system

Abstract

We provide the system. [Solution] A means of inputting dietary information, A means of analyzing past dietary history and health data, A means of generating a meal plan based on nutritional balance, A means of outputting a list of selected ingredients, A means of providing dietary guidance tailored to one's health condition, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, with busy daily lives and an increasing frequency of using convenience stores, it has become difficult to maintain a nutritionally balanced diet. As a result, unbalanced diets often have an adverse effect on health, and nutrient deficiencies and overconsumption have become social issues. In addition, there are limited opportunities to receive appropriate dietary guidance according to individual health conditions, and there is a problem that it is difficult to manage health.

Means for Solving the Problems

[0005] This invention provides a system that analyzes past meal history and health data based on input dietary information and automatically generates an optimal meal plan based on nutritional balance. Furthermore, it outputs a list of selected ingredients and provides dietary guidance based on the user's health condition as needed, thereby supporting users in easily achieving a healthy diet. This system handles user information securely using encryption technology and also generates practical recipes based on available ingredients, enabling users to optimize their daily meal choices.

[0006] "Means for inputting dietary information" refers to a method or interface for users to record information about their own diet and transmit it to a system.

[0007] "Means for analyzing past dietary history and health data" refers to the process or technology for collecting and analyzing data related to a user's dietary history and health.

[0008] "Methods for generating meal plans based on nutritional balance" refers to algorithms or systems for constructing meal plans that include appropriate nutrients based on the user's health condition and nutritional needs.

[0009] "Means for outputting a list of selected ingredients" refers to a function or method by which the system presents a list of recommended ingredients to the user.

[0010] "Means of providing dietary guidance tailored to health conditions" refers to methods of providing guidelines or advice to propose an optimal dietary lifestyle, taking into account the user's current health condition and goals. [Brief explanation of the drawing]

[0011] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0012] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0013] First, let's explain the terminology used in the following explanation.

[0014] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0015] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0016] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0017] In the following embodiments, the numbered communication I / F (Interface) is an interface including a communication processor and 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), or Bluetooth (registered trademark), and the like.

[0018] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0019] [First Embodiment]

[0020] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0021] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0022] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0023] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0024] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0025] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0026] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0027] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0028] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0029] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0030] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0031] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0032] This invention is a system that provides users with a well-balanced meal plan using ingredients readily available at convenience stores, enabling them to maintain healthy eating habits. The system takes user dietary information as input, analyzes past meal history and health data, and automatically generates a meal plan based on nutritional balance.

[0033] The server is responsible for generating this meal plan, receiving and analyzing the user's meal history and health data. Furthermore, the server generates a nutritionally balanced meal plan and creates a list of ingredients based on it. The generated plan is then customized according to the user's nutritional needs.

[0034] This system also includes a function to provide dietary guidance tailored to the user's health condition. Specifically, the server analyzes the user's health status and provides appropriate advice based on that analysis. This advice includes suggestions on how to supplement necessary nutrients and which foods to avoid.

[0035] The terminal transmits user-inputted information to a server, receives the processing results, and presents them to the user. Users can purchase ingredients at a convenience store according to the provided meal plan and easily prepare the meal. The terminal also displays the recipe along with the meal plan, guiding the user on how to cook.

[0036] For example, if a user enters their eating history and indicates that they are "easily fatigued" as their recent physical condition, the server will perform an analysis based on this information. If it determines that the user is lacking essential nutrients, it will suggest a meal plan that includes iron-rich foods and present it to the user via their device along with the recipe. In this way, the present invention helps users easily adopt a healthy diet.

[0037] The following describes the processing flow.

[0038] Step 1:

[0039] Users access a dietary information form on their device and enter their eating history, allergy information, health condition, etc. This information is then sent to the system as data.

[0040] Step 2:

[0041] The terminal encrypts the information entered by the user as a security measure and sends it to the server. The encrypted data is communicated using a secure protocol.

[0042] Step 3:

[0043] The server decrypts the received data and stores it in the database. Here, the information is organized for each user, and management is performed to maintain data integrity.

[0044] Step 4:

[0045] The server analyzes the original data and uses nutritional algorithms to assess the user's nutritional needs. This analysis identifies necessary nutrients and dietary trends.

[0046] Step 5:

[0047] The server generates a nutritionally balanced meal plan based on the analysis results. This plan is customized according to the user's health condition and dietary preferences.

[0048] Step 6:

[0049] The server creates a shopping list of items that can be purchased at a convenience store based on the ingredients included in the meal plan. At the same time, it calculates the calorie and nutritional details of the suggested meals.

[0050] Step 7:

[0051] The server sends the generated meal plan, shopping list, and nutritional information to the device. This information also includes health advice.

[0052] Step 8:

[0053] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and prepare a meal according to the suggested recipe.

[0054] (Example 1)

[0055] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0056] In today's lifestyle, it is difficult for individuals to maintain healthy eating habits. Lack of time and insufficient knowledge about food selection make it challenging to prepare nutritionally balanced meals. Furthermore, there is a need for a system that effectively provides nutrients tailored to the user's health condition.

[0057] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0058] In this invention, the server includes means for inputting dietary habit data, means for analyzing past eating and drinking history and health status data, and means for generating a meal plan based on nutritional balance. This enables users to be provided with appropriate nutrients according to their health status and to achieve a balanced diet using readily available ingredients.

[0059] "Dietary habit data" refers to data that represents information about a user's daily eating habits.

[0060] "Dining history" refers to a record of food and drinks that a user has consumed in the past.

[0061] "Health status data" refers to data that includes information about the user's physical condition and health.

[0062] "Nutritional balance" refers to a state in which the body is consuming the necessary nutrients in a balanced manner.

[0063] A "dining plan" refers to a meal menu and structure designed to suit a specific purpose or condition.

[0064] A "food ingredient list" refers to a list of ingredients needed for a specific dish or dining plan.

[0065] A "cooking method" is a set of instructions that shows how to cook specific ingredients and complete a dish.

[0066] A "generative AI model" is an artificial intelligence model that uses a large amount of data to derive the optimal solution for a specific purpose.

[0067] In this invention, the server plays a central role. The server is equipped with a processor and storage to receive dietary habit data entered by the user. The server stores this data and analyzes the user's eating history and health status data. Data processing libraries such as Python and R are used for the analysis.

[0068] The server uses a generative AI model to evaluate past eating patterns and automatically generate meal plans based on nutritional balance. The generated meal plans include a list of selected ingredients and corresponding cooking methods. This allows users to easily create balanced meals using readily available ingredients.

[0069] Users input their eating habits data using a device. The entered data is encrypted on the device and securely transmitted to the server. The device displays the meal plan and cooking methods received from the server, providing users with specific guidance on their eating habits.

[0070] For example, if a user enters information about their health, such as "I've been feeling tired lately," into their device and sends it, the server analyzes this information and generates a meal plan centered around foods rich in iron and vitamins. The device displays cooking instructions for dishes like "blanched spinach" and "liver dishes," along with a list of ingredients that should be purchased.

[0071] An example of a prompt message would be, "Consider the user's recent health data and generate a meal plan that includes the necessary nutrients." This process allows users to efficiently engage in healthy eating and drinking behaviors.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The user inputs dietary habit data and health status data using a terminal. This data includes detailed information about their current diet and physical condition. The terminal converts this data into a predetermined format and prepares it for secure transmission to the server. The input includes text information about health status and a list of specific foods.

[0075] Step 2:

[0076] The terminal encrypts the input data using protocols such as SSL / TLS and sends it to the server. This reduces the risk of data leakage. As output, the server securely receives the encrypted data.

[0077] Step 3:

[0078] The server analyzes the received data. First, it deserializes the data to identify the user's past eating and drinking history and current health status. It preprocesses the data using the Python Pandas library and formats it into a dataframe. The analysis identifies any nutrient deficiencies necessary for creating a new eating and drinking plan.

[0079] Step 4:

[0080] The server uses a generation AI model to generate a nutritionally balanced meal plan based on the analysis results obtained. The model has learned from past data patterns and is ready to suggest the most suitable ingredient list and cooking method for the user. As output, the meal plan is generated in digital format.

[0081] Step 5:

[0082] The server sends the generated meal plan and corresponding ingredient list to the terminal. The data is encrypted again and securely delivered to the recipient's intended device. As output, the terminal receives the data and prepares for the next step.

[0083] Step 6:

[0084] The terminal displays the received dining plan and provides the user with a detailed operating guide. Cooking instructions and a list of ingredients to purchase are clearly displayed on the screen, allowing the user to proceed with shopping at the store and cooking based on this information. The output is that the user has purchased the ingredients according to the plan and prepared for cooking.

[0085] (Application Example 1)

[0086] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0087] In today's fast-paced lifestyle, maintaining healthy eating habits is not easy for individuals. To address this challenge, a system is needed that provides meal plans tailored to individual health conditions and offers concrete support throughout the process of food selection, purchasing, and cooking. However, many existing systems are limited to user-dependent information provision and simple meal suggestions, and currently lack comprehensive support to enable users to consistently engage in healthy food consumption.

[0088] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0089] In this invention, the server includes a device for inputting food consumption behavior information, a device for analyzing past food consumption history and health information, and a device for generating meal plans based on nutritional balance. This enables the automatic generation of food consumption plans optimized for individual users, and further allows for purchase assistance through an automated, remotely operated humanoid device. This supports the entire process, from selecting and purchasing food ingredients to cooking, providing comprehensive lifestyle management support for maintaining good health. Furthermore, by providing detailed visual and audio guidance on cooking procedures, users can easily complete healthy meals.

[0090] A "food consumption behavior information input device" is a device for receiving and recording information about food consumption from users.

[0091] A "food consumption history analysis device" is a device that collects and analyzes past food consumption history data.

[0092] A "health information analysis device" is a device that analyzes and evaluates data related to a user's health status.

[0093] A "meal plan generator" is a device that creates a meal plan optimized for each individual user, taking nutritional balance into consideration.

[0094] A "food ingredient list output device" is a device that outputs a list of necessary food ingredients based on a meal plan.

[0095] A "food consumption guidance device" is a device that provides guidance on diet and nutrition tailored to the user's health condition, supporting improvements in lifestyle habits.

[0096] An "automated humanoid remote-controlled device control system" is a device that controls an automated humanoid device that operates based on user instructions and assists in the food purchasing process.

[0097] A "visual and audio cooking procedure guidance device" is a device that guides users through cooking procedures using visual and audio means, and supports them in completing a dish.

[0098] This invention is a system that supports users' healthy eating habits by utilizing food consumption behavior information. The server collects the user's daily food consumption data through a food consumption behavior information input device. Users input their food consumption history and health information using devices such as smartphones and tablets. This data is transmitted to the server in real time and analyzed in detail by a food consumption history analysis device and a health information analysis device. The server uses hardware such as NVIDIA Jetson Orin and Raspberry Pi, and processes the data using software such as Python and TENSORFLOW®.

[0099] Based on the analysis, the meal plan generator utilizes a generation AI model to automatically create a meal plan tailored to the user's health condition. A list of necessary food ingredients is generated and presented to the user via a food ingredient list output device. This system can flexibly customize the plan according to the user's preferences and constraints.

[0100] Furthermore, an automated, humanoid, remotely operated device is used to assist the user in the food purchasing process. This device is designed for easy user operation and allows users to select and purchase food based on their meal plan. After the purchase is complete, a visual and audio cooking instruction device guides the user through the cooking process in detail. The cooking guide is provided through visual information and audio guidance, allowing users to easily prepare healthy meals.

[0101] As a concrete example, a user might input "easily fatigued" as their health condition, and the server would then suggest a meal plan containing iron based on the generated data. Examples of prompts in this process include, "Please suggest a balanced meal plan for my easily fatigued condition," or "Please provide appropriate recipes for iron supplementation." This allows users to efficiently obtain the necessary nutrients and maintain their health.

