for transmitting information to a delivery service and having the food or food delivered to a specified location after a user has confirmed an order for ingredients or food.

[0177] This invention is a system that provides a menu and cooking methods optimized based on information entered by the user, and also provides a service that delivers the ingredients and dishes required for that menu. The basic system configuration, data flow, and specific operating procedures are described in detail below.

[0178] System configuration

[0179] 1. Hardware

[0180] Smartphone

[0181] Cloud server (e.g., AWS (registered trademark), Google (registered trademark) Cloud)

[0182] 2. Software

[0183] Mobile app development frameworks (e.g., Flutter (registered trademark), React Native)

[0184] Database management systems (e.g., MySQL (registered trademark), MongoDB)

[0185] Data analysis libraries (e.g., Python, Pandas, TensorFlow)

[0186] Data flow and processing method

[0187] 1. User registration and initial settings

[0188] Device: The user installs the mobile app on their smartphone and creates an account. The user enters information about currently available ingredients, budget information, user location information, cooking preferences, health goals, etc.

[0189] Server: Saves the entered information in a database on the cloud and creates a user profile.

[0190] 2. Data analysis and menu generation

[0191] Server: Analyzes the information entered by the user using a data analysis module (e.g., Python, Pandas) and derives evaluation data for generating optimal menus. The generated menus include specific dish names and ingredient lists based on the information entered by the user.

[0192] Example: For example, if a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a database of Japanese food recipes and suggest the most suitable recipe.

[0193] 3. Menu and delivery method

[0194] Server: Based on the generated menu, it coordinates with delivery companies to determine the necessary ingredients and dishes, and presents ordering options to the user's device.

[0195] On device: The user is notified of the suggested meal plan and presented with detailed cooking instructions and purchasing options.

[0196] 4. Delivery arrangements and cost management

[0197] Server: After the user confirms the order, the server contacts the delivery company and arranges for the delivery of ingredients and food. At this time, the server evaluates the cost within the budget and ensures economical and efficient delivery.

[0198] Example: Once the necessary ingredients and dishes have been ordered based on the menu selected by the user, the server will request delivery from a delivery company. The user simply waits for the food to arrive while checking the progress on their smartphone.

[0199] 5. User Feedback and Improvements

[0200] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0201] Server: User feedback is stored in a database and analyzed. This feedback is reflected in the next menu suggestion, allowing for even more personalized suggestions.

[0202] Prompt Sentence Examples

[0203] The user has entered "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss." Based on this information, please generate the optimal Japanese food menu.

[0204] By implementing this invention, users can conveniently enjoy healthy meals that are within their budget, and can easily order and receive the ingredients and dishes.

[0205] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0206] Step 1:

[0207] User registration and initial settings

[0208] Input: A user installs the mobile app on their smartphone and creates an account. Input fields include email address, password, currently available ingredients, budget information, user location information, cooking preferences, and health goals.

[0209] Specific operation: When a user enters information on the terminal and presses the send button, this information is sent to the server.

[0210] Processing: The server stores the entered information in a cloud database (e.g., MySQL, MongoDB) and creates a user profile.

[0211] Output: A user profile is generated, storing data about ingredients, budget, location, preferences, and health goals.

[0212] Step 2:

[0213] Data analysis and menu generation

[0214] Input: User-entered information about ingredients, budget information, location, food preferences, and health goals.

[0215] Specific operation: The server receives this information and passes it to a data analysis module (e.g., Python, Pandas).

[0216] Processing: The server uses an analysis module to analyze the user's input information and derive evaluation data for generating optimal menus, including the availability of ingredients, budget range, local characteristics, user preferences, and health goals.

[0217] Output: A user-optimized menu is generated and the information is saved in a database.

[0218] Step 3:

[0219] Menu and delivery options

[0220] Input: Server-generated menu information.

[0221] Specific operation: The server coordinates with delivery companies to find the ingredients and dishes needed for the generated menu and presents delivery options.

[0222] Processing: The server calls the delivery company's API to retrieve discoverable delivery options, which provides the best delivery company and pricing information based on the user's location. This information is then sent to the user's device.

[0223] Output: The user device displays the suggested meal plan, cooking instructions, and delivery options.

[0224] Step 4:

[0225] Delivery arrangements and cost management

[0226] Input: The delivery option selected and confirmed by the user.

[0227] What happens: A user uses a smartphone app to select a delivery option and place an order.

[0228] Processing: After the user confirms the order of ingredients and dishes necessary for the optimal menu, the server contacts the delivery company to arrange delivery. At this time, the server evaluates whether the delivery cost is within the user's budget and notifies the user.

[0229] Output: The delivery company delivers the ingredients and food to the user's location.

[0230] Step 5:

[0231] User Feedback and Improvements

[0232] Input: Feedback information such as the taste of the food the user experienced, cooking procedures, and satisfaction level.

[0233] What happens: The user creates a dish and provides feedback through the app.

[0234] Processing: The server stores the received feedback in a database and analyzes the data to reflect it in the next menu suggestion. The feedback analysis will be used to improve the analysis module in the future.

[0235] Output: The user's feedback will be reflected in the next menu suggestion, making it more suitable for the user.

[0236] 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.

[0237] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0238] User registration and initial settings

[0239] Device: The user installs the application and creates an account. The user enters their email address and password and receives a confirmation email. The user also enters their currently available ingredients, budget, location, cooking preferences, and health goals.

[0240] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[0241] Data analysis and menu generation

[0242] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[0243] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0244] Menu and cooking instructions

[0245] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[0246] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0247] Measuring costs and health benefits

[0248] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0249] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0250] User Feedback and Improvements

[0251] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0252] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[0253] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0254] Emotion recognition and menu adjustment

[0255] Device: When a user uses an application, the emotion engine is activated. The emotion engine analyzes the user's facial expressions and speech to recognize their current emotional state.

[0256] Server: Receives information from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the server will suggest dishes using ingredients that have a relaxing effect.

[0257] Example: If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Providing menus that take emotions into account in this way makes it possible to make more personalized suggestions.

[0258] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals within their budget, and also provides menu suggestions that match their mood and emotions at the time.

[0259] The processing flow will be explained below.

[0260] Step 1:

[0261] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[0262] Step 2:

[0263] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[0264] Step 3:

[0265] An emotion engine is activated on the device and analyzes the user's facial expressions and speech to recognize their current emotional state. For example, the user inputs their emotions using a camera or microphone, and the emotion engine analyzes the data.

[0266] Step 4:

[0267] The server analyzes the user's input information and emotional data. It derives evaluation data based on each variable (ingredients, budget, location, preferences, health goals, and emotions). The server then prepares to generate the optimal menu based on the user information.

[0268] Step 5:

[0269] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[0270] Step 6:

[0271] The server generates optimal menus, selecting nutritionally balanced recipes and creating optimal menus based on the user's health goals and emotions, and generating menus that include specific recipes, ingredient lists, and cooking instructions.

[0272] Step 7:

[0273] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[0274] Step 8:

[0275] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[0276] Step 9:

[0277] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[0278] Step 10:

[0279] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[0280] Step 11:

[0281] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[0282] Step 12:

[0283] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[0284] Step 13:

[0285] The emotion engine continuously monitors the user's emotions and evaluates their emotional response to suggested menus and cooking methods. For example, if the user smiles at a particular dish, it will determine that the dish was well-received and reflect this in future suggestions.

[0286] These are the specific processing steps of the system that combines the emotion engine. This allows users to easily enjoy healthy meals within their budget, and receives menu suggestions that match their mood and emotions at the time.

[0287] Example 2

[0288] 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."

[0289] In modern society, busy lifestyles make it difficult to easily prepare healthy meals. In particular, there is a need for planning balanced menus within a budget and for recipe suggestions tailored to the user's health goals and emotions. However, existing systems have difficulty adequately addressing individual user needs. Therefore, a system is needed that provides appropriate menus and cooking methods based on the user's input information and emotional state, helping them save money on food and improve their health.

[0290] 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.

[0291] In this invention, the server includes a means for the user to input currently available ingredients, budget, location, cooking preferences, and health goals as initial settings, a means for saving and analyzing the information and creating a user profile based on the above information, a means for generating an optimal menu based on the input information using a generative AI model, a means for transmitting and presenting the generated menu and cooking methods to the user's terminal, and a means for evaluating costs and nutritional values ​​within the budget and measuring health benefits. This allows users to not only easily enjoy healthy meals within their budget, but also to receive personalized menu suggestions tailored to their moods and emotions at the time.

[0292] "User input as initial settings" means that after the user installs the application, they input personal information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0293] A "generative AI model" is an artificial intelligence model that generates optimal menus based on input information.

[0294] A "user profile" is a collection of data that stores individual information entered by a user and is used to perform various analyses and make suggestions based on that information.

[0295] A "menu" is a specific combination of dishes and a list of ingredients for a user to cook.

[0296] "Cooking method" refers to the steps and methods for preparing a dish based on the generated menu.

[0297] "Cost evaluation" involves calculating the prices of ingredients required for the generated menu and evaluating whether they are within the budget set by the user.

[0298] "Nutritional value" is an evaluation of the amount of nutrients contained in the generated menu, measuring its contribution to the user's health goals.

[0299] "Health Benefit" refers to an assessment of how much the generated menu contributes to the user's health goals.

[0300] "Feedback" refers to the user providing their thoughts and opinions about the suggested menu and cooking methods.

[0301] The "emotional state" refers to the user's current psychological state, which can be obtained by analyzing the user's facial expressions, speech content, and the like.

[0302] "Adjusting menu suggestions based on emotions" refers to changing or adjusting the menu suggestions depending on the user's emotional state.

[0303] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0304] User registration and initial settings

[0305] Device:

[0306] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and initially enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[0307] server:

[0308] The system stores the user's registration information sent from the device in a database and creates a user profile based on that information, which includes a wide range of information such as ingredients, budget, location, cooking preferences, and health goals.

[0309] Data analysis and menu generation

[0310] server:

[0311] The information entered by the user is analyzed and rating data is generated based on each variable (ingredients, budget, location, preferences, and health goals). The rating data is then analyzed using a generative AI model, which then references the ingredient database, recipe database, budget analysis, and health database to generate the optimal menu.

[0312] Examples:

[0313] If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the server will search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0314] Menu and cooking instructions

[0315] server:

[0316] The generated menu is sent to the user's device, and includes the specific dish names and ingredient lists.

[0317] Device:

[0318] The user is notified of the generated menu suggestion and is shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0319] Measuring costs and health benefits

[0320] server:

[0321] The system calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user, evaluates whether it is within budget and measures the financial savings, and evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0322] Examples:

[0323] For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0324] User Feedback and Improvements

[0325] Device:

[0326] Users prepare the proposed meal and then provide feedback, including the taste of the dish, the ease of the process, and their satisfaction level.

[0327] server:

[0328] User feedback is stored in a database and analyzed, and the feedback is reflected in the next menu suggestions, allowing for menus that better suit the user's preferences and requests.

[0329] Examples:

[0330] For example, if the user's feedback is "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0331] Emotion recognition and menu adjustment

[0332] Device:

[0333] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[0334] server:

[0335] The system receives emotional information sent from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the system will suggest dishes using ingredients that have a relaxing effect.

[0336] Examples:

[0337] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[0338] Prompt Sentence Examples

[0339] Examples of prompts that allow users to easily input instructions to the system include the following:

[0340] "A user is looking for a Japanese meal using chicken breast, carrots, and potatoes, costing less than 500 yen, and aimed at weight loss. Please suggest the best menu."

[0341] This prompt makes it easier for the generative AI model to make specific cooking suggestions.

[0342] In this way, the system allows users to easily enjoy healthy meals within their budget, and also provides personalized menu suggestions that match their mood and emotions at the time.

[0343] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0344] Step 1:

[0345] User registration and initial settings

[0346] User:

[0347] A user installs the application and creates an account. They enter an email address and password. After entering this information, they receive a confirmation email containing a link to activate their account. They then enter initial information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0348] Device:

[0349] All information entered by the user is sent to the server.

[0350] server:

[0351] The information entered is saved in a database. A user profile is created based on the saved information. The profile contains all of the information entered.

[0352] Input: User email address, password, currently available ingredients, budget, location, cooking preferences, health goals

[0353] Output: User profile stored in the database

[0354] Step 2:

[0355] Data analysis and menu generation

[0356] server:

[0357] Data analysis is performed based on the saved user profile. The information analyzed includes ingredients, budget, location, cooking preferences, and health goals. Evaluation data is generated based on this information. Next, an optimal menu is generated using a generative AI model. Recipes that meet the given criteria are selected by referencing the ingredient database, recipe database, budget analysis, and health database.

[0358] Examples:

[0359] Based on information such as "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the system searches for low-calorie recipes from a Japanese food recipe database and generates the optimal menu.

[0360] Input: User profile, ingredient database, recipe database, budget analysis data, health database

[0361] Output: Optimal menu data

[0362] Step 3:

[0363] Menu and cooking instructions

[0364] server:

[0365] The generated menu data is sent to the user's device. The menu data includes specific dish names and ingredient lists.

[0366] Device:

[0367] The user is notified of meal suggestions and shown detailed cooking instructions, including cooking times, necessary tools, and specific instructions for each step.

[0368] Input: Menu data

[0369] Output: Notification to user device, detailed cooking instructions

[0370] Step 4:

[0371] Measuring costs and health benefits

[0372] server:

[0373] It calculates the cost of ingredients needed for the generated meal plan, compares the calculation results with the budget information entered by the user to assess whether it is within budget, and measures the financial savings. It also evaluates the nutritional value of the meal plan to measure its contribution to the user's health goals.

[0374] Examples:

[0375] If the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of the ingredients is 450 yen, it will be evaluated as being economical because it is within the budget of 500 yen. Also, because it is low in calories and high in protein, it will be evaluated as contributing to the health goal of weight loss.

[0376] Input: Menu data, budget information, nutritional data

[0377] Output: Cost assessment results, health effect assessment results

[0378] Step 5:

[0379] User Feedback and Improvements

[0380] Device:

[0381] Users create the suggested meals and then provide feedback, including the taste of the food, the ease of the process, and satisfaction.

[0382] server:

[0383] The feedback received from users is stored in a database and analyzed, and the analysis results are reflected in the next menu proposal.

[0384] Examples:

[0385] If the user gives feedback such as "The food was delicious, but I would prefer a simpler recipe," the next time the system will prioritize suggestions that are simpler and have fewer cooking steps.

[0386] Input: User feedback

[0387] Output: Feedback analysis results, improved menu suggestions

[0388] Step 6:

[0389] Emotion recognition and menu adjustment

[0390] Device:

[0391] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[0392] server:

[0393] The system receives the emotional information sent by the emotion engine and adjusts the menu suggestions based on the user's emotions. For example, if the user is feeling stressed, it will suggest dishes using ingredients that have a relaxing effect.

[0394] Examples:

[0395] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[0396] Input: Emotion information

[0397] Output: Emotion-based menu suggestions

[0398] (Application example 2)

[0399] 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."

[0400] While many support systems exist today to help users prepare healthy and economical meals at home, these systems rarely take into account the user's emotions or momentary moods when making suggestions. Systems that can suggest suitable dishes, especially when users are stressed or tired, are lacking. Furthermore, there is a lack of integration with food delivery services that allow users to easily order the suggested meals. Therefore, there is a need for a system that can suggest meals that meet the user's health goals and budget while taking into account the user's emotions, and that can instantly order the meals.

[0401] The specification processing by the specification 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 inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting cooking preferences, means for inputting health goals, means for recognizing the user's emotions, means for generating an optimal menu based on the above information and the user's emotions, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, and means for food delivery that allows the user to order the generated menu and cooking method. This allows the user to receive suggestions for an appropriate menu that matches their emotions and mood at the time, and to easily order meals that meet their health goals and budget.

