system

Abstract

システムを提供する。【解決手段】家庭構成員ごとの基本属性情報を入力する取得手段と、上記基本属性情報に基づき栄養要求を解析する解析手段と、上記解析結果に基づいて食事計画を生成する生成手段と、活動情報を入力し伝達する取得手段と、上記活動情報に基づいて運動計画を提案する提案手段と、子供向けの学習内容を生成し提供する供給手段と、家庭用機械装置を用いて健康状態を管理し、音声認識機能を用いて情報を対話形式で提供する対話手段と、を含むシステム。

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 steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] "Input method" refers to the means of inputting basic attribute data and activity data for each household member into the system.

[0007] "Analysis tools" refer to methods for analyzing the nutritional needs of each household member based on the input basic attribute data.

[0008] "Generation method" refers to a means of generating meal menus suitable for each household member based on the analysis results.

[0009] "Suggestion methods" refer to methods for suggesting exercise plans and health advice based on the activity data of household members.

[0010] "Means of provision" refers to the means of generating and providing educational content for children. [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 provides a system that supports a healthy lifestyle in the home. The following describes each component of the system and the processes it performs.

[0033] First, the user uses a device to input basic attribute data for each household member, such as age, gender, height, weight, allergy information, and food preferences. This data is sent from the device to the server, which then receives it.

[0034] Next, the server calculates and analyzes each member's nutritional needs based on the received basic attribute data. This analysis includes calculating basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients.

[0035] Based on this analysis, the server uses a generative AI model to generate healthy meal plans tailored to each member. These plans are suggested weekly and include specific recipes, cooking times, and a list of necessary ingredients.

[0036] Users input activity data obtained from smartwatches and fitness trackers back into the device, which then sends it to a server. The server analyzes this activity data and assesses the exercise level of each household member. Furthermore, exercise plans and health maintenance advice are suggested based on these analysis results. This allows each member to manage their health according to their individual needs.

[0037] Furthermore, the server generates educational content for children at home. This content is presented in the form of games and quizzes, allowing children to learn about health while having fun. The device notifies the user of the generated content, making it accessible to the children.

[0038] For example, in one family where the child doesn't particularly like vegetables, the server suggests recipes that make vegetables delicious and provides educational content that makes eating them fun. Also, even if parents are busy, the system provides simple exercise plans to prevent a sedentary lifestyle and support their health.

[0039] In this way, "Healthy Family AI" is a system that provides comprehensive support for a healthy lifestyle for the entire family.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] The user enters basic attribute data for each household member (age, gender, height, weight, allergy information, food preferences, etc.) into the terminal. The terminal verifies the entered data, checks that the format is correct, and then sends it to the server.

[0043] Step 2:

[0044] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. Specifically, it calculates basal metabolic rate and recommended calorie intake, and identifies the amount of nutrients that need to be consumed.

[0045] Step 3:

[0046] Based on the results of the nutrition needs analysis, the server uses a generative AI model to generate appropriate meal plans. These plans take into account each member's preferences and nutritional needs, and include weekly recipes, cooking times, and ingredient lists.

[0047] Step 4:

[0048] The user inputs activity data obtained from a smartwatch or fitness tracker into the device. The device then sends this data to the server.

[0049] Step 5:

[0050] The server receives activity data, analyzes it, and assesses the exercise level of each household member. Based on the assessment, it generates exercise plans and health maintenance advice tailored to each member's needs.

[0051] Step 6:

[0052] The server generates educational content for children. Specifically, it creates games and quizzes that make learning about health information fun. This content is provided for educational purposes within the home.

[0053] Step 7:

[0054] The device displays generated meal plans, exercise plans, and educational content to the user. The user reviews these and uses them to promote a healthy lifestyle at home.

[0055] (Example 1)

[0056] 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."

[0057] In modern families, managing the health of each member is important, but developing individualized nutrition and exercise plans is difficult. Furthermore, there is limited content available to educate children about healthy habits. These circumstances make maintaining overall family health challenging.

[0058] 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.