[0102] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0103] Step 1:

[0104] The terminal receives input from the user and collects data on food consumption behavior and health status. This input data includes information on the type and quantity of food consumed, the time of consumption, and the user's current health status. This information will be transmitted from the input device, such as a smartphone or tablet, to the server.

[0105] Step 2:

[0106] The server sends the received user input data to a food consumption history analysis device, which analyzes past food consumption history and current health information. This process uses a database to search the user's historical data and applies machine learning algorithms to assess their current health status. This results in the output of information about imbalances in nutrient intake.

[0107] Step 3:

[0108] The server uses a meal plan generator to create a meal plan that takes nutritional balance into consideration. In this step, a generation AI model is used to generate an optimal meal plan that reflects the user's preferences and health goals, based on the analysis results from step 2. The meal plan created here includes the necessary food ingredients and their quantities, so a list of specific food ingredients is output.

[0109] Step 4:

[0110] The terminal displays a meal plan and a list of food ingredients received from the server to the user. Here, a visually easy-to-understand interface is used to display the list of ingredients and recommended recipes, and voice guidance is provided to the user to encourage healthy food consumption.

[0111] Step 5:

[0112] The user reviews the presented meal plan and ingredients, and, if necessary, initiates food purchase assistance using an automated humanoid remote-controlled device. The automated humanoid remote-controlled device physically assists with ingredient selection and purchase, and reports the purchased ingredients to the user after the purchase is complete.

[0113] Step 6:

[0114] The device guides the user through cooking instructions via visual and audio guidance. Specifically, it provides detailed and easy-to-understand explanations of each cooking step, follows the cooking process in real time, and helps the user complete a healthy meal. At this stage, it provides prompts to help the user follow the appropriate cooking procedures, supporting a smooth user experience.

[0115] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0116] This invention is a system that combines an emotional engine with ingredients available at convenience stores, with the aim of helping users maintain a healthy diet. Through this, it aims to provide meal plans tailored to the user's emotional state and improve the quality of their diet.

[0117] First, the user inputs information about their diet and physical condition through the device. At this time, the emotion engine recognizes the user's emotions and identifies their current mood. Emotion recognition is achieved by using voice input, text input, and sensors that analyze facial expressions on the screen.

[0118] The server receives data entered by the user, decrypts the encrypted information, and stores it in a database. Next, the server analyzes the stored meal history and health data, incorporates emotional information from the emotion engine, and generates an optimal meal plan for the user. This meal plan is tailored to evoke positive emotions, taking into account the user's emotional state in particular.

[0119] The generated meal plan includes suggestions for nutritionally balanced meals and a list of ingredients available at convenience stores. Furthermore, it includes specific dietary guidance tailored to the user's emotions. For example, if the user is feeling stressed, meals containing relaxing ingredients will be recommended.

[0120] The device presents the user with meal plans, ingredient lists, and health advice sent from the server. This allows users to easily adopt a diet tailored to their current state and promote emotional stability. For example, if the emotion engine detects that the user is feeling "depressed," it will recommend recipes using specific ingredients that promote serotonin production to enhance feelings of happiness.

[0121] Thus, the present invention provides a system that supports both emotional and physical aspects by adapting to the user's emotions.

[0122] The following describes the processing flow.

[0123] Step 1:

[0124] Users access a form on their device to input information about their eating habits and health status. This input includes daily meal history, physical condition, and personal health goals. Furthermore, they input their current emotional state by selecting options to express their emotions or by using voice or facial expression analysis functions.

[0125] Step 2:

[0126] The terminal encrypts the dietary information and emotional data entered by the user and transmits it to the server using a secure communication protocol.

[0127] Step 3:

[0128] The server decrypts the received data and stores it in a database for each user. The stored data includes individual meal histories and emotional states.

[0129] Step 4:

[0130] The server analyzes user data in the database and evaluates emotional information using an emotion engine. This allows it to consider the impact of emotional states on diet and understand individual nutritional needs.

[0131] Step 5:

[0132] Based on the analysis results, the server generates a meal plan tailored to the user's nutritional balance and emotional state. For example, if a user is feeling stressed, the server will create a plan that includes ingredients and recipes suitable for relieving that stress.

[0133] Step 6:

[0134] The server creates a list of ingredients included in the generated meal plan and verifies whether these ingredients are available for purchase at convenience stores. The meal plan also includes dietary guidance to address the user's emotional needs.

[0135] Step 7:

[0136] The server sends the final meal plan, ingredient list, and health and emotional advice to the device.

[0137] Step 8:

[0138] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and cook at home. This process is designed to support both the user's emotional well-being and health.

[0139] (Example 2)

[0140] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0141] In today's busy lifestyle, many people find it difficult to maintain both a healthy diet and emotional stability simultaneously. In particular, there is a lack of readily available options for choosing meals that consider both nutritional balance and emotional state. A system is needed to address this problem and provide healthy meals that adapt to individual emotional needs.

[0142] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0143] In this invention, the server includes means for inputting dietary information and emotional state, means for analyzing past meal history, health data, and emotional information, and means for generating a meal plan based on nutritional balance and emotional state. This enables the provision of an appropriate meal plan tailored to each user's health and emotional state, providing support in both health and emotional aspects.

[0144] "Dietary information" refers to data about the user's eating habits and nutritional intake.

[0145] "Emotional state" refers to the user's mental and emotional condition, and is information that is recognized and analyzed through the emotion engine.

[0146] "Meal history" refers to data that records the contents of meals a user has eaten in the past.

[0147] "Health data" refers to information about a user's health status, including their physical condition, medical history, and habits.

[0148] "Emotional information" refers to data about a user's emotional state, collected using methods such as voice, text, and facial expressions.

[0149] "Nutritional balance" refers to the appropriate distribution of nutrients necessary for the body and forms the basis of a healthy meal plan.

[0150] A "meal plan" is a detailed plan of meals suggested based on the user's health and emotional state.

[0151] A "food list" refers to a list of ingredients that need to be purchased based on the proposed meal plan.

[0152] "Dietary guidance" refers to advice and instructions for improving dietary habits, provided based on the user's health and emotional state.

[0153] "Encryption" is a technology that transforms data to ensure secure communication and prevent it from being leaked to third parties.

[0154] This invention is a system designed to support users in maintaining a healthy diet and emotional state. This system is constructed by combining technical elements such as terminals, servers, and generative AI models.

[0155] First, the user uses a device to input information about their diet and emotional state. The device utilizes voice input, text input, or facial recognition sensors to identify the user's emotional state via an emotion engine. This emotional information, along with the user's personal dietary information, is encrypted and sent to the server.

[0156] Next, the server decrypts the received data and securely stores it in a database. The server analyzes this data and generates an optimal meal plan for the user based on past eating history, health data, and emotional information. A generative AI model is used in this process to improve the accuracy and personalization of the plan.

[0157] For example, if a user enters "I'm feeling stressed," the server will suggest a menu featuring relaxing herbal teas and legumes. Furthermore, the generated meal plan includes a list of ingredients available at convenience stores, allowing the user to easily obtain the necessary ingredients.

[0158] The device ultimately displays meal plans, ingredient lists, and health advice sent from the server to the user. This makes it easier for the user to practice a diet that suits their current emotional state and health needs.

[0159] An example of a prompt message could be input to the generating AI model, such as, "Suggest the optimal meal plan if the user is experiencing stress." Using this prompt, it becomes possible to provide a specific and effective meal plan tailored to the user's condition.

[0160] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0161] Step 1:

[0162] The user inputs information about their eating habits and emotional state through the device. At this time, the device uses voice input, text input, or facial recognition sensors to analyze the actual emotional state using an emotion engine, obtaining the user's emotional data. After the input information is processed, it is packaged and sent to the server.

[0163] Step 2:

[0164] The server receives data sent from the user and decrypts the input information using an encrypted method. This secured data is stored in a database and prepared for subsequent analysis steps.

[0165] Step 3:

[0166] The server uses a generative AI model to analyze stored meal history, health data, and even emotional information. This prompt uses specific instructions to the AI ​​model, such as "Suggest a meal plan best suited to the user's current stress levels." This analysis step generates a meal plan that is most appropriate for the individual's needs.

[0167] Step 4:

[0168] The server considers nutritional balance and emotional state to generate an optimal meal plan and a list of available ingredients for the user. The output includes suggestions for nutritious meals tailored to a specific emotional state, along with a list of ingredients.

[0169] Step 5:

[0170] The device displays meal plans, ingredient lists, and health advice sent from the server to the user. This allows users to practice a diet tailored to their individual health and emotional needs and achieve the desired results.

[0171] (Application Example 2)

[0172] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0173] There is a lack of systems that can automatically provide healthy eating suggestions that take into account the user's emotional state. In particular, there is a need for a means to suggest appropriate meal plans according to different emotional states, thereby simultaneously supporting the user's mental and physical health.

[0174] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0175] In this invention, the server includes means for inputting dietary information, means for analyzing past meal history and health data, and means for recognizing and analyzing emotions. This makes it possible to provide an optimal meal plan based on the user's emotional state.

[0176] "Means for inputting dietary information" refers to an interface for users to register information about their own diet in the system.

[0177] "Methods for analyzing past dietary history and health data" refers to the process of analyzing data related to a user's past eating records and health status to extract trends and patterns.

[0178] "A means of generating meal plans based on nutritional balance" refers to a function that designs the optimal combination of meals, taking into account the nutrients the user needs.

[0179] "Means for recognizing and analyzing emotions" refers to technologies that identify a user's emotional state from their voice, facial expressions, etc., and perform analysis based on that data.

[0180] "A method for generating meal plans that take into account the user's emotional state" refers to a process that takes emotional data into consideration and proposes meal content that promotes the emotional state desired by the user.

[0181] "A means of outputting a list of selected ingredients" refers to a method of presenting the user with a list of ingredients that can be purchased based on the generated meal plan.

[0182] "A means of providing dietary guidance based on emotions according to health status" refers to a function that provides appropriate dietary and lifestyle advice tailored to the user's current health status and emotions.

[0183] The system that realizes this invention consists of a user, a server, and a terminal. The user first inputs dietary information using the terminal. This terminal is equipped with voice input and a camera and operates to identify the user's emotional state. Emotion recognition software is used for emotion recognition.

[0184] The server receives encrypted information sent by users and stores and analyzes meal history and health data. The server is equipped with software for performing data analysis and predictive modeling; for example, a database management system is used for data analysis, and machine learning libraries such as TensorFlow are applied to predictive models.

[0185] This allows the server to consider the user's emotions and health status and generate an optimal meal plan. This meal plan suggests menus containing specific nutrients to improve emotions. The generated meal plan, along with a list of ingredients available at convenience stores, is sent to the user's device and presented to them.

[0186] For example, if a user is feeling stressed, the server generates a menu containing ingredients that promote relaxation and suggests this list to the user via their device. This allows the user to easily prepare a meal that suits their situation.

[0187] An example of a prompt for a generative AI model is, "What foods are recommended when a user feels tired?" Based on this prompt, an appropriate meal plan is dynamically generated.

[0188] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0189] Step 1:

[0190] The device receives dietary information and emotional states from the user. The user provides information about their emotions and health to the device using voice commands, text input, or facial recognition. This input data is collected as initial data.

[0191] Step 2:

[0192] The server receives information sent from the terminal and encrypts the data to protect it. The server receives the encrypted data, stores it in a secure environment, and decrypts it for use when necessary. This data serves as foundational data for use in later steps.

[0193] Step 3:

[0194] The server analyzes the received data and retrieves past meal history and health data from the database. Using this data, the server analyzes trends in the user's eating habits and health status, and integrates this with current emotional data. A database management system is used for the analysis.

[0195] Step 4:

[0196] The server uses an emotion recognition module to analyze the user's current emotional state. Voice and facial expression analysis software is used to quantify the user's emotions and record the identified emotion values. This data is used to optimize meal plans.

[0197] Step 5:

[0198] The server uses a generative AI model to generate an optimal meal plan based on emotional and health data. The model takes the collected data as input and suggests ingredients and menus that promote positive emotional changes. The output is a specific meal plan that takes nutritional balance into consideration.