[0402] "Currently available ingredients" refers to food ingredients that the user owns or plans to procure.

[0403] "Budget information" refers to data indicating the range of amounts that the user can spend on food, as set by the user.

[0404] "User location information" refers to information indicating the area where the user resides or stays.

[0405] "Cuisine preferences" refers to data indicating the types of cuisine a user likes and their preferences for specific ingredients.

[0406] "Health goals" refers to information indicating the health status or nutritional balance that a user wants to achieve, such as weight loss or high protein intake.

[0407] "Means for recognizing the user's emotions" refers to technology that analyzes and recognizes the user's current emotional state from their facial expressions and speech content.

[0408] "Means for generating optimal menus" refers to a system that suggests the most suitable combination of dishes based on the user's input information and emotional data.

[0409] "Means for presenting cooking methods" refers to a mechanism that provides users with cooking procedures and how to use ingredients for the generated menu.

[0410] "Means for cost evaluation" refers to a system that calculates the cost of ingredients required for a proposed menu and evaluates whether it is within budget.

[0411] "Food delivery means" refers to a service that orders food based on the generated menu and delivers it to the user.

[0412] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system works in conjunction with food delivery services to provide menus that take into account the user's health goals and budget.

[0413] System configuration

[0414] The system mainly consists of the following components:

[0415] 1. User device: User information is input on a smartphone or tablet, and emotional state is recognized.

[0416] 2. Server: Generates menus, recognizes emotions, evaluates costs, and manages food delivery.

[0417] 3. Database: Includes food database, recipe database, health database, and budget database.

[0418] User registration and initial settings

[0419] The user installs the application and creates an account. The user enters the following information:

[0420] Currently available ingredients

[0421] Budget Information

[0422] User Location

[0423] Food preferences

[0424] health goals

[0425] This information is sent to a server and stored in a database.

[0426] Emotion Recognition and Data Analysis

[0427] The device uses an emotion recognition engine to analyze the user's facial expressions and voice to recognize their emotional state. This emotional data is sent to the server and stored in a database. The server then analyzes the user's input information and emotional state to generate an optimal menu. The following technologies are used for the analysis:

[0428] EmotionEngine: Software for recognizing user emotions.

[0429] RecipeRecommender: A system that suggests optimal menus based on user input and emotions.

[0430] Menu generation and presentation

[0431] The server generates an optimal menu based on the user's information and emotional data and sends it to the device. The device receives it and presents the menu and cooking instructions to the user. The cooking instructions include specific steps, cooking time, and necessary tools.

[0432] Cost assessment and health benefit measurement

[0433] The server calculates the cost of ingredients in the generated menu and compares it with the user's set budget. If the menu is within the budget, it presents the menu to the user. It also evaluates the health benefits of the generated menu based on its nutritional value and calculates its contribution to the user's health goals.

[0434] Food delivery service

[0435] If the user likes the suggested menu and places an order, the server will arrange for the food to be delivered to the user's location via a food delivery service, allowing the user to easily enjoy healthy meals on a budget.

[0436] User feedback and system improvements

[0437] Users provide feedback on the food they are served, including taste, ease of cooking, and satisfaction. This feedback is sent to the server and reflected in the next recommendation. This allows the system to continually improve to suit the user's preferences.

[0438] Specific examples

[0439] For example, if the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that the budget is met.

[0440] Prompt Sentence Examples

[0441] text

[0442] The user is stressed. Can you suggest some Japanese-style chicken and carrot recipes that are good for weight loss and have a budget of 1000 yen?

[0443] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0444] Step 1:

[0445] A user installs an application using a terminal and creates an account. The user enters an email address and password and receives a confirmation email for creating the account. This sends the user's basic information to the server and completes the initial setup. The input data is an email address and password, and the output is that the account has been created.

[0446] Step 2:

[0447] The user uses a terminal to input currently available ingredients, budget information, location information, cooking preferences, and health goals. The server retrieves the input information and stores it in a database. The input data is ingredients, budget, location, preferences, and health goals, and the output is an updated user profile. The server references the database to analyze this information.

[0448] Step 3:

[0449] The user uses the device to activate the emotion recognition engine. The device analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., stress, fatigue, joy). The recognized emotion data is sent to the server and stored in a database. The input data is the user's facial expressions and voice, and the output is the recognized emotion data. The EmotionEngine processes this and analyzes the emotion.

[0450] Step 4:

[0451] The server analyzes the user's input information and emotional data to generate an optimal menu. The analysis refers to the ingredient database, recipe database, budget database, and health database. Specifically, a RecipeRecommender is used to select recipes that meet the user's criteria based on ingredients, budget, preferences, health goals, and emotions. The input data are the user profile and emotional data, and the output is the generated menu.

[0452] Step 5:

[0453] The server sends the generated menu to the user's device. The device receives the menu and notifies the user. The menu includes specific dish names, ingredient lists, and cooking instructions. The input data is the generated menu, and the output is the menu and cooking instructions displayed to the user.

[0454] Step 6:

[0455] The user reviews the proposed menu and, if they wish to have food delivered, places an order from their device. The server accepts the order and sends a request to the appropriate food delivery service. The input data is the user's order, and the output is a request to the food delivery service, which then delivers the food to the user's location.

[0456] Step 7:

[0457] After receiving and eating the food, the user provides feedback using a terminal. The feedback includes the taste of the food, the ease of the process, and satisfaction level, and is sent to the server. The server stores the feedback in a database and reflects it in the next menu suggestion. The input data is the user's feedback, and the output is updated analysis data. This allows the system to be continuously improved.

[0458] Examples:

[0459] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that they are within the budget.

[0460] 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.

[0461] 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.

[0462] 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.

[0463] [Second embodiment]

[0464] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0465] 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.

[0466] 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).

[0467] 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.

[0468] 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.

[0469] 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).

[0470] 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. 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.

[0471] 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.

[0472] 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.

[0473] 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.

[0474] 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.

[0475] 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."

[0476] The present invention is a system that provides optimized menus and cooking methods based on information input by a user. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0477] User registration and initial settings

[0478] Device: The user installs the application and creates an account. When creating an account, they enter required information such as an email address and password. In addition, the user enters information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0479] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[0480] Data analysis and menu generation

[0481] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[0482] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0483] Menu and cooking instructions

[0484] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[0485] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0486] Measuring costs and health benefits

[0487] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0488] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0489] User Feedback and Improvements

[0490] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0491] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[0492] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0493] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals that are within their budget.

[0494] The processing flow will be explained below.

[0495] Step 1:

[0496] A user installs the application and creates an account. The user enters an email address and password and receives a confirmation email.

[0497] Step 2:

[0498] The user inputs initial information into the device, including currently available ingredients, budget, location, cooking preferences, and health goals. This information is entered in detail.

[0499] Step 3:

[0500] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[0501] Step 4:

[0502] The server analyzes the user's input information and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). The server then prepares to generate the optimal menu based on the user information.

[0503] Step 5:

[0504] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[0505] Step 6:

[0506] The server generates optimal menus, selecting nutritionally balanced recipes based on the user's health goals, and creating optimal menus that include specific recipes, ingredient lists, and cooking instructions.

[0507] Step 7:

[0508] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[0509] Step 8:

[0510] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[0511] Step 9:

[0512] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[0513] Step 10:

[0514] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[0515] Step 11:

[0516] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[0517] Step 12:

[0518] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[0519] The above are the specific processing steps of the system.

[0520] Example 1

[0521] 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."

[0522] In today's busy world, consumers need easy ways to prepare healthy and economical meals. However, coming up with optimal menus with limited ingredients and a limited budget is a challenge for many people. Furthermore, there are few systems that suggest menus that meet individual health goals and culinary preferences. Therefore, a user-friendly menu suggestion system is needed.

[0523] 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.

[0524] In this invention, the server includes a means for inputting currently available ingredients, a means for inputting budget information, a means for inputting user location information, a means for inputting cooking preferences, a means for inputting health goals, a means for analyzing the above information and deriving evaluation data based on variables, a means for generating an optimal menu by referencing a database based on the evaluation data, a means for presenting cooking methods related to the generated menu, a means for evaluating costs within the budget, a means for storing and analyzing user feedback in a database, and a means for reflecting the feedback in the next menu proposal. This allows users to easily obtain optimal menus and cooking methods tailored to their individual requirements. Furthermore, the generated menu can be evaluated to see whether it is within budget and how much it contributes to health goals, allowing users to easily achieve an economical and healthy diet. Furthermore, by reflecting user feedback in the next proposal, more personalized menu proposals are possible.

[0525] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[0526] "Budget information" is data indicating the upper limit of the cost that a user is willing to spend on a single meal.

[0527] "User location information" is information about the user's residential area or current location, and is a factor that affects the ingredients and cooking methods available depending on the area.

[0528] "Cooking preferences" is information that indicates the genres, styles, and seasonings of cooking that the user particularly likes.

[0529] "Health goals" are health conditions and weight management goals that a user aims for, and include dieting and improving nutritional balance.

[0530] "Means for deriving evaluation data" refers to a function that analyzes various information entered by the user and calculates specific evaluation values ​​and indicators.

[0531] The "means for generating the optimal menu by referring to the database" is a function that selects the optimal menu from a database of saved recipes and ingredient information based on the analyzed evaluation data.

[0532] The "means for presenting cooking methods" is a function that provides the user with detailed information such as the steps to prepare the dish, the necessary tools, and cooking time based on the generated menu.

[0533] The "means for performing cost evaluation" is a function that calculates the cost of ingredients required for the generated menu and compares this with the user's budget to perform an economic evaluation.

[0534] "Means for saving and analyzing feedback in a database" is a function for saving evaluations and opinions provided by users in a database, analyzing them, and reflecting them in the next proposal.

[0535] The present invention is a system that provides optimized menus and cooking methods based on information entered by a user. The system aims to improve health and reduce food costs, and specific embodiments are described below.

[0536] User registration and initial settings

[0537] On the device: The user installs the application and creates an account, entering basic information such as an email address and password, as well as details such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0538] Server: The server stores the entered information in a database and generates a user profile, which is used for subsequent menu suggestions.

[0539] Data analysis and menu generation

[0540] Server: Analyzes the information entered by the user (ingredients, budget, location, preferences, and health goals) and derives evaluation data. This analysis is performed using data analysis libraries such as Python's pandas and scikit-learn. Based on the analyzed data, the optimal menu is generated by referencing the ingredient database, recipe database, budget analysis, and health database.

[0541] Example: If a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server uses this information to search a Japanese food recipe database for low-calorie recipes that fit within the user's budget and generate the optimal menu. It suggests "stir-fried chicken breast and vegetables."

[0542] Menu and cooking instructions

[0543] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[0544] On the device: The user is notified and shown detailed cooking instructions. The app UI provides step-by-step instructions and allows users to track their progress.

[0545] Measuring costs and health benefits

[0546] Server: Calculates the cost of ingredients needed for the generated menu. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. This evaluates the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0547] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[0548] User Feedback and Improvements

[0549] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[0550] User: Fill out the feedback form and click the "Submit" button.

[0551] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal. For analysis using AI models, generative AI models such as TensorFlow and PyTorch are used.

[0552] Example prompt sentence:

[0553] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[0554] This system allows users to easily enjoy healthy meals within their budget, and by incorporating user feedback, it is possible to provide more personalized menu suggestions.

[0555] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0556] Step 1: Install the app and create an account

[0557] Device: The user installs and opens the application. The account creation screen appears.

[0558] User: Enter your email address, password, and other required information and click the "Register" button.

[0559] Input: Email address, password, and other personal information.

[0560] Server: Receives the entered information and stores it in a database. It creates a user profile and sends a message to the terminal indicating successful registration.

[0561] Output: Registration successful message.

[0562] Step 2: Enter the initial configuration information

[0563] Terminal: Displays an input form for the user to enter information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0564] User: Enter the current ingredients (e.g., "chicken breast," "carrots," and "potatoes"), budget (e.g., 500 yen), location (e.g., Tokyo), preferences (e.g., Japanese food), and health goals (e.g., weight loss), then press the "Save" button.

[0565] Input: ingredients, budget, location, preferences, health goals.

[0566] Server: Receives the entered information and stores it in a database. Updates the user profile based on this information.

[0567] Output: Initial configuration information stored in the database.

[0568] Step 3: Information analysis and evaluation data derivation

[0569] Server: Analyzes the information entered by the user and creates evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Data analysis libraries such as Python's pandas and scikit-learn are used for the analysis.

[0570] Input: Initial setup information (ingredients, budget, location, preferences, health goals).

[0571] Data processing / data calculation: Analyze numerical and categorical data using Python's pandas and scikit-learn to generate evaluation data.

[0572] Output: Evaluation data.

[0573] Step 4: Menu generation

[0574] Server: Based on the analyzed data, the server generates the optimal menu by referencing the food ingredient database, recipe database, budget analysis, and health database.

[0575] Input: Evaluation data, various databases.

[0576] Data processing / data calculation: Run queries against the database to extract the recipe that best suits the evaluation data.

[0577] Example: If the user inputs "chicken breast," "carrot," "potato," budget of 500 yen, location of "Tokyo," preference of "Japanese food," and health goal of "weight loss," the system will search a Japanese food recipe database for low-calorie recipes that fit within the budget and suggest "stir-fried chicken breast and vegetables."

[0578] Output: Optimal menu.

[0579] Step 5: Present the menu and cooking instructions

[0580] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[0581] Input: The generated menu.

[0582] On the device: The user is notified and shown detailed cooking instructions. The app UI displays step-by-step instructions and allows users to track their progress.

[0583] Output: Menu and cooking instructions displayed on the terminal.

[0584] Step 6: Cost and health assessment

[0585] Server: Calculates the cost of ingredients needed for the generated meal plan. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. Evaluates the financial savings. Also analyzes the nutritional value of the meal plan to measure its contribution to the user's health goals.

[0586] Input: Generated menu and price database.

[0587] Data processing / data calculation: Based on price data, the cost of ingredients is added up and evaluated to see if it is within the user's budget. Also, based on nutritional data, the degree of achievement toward health goals is calculated.

[0588] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[0589] Output: Cost assessment and health assessment results.

[0590] Step 7: Gather user feedback

[0591] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[0592] User: Fill out the feedback form and click the "Submit" button.

[0593] Input: User feedback.

[0594] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal.

[0595] Output: Feedback data.

[0596] Example prompt sentence:

[0597] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[0598] (Application example 1)

[0599] 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."

[0600] Conventional menu suggestion systems require users to purchase ingredients and cook the meals themselves based on the suggested menu, which is time-consuming, especially for busy modern people. Furthermore, there was a lack of an efficient way to obtain ingredients and meals, so integration with delivery services was required. Therefore, a system was needed that would allow users to easily secure healthy meals within their budget.

[0601] 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.

[0602] In this invention, the server includes means for inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting food preferences, means for inputting health goals, means for generating an optimal menu based on this information, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, means for coordinating ingredients and dishes required for the optimal menu with a delivery company and presenting ordering options, and means for contacting the delivery company and delivering the ingredients and dishes after the user confirms the order. This allows the user to automatically order and receive ingredients and dishes based on the menu suggestions, ensuring healthy and efficient meals with significantly less hassle.

[0603] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[0604] "Budget information" refers to the amount of money a user can spend on ingredients and dishes.

[0605] "User location information" refers to geographical information about the location where the user resides.

[0606] "Cooking preferences" refers to the user's preferences regarding the food and cooking styles they prefer to eat.