[0059] In this invention, the server includes means for calculating and analyzing nutritional requirements based on basic cultural data for each household member, means for proposing personalized exercise plans based on individual activity information, and means for generating and providing educational materials. This makes it possible to provide nutritional management and exercise plans tailored to each member while also providing educational content that is fun to learn from.

[0060] "Family members" refers to individual members belonging to the same household, and includes multiple groups of different ages and genders.

[0061] "Basic cultural data" refers to attribute information about household members, such as age, gender, height, weight, allergy information, and food preferences. This data forms the basis for nutrition and health management.

[0062] "Nutritional requirements" refer to the amount of nutrients necessary for maintaining physical health and activity, and are calculated based on individual attributes.

[0063] "Device for providing" refers to hardware or software that provides meal plans and exercise suggestions tailored to each household member based on calculated nutritional requirements.

[0064] "Activity information" refers to data about physical activity obtained from smart devices, including information such as the number of steps taken and exercise time.

[0065] An "individualized exercise plan" refers to an optimized exercise schedule proposed based on the activity information of each household member.

[0066] "Educational materials" refer to content created to make learning about health, nutrition, and exercise fun, and are provided in the form of games or quizzes.

[0067] This invention is designed as a system to support health management within the home. Specific embodiments of the invention are described below.

[0068] The user enters basic cultural data for each household member into a terminal. This terminal is a standard computer or smart device equipped with an interface for entering information. This data includes each member's age, gender, height, weight, allergy information, and food preferences.

[0069] The terminal sends the entered information to the server. The server is deployed on a cloud-based computing platform or within a local network and analyzes the received data. The server calculates nutritional requirements based on basic cultural data. This includes algorithms for calculating basal metabolic rate and the required intake of individual nutrients.

[0070] The server generates meal plans using a generative AI model. Based on the prompt, the AI ​​model suggests appropriate meal recipes, lists of necessary ingredients, cooking times, and more. For example, a prompt might be: "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy meal plan for him for one week."

[0071] Furthermore, users can input activity information from smartwatches and fitness trackers into the device. The device sends this information to a server, which then proposes a personalized exercise plan based on that data. This ensures that each member receives a healthy exercise plan tailored to their needs.

[0072] Furthermore, the server generates educational materials for children at home, and the device notifies them. These educational materials include games and quizzes about health and nutrition, making learning fun for children. The device notifies the user of the generated content, providing an environment where children can access it.

[0073] This system provides comprehensive support for a healthy lifestyle for the entire family, helping to create optimal lifestyle habits tailored to individual health needs.

[0074] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0075] Step 1:

[0076] The user enters basic cultural data for each household member into the terminal. This data includes age, gender, height, weight, allergy information, and food preferences. The terminal formats this data and prepares it for transmission to the server. Specifically, the user enters the required information into the input form and clicks the "Submit" button.

[0077] Step 2:

[0078] The terminal sends formatted basic cultural data to the server. The server temporarily stores the received data and creates a profile of each member. In this step, the data integrity is checked and any missing information is verified. The server then prepares to calculate nutritional requirements based on the input data.

[0079] Step 3:

[0080] The server calculates and analyzes the nutritional requirements of each household member based on stored basic cultural data. The server uses algorithms to calculate basal metabolic rate and the required intake of specific nutrients. Based on this input, it outputs the optimal energy expenditure and nutrient intake for maintaining health. Specific actions performed by the server include applying existing nutrition calculation formulas and reflecting the data in individual profiles.

[0081] Step 4:

[0082] The server uses a generative AI model to generate a meal plan based on the analyzed nutritional requirements. The AI ​​model is input with a prompt such as, "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy weekly meal plan for him." The AI ​​model then suggests and outputs nutritionally balanced recipes, ingredient lists, and cooking times. The server then provides these suggestions to the user as a weekly meal plan.

[0083] Step 5:

[0084] The user inputs daily activity information obtained from a smartwatch or fitness tracker into the device. The device then converts this information into a data format for transmission to the server. Specifically, it uses an activity tracking app to acquire data and imports that information into the device app.