[0199] Step 6:

[0200] The server reconstructs the meal plan it generates and sends a list of available ingredients as output data to the user's terminal. The user can receive this specific ingredient list through their terminal and arrange for the necessary ingredients based on this list.

[0201] Step 7:

[0202] Users use their devices to refer to the received ingredient list and meal plan, and then follow the suggested menu. By following the meal plan, users can improve their daily eating habits.

[0203] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0204] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0205] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0206] [Second Embodiment]

[0207] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0208] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0209] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0210] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0211] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0212] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0213] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0214] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0215] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0216] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0217] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0218] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0219] This invention is a system that provides users with a well-balanced meal plan using ingredients readily available at convenience stores, enabling them to maintain healthy eating habits. The system takes user dietary information as input, analyzes past meal history and health data, and automatically generates a meal plan based on nutritional balance.

[0220] The server is responsible for generating this meal plan, receiving and analyzing the user's meal history and health data. Furthermore, the server generates a nutritionally balanced meal plan and creates a list of ingredients based on it. The generated plan is then customized according to the user's nutritional needs.

[0221] This system also includes a function to provide dietary guidance tailored to the user's health condition. Specifically, the server analyzes the user's health status and provides appropriate advice based on that analysis. This advice includes suggestions on how to supplement necessary nutrients and which foods to avoid.

[0222] The terminal transmits user-inputted information to a server, receives the processing results, and presents them to the user. Users can purchase ingredients at a convenience store according to the provided meal plan and easily prepare the meal. The terminal also displays the recipe along with the meal plan, guiding the user on how to cook.

[0223] For example, if a user enters their eating history and indicates that they are "easily fatigued" as their recent physical condition, the server will perform an analysis based on this information. If it determines that the user is lacking essential nutrients, it will suggest a meal plan that includes iron-rich foods and present it to the user via their device along with the recipe. In this way, the present invention helps users easily adopt a healthy diet.

[0224] The following describes the processing flow.

[0225] Step 1:

[0226] Users access a dietary information form on their device and enter their eating history, allergy information, health condition, etc. This information is then sent to the system as data.

[0227] Step 2:

[0228] The terminal encrypts the information entered by the user as a security measure and sends it to the server. The encrypted data is communicated using a secure protocol.

[0229] Step 3:

[0230] The server decrypts the received data and stores it in the database. Here, the information is organized for each user, and management is performed to maintain data integrity.

[0231] Step 4:

[0232] The server analyzes the original data and uses nutritional algorithms to assess the user's nutritional needs. This analysis identifies necessary nutrients and dietary trends.

[0233] Step 5:

[0234] The server generates a nutritionally balanced meal plan based on the analysis results. This plan is customized according to the user's health condition and dietary preferences.

[0235] Step 6:

[0236] The server creates a shopping list of items that can be purchased at a convenience store based on the ingredients included in the meal plan. At the same time, it calculates the calorie and nutritional details of the suggested meals.

[0237] Step 7:

[0238] The server sends the generated meal plan, shopping list, and nutritional information to the device. This information also includes health advice.

[0239] Step 8:

[0240] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and prepare a meal according to the suggested recipe.

[0241] (Example 1)

[0242] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0243] In today's lifestyle, it is difficult for individuals to maintain healthy eating habits. Lack of time and insufficient knowledge about food selection make it challenging to prepare nutritionally balanced meals. Furthermore, there is a need for a system that effectively provides nutrients tailored to the user's health condition.

[0244] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0245] In this invention, the server includes means for inputting dietary habit data, means for analyzing past eating and drinking history and health status data, and means for generating a meal plan based on nutritional balance. This enables users to be provided with appropriate nutrients according to their health status and to achieve a balanced diet using readily available ingredients.

[0246] "Dietary habit data" refers to data that represents information about a user's daily eating habits.

[0247] "Dining history" refers to a record of food and drinks that a user has consumed in the past.

[0248] "Health status data" refers to data that includes information about the user's physical condition and health.

[0249] "Nutritional balance" refers to a state in which the body is consuming the necessary nutrients in a balanced manner.

[0250] A "dining plan" refers to a meal menu and structure designed to suit a specific purpose or condition.

[0251] A "food ingredient list" refers to a list of ingredients needed for a specific dish or dining plan.

[0252] A "cooking method" is a set of instructions that shows how to cook specific ingredients and complete a dish.

[0253] A "generative AI model" is an artificial intelligence model that uses a large amount of data to derive the optimal solution for a specific purpose.

[0254] In this invention, the server plays a central role. The server is equipped with a processor and storage to receive dietary habit data entered by the user. The server stores this data and analyzes the user's eating history and health status data. Data processing libraries such as Python and R are used for the analysis.

[0255] The server uses a generative AI model to evaluate past eating patterns and automatically generate meal plans based on nutritional balance. The generated meal plans include a list of selected ingredients and corresponding cooking methods. This allows users to easily create balanced meals using readily available ingredients.

[0256] Users input their eating habits data using a device. The entered data is encrypted on the device and securely transmitted to the server. The device displays the meal plan and cooking methods received from the server, providing users with specific guidance on their eating habits.

[0257] For example, if a user enters information about their health, such as "I've been feeling tired lately," into their device and sends it, the server analyzes this information and generates a meal plan centered around foods rich in iron and vitamins. The device displays cooking instructions for dishes like "blanched spinach" and "liver dishes," along with a list of ingredients that should be purchased.

[0258] An example of a prompt message would be, "Consider the user's recent health data and generate a meal plan that includes the necessary nutrients." This process allows users to efficiently engage in healthy eating and drinking behaviors.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The user inputs dietary habit data and health status data using a terminal. This data includes detailed information about their current diet and physical condition. The terminal converts this data into a predetermined format and prepares it for secure transmission to the server. The input includes text information about health status and a list of specific foods.

[0262] Step 2:

[0263] The terminal encrypts the input data using protocols such as SSL / TLS and sends it to the server. This reduces the risk of data leakage. As output, the server securely receives the encrypted data.

[0264] Step 3:

[0265] The server analyzes the received data. First, it deserializes the data to identify the user's past eating and drinking history and current health status. It preprocesses the data using the Python Pandas library and formats it into a dataframe. The analysis identifies any nutrient deficiencies necessary for creating a new eating and drinking plan.

[0266] Step 4:

[0267] The server uses a generation AI model to generate a nutritionally balanced meal plan based on the analysis results obtained. The model has learned from past data patterns and is ready to suggest the most suitable ingredient list and cooking method for the user. As output, the meal plan is generated in digital format.

[0268] Step 5:

[0269] The server sends the generated meal plan and corresponding ingredient list to the terminal. The data is encrypted again and securely delivered to the recipient's intended device. As output, the terminal receives the data and prepares for the next step.

[0270] Step 6:

[0271] The terminal displays the received dining plan and provides the user with a detailed operating guide. Cooking instructions and a list of ingredients to purchase are clearly displayed on the screen, allowing the user to proceed with shopping at the store and cooking based on this information. The output is that the user has purchased the ingredients according to the plan and prepared for cooking.

[0272] (Application Example 1)

[0273] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] In today's fast-paced lifestyle, maintaining healthy eating habits is not easy for individuals. To address this challenge, a system is needed that provides meal plans tailored to individual health conditions and offers concrete support throughout the process of food selection, purchasing, and cooking. However, many existing systems are limited to user-dependent information provision and simple meal suggestions, and currently lack comprehensive support to enable users to consistently engage in healthy food consumption.

[0275] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0276] In this invention, the server includes a device for inputting food consumption behavior information, a device for analyzing past food consumption history and health information, and a device for generating meal plans based on nutritional balance. This enables the automatic generation of food consumption plans optimized for individual users, and further allows for purchase assistance through an automated, remotely operated humanoid device. This supports the entire process, from selecting and purchasing food ingredients to cooking, providing comprehensive lifestyle management support for maintaining good health. Furthermore, by providing detailed visual and audio guidance on cooking procedures, users can easily complete healthy meals.

[0277] The "Food Consumption Behavior Information Input Device" is a device for receiving and recording information on food consumption from users.

[0278] The "Food Consumption History Analysis Device" is a device for collecting and analyzing past food consumption history data.

[0279] The "Health Information Analysis Device" is a device for analyzing and evaluating data related to the health status of users.

[0280] The "Meal Plan Generation Device" is a device for creating an optimized meal plan for each individual user considering nutritional balance.

[0281] The "Food Ingredients List Output Device" is a device for outputting the necessary food ingredients as a list based on the meal plan.

[0282] The "Food Consumption Guidance Providing Device" is a device for providing guidance on diet and nutrition according to the health status of users and supporting the improvement of lifestyle habits.

[0283] The "Automated Humanoid Remote Operating Equipment Control Device" is a device for operating based on user instructions and controlling an automated humanoid device to assist in the food purchase process.

[0284] The "Visual and Audio Cooking Procedure Guidance Device" is a device for guiding the cooking procedure to the user visually and audibly and supporting the completion of cooking.

[0285] This invention is a system that utilizes food consumption behavior information to support users' healthy eating habits. The server collects daily food consumption data of users through a food consumption behavior information input device. Users input their own food consumption history and health information using terminals such as smartphones and tablets. This data is sent to the server in real-time and analyzed in detail by a food consumption history analysis device and a health information analysis device. The server uses hardware such as NVIDIA Jetson Orin and Raspberry Pi and software such as Python and TensorFlow to perform data processing.

[0286] Based on the analysis, the meal plan generation device utilizes a generation AI model to automatically create a meal plan that suits the user's health condition. A list of required food ingredients is generated through a food ingredient list output device and presented to the user. This system can flexibly customize the plan according to the user's preferences and constraints.

[0287] Furthermore, an automated humanoid remote operation device is used to support the user's food purchasing process. This device is designed to be easily operated by the user and selects and purchases food based on the meal plan. After the purchase is completed, a visual and voice cooking procedure guidance device guides the user in detail through the cooking procedure. The cooking guide is provided through visual information and voice guidance, enabling the user to easily cook healthy meals.

[0288] As a specific example, the user inputs their own health condition as "easily fatigued", and based on the generated data, the server proposes a meal plan containing iron. Examples of prompt sentences in this case include "Please propose a balanced meal for an easily fatigued state." and "Please teach me an appropriate recipe for iron supplementation." Thus, the user can efficiently摄取 the necessary nutrients and strive to maintain their health.

[0289] The flow of specific processing in Application Example 1 will be described using FIG. 12.

[0290] Step 1:

[0291] The terminal receives input from the user and collects data on food consumption behavior and health status. This input data includes information on the type and quantity of food consumed, the time of consumption, and the user's current health status. This information will be transmitted from the input device, such as a smartphone or tablet, to the server.

[0292] Step 2:

[0293] The server sends the received user input data to a food consumption history analysis device, which analyzes past food consumption history and current health information. This process uses a database to search the user's historical data and applies machine learning algorithms to assess their current health status. This results in the output of information about imbalances in nutrient intake.

[0294] Step 3:

[0295] The server uses a meal plan generator to create a meal plan that takes nutritional balance into consideration. In this step, a generation AI model is used to generate an optimal meal plan that reflects the user's preferences and health goals, based on the analysis results from step 2. The meal plan created here includes the necessary food ingredients and their quantities, so a list of specific food ingredients is output.

[0296] Step 4:

[0297] The terminal displays a meal plan and a list of food ingredients received from the server to the user. Here, a visually easy-to-understand interface is used to display the list of ingredients and recommended recipes, and voice guidance is provided to the user to encourage healthy food consumption.

[0298] Step 5:

[0299] The user reviews the presented meal plan and ingredients, and, if necessary, initiates food purchase assistance using an automated humanoid remote-controlled device. The automated humanoid remote-controlled device physically assists with ingredient selection and purchase, and reports the purchased ingredients to the user after the purchase is complete.