[0607] A "health goal" is a health-related goal that a user wants to achieve, such as losing weight or improving nutritional balance.

[0608] A "means for generating an optimal menu" is a method or system for deriving appropriate dish and meal combinations based on information entered by the user.

[0609] "Means for presenting cooking methods related to the generated menu" refers to a method or system for instructing the user on specific cooking methods and procedures for the menu generated by the system.

[0610] The "means for evaluating costs within a budget" refers to a method or system for evaluating whether the ingredients and dishes required for the generated menu fit within the user's budget.

[0611] "Means for coordinating with delivery companies the ingredients and dishes required for the optimal menu and presenting ordering options" refers to a method or system that works with a delivery service to coordinate the ingredients and dishes required for the generated menu and provides the user with ordering options.

[0612] "Means for contacting a delivery company to deliver ingredients or food after a user has confirmed an order" refers to a method or system for transmitting information to a delivery service and having the food or food delivered to a specified location after a user has confirmed an order for ingredients or food.

[0613] This invention is a system that provides a menu and cooking methods optimized based on information entered by the user, and also provides a service that delivers the ingredients and dishes required for that menu. The basic system configuration, data flow, and specific operating procedures are described in detail below.

[0614] System configuration

[0615] 1. Hardware

[0616] Smartphone

[0617] Cloud server (e.g. AWS, Google Cloud)

[0618] 2. Software

[0619] Mobile app development frameworks (e.g., Flutter, React Native)

[0620] Database management systems (e.g., MySQL, MongoDB)

[0621] Data analysis libraries (e.g., Python, Pandas, TensorFlow)

[0622] Data flow and processing method

[0623] 1. User registration and initial settings

[0624] Device: The user installs the mobile app on their smartphone and creates an account. The user enters information about currently available ingredients, budget information, user location information, cooking preferences, health goals, etc.

[0625] Server: Saves the entered information in a database on the cloud and creates a user profile.

[0626] 2. Data analysis and menu generation

[0627] Server: Analyzes the information entered by the user using a data analysis module (e.g., Python, Pandas) and derives evaluation data for generating optimal menus. The generated menus include specific dish names and ingredient lists based on the information entered by the user.

[0628] Example: For example, if a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a database of Japanese food recipes and suggest the most suitable recipe.

[0629] 3. Menu and delivery method

[0630] Server: Based on the generated menu, it coordinates with delivery companies to determine the necessary ingredients and dishes, and presents ordering options to the user's device.

[0631] On device: The user is notified of the suggested meal plan and presented with detailed cooking instructions and purchasing options.

[0632] 4. Delivery arrangements and cost management

[0633] Server: After the user confirms the order, the server contacts the delivery company and arranges for the delivery of ingredients and food. At this time, the server evaluates the cost within the budget and ensures economical and efficient delivery.

[0634] Example: Once the necessary ingredients and dishes have been ordered based on the menu selected by the user, the server will request delivery from a delivery company. The user simply waits for the food to arrive while checking the progress on their smartphone.

[0635] 5. User Feedback and Improvements

[0636] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0637] Server: User feedback is stored in a database and analyzed. This feedback is reflected in the next menu suggestion, allowing for even more personalized suggestions.

[0638] Prompt Sentence Examples

[0639] The user has entered "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss." Based on this information, please generate the optimal Japanese food menu.

[0640] By implementing this invention, users can conveniently enjoy healthy meals that are within their budget, and can easily order and receive the ingredients and dishes.

[0641] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0642] Step 1:

[0643] User registration and initial settings

[0644] Input: A user installs the mobile app on their smartphone and creates an account. Input fields include email address, password, currently available ingredients, budget information, user location information, cooking preferences, and health goals.

[0645] Specific operation: When a user enters information on the terminal and presses the send button, this information is sent to the server.

[0646] Processing: The server stores the entered information in a cloud database (e.g., MySQL, MongoDB) and creates a user profile.

[0647] Output: A user profile is generated, storing data about ingredients, budget, location, preferences, and health goals.

[0648] Step 2:

[0649] Data analysis and menu generation

[0650] Input: User-entered information about ingredients, budget information, location, food preferences, and health goals.

[0651] Specific operation: The server receives this information and passes it to a data analysis module (e.g., Python, Pandas).

[0652] Processing: The server uses an analysis module to analyze the user's input information and derive evaluation data for generating optimal menus, including the availability of ingredients, budget range, local characteristics, user preferences, and health goals.

[0653] Output: A user-optimized menu is generated and the information is saved in a database.

[0654] Step 3:

[0655] Menu and delivery options

[0656] Input: Server-generated menu information.

[0657] Specific operation: The server coordinates with delivery companies to find the ingredients and dishes needed for the generated menu and presents delivery options.

[0658] Processing: The server calls the delivery company's API to retrieve discoverable delivery options, which provides the best delivery company and pricing information based on the user's location. This information is then sent to the user's device.

[0659] Output: The user device displays the suggested meal plan, cooking instructions, and delivery options.

[0660] Step 4:

[0661] Delivery arrangements and cost management

[0662] Input: The delivery option selected and confirmed by the user.

[0663] What happens: A user uses a smartphone app to select a delivery option and place an order.

[0664] Processing: After the user confirms the order of ingredients and dishes necessary for the optimal menu, the server contacts the delivery company to arrange delivery. At this time, the server evaluates whether the delivery cost is within the user's budget and notifies the user.

[0665] Output: The delivery company delivers the ingredients and food to the user's location.

[0666] Step 5:

[0667] User Feedback and Improvements

[0668] Input: Feedback information such as the taste of the food the user experienced, cooking procedures, and satisfaction level.

[0669] What happens: The user creates a dish and provides feedback through the app.

[0670] Processing: The server stores the received feedback in a database and analyzes the data to reflect it in the next menu suggestion. The feedback analysis will be used to improve the analysis module in the future.

[0671] Output: The user's feedback will be reflected in the next menu suggestion, making it more suitable for the user.

[0672] 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.

[0673] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0674] User registration and initial settings

[0675] Device: The user installs the application and creates an account. The user enters their email address and password and receives a confirmation email. The user also enters their currently available ingredients, budget, location, cooking preferences, and health goals.

[0676] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[0677] Data analysis and menu generation

[0678] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[0679] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0680] Menu and cooking instructions

[0681] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[0682] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0683] Measuring costs and health benefits

[0684] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0685] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0686] User Feedback and Improvements

[0687] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0688] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[0689] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0690] Emotion recognition and menu adjustment

[0691] Device: When a user uses an application, the emotion engine is activated. The emotion engine analyzes the user's facial expressions and speech to recognize their current emotional state.

[0692] Server: Receives information from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the server will suggest dishes using ingredients that have a relaxing effect.

[0693] Example: If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Providing menus that take emotions into account in this way makes it possible to make more personalized suggestions.

[0694] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals within their budget, and also provides menu suggestions that match their mood and emotions at the time.

[0695] The processing flow will be explained below.

[0696] Step 1:

[0697] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[0698] Step 2:

[0699] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[0700] Step 3:

[0701] An emotion engine is activated on the device and analyzes the user's facial expressions and speech to recognize their current emotional state. For example, the user inputs their emotions using a camera or microphone, and the emotion engine analyzes the data.

[0702] Step 4:

[0703] The server analyzes the user's input information and emotional data. It derives evaluation data based on each variable (ingredients, budget, location, preferences, health goals, and emotions). The server then prepares to generate the optimal menu based on the user information.

[0704] Step 5:

[0705] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[0706] Step 6:

[0707] The server generates optimal menus, selecting nutritionally balanced recipes and creating optimal menus based on the user's health goals and emotions, and generating menus that include specific recipes, ingredient lists, and cooking instructions.

[0708] Step 7:

[0709] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[0710] Step 8:

[0711] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[0712] Step 9:

[0713] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[0714] Step 10:

[0715] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[0716] Step 11:

[0717] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[0718] Step 12:

[0719] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[0720] Step 13:

[0721] The emotion engine continuously monitors the user's emotions and evaluates their emotional response to suggested menus and cooking methods. For example, if the user smiles at a particular dish, it will determine that the dish was well-received and reflect this in future suggestions.

[0722] These are the specific processing steps of the system that combines the emotion engine. This allows users to easily enjoy healthy meals within their budget, and receives menu suggestions that match their mood and emotions at the time.

[0723] Example 2

[0724] 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."

[0725] In modern society, busy lifestyles make it difficult to easily prepare healthy meals. In particular, there is a need for planning balanced menus within a budget and for recipe suggestions tailored to the user's health goals and emotions. However, existing systems have difficulty adequately addressing individual user needs. Therefore, a system is needed that provides appropriate menus and cooking methods based on the user's input information and emotional state, helping them save money on food and improve their health.

[0726] 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.

[0727] In this invention, the server includes a means for the user to input currently available ingredients, budget, location, cooking preferences, and health goals as initial settings, a means for saving and analyzing the information and creating a user profile based on the above information, a means for generating an optimal menu based on the input information using a generative AI model, a means for transmitting and presenting the generated menu and cooking methods to the user's terminal, and a means for evaluating costs and nutritional values ​​within the budget and measuring health benefits. This allows users to not only easily enjoy healthy meals within their budget, but also to receive personalized menu suggestions tailored to their moods and emotions at the time.

[0728] "User input as initial settings" means that after the user installs the application, they input personal information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0729] A "generative AI model" is an artificial intelligence model that generates optimal menus based on input information.

[0730] A "user profile" is a collection of data that stores individual information entered by a user and is used to perform various analyses and make suggestions based on that information.

[0731] A "menu" is a specific combination of dishes and a list of ingredients for a user to cook.

[0732] "Cooking method" refers to the steps and methods for preparing a dish based on the generated menu.

[0733] "Cost evaluation" involves calculating the prices of ingredients required for the generated menu and evaluating whether they are within the budget set by the user.

[0734] "Nutritional value" is an evaluation of the amount of nutrients contained in the generated menu, measuring its contribution to the user's health goals.

[0735] "Health Benefit" refers to an assessment of how much the generated menu contributes to the user's health goals.

[0736] "Feedback" refers to the user providing their thoughts and opinions about the suggested menu and cooking methods.

[0737] The "emotional state" refers to the user's current psychological state, which can be obtained by analyzing the user's facial expressions, speech content, and the like.

[0738] "Adjusting menu suggestions based on emotions" refers to changing or adjusting the menu suggestions depending on the user's emotional state.

[0739] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0740] User registration and initial settings

[0741] Device:

[0742] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and initially enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[0743] server:

[0744] The system stores the user's registration information sent from the device in a database and creates a user profile based on that information, which includes a wide range of information such as ingredients, budget, location, cooking preferences, and health goals.

[0745] Data analysis and menu generation

[0746] server:

[0747] The information entered by the user is analyzed and rating data is generated based on each variable (ingredients, budget, location, preferences, and health goals). The rating data is then analyzed using a generative AI model, which then references the ingredient database, recipe database, budget analysis, and health database to generate the optimal menu.

[0748] Examples:

[0749] If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the server will search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0750] Menu and cooking instructions

[0751] server:

[0752] The generated menu is sent to the user's device, and includes the specific dish names and ingredient lists.

[0753] Device:

[0754] The user is notified of the generated menu suggestion and is shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0755] Measuring costs and health benefits

[0756] server:

[0757] The system calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user, evaluates whether it is within budget and measures the financial savings, and evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0758] Examples:

[0759] For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0760] User Feedback and Improvements

[0761] Device:

[0762] Users prepare the proposed meal and then provide feedback, including the taste of the dish, the ease of the process, and their satisfaction level.

[0763] server:

[0764] User feedback is stored in a database and analyzed, and the feedback is reflected in the next menu suggestions, allowing for menus that better suit the user's preferences and requests.

[0765] Examples:

[0766] For example, if the user's feedback is "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0767] Emotion recognition and menu adjustment

[0768] Device:

[0769] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[0770] server:

[0771] The system receives emotional information sent from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the system will suggest dishes using ingredients that have a relaxing effect.

[0772] Examples:

[0773] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[0774] Prompt Sentence Examples

[0775] Examples of prompts that allow users to easily input instructions to the system include the following:

[0776] "A user is looking for a Japanese meal using chicken breast, carrots, and potatoes, costing less than 500 yen, and aimed at weight loss. Please suggest the best menu."

[0777] This prompt makes it easier for the generative AI model to make specific cooking suggestions.

[0778] In this way, the system allows users to easily enjoy healthy meals within their budget, and also provides personalized menu suggestions that match their mood and emotions at the time.

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

[0780] Step 1:

[0781] User registration and initial settings

[0782] User:

[0783] A user installs the application and creates an account. They enter an email address and password. After entering this information, they receive a confirmation email containing a link to activate their account. They then enter initial information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0784] Device:

[0785] All information entered by the user is sent to the server.

[0786] server:

[0787] The information entered is saved in a database. A user profile is created based on the saved information. The profile contains all of the information entered.

[0788] Input: User email address, password, currently available ingredients, budget, location, cooking preferences, health goals

[0789] Output: User profile stored in the database

[0790] Step 2:

[0791] Data analysis and menu generation

[0792] server:

[0793] Data analysis is performed based on the saved user profile. The information analyzed includes ingredients, budget, location, cooking preferences, and health goals. Evaluation data is generated based on this information. Next, an optimal menu is generated using a generative AI model. Recipes that meet the given criteria are selected by referencing the ingredient database, recipe database, budget analysis, and health database.

[0794] Examples:

[0795] Based on information such as "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the system searches for low-calorie recipes from a Japanese food recipe database and generates the optimal menu.

[0796] Input: User profile, ingredient database, recipe database, budget analysis data, health database

[0797] Output: Optimal menu data

[0798] Step 3:

[0799] Menu and cooking instructions

[0800] server:

[0801] The generated menu data is sent to the user's device. The menu data includes specific dish names and ingredient lists.

[0802] Device:

[0803] The user is notified of meal suggestions and shown detailed cooking instructions, including cooking times, necessary tools, and specific instructions for each step.

[0804] Input: Menu data

[0805] Output: Notification to user device, detailed cooking instructions

[0806] Step 4:

[0807] Measuring costs and health benefits

[0808] server:

[0809] It calculates the cost of ingredients needed for the generated meal plan, compares the calculation results with the budget information entered by the user to assess whether it is within budget, and measures the financial savings. It also evaluates the nutritional value of the meal plan to measure its contribution to the user's health goals.

[0810] Examples:

[0811] If the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of the ingredients is 450 yen, it will be evaluated as being economical because it is within the budget of 500 yen. Also, because it is low in calories and high in protein, it will be evaluated as contributing to the health goal of weight loss.

[0812] Input: Menu data, budget information, nutritional data

[0813] Output: Cost assessment results, health effect assessment results

[0814] Step 5:

[0815] User Feedback and Improvements

[0816] Device:

[0817] Users create the suggested meals and then provide feedback, including the taste of the food, the ease of the process, and satisfaction.

[0818] server:

[0819] The feedback received from users is stored in a database and analyzed, and the analysis results are reflected in the next menu proposal.

[0820] Examples:

[0821] If the user gives feedback such as "The food was delicious, but I would prefer a simpler recipe," the next time the system will prioritize suggestions that are simpler and have fewer cooking steps.

[0822] Input: User feedback

[0823] Output: Feedback analysis results, improved menu suggestions

[0824] Step 6:

[0825] Emotion recognition and menu adjustment

[0826] Device:

[0827] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[0828] server:

[0829] The system receives the emotional information sent by the emotion engine and adjusts the menu suggestions based on the user's emotions. For example, if the user is feeling stressed, it will suggest dishes using ingredients that have a relaxing effect.