[0085] Step 6:

[0086] Based on the activity information received by the server, it evaluates the exercise level of each household member. The server aggregates the data and uses an algorithm to analyze daily exercise volume and patterns. Based on the calculated exercise level, it generates an individualized exercise plan and provides it to the user. At this stage, the server suggests specific exercises to supplement any insufficient exercise.

[0087] Step 7:

[0088] The server uses a generative AI model to develop and deliver educational content for children. This content includes quizzes and game-based learning materials, which the server sends to the user's device and notifies them. Users and their families can access this content via their devices and use it as an opportunity for learning and entertainment.

[0089] (Application Example 1)

[0090] 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."

[0091] There is a need to efficiently manage the health status of each family member and provide exercise and nutritional suggestions tailored to individual needs. Furthermore, there is a need for educational content that allows children to learn about health in an enjoyable way. However, conventional systems struggle to comprehensively meet these requirements, and the provision of services integrated with home devices is insufficient.

[0092] 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.

[0093] In this invention, the server includes an acquisition means for inputting basic attribute information for each household member, an analysis means for analyzing nutritional requirements based on the basic attribute information, and a generation means for generating a meal plan based on the analysis results. This enables health management using a home appliance and allows for the provision of individually optimized nutrition and exercise plans. Furthermore, by using a dialogue means equipped with voice recognition functionality, information can be provided through natural dialogue with the user, and consideration can be given to making learning content for children enjoyable to use.

[0094] "Family members" refers to each individual belonging to a household, and each of them is responsible for managing their own health.

[0095] "Basic attribute information" refers to data such as an individual's age, gender, height, weight, allergy information, and food preferences, and is fundamental data used for nutritional analysis and exercise plan development.

[0096] "Nutritional requirements" refer to the amount of nutrients and calories needed to maintain the health of each household member, and by analyzing them, it becomes possible to create an optimal meal plan.

[0097] "Analysis means" refers to a function that calculates and analyzes nutritional requirements based on the input basic attribute information, and is a process for generating an appropriate meal plan.

[0098] "Generation means" refers to the process or system for formulating meal plans to be provided to each member based on the results obtained from the analysis means.

[0099] "Activity information" refers to data on an individual's exercise volume and activity status obtained from smartwatches, fitness trackers, etc., and is necessary information for suggesting exercise plans.

[0100] An "exercise plan" is a plan that proposes individually optimized exercise content and schedules based on the activity information of each household member.

[0101] "Supplying means" refers to a system or process that provides members with generated learning content and meal plans, and includes providing diverse information, including learning content for children, in an easy-to-understand manner.

[0102] "Household medical devices" refer to equipment that can be used within the home and have functions to provide information and interact with others for health management.

[0103] "Dialogue methods" refer to processes and functions that use speech recognition technology to engage in natural interactions with users and provide them with necessary information.

[0104] This invention is a system designed to support health management within the home, efficiently collecting and analyzing health data for each household member and presenting an optimal nutrition and exercise plan. The embodiments of this system are described in detail below.

[0105] First, users input basic attribute information for each household member using a terminal. This information includes age, gender, height, weight, allergy information, and food preferences. This data is sent to a server and used as basic data for analyzing nutritional requirements.

[0106] The server analyzes each member's nutritional requirements based on the received basic attribute information. This process includes calculating each individual's basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients. Based on the analysis results, the server uses a generative AI model to generate a meal plan optimized for each member. This meal plan includes specific recipes and a list of necessary ingredients.

[0107] Furthermore, users transmit activity information obtained from smartwatches and fitness trackers to the server via their devices. Based on this activity information, the server evaluates each member's exercise level and proposes a personalized exercise plan. This exercise plan includes specific advice for maintaining the health of household members.

[0108] For children's learning, the server generates educational content in the form of games and quizzes, which are then delivered through the device. This allows children to learn about health-related knowledge in an enjoyable way.