[0300] Step 6:

[0301] The device guides the user through cooking instructions via visual and audio guidance. Specifically, it provides detailed and easy-to-understand explanations of each cooking step, follows the cooking process in real time, and helps the user complete a healthy meal. At this stage, it provides prompts to help the user follow the appropriate cooking procedures, supporting a smooth user experience.

[0302] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0303] This invention is a system that combines an emotional engine with ingredients available at convenience stores, with the aim of helping users maintain a healthy diet. Through this, it aims to provide meal plans tailored to the user's emotional state and improve the quality of their diet.

[0304] First, the user inputs information about their diet and physical condition through the device. At this time, the emotion engine recognizes the user's emotions and identifies their current mood. Emotion recognition is achieved by using voice input, text input, and sensors that analyze facial expressions on the screen.

[0305] The server receives data entered by the user, decrypts the encrypted information, and stores it in a database. Next, the server analyzes the stored meal history and health data, incorporates emotional information from the emotion engine, and generates an optimal meal plan for the user. This meal plan is tailored to evoke positive emotions, taking into account the user's emotional state in particular.

[0306] The generated meal plan includes suggestions for dishes considering nutritional balance, and provides a list of ingredients that can be purchased at convenience stores. Furthermore, it also includes specific dietary guidance according to emotions. For example, when the user is feeling stressed, a diet containing ingredients with a relaxing effect is recommended.

[0307] The terminal presents the user with the meal plan and ingredient list sent from the server, as well as advice on health. This enables the user to easily practice a diet suitable for their current condition and achieve emotional stability. As a specific example, when the emotion engine senses that the user is "feeling down", a recipe using specific ingredients that promote serotonin production is recommended to enhance happiness.

[0308] Thus, the present invention provides a system that supports both the emotional and health aspects by adapting to the user's emotions.

[0309] The processing flow will be described below.

[0310] Step 1:

[0311] The user accesses a form for inputting dietary information and health status on the terminal. This input includes daily meal history, physical condition, health goals the user seeks, etc. Furthermore, the user selects options for expressing emotions or utilizes the function of analyzing voice or expressions to input the current emotional state.

[0312] Step 2:

[0313] The terminal encrypts the dietary information and emotional data input by the user and transmits them to the server using a secure communication protocol.

[0314] Step 3:

[0315] The server decrypts the received data and stores it in a database for each user. The stored data includes individual meal histories and emotional states.

[0316] Step 4:

[0317] The server analyzes user data in the database and evaluates emotional information using an emotion engine. This allows it to consider the impact of emotional states on diet and understand individual nutritional needs.

[0318] Step 5:

[0319] Based on the analysis results, the server generates a meal plan tailored to the user's nutritional balance and emotional state. For example, if a user is feeling stressed, the server will create a plan that includes ingredients and recipes suitable for relieving that stress.

[0320] Step 6:

[0321] The server creates a list of ingredients included in the generated meal plan and verifies whether these ingredients are available for purchase at convenience stores. The meal plan also includes dietary guidance to address the user's emotional needs.

[0322] Step 7:

[0323] The server sends the final meal plan, ingredient list, and health and emotional advice to the device.

[0324] Step 8:

[0325] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and cook at home. This process is designed to support both the user's emotional well-being and health.

[0326] (Example 2)

[0327] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0328] In today's busy lifestyle, many people find it difficult to maintain both a healthy diet and emotional stability simultaneously. In particular, there is a lack of readily available options for choosing meals that consider both nutritional balance and emotional state. A system is needed to address this problem and provide healthy meals that adapt to individual emotional needs.

[0329] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0330] In this invention, the server includes means for inputting dietary information and emotional state, means for analyzing past meal history, health data, and emotional information, and means for generating a meal plan based on nutritional balance and emotional state. This enables the provision of an appropriate meal plan tailored to each user's health and emotional state, providing support in both health and emotional aspects.

[0331] "Dietary information" refers to data about the user's eating habits and nutritional intake.

[0332] "Emotional state" refers to the user's mental and emotional condition, and is information that is recognized and analyzed through the emotion engine.

[0333] "Meal history" refers to data that records the contents of meals a user has eaten in the past.

[0334] "Health data" refers to information about a user's health status, including their physical condition, medical history, and habits.

[0335] "Emotional information" refers to data about a user's emotional state, collected using methods such as voice, text, and facial expressions.

[0336] "Nutritional balance" refers to the appropriate distribution of nutrients necessary for the body and forms the basis of a healthy meal plan.

[0337] A "meal plan" is a detailed plan of meals suggested based on the user's health and emotional state.

[0338] A "food list" refers to a list of ingredients that need to be purchased based on the proposed meal plan.

[0339] "Dietary guidance" refers to advice and instructions for improving dietary habits, provided based on the user's health and emotional state.

[0340] "Encryption" is a technology that transforms data to ensure secure communication and prevent it from being leaked to third parties.

[0341] This invention is a system designed to support users in maintaining a healthy diet and emotional state. This system is constructed by combining technical elements such as terminals, servers, and generative AI models.

[0342] First, the user uses a device to input information about their diet and emotional state. The device utilizes voice input, text input, or facial recognition sensors to identify the user's emotional state via an emotion engine. This emotional information, along with the user's personal dietary information, is encrypted and sent to the server.

[0343] Next, the server decrypts the received data and securely stores it in a database. The server analyzes this data and generates an optimal meal plan for the user based on past eating history, health data, and emotional information. A generative AI model is used in this process to improve the accuracy and personalization of the plan.

[0344] For example, if a user enters "I'm feeling stressed," the server will suggest a menu featuring relaxing herbal teas and legumes. Furthermore, the generated meal plan includes a list of ingredients available at convenience stores, allowing the user to easily obtain the necessary ingredients.

[0345] The device ultimately displays meal plans, ingredient lists, and health advice sent from the server to the user. This makes it easier for the user to practice a diet that suits their current emotional state and health needs.

[0346] An example of a prompt message could be input to the generating AI model, such as, "Suggest the optimal meal plan if the user is experiencing stress." Using this prompt, it becomes possible to provide a specific and effective meal plan tailored to the user's condition.

[0347] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0348] Step 1:

[0349] The user inputs information about their eating habits and emotional state through the device. At this time, the device uses voice input, text input, or facial recognition sensors to analyze the actual emotional state using an emotion engine, obtaining the user's emotional data. After the input information is processed, it is packaged and sent to the server.

[0350] Step 2:

[0351] The server receives data sent from the user and decrypts the input information using an encrypted method. This secured data is stored in a database and prepared for subsequent analysis steps.

[0352] Step 3:

[0353] The server uses a generative AI model to analyze stored meal history, health data, and even emotional information. This prompt uses specific instructions to the AI ​​model, such as "Suggest a meal plan best suited to the user's current stress levels." This analysis step generates a meal plan that is most appropriate for the individual's needs.

[0354] Step 4:

[0355] The server considers nutritional balance and emotional state to generate an optimal meal plan and a list of available ingredients for the user. The output includes suggestions for nutritious meals tailored to a specific emotional state, along with a list of ingredients.

[0356] Step 5:

[0357] The device displays meal plans, ingredient lists, and health advice sent from the server to the user. This allows users to practice a diet tailored to their individual health and emotional needs and achieve the desired results.

[0358] (Application Example 2)

[0359] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0360] There is a lack of systems that can automatically provide healthy eating suggestions that take into account the user's emotional state. In particular, there is a need for a means to suggest appropriate meal plans according to different emotional states, thereby simultaneously supporting the user's mental and physical health.

[0361] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0362] In this invention, the server includes means for inputting dietary information, means for analyzing past meal history and health data, and means for recognizing and analyzing emotions. This makes it possible to provide an optimal meal plan based on the user's emotional state.

[0363] "Means for inputting dietary information" refers to an interface for users to register information about their own diet in the system.

[0364] "Methods for analyzing past dietary history and health data" refers to the process of analyzing data related to a user's past eating records and health status to extract trends and patterns.

[0365] "A means of generating meal plans based on nutritional balance" refers to a function that designs the optimal combination of meals, taking into account the nutrients the user needs.

[0366] "Means for recognizing and analyzing emotions" refers to technologies that identify a user's emotional state from their voice, facial expressions, etc., and perform analysis based on that data.

[0367] "A method for generating meal plans that take into account the user's emotional state" refers to a process that takes emotional data into consideration and proposes meal content that promotes the emotional state desired by the user.

[0368] "A means of outputting a list of selected ingredients" refers to a method of presenting the user with a list of ingredients that can be purchased based on the generated meal plan.

[0369] "A means of providing dietary guidance based on emotions according to health status" refers to a function that provides appropriate dietary and lifestyle advice tailored to the user's current health status and emotions.

[0370] The system that realizes this invention consists of a user, a server, and a terminal. The user first inputs dietary information using the terminal. This terminal is equipped with voice input and a camera and operates to identify the user's emotional state. Emotion recognition software is used for emotion recognition.

[0371] The server receives encrypted information sent by users and stores and analyzes meal history and health data. The server is equipped with software for performing data analysis and predictive modeling; for example, a database management system is used for data analysis, and machine learning libraries such as TensorFlow are applied to predictive models.

[0372] This allows the server to consider the user's emotions and health status and generate an optimal meal plan. This meal plan suggests menus containing specific nutrients to improve emotions. The generated meal plan, along with a list of ingredients available at convenience stores, is sent to the user's device and presented to them.

[0373] For example, if a user is feeling stressed, the server generates a menu containing ingredients that promote relaxation and suggests this list to the user via their device. This allows the user to easily prepare a meal that suits their situation.

[0374] An example of a prompt for a generative AI model is, "What foods are recommended when a user feels tired?" Based on this prompt, an appropriate meal plan is dynamically generated.

[0375] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0376] Step 1:

[0377] The device receives dietary information and emotional states from the user. The user provides information about their emotions and health to the device using voice commands, text input, or facial recognition. This input data is collected as initial data.

[0378] Step 2:

[0379] The server receives information sent from the terminal and encrypts the data to protect it. The server receives the encrypted data, stores it in a secure environment, and decrypts it for use when necessary. This data serves as foundational data for use in later steps.

[0380] Step 3:

[0381] The server analyzes the received data and retrieves past meal history and health data from the database. Using this data, the server analyzes trends in the user's eating habits and health status, and integrates this with current emotional data. A database management system is used for the analysis.

[0382] Step 4:

[0383] The server uses an emotion recognition module to analyze the user's current emotional state. Voice and facial expression analysis software is used to quantify the user's emotions and record the identified emotion values. This data is used to optimize meal plans.

[0384] Step 5:

[0385] The server uses a generative AI model to generate an optimal meal plan based on emotional and health data. The model takes the collected data as input and suggests ingredients and menus that promote positive emotional changes. The output is a specific meal plan that takes nutritional balance into consideration.

[0386] Step 6:

[0387] The server reconstructs the meal plan it generates and sends a list of available ingredients as output data to the user's terminal. The user can receive this specific ingredient list through their terminal and arrange for the necessary ingredients based on this list.

[0388] Step 7:

[0389] Users use their devices to refer to the received ingredient list and meal plan, and then follow the suggested menu. By following the meal plan, users can improve their daily eating habits.

[0390] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0391] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0392] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0393] [Third Embodiment]

[0394] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0395] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0396] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0397] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0398] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0399] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0400] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0401] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0402] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0403] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0404] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0405] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0406] This invention is a system that provides users with a well-balanced meal plan using ingredients readily available at convenience stores, enabling them to maintain healthy eating habits. The system takes user dietary information as input, analyzes past meal history and health data, and automatically generates a meal plan based on nutritional balance.

[0407] The server is responsible for generating this meal plan, receiving and analyzing the user's meal history and health data. Furthermore, the server generates a nutritionally balanced meal plan and creates a list of ingredients based on it. The generated plan is then customized according to the user's nutritional needs.

[0408] This system also includes a function to provide dietary guidance tailored to the user's health condition. Specifically, the server analyzes the user's health status and provides appropriate advice based on that analysis. This advice includes suggestions on how to supplement necessary nutrients and which foods to avoid.