[0830] Examples:

[0831] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[0832] Input: Emotion information

[0833] Output: Emotion-based menu suggestions

[0834] (Application example 2)

[0835] 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."

[0836] While many support systems exist today to help users prepare healthy and economical meals at home, these systems rarely take into account the user's emotions or momentary moods when making suggestions. Systems that can suggest suitable dishes, especially when users are stressed or tired, are lacking. Furthermore, there is a lack of integration with food delivery services that allow users to easily order the suggested meals. Therefore, there is a need for a system that can suggest meals that meet the user's health goals and budget while taking into account the user's emotions, and that can instantly order the meals.

[0837] The specification processing by the specification 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 inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting cooking preferences, means for inputting health goals, means for recognizing the user's emotions, means for generating an optimal menu based on the above information and the user's emotions, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, and means for food delivery that allows the user to order the generated menu and cooking method. This allows the user to receive suggestions for an appropriate menu that matches their emotions and mood at the time, and to easily order meals that meet their health goals and budget.

[0838] "Currently available ingredients" refers to food ingredients that the user owns or plans to procure.

[0839] "Budget information" refers to data indicating the range of amounts that the user can spend on food, as set by the user.

[0840] "User location information" refers to information indicating the area where the user resides or stays.

[0841] "Cuisine preferences" refers to data indicating the types of cuisine a user likes and their preferences for specific ingredients.

[0842] "Health goals" refers to information indicating the health status or nutritional balance that a user wants to achieve, such as weight loss or high protein intake.

[0843] "Means for recognizing the user's emotions" refers to technology that analyzes and recognizes the user's current emotional state from their facial expressions and speech content.

[0844] "Means for generating optimal menus" refers to a system that suggests the most suitable combination of dishes based on the user's input information and emotional data.

[0845] "Means for presenting cooking methods" refers to a mechanism that provides users with cooking procedures and how to use ingredients for the generated menu.

[0846] "Means for cost evaluation" refers to a system that calculates the cost of ingredients required for a proposed menu and evaluates whether it is within budget.

[0847] "Food delivery means" refers to a service that orders food based on the generated menu and delivers it to the user.

[0848] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system works in conjunction with food delivery services to provide menus that take into account the user's health goals and budget.

[0849] System configuration

[0850] The system mainly consists of the following components:

[0851] 1. User device: User information is input on a smartphone or tablet, and emotional state is recognized.

[0852] 2. Server: Generates menus, recognizes emotions, evaluates costs, and manages food delivery.

[0853] 3. Database: Includes food database, recipe database, health database, and budget database.

[0854] User registration and initial settings

[0855] The user installs the application and creates an account. The user enters the following information:

[0856] Currently available ingredients

[0857] Budget Information

[0858] User Location

[0859] Food preferences

[0860] health goals

[0861] This information is sent to a server and stored in a database.

[0862] Emotion Recognition and Data Analysis

[0863] The device uses an emotion recognition engine to analyze the user's facial expressions and voice to recognize their emotional state. This emotional data is sent to the server and stored in a database. The server then analyzes the user's input information and emotional state to generate an optimal menu. The following technologies are used for the analysis:

[0864] EmotionEngine: Software for recognizing user emotions.

[0865] RecipeRecommender: A system that suggests optimal menus based on user input and emotions.

[0866] Menu generation and presentation

[0867] The server generates an optimal menu based on the user's information and emotional data and sends it to the device. The device receives it and presents the menu and cooking instructions to the user. The cooking instructions include specific steps, cooking time, and necessary tools.

[0868] Cost assessment and health benefit measurement

[0869] The server calculates the cost of ingredients in the generated menu and compares it with the user's set budget. If the menu is within the budget, it presents the menu to the user. It also evaluates the health benefits of the generated menu based on its nutritional value and calculates its contribution to the user's health goals.

[0870] Food delivery service

[0871] If the user likes the suggested menu and places an order, the server will arrange for the food to be delivered to the user's location via a food delivery service, allowing the user to easily enjoy healthy meals on a budget.

[0872] User feedback and system improvements

[0873] Users provide feedback on the food they are served, including taste, ease of cooking, and satisfaction. This feedback is sent to the server and reflected in the next recommendation. This allows the system to continually improve to suit the user's preferences.

[0874] Specific examples

[0875] For example, if the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that the budget is met.

[0876] Prompt Sentence Examples

[0877] text

[0878] The user is stressed. Can you suggest some Japanese-style chicken and carrot recipes that are good for weight loss and have a budget of 1000 yen?

[0879] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0880] Step 1:

[0881] A user installs an application using a terminal and creates an account. The user enters an email address and password and receives a confirmation email for creating the account. This sends the user's basic information to the server and completes the initial setup. The input data is an email address and password, and the output is that the account has been created.

[0882] Step 2:

[0883] The user uses a terminal to input currently available ingredients, budget information, location information, cooking preferences, and health goals. The server retrieves the input information and stores it in a database. The input data is ingredients, budget, location, preferences, and health goals, and the output is an updated user profile. The server references the database to analyze this information.

[0884] Step 3:

[0885] The user uses the device to activate the emotion recognition engine. The device analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., stress, fatigue, joy). The recognized emotion data is sent to the server and stored in a database. The input data is the user's facial expressions and voice, and the output is the recognized emotion data. The EmotionEngine processes this and analyzes the emotion.

[0886] Step 4:

[0887] The server analyzes the user's input information and emotional data to generate an optimal menu. The analysis refers to the ingredient database, recipe database, budget database, and health database. Specifically, a RecipeRecommender is used to select recipes that meet the user's criteria based on ingredients, budget, preferences, health goals, and emotions. The input data are the user profile and emotional data, and the output is the generated menu.

[0888] Step 5:

[0889] The server sends the generated menu to the user's device. The device receives the menu and notifies the user. The menu includes specific dish names, ingredient lists, and cooking instructions. The input data is the generated menu, and the output is the menu and cooking instructions displayed to the user.

[0890] Step 6:

[0891] The user reviews the proposed menu and, if they wish to have food delivered, places an order from their device. The server accepts the order and sends a request to the appropriate food delivery service. The input data is the user's order, and the output is a request to the food delivery service, which then delivers the food to the user's location.

[0892] Step 7:

[0893] After receiving and eating the food, the user provides feedback using a terminal. The feedback includes the taste of the food, the ease of the process, and satisfaction level, and is sent to the server. The server stores the feedback in a database and reflects it in the next menu suggestion. The input data is the user's feedback, and the output is updated analysis data. This allows the system to be continuously improved.

[0894] Examples:

[0895] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that they are within the budget.

[0896] 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.

[0897] 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.

[0898] 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.

[0899] [Third embodiment]

[0900] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0901] 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.

[0902] 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).

[0903] 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.

[0904] 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.

[0905] 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).

[0906] 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. 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.

[0907] 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.

[0908] 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.

[0909] 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.

[0910] 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.

[0911] 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."

[0912] The present invention is a system that provides optimized menus and cooking methods based on information input by a user. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[0913] User registration and initial settings

[0914] Device: The user installs the application and creates an account. When creating an account, they enter required information such as an email address and password. In addition, the user enters information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0915] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[0916] Data analysis and menu generation

[0917] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[0918] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[0919] Menu and cooking instructions

[0920] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[0921] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[0922] Measuring costs and health benefits

[0923] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0924] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[0925] User Feedback and Improvements

[0926] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[0927] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[0928] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[0929] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals that are within their budget.

[0930] The processing flow will be explained below.

[0931] Step 1:

[0932] A user installs the application and creates an account. The user enters an email address and password and receives a confirmation email.

[0933] Step 2:

[0934] The user inputs initial information into the device, including currently available ingredients, budget, location, cooking preferences, and health goals. This information is entered in detail.

[0935] Step 3:

[0936] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[0937] Step 4:

[0938] The server analyzes the user's input information and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). The server then prepares to generate the optimal menu based on the user information.

[0939] Step 5:

[0940] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[0941] Step 6:

[0942] The server generates optimal menus, selecting nutritionally balanced recipes based on the user's health goals, and creating optimal menus that include specific recipes, ingredient lists, and cooking instructions.

[0943] Step 7:

[0944] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[0945] Step 8:

[0946] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[0947] Step 9:

[0948] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[0949] Step 10:

[0950] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[0951] Step 11:

[0952] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[0953] Step 12:

[0954] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[0955] The above are the specific processing steps of the system.

[0956] Example 1

[0957] 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."

[0958] In today's busy world, consumers need easy ways to prepare healthy and economical meals. However, coming up with optimal menus with limited ingredients and a limited budget is a challenge for many people. Furthermore, there are few systems that suggest menus that meet individual health goals and culinary preferences. Therefore, a user-friendly menu suggestion system is needed.

[0959] 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.

[0960] In this invention, the server includes a means for inputting currently available ingredients, a means for inputting budget information, a means for inputting user location information, a means for inputting cooking preferences, a means for inputting health goals, a means for analyzing the above information and deriving evaluation data based on variables, a means for generating an optimal menu by referencing a database based on the evaluation data, a means for presenting cooking methods related to the generated menu, a means for evaluating costs within the budget, a means for storing and analyzing user feedback in a database, and a means for reflecting the feedback in the next menu proposal. This allows users to easily obtain optimal menus and cooking methods tailored to their individual requirements. Furthermore, the generated menu can be evaluated to see whether it is within budget and how much it contributes to health goals, allowing users to easily achieve an economical and healthy diet. Furthermore, by reflecting user feedback in the next proposal, more personalized menu proposals are possible.

[0961] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[0962] "Budget information" is data indicating the upper limit of the cost that a user is willing to spend on a single meal.

[0963] "User location information" is information about the user's residential area or current location, and is a factor that affects the ingredients and cooking methods available depending on the area.

[0964] "Cooking preferences" is information that indicates the genres, styles, and seasonings of cooking that the user particularly likes.

[0965] "Health goals" are health conditions and weight management goals that a user aims for, and include dieting and improving nutritional balance.

[0966] "Means for deriving evaluation data" refers to a function that analyzes various information entered by the user and calculates specific evaluation values ​​and indicators.

[0967] The "means for generating the optimal menu by referring to the database" is a function that selects the optimal menu from a database of saved recipes and ingredient information based on the analyzed evaluation data.

[0968] The "means for presenting cooking methods" is a function that provides the user with detailed information such as the steps to prepare the dish, the necessary tools, and cooking time based on the generated menu.

[0969] The "means for performing cost evaluation" is a function that calculates the cost of ingredients required for the generated menu and compares this with the user's budget to perform an economic evaluation.

[0970] "Means for saving and analyzing feedback in a database" is a function for saving evaluations and opinions provided by users in a database, analyzing them, and reflecting them in the next proposal.

[0971] The present invention is a system that provides optimized menus and cooking methods based on information entered by a user. The system aims to improve health and reduce food costs, and specific embodiments are described below.

[0972] User registration and initial settings

[0973] On the device: The user installs the application and creates an account, entering basic information such as an email address and password, as well as details such as currently available ingredients, budget, location, cooking preferences, and health goals.

[0974] Server: The server stores the entered information in a database and generates a user profile, which is used for subsequent menu suggestions.

[0975] Data analysis and menu generation

[0976] Server: Analyzes the information entered by the user (ingredients, budget, location, preferences, and health goals) and derives evaluation data. This analysis is performed using data analysis libraries such as Python's pandas and scikit-learn. Based on the analyzed data, the optimal menu is generated by referencing the ingredient database, recipe database, budget analysis, and health database.

[0977] Example: If a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server uses this information to search a Japanese food recipe database for low-calorie recipes that fit within the user's budget and generate the optimal menu. It suggests "stir-fried chicken breast and vegetables."

[0978] Menu and cooking instructions

[0979] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[0980] On the device: The user is notified and shown detailed cooking instructions. The app UI provides step-by-step instructions and allows users to track their progress.

[0981] Measuring costs and health benefits

[0982] Server: Calculates the cost of ingredients needed for the generated menu. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. This evaluates the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[0983] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[0984] User Feedback and Improvements

[0985] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[0986] User: Fill out the feedback form and click the "Submit" button.

[0987] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal. For analysis using AI models, generative AI models such as TensorFlow and PyTorch are used.

[0988] Example prompt sentence:

[0989] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[0990] This system allows users to easily enjoy healthy meals within their budget, and by incorporating user feedback, it is possible to provide more personalized menu suggestions.

[0991] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0992] Step 1: Install the app and create an account

[0993] Device: The user installs and opens the application. The account creation screen appears.

[0994] User: Enter your email address, password, and other required information and click the "Register" button.

[0995] Input: Email address, password, and other personal information.

[0996] Server: Receives the entered information and stores it in a database. It creates a user profile and sends a message to the terminal indicating successful registration.

[0997] Output: Registration successful message.

[0998] Step 2: Enter the initial configuration information

[0999] Terminal: Displays an input form for the user to enter information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1000] User: Enter the current ingredients (e.g., "chicken breast," "carrots," and "potatoes"), budget (e.g., 500 yen), location (e.g., Tokyo), preferences (e.g., Japanese food), and health goals (e.g., weight loss), then press the "Save" button.

[1001] Input: ingredients, budget, location, preferences, health goals.

[1002] Server: Receives the entered information and stores it in a database. Updates the user profile based on this information.

[1003] Output: Initial configuration information stored in the database.

[1004] Step 3: Information analysis and evaluation data derivation

[1005] Server: Analyzes the information entered by the user and creates evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Data analysis libraries such as Python's pandas and scikit-learn are used for the analysis.

[1006] Input: Initial setup information (ingredients, budget, location, preferences, health goals).

[1007] Data processing / data calculation: Analyze numerical and categorical data using Python's pandas and scikit-learn to generate evaluation data.

[1008] Output: Evaluation data.

[1009] Step 4: Menu generation

[1010] Server: Based on the analyzed data, the server generates the optimal menu by referencing the food ingredient database, recipe database, budget analysis, and health database.

[1011] Input: Evaluation data, various databases.

[1012] Data processing / data calculation: Run queries against the database to extract the recipe that best suits the evaluation data.

[1013] Example: If the user inputs "chicken breast," "carrot," "potato," budget of 500 yen, location of "Tokyo," preference of "Japanese food," and health goal of "weight loss," the system will search a Japanese food recipe database for low-calorie recipes that fit within the budget and suggest "stir-fried chicken breast and vegetables."

[1014] Output: Optimal menu.

[1015] Step 5: Present the menu and cooking instructions

[1016] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[1017] Input: The generated menu.

[1018] On the device: The user is notified and shown detailed cooking instructions. The app UI displays step-by-step instructions and allows users to track their progress.

[1019] Output: Menu and cooking instructions displayed on the terminal.

[1020] Step 6: Cost and health assessment

[1021] Server: Calculates the cost of ingredients needed for the generated meal plan. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. Evaluates the financial savings. Also analyzes the nutritional value of the meal plan to measure its contribution to the user's health goals.

[1022] Input: Generated menu and price database.

[1023] Data processing / data calculation: Based on price data, the cost of ingredients is added up and evaluated to see if it is within the user's budget. Also, based on nutritional data, the degree of achievement toward health goals is calculated.

[1024] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[1025] Output: Cost assessment and health assessment results.

[1026] Step 7: Gather user feedback

[1027] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[1028] User: Fill out the feedback form and click the "Submit" button.

[1029] Input: User feedback.

[1030] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal.

[1031] Output: Feedback data.

[1032] Example prompt sentence:

[1033] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[1034] (Application example 1)

[1035] 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."

[1036] Conventional menu suggestion systems require users to purchase ingredients and cook the meals themselves based on the suggested menu, which can be time-consuming, especially for busy modern people. Furthermore, there was a lack of an efficient way to obtain ingredients and meals, so integration with delivery services was required. Therefore, a system was needed that would allow users to easily secure healthy meals within their budget.