[0109] For example, based on a prompt such as, "Please suggest a healthy dessert recipe that a 12-year-old child can enjoy," the system will suggest meals and snacks suitable for children. Similarly, through a prompt such as, "Please create a one-week meal plan for a man in his 30s, taking calories and nutritional value into consideration," an individualized nutrition plan will be provided.

[0110] The hardware uses a Raspberry Pi as the home device, and the software employs a generative AI model built with Python and Tensorflow®. General-purpose speech processing software is used for speech recognition, enabling efficient health management within the home through voice interaction with the user.

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] Users use a terminal to enter basic attribute information of household members. This information includes age, gender, height, weight, allergy information, and food preferences. The entered data must be recorded accurately and in detail, as it will be used as initial settings in the system. This information is sent to the server and stored in the database.

[0114] Step 2:

[0115] Based on the received basic attribute information, the server uses a generating AI model to analyze the nutritional requirements of each member. Specifically, it calculates the basal metabolic rate and required calorie intake, and identifies the required intake of specific nutrients. This analysis is performed using a Python program and TensorFlow, and the output is data on the optimal nutritional requirements for each member.

[0116] Step 3:

[0117] The server uses an AI model based on the analysis results to generate a meal plan optimized for each member. The generated plan includes specific recipes, cooking times, and a list of necessary ingredients. This output is sent to the terminal and made available to the user.

[0118] Step 4:

[0119] Users input activity information obtained from smartwatches or fitness trackers into the device. This data includes steps taken, calories burned, and heart rate. The entered activity data is sent to a server and serves as the basis for evaluating exercise levels.

[0120] Step 5:

[0121] The server analyzes the input activity information and assesses each member's exercise level. Based on this assessment, an individual exercise plan is generated. The exercise plan includes the type and frequency of exercise to be performed, and incorporates advice to promote the user's health.

[0122] Step 6:

[0123] To generate learning content for children, the server utilizes a generation AI model to create educational content in game and quiz formats. This content is delivered and accessible via the user's device. The content is designed to allow children to learn about health in an enjoyable way.

[0124] Step 7:

[0125] The generated meal plans, exercise plans, and educational content are notified to the user via the device, supporting them in managing their health at home. Users can access the system interactively using voice recognition and request more detailed information or additional instructions.

[0126] 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.

[0127] This invention combines an emotional engine with a system that supports healthy living at home to achieve even more personalized health management. The system begins by inputting basic attribute data for each family member and analyzing their nutritional needs based on that data.

[0128] First, the user uses their device to input basic attribute data for each family member. This data is sent to a server, which analyzes each member's nutritional needs. Specifically, it calculates the required calorie intake and the required amounts of specific nutrients.

[0129] Based on these results, the server uses a generative AI model to create an appropriate meal plan and presents it to the user via the terminal. The user also inputs activity data into the terminal, and the server analyzes this data to provide appropriate exercise plans and health advice.

[0130] Furthermore, this system is equipped with an emotion engine that recognizes the user's emotional state. Based on the data from this emotion engine, the server can adjust the suggested meal menus and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, the system will suggest menus using ingredients with relaxing effects and exercise plans that promote relaxation.

[0131] Furthermore, educational content for children will be customized using emotional data. Specifically, content that is more engaging and enjoyable to learn from will be provided according to the child's emotional state, making it possible to increase their interest in health.

[0132] For example, if the emotional engine detects stress signals when parents are busy in a particular household, the server suggests a simple, healthy meal that can be prepared quickly, and recommends moderate exercise and meditation exercises to reduce stress. Furthermore, if a child is feeling bored, it provides educational content in the form of games that encourage active physical movement.

[0133] In this way, this system, which combines emotional engines, comprehensively supports the mental and physical health of the entire family.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] The user enters basic attribute data for each household member (e.g., age, gender, weight, height, allergy information, food preferences) into the device. The device then sends this data to the server.

[0137] Step 2:

[0138] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. This calculation includes required calorie intake and target intake of specific nutrients, providing an analysis tailored to each individual's health condition.