[0409] The terminal transmits user-inputted information to a server, receives the processing results, and presents them to the user. Users can purchase ingredients at a convenience store according to the provided meal plan and easily prepare the meal. The terminal also displays the recipe along with the meal plan, guiding the user on how to cook.

[0410] For example, if a user enters their eating history and indicates that they are "easily fatigued" as their recent physical condition, the server will perform an analysis based on this information. If it determines that the user is lacking essential nutrients, it will suggest a meal plan that includes iron-rich foods and present it to the user via their device along with the recipe. In this way, the present invention helps users easily adopt a healthy diet.

[0411] The following describes the processing flow.

[0412] Step 1:

[0413] Users access a dietary information form on their device and enter their eating history, allergy information, health condition, etc. This information is then sent to the system as data.

[0414] Step 2:

[0415] The terminal encrypts the information entered by the user as a security measure and sends it to the server. The encrypted data is communicated using a secure protocol.

[0416] Step 3:

[0417] The server decrypts the received data and stores it in the database. Here, the information is organized for each user, and management is performed to maintain data integrity.

[0418] Step 4:

[0419] The server analyzes the original data and uses nutritional algorithms to assess the user's nutritional needs. This analysis identifies necessary nutrients and dietary trends.

[0420] Step 5:

[0421] The server generates a nutritionally balanced meal plan based on the analysis results. This plan is customized according to the user's health condition and dietary preferences.

[0422] Step 6:

[0423] The server creates a shopping list of items that can be purchased at a convenience store based on the ingredients included in the meal plan. At the same time, it calculates the calorie and nutritional details of the suggested meals.

[0424] Step 7:

[0425] The server sends the generated meal plan, shopping list, and nutritional information to the device. This information also includes health advice.

[0426] Step 8:

[0427] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and prepare a meal according to the suggested recipe.

[0428] (Example 1)

[0429] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0430] In today's lifestyle, it is difficult for individuals to maintain healthy eating habits. Lack of time and insufficient knowledge about food selection make it challenging to prepare nutritionally balanced meals. Furthermore, there is a need for a system that effectively provides nutrients tailored to the user's health condition.

[0431] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0432] In this invention, the server includes means for inputting dietary habit data, means for analyzing past eating and drinking history and health status data, and means for generating a meal plan based on nutritional balance. This enables users to be provided with appropriate nutrients according to their health status and to achieve a balanced diet using readily available ingredients.

[0433] "Dietary habit data" refers to data that represents information about a user's daily eating habits.

[0434] "Dining history" refers to a record of food and drinks that a user has consumed in the past.

[0435] "Health status data" refers to data that includes information about the user's physical condition and health.

[0436] "Nutritional balance" refers to a state in which the body is consuming the necessary nutrients in a balanced manner.

[0437] A "dining plan" refers to a meal menu and structure designed to suit a specific purpose or condition.

[0438] A "food ingredient list" refers to a list of ingredients needed for a specific dish or dining plan.

[0439] A "cooking method" is a set of instructions that shows how to cook specific ingredients and complete a dish.

[0440] A "generative AI model" is an artificial intelligence model that uses a large amount of data to derive the optimal solution for a specific purpose.

[0441] In this invention, the server plays a central role. The server is equipped with a processor and storage to receive dietary habit data entered by the user. The server stores this data and analyzes the user's eating history and health status data. Data processing libraries such as Python and R are used for the analysis.

[0442] The server uses a generative AI model to evaluate past eating patterns and automatically generate meal plans based on nutritional balance. The generated meal plans include a list of selected ingredients and corresponding cooking methods. This allows users to easily create balanced meals using readily available ingredients.

[0443] Users input their eating habits data using a device. The entered data is encrypted on the device and securely transmitted to the server. The device displays the meal plan and cooking methods received from the server, providing users with specific guidance on their eating habits.

[0444] For example, if a user enters information about their health, such as "I've been feeling tired lately," into their device and sends it, the server analyzes this information and generates a meal plan centered around foods rich in iron and vitamins. The device displays cooking instructions for dishes like "blanched spinach" and "liver dishes," along with a list of ingredients that should be purchased.

[0445] An example of a prompt message would be, "Consider the user's recent health data and generate a meal plan that includes the necessary nutrients." This process allows users to efficiently engage in healthy eating and drinking behaviors.

[0446] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0447] Step 1:

[0448] The user inputs dietary habit data and health status data using a terminal. This data includes detailed information about their current diet and physical condition. The terminal converts this data into a predetermined format and prepares it for secure transmission to the server. The input includes text information about health status and a list of specific foods.

[0449] Step 2:

[0450] The terminal encrypts the input data using protocols such as SSL / TLS and sends it to the server. This reduces the risk of data leakage. As output, the server securely receives the encrypted data.

[0451] Step 3:

[0452] The server analyzes the received data. First, it deserializes the data to identify the user's past eating and drinking history and current health status. It preprocesses the data using the Python Pandas library and formats it into a dataframe. The analysis identifies any nutrient deficiencies necessary for creating a new eating and drinking plan.

[0453] Step 4:

[0454] The server uses a generation AI model to generate a nutritionally balanced meal plan based on the analysis results obtained. The model has learned from past data patterns and is ready to suggest the most suitable ingredient list and cooking method for the user. As output, the meal plan is generated in digital format.

[0455] Step 5:

[0456] The server sends the generated meal plan and corresponding ingredient list to the terminal. The data is encrypted again and securely delivered to the recipient's intended device. As output, the terminal receives the data and prepares for the next step.

[0457] Step 6:

[0458] The terminal displays the received dining plan and provides the user with a detailed operating guide. Cooking instructions and a list of ingredients to purchase are clearly displayed on the screen, allowing the user to proceed with shopping at the store and cooking based on this information. The output is that the user has purchased the ingredients according to the plan and prepared for cooking.

[0459] (Application Example 1)

[0460] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0461] In today's fast-paced lifestyle, maintaining healthy eating habits is not easy for individuals. To address this challenge, a system is needed that provides meal plans tailored to individual health conditions and offers concrete support throughout the process of food selection, purchasing, and cooking. However, many existing systems are limited to user-dependent information provision and simple meal suggestions, and currently lack comprehensive support to enable users to consistently engage in healthy food consumption.

[0462] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0463] In this invention, the server includes a device for inputting food consumption behavior information, a device for analyzing past food consumption history and health information, and a device for generating meal plans based on nutritional balance. This enables the automatic generation of food consumption plans optimized for individual users, and further allows for purchase assistance through an automated, remotely operated humanoid device. This supports the entire process, from selecting and purchasing food ingredients to cooking, providing comprehensive lifestyle management support for maintaining good health. Furthermore, by providing detailed visual and audio guidance on cooking procedures, users can easily complete healthy meals.

[0464] A "food consumption behavior information input device" is a device for receiving and recording information about food consumption from users.

[0465] A "food consumption history analysis device" is a device that collects and analyzes past food consumption history data.

[0466] A "health information analysis device" is a device that analyzes and evaluates data related to a user's health status.

[0467] A "meal plan generator" is a device that creates a meal plan optimized for each individual user, taking nutritional balance into consideration.

[0468] A "food ingredient list output device" is a device that outputs a list of necessary food ingredients based on a meal plan.

[0469] A "food consumption guidance device" is a device that provides guidance on diet and nutrition tailored to the user's health condition, supporting improvements in lifestyle habits.

[0470] An "automated humanoid remote-controlled device control system" is a device that controls an automated humanoid device that operates based on user instructions and assists in the food purchasing process.

[0471] A "visual and audio cooking procedure guidance device" is a device that guides users through cooking procedures using visual and audio means, and supports them in completing a dish.

[0472] This invention is a system that supports users' healthy eating habits by utilizing food consumption behavior information. The server collects the user's daily food consumption data through a food consumption behavior information input device. Users input their food consumption history and health information using devices such as smartphones and tablets. This data is transmitted to the server in real time and analyzed in detail by a food consumption history analysis device and a health information analysis device. The server uses hardware such as NVIDIA Jetson Orin and Raspberry Pi, and processes the data using software such as Python and TensorFlow.

[0473] Based on the analysis, the meal plan generator utilizes a generation AI model to automatically create a meal plan tailored to the user's health condition. A list of necessary food ingredients is generated and presented to the user via a food ingredient list output device. This system can flexibly customize the plan according to the user's preferences and constraints.

[0474] Furthermore, an automated, humanoid, remotely operated device is used to assist the user in the food purchasing process. This device is designed for easy user operation and allows users to select and purchase food based on their meal plan. After the purchase is complete, a visual and audio cooking instruction device guides the user through the cooking process in detail. The cooking guide is provided through visual information and audio guidance, allowing users to easily prepare healthy meals.

[0475] As a concrete example, a user might input "easily fatigued" as their health condition, and the server would then suggest a meal plan containing iron based on the generated data. Examples of prompts in this process include, "Please suggest a balanced meal plan for my easily fatigued condition," or "Please provide appropriate recipes for iron supplementation." This allows users to efficiently obtain the necessary nutrients and maintain their health.

[0476] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0477] Step 1:

[0478] The terminal receives input from the user and collects data on food consumption behavior and health status. This input data includes information on the type and quantity of food consumed, the time of consumption, and the user's current health status. This information will be transmitted from the input device, such as a smartphone or tablet, to the server.

[0479] Step 2:

[0480] The server sends the received user input data to a food consumption history analysis device, which analyzes past food consumption history and current health information. This process uses a database to search the user's historical data and applies machine learning algorithms to assess their current health status. This results in the output of information about imbalances in nutrient intake.

[0481] Step 3:

[0482] The server uses a meal plan generator to create a meal plan that takes nutritional balance into consideration. In this step, a generation AI model is used to generate an optimal meal plan that reflects the user's preferences and health goals, based on the analysis results from step 2. The meal plan created here includes the necessary food ingredients and their quantities, so a list of specific food ingredients is output.

[0483] Step 4:

[0484] The terminal displays a meal plan and a list of food ingredients received from the server to the user. Here, a visually easy-to-understand interface is used to display the list of ingredients and recommended recipes, and voice guidance is provided to the user to encourage healthy food consumption.

[0485] Step 5:

[0486] The user reviews the presented meal plan and ingredients, and, if necessary, initiates food purchase assistance using an automated humanoid remote-controlled device. The automated humanoid remote-controlled device physically assists with ingredient selection and purchase, and reports the purchased ingredients to the user after the purchase is complete.

[0487] Step 6:

[0488] The device guides the user through cooking instructions via visual and audio guidance. Specifically, it provides detailed and easy-to-understand explanations of each cooking step, follows the cooking process in real time, and helps the user complete a healthy meal. At this stage, it provides prompts to help the user follow the appropriate cooking procedures, supporting a smooth user experience.

[0489] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0490] This invention is a system that combines an emotional engine with ingredients available at convenience stores, with the aim of helping users maintain a healthy diet. Through this, it aims to provide meal plans tailored to the user's emotional state and improve the quality of their diet.

[0491] First, the user inputs information about their diet and physical condition through the device. At this time, the emotion engine recognizes the user's emotions and identifies their current mood. Emotion recognition is achieved by using voice input, text input, and sensors that analyze facial expressions on the screen.

[0492] The server receives data entered by the user, decrypts the encrypted information, and stores it in a database. Next, the server analyzes the stored meal history and health data, incorporates emotional information from the emotion engine, and generates an optimal meal plan for the user. This meal plan is tailored to evoke positive emotions, taking into account the user's emotional state in particular.

[0493] The generated meal plan includes suggestions for nutritionally balanced meals and a list of ingredients available at convenience stores. Furthermore, it includes specific dietary guidance tailored to the user's emotions. For example, if the user is feeling stressed, meals containing relaxing ingredients will be recommended.

[0494] The device presents the user with meal plans, ingredient lists, and health advice sent from the server. This allows users to easily adopt a diet tailored to their current state and promote emotional stability. For example, if the emotion engine detects that the user is feeling "depressed," it will recommend recipes using specific ingredients that promote serotonin production to enhance feelings of happiness.