[1037] 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.

[1038] In this invention, the server includes means for inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting food preferences, means for inputting health goals, means for generating an optimal menu based on this information, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, means for coordinating ingredients and dishes required for the optimal menu with a delivery company and presenting ordering options, and means for contacting the delivery company and delivering the ingredients and dishes after the user confirms the order. This allows the user to automatically order and receive ingredients and dishes based on the menu suggestions, ensuring healthy and efficient meals with significantly less hassle.

[1039] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[1040] "Budget information" refers to the amount of money a user can spend on ingredients and dishes.

[1041] "User location information" refers to geographical information about the location where the user resides.

[1042] "Cooking preferences" refers to the user's preferences regarding the food and cooking styles they prefer to eat.

[1043] A "health goal" is a health-related goal that a user wants to achieve, such as losing weight or improving nutritional balance.

[1044] A "means for generating an optimal menu" is a method or system for deriving appropriate dish and meal combinations based on information entered by the user.

[1045] "Means for presenting cooking methods related to the generated menu" refers to a method or system for instructing the user on specific cooking methods and procedures for the menu generated by the system.

[1046] The "means for evaluating costs within a budget" refers to a method or system for evaluating whether the ingredients and dishes required for the generated menu fit within the user's budget.

[1047] "Means for coordinating with delivery companies the ingredients and dishes required for the optimal menu and presenting ordering options" refers to a method or system that works with a delivery service to coordinate the ingredients and dishes required for the generated menu and provides the user with ordering options.

[1048] "Means for contacting a delivery company to deliver ingredients or food after a user has confirmed an order" refers to a method or system for transmitting information to a delivery service and having the food or food delivered to a specified location after a user has confirmed an order for ingredients or food.

[1049] This invention is a system that provides a menu and cooking methods optimized based on information entered by the user, and also provides a service that delivers the ingredients and dishes required for that menu. The basic system configuration, data flow, and specific operating procedures are described in detail below.

[1050] System configuration

[1051] 1. Hardware

[1052] Smartphone

[1053] Cloud server (e.g. AWS, Google Cloud)

[1054] 2. Software

[1055] Mobile app development frameworks (e.g., Flutter, React Native)

[1056] Database management systems (e.g., MySQL, MongoDB)

[1057] Data analysis libraries (e.g., Python, Pandas, TensorFlow)

[1058] Data flow and processing method

[1059] 1. User registration and initial settings

[1060] Device: The user installs the mobile app on their smartphone and creates an account. The user enters information about currently available ingredients, budget information, user location information, cooking preferences, health goals, etc.

[1061] Server: Saves the entered information in a database on the cloud and creates a user profile.

[1062] 2. Data analysis and menu generation

[1063] Server: Analyzes the information entered by the user using a data analysis module (e.g., Python, Pandas) and derives evaluation data for generating optimal menus. The generated menus include specific dish names and ingredient lists based on the information entered by the user.

[1064] Example: For example, if a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a database of Japanese food recipes and suggest the most suitable recipe.

[1065] 3. Menu and delivery method

[1066] Server: Based on the generated menu, it coordinates with delivery companies to determine the necessary ingredients and dishes, and presents ordering options to the user's device.

[1067] On device: The user is notified of the suggested meal plan and presented with detailed cooking instructions and purchasing options.

[1068] 4. Delivery arrangements and cost management

[1069] Server: After the user confirms the order, the server contacts the delivery company and arranges for the delivery of ingredients and food. At this time, the server evaluates the cost within the budget and ensures economical and efficient delivery.

[1070] Example: Once the necessary ingredients and dishes have been ordered based on the menu selected by the user, the server will request delivery from a delivery company. The user simply waits for the food to arrive while checking the progress on their smartphone.

[1071] 5. User Feedback and Improvements

[1072] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[1073] Server: User feedback is stored in a database and analyzed. This feedback is reflected in the next menu suggestion, allowing for even more personalized suggestions.

[1074] Prompt Sentence Examples

[1075] The user has entered "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss." Based on this information, please generate the optimal Japanese food menu.

[1076] By implementing this invention, users can conveniently enjoy healthy meals that are within their budget, and can easily order and receive the ingredients and dishes.

[1077] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1078] Step 1:

[1079] User registration and initial settings

[1080] Input: A user installs the mobile app on their smartphone and creates an account. Input fields include email address, password, currently available ingredients, budget information, user location information, cooking preferences, and health goals.

[1081] Specific operation: When a user enters information on the terminal and presses the send button, this information is sent to the server.

[1082] Processing: The server stores the entered information in a cloud database (e.g., MySQL, MongoDB) and creates a user profile.

[1083] Output: A user profile is generated, storing data about ingredients, budget, location, preferences, and health goals.

[1084] Step 2:

[1085] Data analysis and menu generation

[1086] Input: User-entered information about ingredients, budget information, location, food preferences, and health goals.

[1087] Specific operation: The server receives this information and passes it to a data analysis module (e.g., Python, Pandas).

[1088] Processing: The server uses an analysis module to analyze the user's input information and derive evaluation data for generating optimal menus, including the availability of ingredients, budget range, local characteristics, user preferences, and health goals.

[1089] Output: A user-optimized menu is generated and the information is saved in a database.

[1090] Step 3:

[1091] Menu and delivery options

[1092] Input: Server-generated menu information.

[1093] Specific operation: The server coordinates with delivery companies to find the ingredients and dishes needed for the generated menu and presents delivery options.

[1094] Processing: The server calls the delivery company's API to retrieve discoverable delivery options, which provides the best delivery company and pricing information based on the user's location. This information is then sent to the user's device.

[1095] Output: The user device displays the suggested meal plan, cooking instructions, and delivery options.

[1096] Step 4:

[1097] Delivery arrangements and cost management

[1098] Input: The delivery option selected and confirmed by the user.

[1099] What happens: A user uses a smartphone app to select a delivery option and place an order.

[1100] Processing: After the user confirms the order of ingredients and dishes necessary for the optimal menu, the server contacts the delivery company to arrange delivery. At this time, the server evaluates whether the delivery cost is within the user's budget and notifies the user.

[1101] Output: The delivery company delivers the ingredients and food to the user's location.

[1102] Step 5:

[1103] User Feedback and Improvements

[1104] Input: Feedback information such as the taste of the food the user experienced, cooking procedures, and satisfaction level.

[1105] What happens: The user creates a dish and provides feedback through the app.

[1106] Processing: The server stores the received feedback in a database and analyzes the data to reflect it in the next menu suggestion. The feedback analysis will be used to improve the analysis module in the future.

[1107] Output: The user's feedback will be reflected in the next menu suggestion, making it more suitable for the user.

[1108] 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.

[1109] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[1110] User registration and initial settings

[1111] Device: The user installs the application and creates an account. The user enters their email address and password and receives a confirmation email. The user also enters their currently available ingredients, budget, location, cooking preferences, and health goals.

[1112] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[1113] Data analysis and menu generation

[1114] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[1115] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[1116] Menu and cooking instructions

[1117] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[1118] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[1119] Measuring costs and health benefits

[1120] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1121] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[1122] User Feedback and Improvements

[1123] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[1124] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[1125] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[1126] Emotion recognition and menu adjustment

[1127] Device: When a user uses an application, the emotion engine is activated. The emotion engine analyzes the user's facial expressions and speech to recognize their current emotional state.

[1128] Server: Receives information from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the server will suggest dishes using ingredients that have a relaxing effect.

[1129] Example: If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Providing menus that take emotions into account in this way makes it possible to make more personalized suggestions.

[1130] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals within their budget, and also provides menu suggestions that match their mood and emotions at the time.

[1131] The processing flow will be explained below.

[1132] Step 1:

[1133] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[1134] Step 2:

[1135] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[1136] Step 3:

[1137] An emotion engine is activated on the device and analyzes the user's facial expressions and speech to recognize their current emotional state. For example, the user inputs their emotions using a camera or microphone, and the emotion engine analyzes the data.

[1138] Step 4:

[1139] The server analyzes the user's input information and emotional data. It derives evaluation data based on each variable (ingredients, budget, location, preferences, health goals, and emotions). The server then prepares to generate the optimal menu based on the user information.

[1140] Step 5:

[1141] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[1142] Step 6:

[1143] The server generates optimal menus, selecting nutritionally balanced recipes and creating optimal menus based on the user's health goals and emotions, and generating menus that include specific recipes, ingredient lists, and cooking instructions.

[1144] Step 7:

[1145] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[1146] Step 8:

[1147] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[1148] Step 9:

[1149] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[1150] Step 10:

[1151] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[1152] Step 11:

[1153] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[1154] Step 12:

[1155] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[1156] Step 13:

[1157] The emotion engine continuously monitors the user's emotions and evaluates their emotional response to suggested menus and cooking methods. For example, if the user smiles at a particular dish, it will determine that the dish was well-received and reflect this in future suggestions.

[1158] These are the specific processing steps of the system that combines the emotion engine. This allows users to easily enjoy healthy meals within their budget, and receives menu suggestions that match their mood and emotions at the time.

[1159] Example 2

[1160] 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."

[1161] In modern society, busy lifestyles make it difficult to easily prepare healthy meals. In particular, there is a need for planning balanced menus within a budget and for recipe suggestions tailored to the user's health goals and emotions. However, existing systems have difficulty adequately addressing individual user needs. Therefore, a system is needed that provides appropriate menus and cooking methods based on the user's input information and emotional state, helping them save money on food and improve their health.

[1162] 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.

[1163] In this invention, the server includes a means for the user to input currently available ingredients, budget, location, cooking preferences, and health goals as initial settings, a means for saving and analyzing the information and creating a user profile based on the above information, a means for generating an optimal menu based on the input information using a generative AI model, a means for transmitting and presenting the generated menu and cooking methods to the user's terminal, and a means for evaluating costs and nutritional values ​​within the budget and measuring health benefits. This allows users to not only easily enjoy healthy meals within their budget, but also to receive personalized menu suggestions tailored to their moods and emotions at the time.

[1164] "User input as initial settings" means that after the user installs the application, they input personal information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1165] A "generative AI model" is an artificial intelligence model that generates optimal menus based on input information.

[1166] A "user profile" is a collection of data that stores individual information entered by a user and is used to perform various analyses and make suggestions based on that information.

[1167] A "menu" is a specific combination of dishes and a list of ingredients for a user to cook.

[1168] "Cooking method" refers to the steps and methods for preparing a dish based on the generated menu.

[1169] "Cost evaluation" involves calculating the prices of ingredients required for the generated menu and evaluating whether they are within the budget set by the user.

[1170] "Nutritional value" is an evaluation of the amount of nutrients contained in the generated menu, measuring its contribution to the user's health goals.

[1171] "Health Benefit" refers to an assessment of how much the generated menu contributes to the user's health goals.

[1172] "Feedback" refers to the user providing their thoughts and opinions about the suggested menu and cooking methods.

[1173] The "emotional state" refers to the user's current psychological state, which can be obtained by analyzing the user's facial expressions, speech content, and the like.

[1174] "Adjusting menu suggestions based on emotions" refers to changing or adjusting the menu suggestions depending on the user's emotional state.

[1175] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[1176] User registration and initial settings

[1177] Device:

[1178] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and initially enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[1179] server:

[1180] The system stores the user's registration information sent from the device in a database and creates a user profile based on that information, which includes a wide range of information such as ingredients, budget, location, cooking preferences, and health goals.

[1181] Data analysis and menu generation

[1182] server:

[1183] The information entered by the user is analyzed and rating data is generated based on each variable (ingredients, budget, location, preferences, and health goals). The rating data is then analyzed using a generative AI model, which then references the ingredient database, recipe database, budget analysis, and health database to generate the optimal menu.

[1184] Examples:

[1185] If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the server will search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[1186] Menu and cooking instructions

[1187] server:

[1188] The generated menu is sent to the user's device, and includes the specific dish names and ingredient lists.

[1189] Device:

[1190] The user is notified of the generated menu suggestion and is shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[1191] Measuring costs and health benefits

[1192] server:

[1193] The system calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user, evaluates whether it is within budget and measures the financial savings, and evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1194] Examples:

[1195] For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[1196] User Feedback and Improvements

[1197] Device:

[1198] Users prepare the proposed meal and then provide feedback, including the taste of the dish, the ease of the process, and their satisfaction level.

[1199] server:

[1200] User feedback is stored in a database and analyzed, and the feedback is reflected in the next menu suggestions, allowing for menus that better suit the user's preferences and requests.

[1201] Examples:

[1202] For example, if the user's feedback is "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[1203] Emotion recognition and menu adjustment

[1204] Device:

[1205] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[1206] server:

[1207] The system receives emotional information sent from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the system will suggest dishes using ingredients that have a relaxing effect.

[1208] Examples:

[1209] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[1210] Prompt Sentence Examples

[1211] Examples of prompts that allow users to easily input instructions to the system include the following:

[1212] "A user is looking for a Japanese meal using chicken breast, carrots, and potatoes, costing less than 500 yen, and aimed at weight loss. Please suggest the best menu."

[1213] This prompt makes it easier for the generative AI model to make specific cooking suggestions.

[1214] In this way, the system allows users to easily enjoy healthy meals within their budget, and also provides personalized menu suggestions that match their mood and emotions at the time.

[1215] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1216] Step 1:

[1217] User registration and initial settings

[1218] User:

[1219] A user installs the application and creates an account. They enter an email address and password. After entering this information, they receive a confirmation email containing a link to activate their account. They then enter initial information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1220] Device:

[1221] All information entered by the user is sent to the server.

[1222] server:

[1223] The information entered is saved in a database. A user profile is created based on the saved information. The profile contains all of the information entered.

[1224] Input: User email address, password, currently available ingredients, budget, location, cooking preferences, health goals

[1225] Output: User profile stored in the database

[1226] Step 2:

[1227] Data analysis and menu generation

[1228] server:

[1229] Data analysis is performed based on the saved user profile. The information analyzed includes ingredients, budget, location, cooking preferences, and health goals. Evaluation data is generated based on this information. Next, an optimal menu is generated using a generative AI model. Recipes that meet the given criteria are selected by referencing the ingredient database, recipe database, budget analysis, and health database.

[1230] Examples:

[1231] Based on information such as "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the system searches for low-calorie recipes from a Japanese food recipe database and generates the optimal menu.

[1232] Input: User profile, ingredient database, recipe database, budget analysis data, health database

[1233] Output: Optimal menu data

[1234] Step 3:

[1235] Menu and cooking instructions

[1236] server:

[1237] The generated menu data is sent to the user's device. The menu data includes specific dish names and ingredient lists.

[1238] Device:

[1239] The user is notified of meal suggestions and shown detailed cooking instructions, including cooking times, necessary tools, and specific instructions for each step.

[1240] Input: Menu data

[1241] Output: Notification to user device, detailed cooking instructions

[1242] Step 4:

[1243] Measuring costs and health benefits

[1244] server:

[1245] It calculates the cost of ingredients needed for the generated meal plan, compares the calculation results with the budget information entered by the user to assess whether it is within budget, and measures the financial savings. It also evaluates the nutritional value of the meal plan to measure its contribution to the user's health goals.

[1246] Examples:

[1247] If the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of the ingredients is 450 yen, it will be evaluated as being economical because it is within the budget of 500 yen. Also, because it is low in calories and high in protein, it will be evaluated as contributing to the health goal of weight loss.

[1248] Input: Menu data, budget information, nutritional data

[1249] Output: Cost assessment results, health effect assessment results

[1250] Step 5:

[1251] User Feedback and Improvements

[1252] Device:

[1253] Users create the suggested meals and then provide feedback, including the taste of the food, the ease of the process, and satisfaction.