[0139] Step 3:

[0140] Based on the analysis results, the server uses a generative AI model to create meal plans tailored to each family member. These meal plans are adjusted according to individual nutritional needs and preferences, and include weekly recipes, cooking times, and lists of necessary ingredients.

[0141] Step 4:

[0142] Users input activity data collected by smartwatches and fitness trackers into their devices, or, if direct transmission is possible, the data is automatically sent to the server. The device is responsible for transmitting this data to the server.

[0143] Step 5:

[0144] The server analyzes activity data and evaluates the exercise level of each household member. Based on the evaluation results, it generates exercise plans and health advice tailored to each member's needs and proposes them to the user via the device.

[0145] Step 6:

[0146] The server activates an emotion engine to recognize the user's emotions, analyzing the user's facial expressions and voice data. It identifies the emotional state and tracks stress levels and emotional changes.

[0147] Step 7:

[0148] The server uses data from the emotion engine to adjust meal plans and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, it will suggest relaxation-promoting meals and lighter exercise plans.

[0149] Step 8:

[0150] The server generates educational content for children based on emotional data. Specifically, it provides games and quizzes customized to the child's mood and interests.

[0151] Step 9:

[0152] The device displays generated meal plans, exercise plans, and educational content to the user. The user can then use these suggestions to plan and carry out healthy activities at home.

[0153] (Example 2)

[0154] 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".

[0155] There is a growing need for more individualized health management within the family, enabling health maintenance tailored to the nutritional and emotional states of each member. However, conventional systems have been insufficient in considering emotional states, making it difficult to provide optimal diets and exercises for each individual. Furthermore, there is a lack of customization of educational content, particularly for children, and efforts are needed to capture their interest.

[0156] 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.

[0157] In this invention, the server includes means for inputting basic attribute information for each household member, means for evaluating nutritional requirements based on the attribute information, and means for recognizing emotional states. This makes it possible to provide each household member with more precise and emotionally sensitive nutritional management and exercise plans. Furthermore, it is possible to conduct health education while attracting the interest of children by generating and providing educational information for them.

[0158] "Household members" refers to individual people who live together within a specific household, and each of them is responsible for managing their own health.

[0159] "Basic attribute information" refers to information necessary for health management, such as age, gender, weight, height, and activity level of each household member.

[0160] "Nutritional requirements" refer to the amount of calories and various nutrients that household members need to maintain their health.

[0161] "Methods of evaluation" refers to the process of analyzing nutritional requirements using the input basic attribute information and calculating the appropriate amount of nutrients and calories needed.

[0162] A "meal plan" refers to a menu of meals that household members should consume, based on their assessed nutritional requirements.

[0163] "Activity status" refers to the types of exercise and physical activity that household members engage in on a daily basis, and is information related to maintaining health.

[0164] An "exercise plan" refers to exercise guidelines or programs designed to promote health, based on the activity levels of household members.

[0165] "Emotional state" refers to the emotional health of family members, including stress and mood swings.

[0166] "Means of recognizing emotional states" refers to technical methods for understanding the emotional states of family members and adjusting proposals based on those states.

[0167] "Educational information" refers specifically to content provided for children to promote learning and health awareness.

[0168] This invention provides a system that personalizes health management for each member of a household. This system uses emotion engine technology to recognize the user's emotional state and adjust meal plans and exercise plans accordingly.

[0169] First, users input basic attribute information for each household member through a terminal used at home. This information includes age, gender, weight, height, and lifestyle. The terminal sends this information to a server. Upon receiving this information, the server uses specialized nutritional analysis software to evaluate the nutritional requirements of each household member. Based on this evaluation, an individualized meal plan is generated, utilizing AI models such as OpenAI®.

[0170] The server then receives activity data from household members and uses it to create an exercise plan. An emotion engine is used to adjust the plan, taking into account the user's emotional state. The emotional state is inferred from voice input and screen interactions, and relaxation-enhancing exercises are suggested as needed.

[0171] As a concrete example, the server runs an AI model based on the prompt "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis. Please suggest a healthy dinner menu suitable for a high-stress situation," and generates a result.