[0495] Thus, the present invention provides a system that supports both emotional and physical aspects by adapting to the user's emotions.

[0496] The following describes the processing flow.

[0497] Step 1:

[0498] Users access a form on their device to input information about their eating habits and health status. This input includes daily meal history, physical condition, and personal health goals. Furthermore, they input their current emotional state by selecting options to express their emotions or by using voice or facial expression analysis functions.

[0499] Step 2:

[0500] The terminal encrypts the dietary information and emotional data entered by the user and transmits it to the server using a secure communication protocol.

[0501] Step 3:

[0502] The server decrypts the received data and stores it in a database for each user. The stored data includes individual meal histories and emotional states.

[0503] Step 4:

[0504] The server analyzes user data in the database and evaluates emotional information using an emotion engine. This allows it to consider the impact of emotional states on diet and understand individual nutritional needs.

[0505] Step 5:

[0506] Based on the analysis results, the server generates a meal plan tailored to the user's nutritional balance and emotional state. For example, if a user is feeling stressed, the server will create a plan that includes ingredients and recipes suitable for relieving that stress.

[0507] Step 6:

[0508] The server creates a list of ingredients included in the generated meal plan and verifies whether these ingredients are available for purchase at convenience stores. The meal plan also includes dietary guidance to address the user's emotional needs.

[0509] Step 7:

[0510] The server sends the final meal plan, ingredient list, and health and emotional advice to the device.

[0511] Step 8:

[0512] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and cook at home. This process is designed to support both the user's emotional well-being and health.

[0513] (Example 2)

[0514] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0515] In today's busy lifestyle, many people find it difficult to maintain both a healthy diet and emotional stability simultaneously. In particular, there is a lack of readily available options for choosing meals that consider both nutritional balance and emotional state. A system is needed to address this problem and provide healthy meals that adapt to individual emotional needs.

[0516] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0517] In this invention, the server includes means for inputting dietary information and emotional state, means for analyzing past meal history, health data, and emotional information, and means for generating a meal plan based on nutritional balance and emotional state. This enables the provision of an appropriate meal plan tailored to each user's health and emotional state, providing support in both health and emotional aspects.

[0518] "Dietary information" refers to data about the user's eating habits and nutritional intake.

[0519] "Emotional state" refers to the user's mental and emotional condition, and is information that is recognized and analyzed through the emotion engine.

[0520] "Meal history" refers to data that records the contents of meals a user has eaten in the past.

[0521] "Health data" refers to information about a user's health status, including their physical condition, medical history, and habits.

[0522] "Emotional information" refers to data about a user's emotional state, collected using methods such as voice, text, and facial expressions.

[0523] "Nutritional balance" refers to the appropriate distribution of nutrients necessary for the body and forms the basis of a healthy meal plan.

[0524] A "meal plan" is a detailed plan of meals suggested based on the user's health and emotional state.

[0525] A "food list" refers to a list of ingredients that need to be purchased based on the proposed meal plan.

[0526] "Dietary guidance" refers to advice and instructions for improving dietary habits, provided based on the user's health and emotional state.

[0527] "Encryption" is a technology that transforms data to ensure secure communication and prevent it from being leaked to third parties.

[0528] This invention is a system designed to support users in maintaining a healthy diet and emotional state. This system is constructed by combining technical elements such as terminals, servers, and generative AI models.

[0529] First, the user uses a device to input information about their diet and emotional state. The device utilizes voice input, text input, or facial recognition sensors to identify the user's emotional state via an emotion engine. This emotional information, along with the user's personal dietary information, is encrypted and sent to the server.

[0530] Next, the server decrypts the received data and securely stores it in a database. The server analyzes this data and generates an optimal meal plan for the user based on past eating history, health data, and emotional information. A generative AI model is used in this process to improve the accuracy and personalization of the plan.

[0531] For example, if a user enters "I'm feeling stressed," the server will suggest a menu featuring relaxing herbal teas and legumes. Furthermore, the generated meal plan includes a list of ingredients available at convenience stores, allowing the user to easily obtain the necessary ingredients.

[0532] The device ultimately displays meal plans, ingredient lists, and health advice sent from the server to the user. This makes it easier for the user to practice a diet that suits their current emotional state and health needs.

[0533] An example of a prompt message could be input to the generating AI model, such as, "Suggest the optimal meal plan if the user is experiencing stress." Using this prompt, it becomes possible to provide a specific and effective meal plan tailored to the user's condition.

[0534] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0535] Step 1:

[0536] The user inputs information about their eating habits and emotional state through the device. At this time, the device uses voice input, text input, or facial recognition sensors to analyze the actual emotional state using an emotion engine, obtaining the user's emotional data. After the input information is processed, it is packaged and sent to the server.

[0537] Step 2:

[0538] The server receives data sent from the user and decrypts the input information using an encrypted method. This secured data is stored in a database and prepared for subsequent analysis steps.

[0539] Step 3:

[0540] The server uses a generative AI model to analyze stored meal history, health data, and even emotional information. This prompt uses specific instructions to the AI ​​model, such as "Suggest a meal plan best suited to the user's current stress levels." This analysis step generates a meal plan that is most appropriate for the individual's needs.

[0541] Step 4:

[0542] The server considers nutritional balance and emotional state to generate an optimal meal plan and a list of available ingredients for the user. The output includes suggestions for nutritious meals tailored to a specific emotional state, along with a list of ingredients.

[0543] Step 5:

[0544] The device displays meal plans, ingredient lists, and health advice sent from the server to the user. This allows users to practice a diet tailored to their individual health and emotional needs and achieve the desired results.

[0545] (Application Example 2)

[0546] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0547] There is a lack of systems that can automatically provide healthy eating suggestions that take into account the user's emotional state. In particular, there is a need for a means to suggest appropriate meal plans according to different emotional states, thereby simultaneously supporting the user's mental and physical health.

[0548] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0549] In this invention, the server includes means for inputting dietary information, means for analyzing past meal history and health data, and means for recognizing and analyzing emotions. This makes it possible to provide an optimal meal plan based on the user's emotional state.

[0550] "Means for inputting dietary information" refers to an interface for users to register information about their own diet in the system.

[0551] "Methods for analyzing past dietary history and health data" refers to the process of analyzing data related to a user's past eating records and health status to extract trends and patterns.

[0552] "A means of generating meal plans based on nutritional balance" refers to a function that designs the optimal combination of meals, taking into account the nutrients the user needs.

[0553] "Means for recognizing and analyzing emotions" refers to technologies that identify a user's emotional state from their voice, facial expressions, etc., and perform analysis based on that data.

[0554] "A method for generating meal plans that take into account the user's emotional state" refers to a process that takes emotional data into consideration and proposes meal content that promotes the emotional state desired by the user.

[0555] "A means of outputting a list of selected ingredients" refers to a method of presenting the user with a list of ingredients that can be purchased based on the generated meal plan.

[0556] "A means of providing dietary guidance based on emotions according to health status" refers to a function that provides appropriate dietary and lifestyle advice tailored to the user's current health status and emotions.

[0557] The system that realizes this invention consists of a user, a server, and a terminal. The user first inputs dietary information using the terminal. This terminal is equipped with voice input and a camera and operates to identify the user's emotional state. Emotion recognition software is used for emotion recognition.

[0558] The server receives encrypted information sent by users and stores and analyzes meal history and health data. The server is equipped with software for performing data analysis and predictive modeling; for example, a database management system is used for data analysis, and machine learning libraries such as TensorFlow are applied to predictive models.

[0559] This allows the server to consider the user's emotions and health status and generate an optimal meal plan. This meal plan suggests menus containing specific nutrients to improve emotions. The generated meal plan, along with a list of ingredients available at convenience stores, is sent to the user's device and presented to them.

[0560] For example, if a user is feeling stressed, the server generates a menu containing ingredients that promote relaxation and suggests this list to the user via their device. This allows the user to easily prepare a meal that suits their situation.

[0561] An example of a prompt for a generative AI model is, "What foods are recommended when a user feels tired?" Based on this prompt, an appropriate meal plan is dynamically generated.

[0562] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0563] Step 1:

[0564] The device receives dietary information and emotional states from the user. The user provides information about their emotions and health to the device using voice commands, text input, or facial recognition. This input data is collected as initial data.

[0565] Step 2:

[0566] The server receives information sent from the terminal and encrypts the data to protect it. The server receives the encrypted data, stores it in a secure environment, and decrypts it for use when necessary. This data serves as foundational data for use in later steps.

[0567] Step 3:

[0568] The server analyzes the received data and retrieves past meal history and health data from the database. Using this data, the server analyzes trends in the user's eating habits and health status, and integrates this with current emotional data. A database management system is used for the analysis.

[0569] Step 4:

[0570] The server uses an emotion recognition module to analyze the user's current emotional state. Voice and facial expression analysis software is used to quantify the user's emotions and record the identified emotion values. This data is used to optimize meal plans.

[0571] Step 5:

[0572] The server uses a generative AI model to generate an optimal meal plan based on emotional and health data. The model takes the collected data as input and suggests ingredients and menus that promote positive emotional changes. The output is a specific meal plan that takes nutritional balance into consideration.

[0573] Step 6:

[0574] The server reconstructs the meal plan it generates and sends a list of available ingredients as output data to the user's terminal. The user can receive this specific ingredient list through their terminal and arrange for the necessary ingredients based on this list.

[0575] Step 7:

[0576] Users use their devices to refer to the received ingredient list and meal plan, and then follow the suggested menu. By following the meal plan, users can improve their daily eating habits.

[0577] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0578] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0579] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0580] [Fourth Embodiment]

[0581] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0582] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0583] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0584] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0585] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0586] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0587] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0588] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0589] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0590] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0591] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0592] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0593] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0594] This invention is a system that provides users with a well-balanced meal plan using ingredients readily available at convenience stores, enabling them to maintain healthy eating habits. The system takes user dietary information as input, analyzes past meal history and health data, and automatically generates a meal plan based on nutritional balance.

[0595] The server is responsible for generating this meal plan, receiving and analyzing the user's meal history and health data. Furthermore, the server generates a nutritionally balanced meal plan and creates a list of ingredients based on it. The generated plan is then customized according to the user's nutritional needs.

[0596] This system also includes a function to provide dietary guidance tailored to the user's health condition. Specifically, the server analyzes the user's health status and provides appropriate advice based on that analysis. This advice includes suggestions on how to supplement necessary nutrients and which foods to avoid.

[0597] The terminal transmits user-inputted information to a server, receives the processing results, and presents them to the user. Users can purchase ingredients at a convenience store according to the provided meal plan and easily prepare the meal. The terminal also displays the recipe along with the meal plan, guiding the user on how to cook.

[0598] For example, if a user enters their eating history and indicates that they are "easily fatigued" as their recent physical condition, the server will perform an analysis based on this information. If it determines that the user is lacking essential nutrients, it will suggest a meal plan that includes iron-rich foods and present it to the user via their device along with the recipe. In this way, the present invention helps users easily adopt a healthy diet.

[0599] The following describes the processing flow.

[0600] Step 1:

[0601] Users access a dietary information form on their device and enter their eating history, allergy information, health condition, etc. This information is then sent to the system as data.

[0602] Step 2:

[0603] The terminal encrypts the information entered by the user as a security measure and sends it to the server. The encrypted data is communicated using a secure protocol.

[0604] Step 3:

[0605] The server decrypts the received data and stores it in the database. Here, the information is organized for each user, and management is performed to maintain data integrity.

[0606] Step 4:

[0607] The server analyzes the original data and uses nutritional algorithms to assess the user's nutritional needs. This analysis identifies necessary nutrients and dietary trends.

[0608] Step 5:

[0609] The server generates a nutritionally balanced meal plan based on the analysis results. This plan is customized according to the user's health condition and dietary preferences.

[0610] Step 6:

[0611] The server creates a shopping list of items that can be purchased at a convenience store based on the ingredients included in the meal plan. At the same time, it calculates the calorie and nutritional details of the suggested meals.