[1254] server:

[1255] The feedback received from users is stored in a database and analyzed, and the analysis results are reflected in the next menu proposal.

[1256] Examples:

[1257] If the user gives feedback such as "The food was delicious, but I would prefer a simpler recipe," the next time the system will prioritize suggestions that are simpler and have fewer cooking steps.

[1258] Input: User feedback

[1259] Output: Feedback analysis results, improved menu suggestions

[1260] Step 6:

[1261] Emotion recognition and menu adjustment

[1262] Device:

[1263] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[1264] server:

[1265] The system receives the emotional information sent by the emotion engine and adjusts the menu suggestions based on the user's emotions. For example, if the user is feeling stressed, it will suggest dishes using ingredients that have a relaxing effect.

[1266] Examples:

[1267] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[1268] Input: Emotion information

[1269] Output: Emotion-based menu suggestions

[1270] (Application example 2)

[1271] 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."

[1272] While many support systems exist today to help users prepare healthy and economical meals at home, these systems rarely take into account the user's emotions or momentary moods when making suggestions. Systems that can suggest suitable dishes, especially when users are stressed or tired, are lacking. Furthermore, there is a lack of integration with food delivery services that allow users to easily order the suggested meals. Therefore, there is a need for a system that can suggest meals that meet the user's health goals and budget while taking into account the user's emotions, and that can instantly order the meals.

[1273] The specification processing by the specification 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 inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting cooking preferences, means for inputting health goals, means for recognizing the user's emotions, means for generating an optimal menu based on the above information and the user's emotions, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, and means for food delivery that allows the user to order the generated menu and cooking method. This allows the user to receive suggestions for an appropriate menu that matches their emotions and mood at the time, and to easily order meals that meet their health goals and budget.

[1274] "Currently available ingredients" refers to food ingredients that the user owns or plans to procure.

[1275] "Budget information" refers to data indicating the range of amounts that the user can spend on food, as set by the user.

[1276] "User location information" refers to information indicating the area where the user resides or stays.

[1277] "Cuisine preferences" refers to data indicating the types of cuisine a user likes and their preferences for specific ingredients.

[1278] "Health goals" refers to information indicating the health status or nutritional balance that a user wants to achieve, such as weight loss or high protein intake.

[1279] "Means for recognizing the user's emotions" refers to technology that analyzes and recognizes the user's current emotional state from their facial expressions and speech content.

[1280] "Means for generating optimal menus" refers to a system that suggests the most suitable combination of dishes based on the user's input information and emotional data.

[1281] "Means for presenting cooking methods" refers to a mechanism that provides users with cooking procedures and how to use ingredients for the generated menu.

[1282] "Means for cost evaluation" refers to a system that calculates the cost of ingredients required for a proposed menu and evaluates whether it is within budget.

[1283] "Food delivery means" refers to a service that orders food based on the generated menu and delivers it to the user.

[1284] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system works in conjunction with food delivery services to provide menus that take into account the user's health goals and budget.

[1285] System configuration

[1286] The system mainly consists of the following components:

[1287] 1. User device: User information is input on a smartphone or tablet, and emotional state is recognized.

[1288] 2. Server: Generates menus, recognizes emotions, evaluates costs, and manages food delivery.

[1289] 3. Database: Includes food database, recipe database, health database, and budget database.

[1290] User registration and initial settings

[1291] The user installs the application and creates an account. The user enters the following information:

[1292] Currently available ingredients

[1293] Budget Information

[1294] User Location

[1295] Food preferences

[1296] health goals

[1297] This information is sent to a server and stored in a database.

[1298] Emotion Recognition and Data Analysis

[1299] The device uses an emotion recognition engine to analyze the user's facial expressions and voice to recognize their emotional state. This emotional data is sent to the server and stored in a database. The server then analyzes the user's input information and emotional state to generate an optimal menu. The following technologies are used for the analysis:

[1300] EmotionEngine: Software for recognizing user emotions.

[1301] RecipeRecommender: A system that suggests optimal menus based on user input and emotions.

[1302] Menu generation and presentation

[1303] The server generates an optimal menu based on the user's information and emotional data and sends it to the device. The device receives it and presents the menu and cooking instructions to the user. The cooking instructions include specific steps, cooking time, and necessary tools.

[1304] Cost assessment and health benefit measurement

[1305] The server calculates the cost of ingredients in the generated menu and compares it with the user's set budget. If the menu is within the budget, it presents the menu to the user. It also evaluates the health benefits of the generated menu based on its nutritional value and calculates its contribution to the user's health goals.

[1306] Food delivery service

[1307] If the user likes the suggested menu and places an order, the server will arrange for the food to be delivered to the user's location via a food delivery service, allowing the user to easily enjoy healthy meals on a budget.

[1308] User feedback and system improvements

[1309] Users provide feedback on the food they are served, including taste, ease of cooking, and satisfaction. This feedback is sent to the server and reflected in the next recommendation. This allows the system to continually improve to suit the user's preferences.

[1310] Specific examples

[1311] For example, if the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that the budget is met.

[1312] Prompt Sentence Examples

[1313] text

[1314] The user is stressed. Can you suggest some Japanese-style chicken and carrot recipes that are good for weight loss and have a budget of 1000 yen?

[1315] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1316] Step 1:

[1317] A user installs an application using a terminal and creates an account. The user enters an email address and password and receives a confirmation email for creating the account. This sends the user's basic information to the server and completes the initial setup. The input data is an email address and password, and the output is that the account has been created.

[1318] Step 2:

[1319] The user uses a terminal to input currently available ingredients, budget information, location information, cooking preferences, and health goals. The server retrieves the input information and stores it in a database. The input data is ingredients, budget, location, preferences, and health goals, and the output is an updated user profile. The server references the database to analyze this information.

[1320] Step 3:

[1321] The user uses the device to activate the emotion recognition engine. The device analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., stress, fatigue, joy). The recognized emotion data is sent to the server and stored in a database. The input data is the user's facial expressions and voice, and the output is the recognized emotion data. The EmotionEngine processes this and analyzes the emotion.

[1322] Step 4:

[1323] The server analyzes the user's input information and emotional data to generate an optimal menu. The analysis refers to the ingredient database, recipe database, budget database, and health database. Specifically, a RecipeRecommender is used to select recipes that meet the user's criteria based on ingredients, budget, preferences, health goals, and emotions. The input data are the user profile and emotional data, and the output is the generated menu.

[1324] Step 5:

[1325] The server sends the generated menu to the user's device. The device receives the menu and notifies the user. The menu includes specific dish names, ingredient lists, and cooking instructions. The input data is the generated menu, and the output is the menu and cooking instructions displayed to the user.

[1326] Step 6:

[1327] The user reviews the proposed menu and, if they wish to have food delivered, places an order from their device. The server accepts the order and sends a request to the appropriate food delivery service. The input data is the user's order, and the output is a request to the food delivery service, which then delivers the food to the user's location.

[1328] Step 7:

[1329] After receiving and eating the food, the user provides feedback using a terminal. The feedback includes the taste of the food, the ease of the process, and satisfaction level, and is sent to the server. The server stores the feedback in a database and reflects it in the next menu suggestion. The input data is the user's feedback, and the output is updated analysis data. This allows the system to be continuously improved.

[1330] Examples:

[1331] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that they are within the budget.

[1332] 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.

[1333] 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.

[1334] 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.

[1335] [Fourth embodiment]

[1336] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1337] 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.

[1338] 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).

[1339] 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.

[1340] 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.

[1341] 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).

[1342] 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. 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.

[1343] 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.

[1344] 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.

[1345] 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.

[1346] 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.

[1347] 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.

[1348] 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."

[1349] The present invention is a system that provides optimized menus and cooking methods based on information input by a user. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[1350] User registration and initial settings

[1351] Device: The user installs the application and creates an account. When creating an account, they enter required information such as an email address and password. In addition, the user enters information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1352] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[1353] Data analysis and menu generation

[1354] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[1355] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[1356] Menu and cooking instructions

[1357] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[1358] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[1359] Measuring costs and health benefits

[1360] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1361] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[1362] User Feedback and Improvements

[1363] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[1364] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[1365] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[1366] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals that are within their budget.

[1367] The processing flow will be explained below.

[1368] Step 1:

[1369] A user installs the application and creates an account. The user enters an email address and password and receives a confirmation email.

[1370] Step 2:

[1371] The user inputs initial information into the device, including currently available ingredients, budget, location, cooking preferences, and health goals. This information is entered in detail.

[1372] Step 3:

[1373] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[1374] Step 4:

[1375] The server analyzes the user's input information and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). The server then prepares to generate the optimal menu based on the user information.

[1376] Step 5:

[1377] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[1378] Step 6:

[1379] The server generates optimal menus, selecting nutritionally balanced recipes based on the user's health goals, and creating optimal menus that include specific recipes, ingredient lists, and cooking instructions.

[1380] Step 7:

[1381] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[1382] Step 8:

[1383] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[1384] Step 9:

[1385] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[1386] Step 10:

[1387] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[1388] Step 11:

[1389] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[1390] Step 12:

[1391] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[1392] The above are the specific processing steps of the system.

[1393] Example 1

[1394] 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."

[1395] In today's busy world, consumers need easy ways to prepare healthy and economical meals. However, coming up with optimal menus with limited ingredients and a limited budget is a challenge for many people. Furthermore, there are few systems that suggest menus that meet individual health goals and culinary preferences. Therefore, a user-friendly menu suggestion system is needed.

[1396] 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.

[1397] In this invention, the server includes a means for inputting currently available ingredients, a means for inputting budget information, a means for inputting user location information, a means for inputting cooking preferences, a means for inputting health goals, a means for analyzing the above information and deriving evaluation data based on variables, a means for generating an optimal menu by referencing a database based on the evaluation data, a means for presenting cooking methods related to the generated menu, a means for evaluating costs within the budget, a means for storing and analyzing user feedback in a database, and a means for reflecting the feedback in the next menu proposal. This allows users to easily obtain optimal menus and cooking methods tailored to their individual requirements. Furthermore, the generated menu can be evaluated to see whether it is within budget and how much it contributes to health goals, allowing users to easily achieve an economical and healthy diet. Furthermore, by reflecting user feedback in the next proposal, more personalized menu proposals are possible.

[1398] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[1399] "Budget information" is data indicating the upper limit of the cost that a user is willing to spend on a single meal.

[1400] "User location information" is information about the user's residential area or current location, and is a factor that affects the ingredients and cooking methods available depending on the area.

[1401] "Cooking preferences" is information that indicates the genres, styles, and seasonings of cooking that the user particularly likes.

[1402] "Health goals" are health conditions and weight management goals that a user aims for, and include dieting and improving nutritional balance.

[1403] "Means for deriving evaluation data" refers to a function that analyzes various information entered by the user and calculates specific evaluation values ​​and indicators.

[1404] The "means for generating the optimal menu by referring to the database" is a function that selects the optimal menu from a database of saved recipes and ingredient information based on the analyzed evaluation data.

[1405] The "means for presenting cooking methods" is a function that provides the user with detailed information such as the steps to prepare the dish, the necessary tools, and cooking time based on the generated menu.

[1406] The "means for performing cost evaluation" is a function that calculates the cost of ingredients required for the generated menu and compares this with the user's budget to perform an economic evaluation.

[1407] "Means for saving and analyzing feedback in a database" is a function for saving evaluations and opinions provided by users in a database, analyzing them, and reflecting them in the next proposal.

[1408] The present invention is a system that provides optimized menus and cooking methods based on information entered by a user. The system aims to improve health and reduce food costs, and specific embodiments are described below.

[1409] User registration and initial settings

[1410] On the device: The user installs the application and creates an account, entering basic information such as an email address and password, as well as details such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1411] Server: The server stores the entered information in a database and generates a user profile, which is used for subsequent menu suggestions.

[1412] Data analysis and menu generation

[1413] Server: Analyzes the information entered by the user (ingredients, budget, location, preferences, and health goals) and derives evaluation data. This analysis is performed using data analysis libraries such as Python's pandas and scikit-learn. Based on the analyzed data, the optimal menu is generated by referencing the ingredient database, recipe database, budget analysis, and health database.

[1414] Example: If a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server uses this information to search a Japanese food recipe database for low-calorie recipes that fit within the user's budget and generate the optimal menu. It suggests "stir-fried chicken breast and vegetables."

[1415] Menu and cooking instructions

[1416] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[1417] On the device: The user is notified and shown detailed cooking instructions. The app UI provides step-by-step instructions and allows users to track their progress.

[1418] Measuring costs and health benefits

[1419] Server: Calculates the cost of ingredients needed for the generated menu. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. This evaluates the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1420] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[1421] User Feedback and Improvements

[1422] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[1423] User: Fill out the feedback form and click the "Submit" button.

[1424] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal. For analysis using AI models, generative AI models such as TensorFlow and PyTorch are used.

[1425] Example prompt sentence:

[1426] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[1427] This system allows users to easily enjoy healthy meals within their budget, and by incorporating user feedback, it is possible to provide more personalized menu suggestions.

[1428] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1429] Step 1: Install the app and create an account

[1430] Device: The user installs and opens the application. The account creation screen appears.

[1431] User: Enter your email address, password, and other required information and click the "Register" button.

[1432] Input: Email address, password, and other personal information.

[1433] Server: Receives the entered information and stores it in a database. It creates a user profile and sends a message to the terminal indicating successful registration.

[1434] Output: Registration successful message.

[1435] Step 2: Enter the initial configuration information

[1436] Terminal: Displays an input form for the user to enter information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1437] User: Enter the current ingredients (e.g., "chicken breast," "carrots," and "potatoes"), budget (e.g., 500 yen), location (e.g., Tokyo), preferences (e.g., Japanese food), and health goals (e.g., weight loss), then press the "Save" button.

[1438] Input: ingredients, budget, location, preferences, health goals.

[1439] Server: Receives the entered information and stores it in a database. Updates the user profile based on this information.

[1440] Output: Initial configuration information stored in the database.

[1441] Step 3: Information analysis and evaluation data derivation

[1442] Server: Analyzes the information entered by the user and creates evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Data analysis libraries such as Python's pandas and scikit-learn are used for the analysis.

[1443] Input: Initial setup information (ingredients, budget, location, preferences, health goals).

[1444] Data processing / data calculation: Analyze numerical and categorical data using Python's pandas and scikit-learn to generate evaluation data.

[1445] Output: Evaluation data.

[1446] Step 4: Menu generation

[1447] Server: Based on the analyzed data, the server generates the optimal menu by referencing the food ingredient database, recipe database, budget analysis, and health database.

[1448] Input: Evaluation data, various databases.

[1449] Data processing / data calculation: Run queries against the database to extract the recipe that best suits the evaluation data.

[1450] Example: If the user inputs "chicken breast," "carrot," "potato," budget of 500 yen, location of "Tokyo," preference of "Japanese food," and health goal of "weight loss," the system will search a Japanese food recipe database for low-calorie recipes that fit within the budget and suggest "stir-fried chicken breast and vegetables."

[1451] Output: Optimal menu.

[1452] Step 5: Present the menu and cooking instructions

[1453] Server: The server sends the generated menu and cooking instructions to the user's device. The contents of the sent information include the specific dish name, ingredient list, cooking time, necessary tools, and instructions for each step.

[1454] Input: The generated menu.

[1455] On the device: The user is notified and shown detailed cooking instructions. The app UI displays step-by-step instructions and allows users to track their progress.

[1456] Output: Menu and cooking instructions displayed on the terminal.