[0172] In this way, the present invention utilizes an emotional engine and is designed to ensure that each member of a household receives optimal health management.

[0173] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0174] Step 1:

[0175] Users use a home terminal to input basic attribute information for each household member. This information includes age, gender, weight, height, and activity level. This information is formatted as digital data and sent from the terminal to the server.

[0176] Step 2:

[0177] The server analyzes the received attribute information and uses nutritional analysis software to evaluate the nutritional requirements of each member. During this process, the necessary calories and nutrients (protein, fat, carbohydrates, etc.) are calculated based on age and activity level. The output generates nutritional information necessary for each member.

[0178] Step 3:

[0179] The server inputs prompt sentences into the generating AI model based on the nutritional requirements assessment results. For example, it might input a sentence like, "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis; suggest a nutritionally balanced meal plan." The generating AI model then generates individual meal plans based on the input prompt sentences. This results in the output of the optimal meal menu for each member.

[0180] Step 4:

[0181] Users input their exercise and daily activity data into the device. This includes daily steps, type of exercise, and duration. The device then sends this activity data back to the server.

[0182] Step 5:

[0183] The server analyzes the transmitted activity data and proposes an exercise plan tailored to the lifestyle of each household member. This analysis assesses the need for excess calorie expenditure and muscle strengthening. As output, an individual exercise plan is generated.

[0184] Step 6:

[0185] The server uses an emotion engine to recognize the user's emotional state. Based on the input data, the user's stress level and emotional changes are analyzed. This emotional data is used to adaptively adjust suggested meal plans and exercise plans. As output, emotionally sensitive advice is provided.

[0186] Step 7:

[0187] The server generates educational content for children based on their emotional state. Specifically, it selects health education materials and games that are likely to interest children. This provides content that is fun to learn while raising children's health awareness.

[0188] (Application Example 2)

[0189] 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".

[0190] In modern society, personal health management is a crucial issue, but achieving effective health management tailored to each family's and individual's lifestyle and emotional state is difficult. Therefore, there is a need for systems that provide more personalized health promotion services.

[0191] 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.

[0192] In this invention, the server includes an input means for inputting basic attribute information for each household member, an emotion recognition means for recognizing and analyzing an individual's emotional state, and an adjustment means for adjusting and providing health promotion plans based on the emotional state. This enables personalized health management tailored to the lifestyle and emotional state of each household.

[0193] "Basic attribute information for each household member" refers to individual data such as age, gender, weight, and height for each member of the household.

[0194] "Nutritional needs" refer to the requirements regarding the intake of specific nutrients and calories necessary for maintaining an individual's health.

[0195] "Analysis means" refers to a method or apparatus for analyzing necessary nutritional needs based on the input basic attribute information.

[0196] "Generating means" refers to a method or apparatus for creating an individualized meal plan according to the analysis results.

[0197] "Activity information" refers to data about the exercise and activities that household members engage in on a daily basis.

[0198] "Proposed means" refers to a method or apparatus for providing an appropriate exercise plan based on activity information.

[0199] "Educational resources" is a general term for learning and educational materials and content provided to children.

[0200] "Emotion recognition means" refers to a method or device for detecting and analyzing an individual's emotional state.

[0201] "Adjustment means" refers to a method or apparatus for appropriately modifying and providing the proposed content in accordance with the recognized emotional state.

[0202] A "means for proposing health events" refers to a method or device for presenting events or activities that promote health improvement in accordance with the living environment of residents.

[0203] This invention realizes a system to support health management in the home. The system begins by inputting basic attribute information for each family member into a terminal and sending it to a server. This basic attribute information includes the age, gender, weight, and height of each family member. Once this data is sent to the server, the server uses a generative AI model to analyze the nutritional needs of each member and generates a meal plan based on that analysis.

[0204] The server also receives activity information from household members and proposes personalized exercise plans based on this information. This activity information includes daily exercise habits and activity levels. Furthermore, the system uses emotion recognition tools to detect and analyze the user's emotional state. This can be done using software such as OpenCV or the Emotion-Recognition API. Based on this emotional data, the server adjusts health promotion suggestions and provides an appropriate health management plan.