[0612] Step 7:

[0613] The server sends the generated meal plan, shopping list, and nutritional information to the device. This information also includes health advice.

[0614] Step 8:

[0615] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and prepare a meal according to the suggested recipe.

[0616] (Example 1)

[0617] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0618] In today's lifestyle, it is difficult for individuals to maintain healthy eating habits. Lack of time and insufficient knowledge about food selection make it challenging to prepare nutritionally balanced meals. Furthermore, there is a need for a system that effectively provides nutrients tailored to the user's health condition.

[0619] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0620] In this invention, the server includes means for inputting dietary habit data, means for analyzing past eating and drinking history and health status data, and means for generating a meal plan based on nutritional balance. This enables users to be provided with appropriate nutrients according to their health status and to achieve a balanced diet using readily available ingredients.

[0621] "Dietary habit data" refers to data that represents information about a user's daily eating habits.

[0622] "Dining history" refers to a record of food and drinks that a user has consumed in the past.

[0623] "Health status data" refers to data that includes information about the user's physical condition and health.

[0624] "Nutritional balance" refers to a state in which the body is consuming the necessary nutrients in a balanced manner.

[0625] A "dining plan" refers to a meal menu and structure designed to suit a specific purpose or condition.

[0626] A "food ingredient list" refers to a list of ingredients needed for a specific dish or dining plan.

[0627] A "cooking method" is a set of instructions that shows how to cook specific ingredients and complete a dish.

[0628] A "generative AI model" is an artificial intelligence model that uses a large amount of data to derive the optimal solution for a specific purpose.

[0629] In this invention, the server plays a central role. The server is equipped with a processor and storage to receive dietary habit data entered by the user. The server stores this data and analyzes the user's eating history and health status data. Data processing libraries such as Python and R are used for the analysis.

[0630] The server uses a generative AI model to evaluate past eating patterns and automatically generate meal plans based on nutritional balance. The generated meal plans include a list of selected ingredients and corresponding cooking methods. This allows users to easily create balanced meals using readily available ingredients.

[0631] Users input their eating habits data using a device. The entered data is encrypted on the device and securely transmitted to the server. The device displays the meal plan and cooking methods received from the server, providing users with specific guidance on their eating habits.

[0632] For example, if a user enters information about their health, such as "I've been feeling tired lately," into their device and sends it, the server analyzes this information and generates a meal plan centered around foods rich in iron and vitamins. The device displays cooking instructions for dishes like "blanched spinach" and "liver dishes," along with a list of ingredients that should be purchased.

[0633] An example of a prompt message would be, "Consider the user's recent health data and generate a meal plan that includes the necessary nutrients." This process allows users to efficiently engage in healthy eating and drinking behaviors.

[0634] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0635] Step 1:

[0636] The user inputs dietary habit data and health status data using a terminal. This data includes detailed information about their current diet and physical condition. The terminal converts this data into a predetermined format and prepares it for secure transmission to the server. The input includes text information about health status and a list of specific foods.

[0637] Step 2:

[0638] The terminal encrypts the input data using protocols such as SSL / TLS and sends it to the server. This reduces the risk of data leakage. As output, the server securely receives the encrypted data.

[0639] Step 3:

[0640] The server analyzes the received data. First, it deserializes the data to identify the user's past eating and drinking history and current health status. It preprocesses the data using the Python Pandas library and formats it into a dataframe. The analysis identifies any nutrient deficiencies necessary for creating a new eating and drinking plan.

[0641] Step 4:

[0642] The server uses a generation AI model to generate a nutritionally balanced meal plan based on the analysis results obtained. The model has learned from past data patterns and is ready to suggest the most suitable ingredient list and cooking method for the user. As output, the meal plan is generated in digital format.

[0643] Step 5:

[0644] The server sends the generated meal plan and corresponding ingredient list to the terminal. The data is encrypted again and securely delivered to the recipient's intended device. As output, the terminal receives the data and prepares for the next step.

[0645] Step 6:

[0646] The terminal displays the received dining plan and provides the user with a detailed operating guide. Cooking instructions and a list of ingredients to purchase are clearly displayed on the screen, allowing the user to proceed with shopping at the store and cooking based on this information. The output is that the user has purchased the ingredients according to the plan and prepared for cooking.

[0647] (Application Example 1)

[0648] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0649] In today's fast-paced lifestyle, maintaining healthy eating habits is not easy for individuals. To address this challenge, a system is needed that provides meal plans tailored to individual health conditions and offers concrete support throughout the process of food selection, purchasing, and cooking. However, many existing systems are limited to user-dependent information provision and simple meal suggestions, and currently lack comprehensive support to enable users to consistently engage in healthy food consumption.

[0650] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0651] In this invention, the server includes a device for inputting food consumption behavior information, a device for analyzing past food consumption history and health information, and a device for generating meal plans based on nutritional balance. This enables the automatic generation of food consumption plans optimized for individual users, and further allows for purchase assistance through an automated, remotely operated humanoid device. This supports the entire process, from selecting and purchasing food ingredients to cooking, providing comprehensive lifestyle management support for maintaining good health. Furthermore, by providing detailed visual and audio guidance on cooking procedures, users can easily complete healthy meals.

[0652] A "food consumption behavior information input device" is a device for receiving and recording information about food consumption from users.

[0653] A "food consumption history analysis device" is a device that collects and analyzes past food consumption history data.

[0654] A "health information analysis device" is a device that analyzes and evaluates data related to a user's health status.

[0655] A "meal plan generator" is a device that creates a meal plan optimized for each individual user, taking nutritional balance into consideration.

[0656] A "food ingredient list output device" is a device that outputs a list of necessary food ingredients based on a meal plan.

[0657] A "food consumption guidance device" is a device that provides guidance on diet and nutrition tailored to the user's health condition, supporting improvements in lifestyle habits.

[0658] An "automated humanoid remote-controlled device control system" is a device that controls an automated humanoid device that operates based on user instructions and assists in the food purchasing process.

[0659] A "visual and audio cooking procedure guidance device" is a device that guides users through cooking procedures using visual and audio means, and supports them in completing a dish.

[0660] This invention is a system that supports users' healthy eating habits by utilizing food consumption behavior information. The server collects the user's daily food consumption data through a food consumption behavior information input device. Users input their food consumption history and health information using devices such as smartphones and tablets. This data is transmitted to the server in real time and analyzed in detail by a food consumption history analysis device and a health information analysis device. The server uses hardware such as NVIDIA Jetson Orin and Raspberry Pi, and processes the data using software such as Python and TensorFlow.

[0661] Based on the analysis, the meal plan generator utilizes a generation AI model to automatically create a meal plan tailored to the user's health condition. A list of necessary food ingredients is generated and presented to the user via a food ingredient list output device. This system can flexibly customize the plan according to the user's preferences and constraints.

[0662] Furthermore, an automated, humanoid, remotely operated device is used to assist the user in the food purchasing process. This device is designed for easy user operation and allows users to select and purchase food based on their meal plan. After the purchase is complete, a visual and audio cooking instruction device guides the user through the cooking process in detail. The cooking guide is provided through visual information and audio guidance, allowing users to easily prepare healthy meals.

[0663] As a concrete example, a user might input "easily fatigued" as their health condition, and the server would then suggest a meal plan containing iron based on the generated data. Examples of prompts in this process include, "Please suggest a balanced meal plan for my easily fatigued condition," or "Please provide appropriate recipes for iron supplementation." This allows users to efficiently obtain the necessary nutrients and maintain their health.

[0664] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0665] Step 1:

[0666] The terminal receives input from the user and collects data on food consumption behavior and health status. This input data includes information on the type and quantity of food consumed, the time of consumption, and the user's current health status. This information will be transmitted from the input device, such as a smartphone or tablet, to the server.

[0667] Step 2:

[0668] The server sends the received user input data to a food consumption history analysis device, which analyzes past food consumption history and current health information. This process uses a database to search the user's historical data and applies machine learning algorithms to assess their current health status. This results in the output of information about imbalances in nutrient intake.

[0669] Step 3:

[0670] The server uses a meal plan generator to create a meal plan that takes nutritional balance into consideration. In this step, a generation AI model is used to generate an optimal meal plan that reflects the user's preferences and health goals, based on the analysis results from step 2. The meal plan created here includes the necessary food ingredients and their quantities, so a list of specific food ingredients is output.

[0671] Step 4:

[0672] The terminal displays a meal plan and a list of food ingredients received from the server to the user. Here, a visually easy-to-understand interface is used to display the list of ingredients and recommended recipes, and voice guidance is provided to the user to encourage healthy food consumption.

[0673] Step 5:

[0674] The user reviews the presented meal plan and ingredients, and, if necessary, initiates food purchase assistance using an automated humanoid remote-controlled device. The automated humanoid remote-controlled device physically assists with ingredient selection and purchase, and reports the purchased ingredients to the user after the purchase is complete.

[0675] Step 6:

[0676] The device guides the user through cooking instructions via visual and audio guidance. Specifically, it provides detailed and easy-to-understand explanations of each cooking step, follows the cooking process in real time, and helps the user complete a healthy meal. At this stage, it provides prompts to help the user follow the appropriate cooking procedures, supporting a smooth user experience.

[0677] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0678] This invention is a system that combines an emotional engine with ingredients available at convenience stores, with the aim of helping users maintain a healthy diet. Through this, it aims to provide meal plans tailored to the user's emotional state and improve the quality of their diet.

[0679] First, the user inputs information about their diet and physical condition through the device. At this time, the emotion engine recognizes the user's emotions and identifies their current mood. Emotion recognition is achieved by using voice input, text input, and sensors that analyze facial expressions on the screen.

[0680] The server receives data entered by the user, decrypts the encrypted information, and stores it in a database. Next, the server analyzes the stored meal history and health data, incorporates emotional information from the emotion engine, and generates an optimal meal plan for the user. This meal plan is tailored to evoke positive emotions, taking into account the user's emotional state in particular.

[0681] The generated meal plan includes suggestions for nutritionally balanced meals and a list of ingredients available at convenience stores. Furthermore, it includes specific dietary guidance tailored to the user's emotions. For example, if the user is feeling stressed, meals containing relaxing ingredients will be recommended.

[0682] The device presents the user with meal plans, ingredient lists, and health advice sent from the server. This allows users to easily adopt a diet tailored to their current state and promote emotional stability. For example, if the emotion engine detects that the user is feeling "depressed," it will recommend recipes using specific ingredients that promote serotonin production to enhance feelings of happiness.

[0683] Thus, the present invention provides a system that supports both emotional and physical aspects by adapting to the user's emotions.

[0684] The following describes the processing flow.

[0685] Step 1:

[0686] Users access a form on their device to input information about their eating habits and health status. This input includes daily meal history, physical condition, and personal health goals. Furthermore, they input their current emotional state by selecting options to express their emotions or by using voice or facial expression analysis functions.

[0687] Step 2:

[0688] The terminal encrypts the dietary information and emotional data entered by the user and transmits it to the server using a secure communication protocol.

[0689] Step 3:

[0690] The server decrypts the received data and stores it in a database for each user. The stored data includes individual meal histories and emotional states.

[0691] Step 4:

[0692] The server analyzes user data in the database and evaluates emotional information using an emotion engine. This allows it to consider the impact of emotional states on diet and understand individual nutritional needs.

[0693] Step 5:

[0694] Based on the analysis results, the server generates a meal plan tailored to the user's nutritional balance and emotional state. For example, if a user is feeling stressed, the server will create a plan that includes ingredients and recipes suitable for relieving that stress.

[0695] Step 6:

[0696] The server creates a list of ingredients included in the generated meal plan and verifies whether these ingredients are available for purchase at convenience stores. The meal plan also includes dietary guidance to address the user's emotional needs.

[0697] Step 7:

[0698] The server sends the final meal plan, ingredient list, and health and emotional advice to the device.