[1457] Step 6: Cost and health assessment

[1458] Server: Calculates the cost of ingredients needed for the generated meal plan. Retrieves the price of each ingredient using a price database and compares the total amount with the user's budget. Evaluates the financial savings. Also analyzes the nutritional value of the meal plan to measure its contribution to the user's health goals.

[1459] Input: Generated menu and price database.

[1460] Data processing / data calculation: Based on price data, the cost of ingredients is added up and evaluated to see if it is within the user's budget. Also, based on nutritional data, the degree of achievement toward health goals is calculated.

[1461] Example: For example, the total cost of the ingredients for "Stir-fried chicken breast and vegetables" is 450 yen, which is within the budget of 500 yen, so it is evaluated as having an economical effect. Also, because it is low in calories and high in protein, it is evaluated as contributing to the health goal of weight loss.

[1462] Output: Cost assessment and health assessment results.

[1463] Step 7: Gather user feedback

[1464] Terminal: After the user creates a dish, a feedback form is displayed. Feedback includes items such as the taste of the dish, the ease of the process, and satisfaction.

[1465] User: Fill out the feedback form and click the "Submit" button.

[1466] Input: User feedback.

[1467] Server: Receives feedback from users and stores it in a database. Analyzes the feedback data and reflects it in the next menu proposal.

[1468] Output: Feedback data.

[1469] Example prompt sentence:

[1470] "Currently, the ingredients available are chicken breast, carrots, and potatoes. I'd like some Japanese recipes within a budget of 500 yen. My health goal is to lose weight."

[1471] (Application example 1)

[1472] 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."

[1473] Conventional menu suggestion systems require users to purchase ingredients and cook the meals themselves based on the suggested menu, which is time-consuming, especially for busy modern people. Furthermore, there was a lack of an efficient way to obtain ingredients and meals, so integration with delivery services was required. Therefore, a system was needed that would allow users to easily secure healthy meals within their budget.

[1474] 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.

[1475] In this invention, the server includes means for inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting food preferences, means for inputting health goals, means for generating an optimal menu based on this information, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, means for coordinating ingredients and dishes required for the optimal menu with a delivery company and presenting ordering options, and means for contacting the delivery company and delivering the ingredients and dishes after the user confirms the order. This allows the user to automatically order and receive ingredients and dishes based on the menu suggestions, ensuring healthy and efficient meals with significantly less hassle.

[1476] "Currently available ingredients" are food ingredients that the user has on hand or readily available.

[1477] "Budget information" refers to the amount of money a user can spend on ingredients and dishes.

[1478] "User location information" refers to geographical information about the location where the user resides.

[1479] "Cooking preferences" refers to the user's preferences regarding the food and cooking styles they prefer to eat.

[1480] A "health goal" is a health-related goal that a user wants to achieve, such as losing weight or improving nutritional balance.

[1481] A "means for generating an optimal menu" is a method or system for deriving appropriate dish and meal combinations based on information entered by the user.

[1482] "Means for presenting cooking methods related to the generated menu" refers to a method or system for instructing the user on specific cooking methods and procedures for the menu generated by the system.

[1483] The "means for evaluating costs within a budget" refers to a method or system for evaluating whether the ingredients and dishes required for the generated menu fit within the user's budget.

[1484] "Means for coordinating with delivery companies the ingredients and dishes required for the optimal menu and presenting ordering options" refers to a method or system that works with a delivery service to coordinate the ingredients and dishes required for the generated menu and provides the user with ordering options.

[1485] "Means for contacting a delivery company to deliver ingredients or food after a user has confirmed an order" refers to a method or system for transmitting information to a delivery service and having the food or food delivered to a specified location after a user has confirmed an order for ingredients or food.

[1486] This invention is a system that provides a menu and cooking methods optimized based on information entered by the user, and also provides a service that delivers the ingredients and dishes required for that menu. The basic system configuration, data flow, and specific operating procedures are described in detail below.

[1487] System configuration

[1488] 1. Hardware

[1489] Smartphone

[1490] Cloud server (e.g. AWS, Google Cloud)

[1491] 2. Software

[1492] Mobile app development frameworks (e.g., Flutter, React Native)

[1493] Database management systems (e.g., MySQL, MongoDB)

[1494] Data analysis libraries (e.g., Python, Pandas, TensorFlow)

[1495] Data flow and processing method

[1496] 1. User registration and initial settings

[1497] Device: The user installs the mobile app on their smartphone and creates an account. The user enters information about currently available ingredients, budget information, user location information, cooking preferences, health goals, etc.

[1498] Server: Saves the entered information in a database on the cloud and creates a user profile.

[1499] 2. Data analysis and menu generation

[1500] Server: Analyzes the information entered by the user using a data analysis module (e.g., Python, Pandas) and derives evaluation data for generating optimal menus. The generated menus include specific dish names and ingredient lists based on the information entered by the user.

[1501] Example: For example, if a user inputs "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a database of Japanese food recipes and suggest the most suitable recipe.

[1502] 3. Menu and delivery method

[1503] Server: Based on the generated menu, it coordinates with delivery companies to determine the necessary ingredients and dishes, and presents ordering options to the user's device.

[1504] On device: The user is notified of the suggested meal plan and presented with detailed cooking instructions and purchasing options.

[1505] 4. Delivery arrangements and cost management

[1506] Server: After the user confirms the order, the server contacts the delivery company and arranges for the delivery of ingredients and food. At this time, the server evaluates the cost within the budget and ensures economical and efficient delivery.

[1507] Example: Once the necessary ingredients and dishes have been ordered based on the menu selected by the user, the server will request delivery from a delivery company. The user simply waits for the food to arrive while checking the progress on their smartphone.

[1508] 5. User Feedback and Improvements

[1509] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[1510] Server: User feedback is stored in a database and analyzed. This feedback is reflected in the next menu suggestion, allowing for even more personalized suggestions.

[1511] Prompt Sentence Examples

[1512] The user has entered "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss." Based on this information, please generate the optimal Japanese food menu.

[1513] By implementing this invention, users can conveniently enjoy healthy meals that are within their budget, and can easily order and receive the ingredients and dishes.

[1514] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1515] Step 1:

[1516] User registration and initial settings

[1517] Input: A user installs the mobile app on their smartphone and creates an account. Input fields include email address, password, currently available ingredients, budget information, user location information, cooking preferences, and health goals.

[1518] Specific operation: When a user enters information on the terminal and presses the send button, this information is sent to the server.

[1519] Processing: The server stores the entered information in a cloud database (e.g., MySQL, MongoDB) and creates a user profile.

[1520] Output: A user profile is generated, storing data about ingredients, budget, location, preferences, and health goals.

[1521] Step 2:

[1522] Data analysis and menu generation

[1523] Input: User-entered information about ingredients, budget information, location, food preferences, and health goals.

[1524] Specific operation: The server receives this information and passes it to a data analysis module (e.g., Python, Pandas).

[1525] Processing: The server uses an analysis module to analyze the user's input information and derive evaluation data for generating optimal menus, including the availability of ingredients, budget range, local characteristics, user preferences, and health goals.

[1526] Output: A user-optimized menu is generated and the information is saved in a database.

[1527] Step 3:

[1528] Menu and delivery options

[1529] Input: Server-generated menu information.

[1530] Specific operation: The server coordinates with delivery companies to find the ingredients and dishes needed for the generated menu and presents delivery options.

[1531] Processing: The server calls the delivery company's API to retrieve discoverable delivery options, which provides the best delivery company and pricing information based on the user's location. This information is then sent to the user's device.

[1532] Output: The user device displays the suggested meal plan, cooking instructions, and delivery options.

[1533] Step 4:

[1534] Delivery arrangements and cost management

[1535] Input: The delivery option selected and confirmed by the user.

[1536] What happens: A user uses a smartphone app to select a delivery option and place an order.

[1537] Processing: After the user confirms the order of ingredients and dishes necessary for the optimal menu, the server contacts the delivery company to arrange delivery. At this time, the server evaluates whether the delivery cost is within the user's budget and notifies the user.

[1538] Output: The delivery company delivers the ingredients and food to the user's location.

[1539] Step 5:

[1540] User Feedback and Improvements

[1541] Input: Feedback information such as the taste of the food the user experienced, cooking procedures, and satisfaction level.

[1542] What happens: The user creates a dish and provides feedback through the app.

[1543] Processing: The server stores the received feedback in a database and analyzes the data to reflect it in the next menu suggestion. The feedback analysis will be used to improve the analysis module in the future.

[1544] Output: The user's feedback will be reflected in the next menu suggestion, making it more suitable for the user.

[1545] 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.

[1546] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[1547] User registration and initial settings

[1548] Device: The user installs the application and creates an account. The user enters their email address and password and receives a confirmation email. The user also enters their currently available ingredients, budget, location, cooking preferences, and health goals.

[1549] Server: Stores the entered information in a database and creates a user profile, which is used to create personalized menu suggestions.

[1550] Data analysis and menu generation

[1551] Server: Analyzes the information entered by the user and derives evaluation data based on each variable (ingredients, budget, location, preferences, and health goals). Based on the analyzed data, the server generates an optimal menu by referencing the ingredient database, recipe database, budget analysis, and health database.

[1552] Example: If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, a location of "Tokyo," a preference of "Japanese food," and a health goal of "weight loss," the server will use this information to search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[1553] Menu and cooking instructions

[1554] Server: Sends the generated menu to the user's device. The menu includes the name of the specific dish and a list of its ingredients.

[1555] Device: The user is notified of the generated menu suggestions and shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[1556] Measuring costs and health benefits

[1557] Server: Calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user. Evaluates whether it is within budget and measures the economic savings. Also, evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1558] Example: For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[1559] User Feedback and Improvements

[1560] Device: The user prepares the proposed meal and then provides feedback, including the taste of the dish, the ease of the process, and satisfaction.

[1561] Server: Stores and analyzes user feedback in a database. This feedback is reflected in the next menu suggestion, enabling the system to provide a menu that better suits the user's preferences and requests.

[1562] Example: For example, if the user's feedback is, "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[1563] Emotion recognition and menu adjustment

[1564] Device: When a user uses an application, the emotion engine is activated. The emotion engine analyzes the user's facial expressions and speech to recognize their current emotional state.

[1565] Server: Receives information from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the server will suggest dishes using ingredients that have a relaxing effect.

[1566] Example: If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Providing menus that take emotions into account in this way makes it possible to make more personalized suggestions.

[1567] The above is a specific embodiment for carrying out the present invention. This system allows users to easily enjoy healthy meals within their budget, and also provides menu suggestions that match their mood and emotions at the time.

[1568] The processing flow will be explained below.

[1569] Step 1:

[1570] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[1571] Step 2:

[1572] The device sends the entered information to the server, which stores it in a database and creates a user profile. This profile allows for personalized menu suggestions.

[1573] Step 3:

[1574] An emotion engine is activated on the device and analyzes the user's facial expressions and speech to recognize their current emotional state. For example, the user inputs their emotions using a camera or microphone, and the emotion engine analyzes the data.

[1575] Step 4:

[1576] The server analyzes the user's input information and emotional data. It derives evaluation data based on each variable (ingredients, budget, location, preferences, health goals, and emotions). The server then prepares to generate the optimal menu based on the user information.

[1577] Step 5:

[1578] The server references the necessary databases (ingredient database, recipe database, budget analysis, health database). The server checks the ingredients the user has on hand from the ingredient database, searches for dishes that suit the user's preferences from the recipe database, and checks whether the dishes can be completed within the budget.

[1579] Step 6:

[1580] The server generates optimal menus, selecting nutritionally balanced recipes and creating optimal menus based on the user's health goals and emotions, and generating menus that include specific recipes, ingredient lists, and cooking instructions.

[1581] Step 7:

[1582] The server sends the generated menu to the user's device, which receives the menu and displays it to the user. A notification is also sent so the user can check the new menu suggestions.

[1583] Step 8:

[1584] The device displays detailed cooking instructions, providing the user with detailed instructions including cooking steps, necessary tools, cooking time, etc. The user can then start cooking by following the instructions.

[1585] Step 9:

[1586] The server evaluates the cost of the menu and cooking method, calculates the cost of ingredients, and compares it with the user's budget information. It evaluates whether the menu is within budget and presents the economic savings to the user.

[1587] Step 10:

[1588] The server evaluates the nutritional value of the menu, measures its health benefits, calculates its contribution to the user's health goals, and provides the evaluation results to the user.

[1589] Step 11:

[1590] After cooking, the user provides feedback, including the taste of the dish, the ease of the cooking process, and their satisfaction. The user inputs this feedback into the terminal and sends it.

[1591] Step 12:

[1592] The server stores and analyzes user feedback in a database, and adjusts and improves the algorithm to reflect the feedback in the next menu suggestion.

[1593] Step 13:

[1594] The emotion engine continuously monitors the user's emotions and evaluates their emotional response to suggested menus and cooking methods. For example, if the user smiles at a particular dish, it will determine that the dish was well-received and reflect this in future suggestions.

[1595] These are the specific processing steps of the system that combines the emotion engine. This allows users to easily enjoy healthy meals within their budget, and receives menu suggestions that match their mood and emotions at the time.

[1596] Example 2

[1597] 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."

[1598] In modern society, busy lifestyles make it difficult to easily prepare healthy meals. In particular, there is a need for planning balanced menus within a budget and for recipe suggestions tailored to the user's health goals and emotions. However, existing systems have difficulty adequately addressing individual user needs. Therefore, a system is needed that provides appropriate menus and cooking methods based on the user's input information and emotional state, helping them save money on food and improve their health.

[1599] 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.

[1600] In this invention, the server includes a means for the user to input currently available ingredients, budget, location, cooking preferences, and health goals as initial settings, a means for saving and analyzing the information and creating a user profile based on the above information, a means for generating an optimal menu based on the input information using a generative AI model, a means for transmitting and presenting the generated menu and cooking methods to the user's terminal, and a means for evaluating costs and nutritional values ​​within the budget and measuring health benefits. This allows users to not only easily enjoy healthy meals within their budget, but also to receive personalized menu suggestions tailored to their moods and emotions at the time.

[1601] "User input as initial settings" means that after the user installs the application, they input personal information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1602] A "generative AI model" is an artificial intelligence model that generates optimal menus based on input information.

[1603] A "user profile" is a collection of data that stores individual information entered by a user and is used to perform various analyses and make suggestions based on that information.

[1604] A "menu" is a specific combination of dishes and a list of ingredients for a user to cook.

[1605] "Cooking method" refers to the steps and methods for preparing a dish based on the generated menu.

[1606] "Cost evaluation" involves calculating the prices of ingredients required for the generated menu and evaluating whether they are within the budget set by the user.

[1607] "Nutritional value" is an evaluation of the amount of nutrients contained in the generated menu, measuring its contribution to the user's health goals.

[1608] "Health Benefit" refers to an assessment of how much the generated menu contributes to the user's health goals.

[1609] "Feedback" refers to the user providing their thoughts and opinions about the suggested menu and cooking methods.

[1610] The "emotional state" refers to the user's current psychological state, which can be obtained by analyzing the user's facial expressions, speech content, and the like.

[1611] "Adjusting menu suggestions based on emotions" refers to changing or adjusting the menu suggestions depending on the user's emotional state.

[1612] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system aims to reduce food costs and improve health, and specific embodiments are described below.

[1613] User registration and initial settings

[1614] Device:

[1615] A user installs the application and creates an account. They enter their email address and password, receive a confirmation email, and initially enter their currently available ingredients, budget, location, cooking preferences, and health goals.

[1616] server:

[1617] The system stores the user's registration information sent from the device in a database and creates a user profile based on that information, which includes a wide range of information such as ingredients, budget, location, cooking preferences, and health goals.