[0205] To give a specific example, if a user inputs their activity information using a device and the emotion recognition system detects "stress," the server will adjust and provide meal and activity suggestions that are appropriate for the user's emotional state. For example, suggestions might include "meals using ingredients effective for relaxation" or "exercise aimed at stress relief."

[0206] An example of a prompt message used as input to a generative AI model is, "Based on the user's emotional state, please suggest the most suitable relaxation method."

[0207] In this way, the system provides a way to comprehensively manage the health status of the entire household.

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The user uses a device to enter basic attribute information for family members. This information includes data such as age, gender, weight, and height. The entered data is temporarily stored on the device.

[0211] Step 2:

[0212] The terminal sends the entered basic attribute information to the server. After receiving this information, the server uses a generative AI model to analyze the nutritional needs. The nutritional needs analysis involves data processing to calculate the required calories and the required amounts of specific nutrients.

[0213] Step 3:

[0214] The server generates a personalized meal plan based on the analysis results. This generation utilizes historical data and the latest nutritional information, and the generating AI model creates prompts to design the optimal meal plan.

[0215] Step 4:

[0216] Users input daily activity information into their devices. This includes data on exercise levels and activity types. This information is sent to a server to supplement health management.

[0217] Step 5:

[0218] After receiving activity information, the server proposes an exercise plan. This process involves data calculations based on the input activity data to select appropriate exercises. This results in a training plan optimized for the user.

[0219] Step 6:

[0220] The device analyzes the user's emotional state through emotion recognition mechanisms. Using camera and sensor data, it identifies emotions using the Emotion-Recognition API. This result is sent to a server and used to adjust health promotion recommendations based on the emotional state.

[0221] Step 7:

[0222] After receiving emotional data, the server adjusts health management suggestions based on that data and provides them to the user. For example, a generative AI model might generate a prompt such as, "Please suggest the best relaxation methods based on the user's emotional state," and then suggest meals and activities appropriate to the user's emotional state.

[0223] Step 8:

[0224] Users can review meal plans, exercise plans, and health management suggestions based on their emotional state, received through their device, and use them to maintain their daily health. This output serves as concrete action guidelines for improving daily lifestyle habits.

[0225] 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.

[0226] 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.

[0227] 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.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] 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.

[0231] 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).

[0232] 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.

[0233] 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.

[0234] 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).

[0235] 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.

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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".

[0241] This invention provides a system that supports a healthy lifestyle in the home. The following describes each component of the system and the processes it performs.

[0242] First, the user uses a device to input basic attribute data for each household member, such as age, gender, height, weight, allergy information, and food preferences. This data is sent from the device to the server, which then receives it.

[0243] Next, the server calculates and analyzes each member's nutritional needs based on the received basic attribute data. This analysis includes calculating basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients.

[0244] Based on this analysis, the server uses a generative AI model to generate healthy meal plans tailored to each member. These plans are suggested weekly and include specific recipes, cooking times, and a list of necessary ingredients.

[0245] Users input activity data obtained from smartwatches and fitness trackers back into the device, which then sends it to a server. The server analyzes this activity data and assesses the exercise level of each household member. Furthermore, exercise plans and health maintenance advice are suggested based on these analysis results. This allows each member to manage their health according to their individual needs.

[0246] Furthermore, the server generates educational content for children at home. This content is presented in the form of games and quizzes, allowing children to learn about health while having fun. The device notifies the user of the generated content, making it accessible to the children.

[0247] For example, in one family where the child doesn't particularly like vegetables, the server suggests recipes that make vegetables delicious and provides educational content that makes eating them fun. Also, even if parents are busy, the system provides simple exercise plans to prevent a sedentary lifestyle and support their health.

[0248] In this way, "Healthy Family AI" is a system that provides comprehensive support for a healthy lifestyle for the entire family.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The user enters basic attribute data for each household member (age, gender, height, weight, allergy information, food preferences, etc.) into the terminal. The terminal verifies the entered data, checks that the format is correct, and then sends it to the server.