[0699] Step 8:

[0700] The terminal displays information received from the server to the user. The user can then use this information to purchase ingredients at a convenience store and cook at home. This process is designed to support both the user's emotional well-being and health.

[0701] (Example 2)

[0702] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0703] In today's busy lifestyle, many people find it difficult to maintain both a healthy diet and emotional stability simultaneously. In particular, there is a lack of readily available options for choosing meals that consider both nutritional balance and emotional state. A system is needed to address this problem and provide healthy meals that adapt to individual emotional needs.

[0704] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0705] In this invention, the server includes means for inputting dietary information and emotional state, means for analyzing past meal history, health data, and emotional information, and means for generating a meal plan based on nutritional balance and emotional state. This enables the provision of an appropriate meal plan tailored to each user's health and emotional state, providing support in both health and emotional aspects.

[0706] "Dietary information" refers to data about the user's eating habits and nutritional intake.

[0707] "Emotional state" refers to the user's mental and emotional condition, and is information that is recognized and analyzed through the emotion engine.

[0708] "Meal history" refers to data that records the contents of meals a user has eaten in the past.

[0709] "Health data" refers to information about a user's health status, including their physical condition, medical history, and habits.

[0710] "Emotional information" refers to data about a user's emotional state, collected using methods such as voice, text, and facial expressions.

[0711] "Nutritional balance" refers to the appropriate distribution of nutrients necessary for the body and forms the basis of a healthy meal plan.

[0712] A "meal plan" is a detailed plan of meals suggested based on the user's health and emotional state.

[0713] A "food list" refers to a list of ingredients that need to be purchased based on the proposed meal plan.

[0714] "Dietary guidance" refers to advice and instructions for improving dietary habits, provided based on the user's health and emotional state.

[0715] "Encryption" is a technology that transforms data to ensure secure communication and prevent it from being leaked to third parties.

[0716] This invention is a system designed to support users in maintaining a healthy diet and emotional state. This system is constructed by combining technical elements such as terminals, servers, and generative AI models.

[0717] First, the user uses a device to input information about their diet and emotional state. The device utilizes voice input, text input, or facial recognition sensors to identify the user's emotional state via an emotion engine. This emotional information, along with the user's personal dietary information, is encrypted and sent to the server.

[0718] Next, the server decrypts the received data and securely stores it in a database. The server analyzes this data and generates an optimal meal plan for the user based on past eating history, health data, and emotional information. A generative AI model is used in this process to improve the accuracy and personalization of the plan.

[0719] For example, if a user enters "I'm feeling stressed," the server will suggest a menu featuring relaxing herbal teas and legumes. Furthermore, the generated meal plan includes a list of ingredients available at convenience stores, allowing the user to easily obtain the necessary ingredients.

[0720] The device ultimately displays meal plans, ingredient lists, and health advice sent from the server to the user. This makes it easier for the user to practice a diet that suits their current emotional state and health needs.

[0721] An example of a prompt message could be input to the generating AI model, such as, "Suggest the optimal meal plan if the user is experiencing stress." Using this prompt, it becomes possible to provide a specific and effective meal plan tailored to the user's condition.

[0722] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0723] Step 1:

[0724] The user inputs information about their eating habits and emotional state through the device. At this time, the device uses voice input, text input, or facial recognition sensors to analyze the actual emotional state using an emotion engine, obtaining the user's emotional data. After the input information is processed, it is packaged and sent to the server.

[0725] Step 2:

[0726] The server receives data sent from the user and decrypts the input information using an encrypted method. This secured data is stored in a database and prepared for subsequent analysis steps.

[0727] Step 3:

[0728] The server uses a generative AI model to analyze stored meal history, health data, and even emotional information. This prompt uses specific instructions to the AI ​​model, such as "Suggest a meal plan best suited to the user's current stress levels." This analysis step generates a meal plan that is most appropriate for the individual's needs.

[0729] Step 4:

[0730] The server considers nutritional balance and emotional state to generate an optimal meal plan and a list of available ingredients for the user. The output includes suggestions for nutritious meals tailored to a specific emotional state, along with a list of ingredients.

[0731] Step 5:

[0732] The device displays meal plans, ingredient lists, and health advice sent from the server to the user. This allows users to practice a diet tailored to their individual health and emotional needs and achieve the desired results.

[0733] (Application Example 2)

[0734] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0735] There is a lack of systems that can automatically provide healthy eating suggestions that take into account the user's emotional state. In particular, there is a need for a means to suggest appropriate meal plans according to different emotional states, thereby simultaneously supporting the user's mental and physical health.

[0736] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0737] In this invention, the server includes means for inputting dietary information, means for analyzing past meal history and health data, and means for recognizing and analyzing emotions. This makes it possible to provide an optimal meal plan based on the user's emotional state.

[0738] "Means for inputting dietary information" refers to an interface for users to register information about their own diet in the system.

[0739] "Methods for analyzing past dietary history and health data" refers to the process of analyzing data related to a user's past eating records and health status to extract trends and patterns.

[0740] "A means of generating meal plans based on nutritional balance" refers to a function that designs the optimal combination of meals, taking into account the nutrients the user needs.

[0741] "Means for recognizing and analyzing emotions" refers to technologies that identify a user's emotional state from their voice, facial expressions, etc., and perform analysis based on that data.

[0742] "A method for generating meal plans that take into account the user's emotional state" refers to a process that takes emotional data into consideration and proposes meal content that promotes the emotional state desired by the user.

[0743] "A means of outputting a list of selected ingredients" refers to a method of presenting the user with a list of ingredients that can be purchased based on the generated meal plan.

[0744] "A means of providing dietary guidance based on emotions according to health status" refers to a function that provides appropriate dietary and lifestyle advice tailored to the user's current health status and emotions.

[0745] The system that realizes this invention consists of a user, a server, and a terminal. The user first inputs dietary information using the terminal. This terminal is equipped with voice input and a camera and operates to identify the user's emotional state. Emotion recognition software is used for emotion recognition.

[0746] The server receives encrypted information sent by users and stores and analyzes meal history and health data. The server is equipped with software for performing data analysis and predictive modeling; for example, a database management system is used for data analysis, and machine learning libraries such as TensorFlow are applied to predictive models.

[0747] This allows the server to consider the user's emotions and health status and generate an optimal meal plan. This meal plan suggests menus containing specific nutrients to improve emotions. The generated meal plan, along with a list of ingredients available at convenience stores, is sent to the user's device and presented to them.

[0748] For example, if a user is feeling stressed, the server generates a menu containing ingredients that promote relaxation and suggests this list to the user via their device. This allows the user to easily prepare a meal that suits their situation.

[0749] An example of a prompt for a generative AI model is, "What foods are recommended when a user feels tired?" Based on this prompt, an appropriate meal plan is dynamically generated.

[0750] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0751] Step 1:

[0752] The device receives dietary information and emotional states from the user. The user provides information about their emotions and health to the device using voice commands, text input, or facial recognition. This input data is collected as initial data.

[0753] Step 2:

[0754] The server receives information sent from the terminal and encrypts the data to protect it. The server receives the encrypted data, stores it in a secure environment, and decrypts it for use when necessary. This data serves as foundational data for use in later steps.

[0755] Step 3:

[0756] The server analyzes the received data and retrieves past meal history and health data from the database. Using this data, the server analyzes trends in the user's eating habits and health status, and integrates this with current emotional data. A database management system is used for the analysis.

[0757] Step 4:

[0758] The server uses an emotion recognition module to analyze the user's current emotional state. Voice and facial expression analysis software is used to quantify the user's emotions and record the identified emotion values. This data is used to optimize meal plans.

[0759] Step 5:

[0760] The server uses a generative AI model to generate an optimal meal plan based on emotional and health data. The model takes the collected data as input and suggests ingredients and menus that promote positive emotional changes. The output is a specific meal plan that takes nutritional balance into consideration.

[0761] Step 6:

[0762] The server reconstructs the meal plan it generates and sends a list of available ingredients as output data to the user's terminal. The user can receive this specific ingredient list through their terminal and arrange for the necessary ingredients based on this list.

[0763] Step 7:

[0764] Users use their devices to refer to the received ingredient list and meal plan, and then follow the suggested menu. By following the meal plan, users can improve their daily eating habits.

[0765] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0766] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0767] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0768] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0769] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0770] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0771] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0772] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0773] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0774] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0775] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0776] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0777] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0778] 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.

[0779] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0780] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0781] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0782] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0783] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0784] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0785] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0786] The following is further disclosed regarding the embodiments described above.

[0787] (Claim 1)

[0788] A means of inputting dietary information,

[0789] A means of analyzing past dietary history and health data,

[0790] A means of generating a meal plan based on nutritional balance,

[0791] A means of outputting a list of selected ingredients,

[0792] A means of providing dietary guidance tailored to one's health condition,

[0793] A system that includes this.

[0794] (Claim 2)

[0795] The system according to claim 1, which encrypts and transmits user input information.

[0796] (Claim 3)

[0797] The system according to claim 1 that generates recipes based on purchasable ingredients.

[0798] "Example 1"

[0799] (Claim 1)

[0800] A means of inputting dietary habit data,

[0801] A means of analyzing past eating and drinking history and health status data,

[0802] A means of generating a meal plan based on nutritional balance,

[0803] A means of outputting a list of selected ingredients,

[0804] A means of providing dietary guidance tailored to one's health condition,

[0805] A means of encrypting and transmitting data via a communication terminal,

[0806] A means of presenting cooking methods based on available food products,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, which recommends nutrients based on the user's condition.

[0810] (Claim 3)

[0811] The system according to claim 1, which performs data analysis using a generative AI model.

[0812] "Application Example 1"

[0813] (Claim 1)

[0814] A device for inputting food consumption behavior information,

[0815] A device that analyzes previous food consumption history and health information,

[0816] A device that generates meal plans based on nutritional balance,

[0817] A device that outputs a list of determined food ingredients,

[0818] A device that provides food consumption guidance tailored to health conditions,

[0819] A device that controls an automated, remotely operated humanoid device and provides purchasing support based on a food consumption plan,

[0820] A device that provides instructions for cooking procedures through visual and auditory means,

[0821] A system that includes this.

[0822] (Claim 2)

[0823] The system according to claim 1, which encodes and communicates user input information.

[0824] (Claim 3)

[0825] The system according to claim 1 for generating cooking methods based on commercially available food ingredients.

[0826] "Example 2 of combining an emotion engine"

[0827] (Claim 1)

[0828] A means of inputting dietary information and emotional state,

[0829] A means of analyzing past dietary history, health data, and emotional information,

[0830] A means of generating a meal plan based on nutritional balance and emotional state,

[0831] A means of outputting a list of selected, purchasable ingredients,

[0832] A means of providing dietary guidance tailored to health and emotional states,

[0833] A system that includes this.

[0834] (Claim 2)

[0835] The system according to claim 1, which encrypts and securely transmits user input information.

[0836] (Claim 3)

[0837] The system according to claim 1 that generates recipes based on selected, purchasable ingredients.

[0838] "Application example 2 when combining with an emotional engine"

[0839] (Claim 1)

[0840] A means of inputting dietary information,

[0841] A means of analyzing past dietary history and health data,

[0842] A means of generating a meal plan based on nutritional balance,

[0843] Means for recognizing and analyzing emotions,

[0844] A means of generating a meal plan that takes into account the user's emotional state,

[0845] A means of outputting a list of selected ingredients,

[0846] A means of providing dietary guidance based on emotions, according to one's health condition,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, which encrypts user input information and identifies the emotional state.

[0850] (Claim 3)

[0851] The system according to claim 1, which generates recipes based on available ingredients and suggests ingredients that match the user's mood. [Explanation of symbols]

[0852] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of inputting dietary information, A means of analyzing past dietary history and health data, A means of generating a meal plan based on nutritional balance, A means of outputting a list of selected ingredients, A means of providing dietary guidance tailored to one's health condition, A system that includes this.

2. The system according to claim 1, which encrypts and transmits user input information.

3. The system according to claim 1 that generates recipes based on purchasable ingredients.

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