[1618] Data analysis and menu generation

[1619] server:

[1620] The information entered by the user is analyzed and rating data is generated based on each variable (ingredients, budget, location, preferences, and health goals). The rating data is then analyzed using a generative AI model, which then references the ingredient database, recipe database, budget analysis, and health database to generate the optimal menu.

[1621] Examples:

[1622] If the information entered by the user is "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the server will search a Japanese food recipe database for low-calorie recipes that fit within the budget and generate the optimal menu.

[1623] Menu and cooking instructions

[1624] server:

[1625] The generated menu is sent to the user's device, and includes the specific dish names and ingredient lists.

[1626] Device:

[1627] The user is notified of the generated menu suggestion and is shown detailed cooking instructions, including cooking time, necessary tools, and step-by-step instructions.

[1628] Measuring costs and health benefits

[1629] server:

[1630] The system calculates the cost of ingredients needed for the generated menu and compares it with the budget information entered by the user, evaluates whether it is within budget and measures the financial savings, and evaluates the nutritional value of the menu and measures its contribution to the user's health goals.

[1631] Examples:

[1632] For example, if the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of ingredients is 450 yen, it will be evaluated as economically saving because it is within the budget of 500 yen. In terms of nutritional value, it will be evaluated as contributing to the health goal of weight loss because it is low in calories and high in protein.

[1633] User Feedback and Improvements

[1634] Device:

[1635] Users prepare the proposed meal and then provide feedback, including the taste of the dish, the ease of the process, and their satisfaction level.

[1636] server:

[1637] User feedback is stored in a database and analyzed, and the feedback is reflected in the next menu suggestions, allowing for menus that better suit the user's preferences and requests.

[1638] Examples:

[1639] For example, if the user's feedback is "The food was delicious, but I would prefer a simpler recipe," the next time the system suggests a simpler recipe with fewer cooking steps.

[1640] Emotion recognition and menu adjustment

[1641] Device:

[1642] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[1643] server:

[1644] The system receives emotional information sent from the emotion engine and adjusts menu suggestions based on the user's emotions. For example, if the user is feeling stressed, the system will suggest dishes using ingredients that have a relaxing effect.

[1645] Examples:

[1646] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[1647] Prompt Sentence Examples

[1648] Examples of prompts that allow users to easily input instructions to the system include the following:

[1649] "A user is looking for a Japanese meal using chicken breast, carrots, and potatoes, costing less than 500 yen, and aimed at weight loss. Please suggest the best menu."

[1650] This prompt makes it easier for the generative AI model to make specific cooking suggestions.

[1651] In this way, the system allows users to easily enjoy healthy meals within their budget, and also provides personalized menu suggestions that match their mood and emotions at the time.

[1652] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1653] Step 1:

[1654] User registration and initial settings

[1655] User:

[1656] A user installs the application and creates an account. They enter an email address and password. After entering this information, they receive a confirmation email containing a link to activate their account. They then enter initial information such as currently available ingredients, budget, location, cooking preferences, and health goals.

[1657] Device:

[1658] All information entered by the user is sent to the server.

[1659] server:

[1660] The information entered is saved in a database. A user profile is created based on the saved information. The profile contains all of the information entered.

[1661] Input: User email address, password, currently available ingredients, budget, location, cooking preferences, health goals

[1662] Output: User profile stored in the database

[1663] Step 2:

[1664] Data analysis and menu generation

[1665] server:

[1666] Data analysis is performed based on the saved user profile. The information analyzed includes ingredients, budget, location, cooking preferences, and health goals. Evaluation data is generated based on this information. Next, an optimal menu is generated using a generative AI model. Recipes that meet the given criteria are selected by referencing the ingredient database, recipe database, budget analysis, and health database.

[1667] Examples:

[1668] Based on information such as "chicken breast," "carrots," "potatoes," a budget of 500 yen, location "Tokyo," preference "Japanese food," and health goal "weight loss," the system searches for low-calorie recipes from a Japanese food recipe database and generates the optimal menu.

[1669] Input: User profile, ingredient database, recipe database, budget analysis data, health database

[1670] Output: Optimal menu data

[1671] Step 3:

[1672] Menu and cooking instructions

[1673] server:

[1674] The generated menu data is sent to the user's device. The menu data includes specific dish names and ingredient lists.

[1675] Device:

[1676] The user is notified of meal suggestions and shown detailed cooking instructions, including cooking times, necessary tools, and specific instructions for each step.

[1677] Input: Menu data

[1678] Output: Notification to user device, detailed cooking instructions

[1679] Step 4:

[1680] Measuring costs and health benefits

[1681] server:

[1682] It calculates the cost of ingredients needed for the generated meal plan, compares the calculation results with the budget information entered by the user to assess whether it is within budget, and measures the financial savings. It also evaluates the nutritional value of the meal plan to measure its contribution to the user's health goals.

[1683] Examples:

[1684] If the generated menu is "Stir-fried chicken breast and vegetables" and the total cost of the ingredients is 450 yen, it will be evaluated as being economical because it is within the budget of 500 yen. Also, because it is low in calories and high in protein, it will be evaluated as contributing to the health goal of weight loss.

[1685] Input: Menu data, budget information, nutritional data

[1686] Output: Cost assessment results, health effect assessment results

[1687] Step 5:

[1688] User Feedback and Improvements

[1689] Device:

[1690] Users create the suggested meals and then provide feedback, including the taste of the food, the ease of the process, and satisfaction.

[1691] server:

[1692] The feedback received from users is stored in a database and analyzed, and the analysis results are reflected in the next menu proposal.

[1693] Examples:

[1694] If the user gives feedback such as "The food was delicious, but I would prefer a simpler recipe," the next time the system will prioritize suggestions that are simpler and have fewer cooking steps.

[1695] Input: User feedback

[1696] Output: Feedback analysis results, improved menu suggestions

[1697] Step 6:

[1698] Emotion recognition and menu adjustment

[1699] Device:

[1700] When a user uses an application, the emotion engine is activated, which analyzes the user's facial expressions and speech to recognize their current emotional state.

[1701] server:

[1702] The system receives the emotional information sent by the emotion engine and adjusts the menu suggestions based on the user's emotions. For example, if the user is feeling stressed, it will suggest dishes using ingredients that have a relaxing effect.

[1703] Examples:

[1704] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue."

[1705] Input: Emotion information

[1706] Output: Emotion-based menu suggestions

[1707] (Application example 2)

[1708] 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."

[1709] While many support systems exist today to help users prepare healthy and economical meals at home, these systems rarely take into account the user's emotions or momentary moods when making suggestions. Systems that can suggest suitable dishes, especially when users are stressed or tired, are lacking. Furthermore, there is a lack of integration with food delivery services that allow users to easily order the suggested meals. Therefore, there is a need for a system that can suggest meals that meet the user's health goals and budget while taking into account the user's emotions, and that can instantly order the meals.

[1710] The specification processing by the specification 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 inputting currently available ingredients, means for inputting budget information, means for inputting user location information, means for inputting cooking preferences, means for inputting health goals, means for recognizing the user's emotions, means for generating an optimal menu based on the above information and the user's emotions, means for presenting cooking methods related to the generated menu, means for evaluating costs within the budget, and means for food delivery that allows the user to order the generated menu and cooking method. This allows the user to receive suggestions for an appropriate menu that matches their emotions and mood at the time, and to easily order meals that meet their health goals and budget.

[1711] "Currently available ingredients" refers to food ingredients that the user owns or plans to procure.

[1712] "Budget information" refers to data indicating the range of amounts that the user can spend on food, as set by the user.

[1713] "User location information" refers to information indicating the area where the user resides or stays.

[1714] "Cuisine preferences" refers to data indicating the types of cuisine a user likes and their preferences for specific ingredients.

[1715] "Health goals" refers to information indicating the health status or nutritional balance that a user wants to achieve, such as weight loss or high protein intake.

[1716] "Means for recognizing the user's emotions" refers to technology that analyzes and recognizes the user's current emotional state from their facial expressions and speech content.

[1717] "Means for generating optimal menus" refers to a system that suggests the most suitable combination of dishes based on the user's input information and emotional data.

[1718] "Means for presenting cooking methods" refers to a mechanism that provides users with cooking procedures and how to use ingredients for the generated menu.

[1719] "Means for cost evaluation" refers to a system that calculates the cost of ingredients required for a proposed menu and evaluates whether it is within budget.

[1720] "Food delivery means" refers to a service that orders food based on the generated menu and delivers it to the user.

[1721] The present invention is a system that optimizes menus and cooking methods based on information entered by the user, and also recognizes the user's emotions and makes suggestions based on those. This system works in conjunction with food delivery services to provide menus that take into account the user's health goals and budget.

[1722] System configuration

[1723] The system mainly consists of the following components:

[1724] 1. User device: User information is input on a smartphone or tablet, and emotional state is recognized.

[1725] 2. Server: Generates menus, recognizes emotions, evaluates costs, and manages food delivery.

[1726] 3. Database: Includes food database, recipe database, health database, and budget database.

[1727] User registration and initial settings

[1728] The user installs the application and creates an account. The user enters the following information:

[1729] Currently available ingredients

[1730] Budget Information

[1731] User Location

[1732] Food preferences

[1733] health goals

[1734] This information is sent to a server and stored in a database.

[1735] Emotion Recognition and Data Analysis

[1736] The device uses an emotion recognition engine to analyze the user's facial expressions and voice to recognize their emotional state. This emotional data is sent to the server and stored in a database. The server then analyzes the user's input information and emotional state to generate an optimal menu. The following technologies are used for the analysis:

[1737] EmotionEngine: Software for recognizing user emotions.

[1738] RecipeRecommender: A system that suggests optimal menus based on user input and emotions.

[1739] Menu generation and presentation

[1740] The server generates an optimal menu based on the user's information and emotional data and sends it to the device. The device receives it and presents the menu and cooking instructions to the user. The cooking instructions include specific steps, cooking time, and necessary tools.

[1741] Cost assessment and health benefit measurement

[1742] The server calculates the cost of ingredients in the generated menu and compares it with the user's set budget. If the menu is within the budget, it presents the menu to the user. It also evaluates the health benefits of the generated menu based on its nutritional value and calculates its contribution to the user's health goals.

[1743] Food delivery service

[1744] If the user likes the suggested menu and places an order, the server will arrange for the food to be delivered to the user's location via a food delivery service, allowing the user to easily enjoy healthy meals on a budget.

[1745] User feedback and system improvements

[1746] Users provide feedback on the food they are served, including taste, ease of cooking, and satisfaction. This feedback is sent to the server and reflected in the next recommendation. This allows the system to continually improve to suit the user's preferences.

[1747] Specific examples

[1748] For example, if the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that the budget is met.

[1749] Prompt Sentence Examples

[1750] text

[1751] The user is stressed. Can you suggest some Japanese-style chicken and carrot recipes that are good for weight loss and have a budget of 1000 yen?

[1752] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1753] Step 1:

[1754] A user installs an application using a terminal and creates an account. The user enters an email address and password and receives a confirmation email for creating the account. This sends the user's basic information to the server and completes the initial setup. The input data is an email address and password, and the output is that the account has been created.

[1755] Step 2:

[1756] The user uses a terminal to input currently available ingredients, budget information, location information, cooking preferences, and health goals. The server retrieves the input information and stores it in a database. The input data is ingredients, budget, location, preferences, and health goals, and the output is an updated user profile. The server references the database to analyze this information.

[1757] Step 3:

[1758] The user uses the device to activate the emotion recognition engine. The device analyzes the user's facial expressions and voice to recognize their current emotional state (e.g., stress, fatigue, joy). The recognized emotion data is sent to the server and stored in a database. The input data is the user's facial expressions and voice, and the output is the recognized emotion data. The EmotionEngine processes this and analyzes the emotion.

[1759] Step 4:

[1760] The server analyzes the user's input information and emotional data to generate an optimal menu. The analysis refers to the ingredient database, recipe database, budget database, and health database. Specifically, a RecipeRecommender is used to select recipes that meet the user's criteria based on ingredients, budget, preferences, health goals, and emotions. The input data are the user profile and emotional data, and the output is the generated menu.

[1761] Step 5:

[1762] The server sends the generated menu to the user's device. The device receives the menu and notifies the user. The menu includes specific dish names, ingredient lists, and cooking instructions. The input data is the generated menu, and the output is the menu and cooking instructions displayed to the user.

[1763] Step 6:

[1764] The user reviews the proposed menu and, if they wish to have food delivered, places an order from their device. The server accepts the order and sends a request to the appropriate food delivery service. The input data is the user's order, and the output is a request to the food delivery service, which then delivers the food to the user's location.

[1765] Step 7:

[1766] After receiving and eating the food, the user provides feedback using a terminal. The feedback includes the taste of the food, the ease of the process, and satisfaction level, and is sent to the server. The server stores the feedback in a database and reflects it in the next menu suggestion. The input data is the user's feedback, and the output is updated analysis data. This allows the system to be continuously improved.

[1767] Examples:

[1768] If the user inputs "I'm tired" or the emotion engine recognizes it from the user's facial expression, the server will suggest "chicken breast soup, which is good for recovering from fatigue." Also, if the user's health goal is weight loss and their budget is 1,000 yen, the server will suggest low-calorie, high-protein dishes while checking that they are within the budget.

[1769] 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.

[1770] 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.

[1771] 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.

[1772] 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.

[1773] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1774] 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.

[1775] 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).

[1776] 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.

[1777] 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."

[1778] 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.

[1779] 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).

[1780] 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.

[1781] 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.

[1782] 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.

[1783] 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.

[1784] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1785] 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.

[1786] 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.

[1787] 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.

[1788] 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.

[1789] 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.

[1790] The following is further disclosed regarding the above embodiment.

[1791] (Claim 1)

[1792] a means of inputting currently available ingredients;

[1793] a means for inputting budget information;

[1794] means for inputting user location information;

[1795] a means for inputting cooking preferences;

[1796] a means for inputting health goals;

[1797] A means for generating an optimal menu based on the above information;

[1798] means for presenting cooking methods related to the generated menu;

[1799] A system that includes a means of assessing costs within a budget.

[1800] (Claim 2)

[1801] 2. The system according to claim 1, further comprising means for receiving feedback from the user regarding optimal menus and cooking methods and reflecting the feedback in the next menu proposal.

[1802] (Claim 3)

[1803] 10. The system of claim 1, further comprising means for evaluating the nutritional value of the menu based on health goals and measuring health benefits.

[1804] "Example 1"

[1805] (Claim 1)

[1806] a means of inputting currently available ingredients;

[1807] a means for inputting budget information;

[1808] means for inputting user location information;

[1809] a means for inputting cooking preferences;

[1810] a means for inputting health goals;

[1811] A means for generating an optimal menu based on the above information;

[1812] means for presenting cooking methods related to the generated menu;

[1813] A means of assessing costs within the budget;

[1814] means for analyzing the information and deriving evaluation data based on the variables;

[1815] A means for generating an optimal menu by referring to a database based on the evaluation data;

[1816] a means for storing and analyzing user feedback in a database;

[1817] A system that includes a means to incorporate feedback into next menu suggestions.

[1818] (Clai...

Claims

1. a means of inputting currently available ingredients; a means for inputting budget information; means for inputting user location information; a means for inputting cooking preferences; a means for inputting health goals; A means for generating an optimal menu based on the above information; means for presenting cooking methods related to the generated menu; A system that includes a means of assessing costs within a budget.

2. The system according to claim 1, further comprising means for receiving feedback from the user regarding the optimum menu and cooking method, and reflecting the feedback in the next menu proposal.

3. 10. The system of claim 1, further comprising means for evaluating the nutritional value of the menu based on the health goal and measuring the health benefits.

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