[0252] Step 2:

[0253] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. Specifically, it calculates basal metabolic rate and recommended calorie intake, and identifies the necessary nutrient intake.

[0254] Step 3:

[0255] Based on the results of the nutrition needs analysis, the server uses a generative AI model to generate appropriate meal plans. These plans take into account each member's preferences and nutritional needs, and include weekly recipes, cooking times, and ingredient lists.

[0256] Step 4:

[0257] The user inputs activity data obtained from a smartwatch or fitness tracker into the device. The device then sends this data to the server.

[0258] Step 5:

[0259] The server receives activity data, analyzes it, and assesses the exercise level of each household member. Based on the assessment, it generates exercise plans and health maintenance advice tailored to each member's needs.

[0260] Step 6:

[0261] The server generates educational content for children. Specifically, it creates games and quizzes that make learning about health information fun. This content is provided for educational purposes within the home.

[0262] Step 7:

[0263] The device displays generated meal plans, exercise plans, and educational content to the user. The user reviews these and uses them to promote a healthy lifestyle at home.

[0264] (Example 1)

[0265] 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."

[0266] In modern families, managing the health of each member is important, but developing individualized nutrition and exercise plans is difficult. Furthermore, there is limited content available to educate children about healthy habits. These circumstances make maintaining overall family health challenging.

[0267] 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.

[0268] In this invention, the server includes means for calculating and analyzing nutritional requirements based on basic cultural data for each household member, means for proposing personalized exercise plans based on individual activity information, and means for generating and providing educational materials. This makes it possible to provide nutritional management and exercise plans tailored to each member while also providing educational content that is fun to learn from.

[0269] "Family members" refers to individual members belonging to the same household, and includes multiple groups of different ages and genders.

[0270] "Basic cultural data" refers to attribute information about household members, such as age, gender, height, weight, allergy information, and food preferences. This data forms the basis for nutrition and health management.

[0271] "Nutritional requirements" refer to the amount of nutrients necessary for maintaining physical health and activity, and are calculated based on individual attributes.

[0272] "Device for providing" refers to hardware or software that provides meal plans and exercise suggestions tailored to each household member based on calculated nutritional requirements.

[0273] "Activity information" refers to data about physical activity obtained from smart devices, including information such as the number of steps taken and exercise time.

[0274] An "individualized exercise plan" refers to an optimized exercise schedule proposed based on the activity information of each household member.

[0275] "Educational materials" refer to content created to make learning about health, nutrition, and exercise fun, and are provided in the form of games or quizzes.

[0276] This invention is designed as a system to support health management within the home. Specific embodiments of the invention are described below.

[0277] The user enters basic cultural data for each household member into a terminal. This terminal is a standard computer or smart device equipped with an interface for entering information. This data includes each member's age, gender, height, weight, allergy information, and food preferences.

[0278] The terminal sends the entered information to the server. The server is deployed on a cloud-based computing platform or within a local network and analyzes the received data. The server calculates nutritional requirements based on basic cultural data. This includes algorithms for calculating basal metabolic rate and the required intake of individual nutrients.

[0279] The server uses a generative AI model to generate meal plans. Based on the prompt text, the AI model proposes appropriate meal recipes, the required ingredient lists, cooking times, etc. For example, a prompt text such as "A 40-year-old man, 175 cm tall, 70 kg in weight, no allergies, and likes Italian cuisine. Please propose a one-week healthy meal plan for him" is used.

[0280] Also, the user can input activity information from a smartwatch or fitness tracker into the terminal. The terminal sends this information to the server, and the server proposes an individualized exercise plan based on that data. Thereby, a healthy exercise plan suitable for each member is provided.

[0281] Furthermore, the server generates educational materials for children within the household and the terminal issues a notification. The educational materials include games and quizzes related to health and nutrition, and are content that allows children to learn in a fun way. The terminal notifies the user of the generated content and provides an environment where children can access it.

[0282] This system provides comprehensive support to sustain a healthy lifestyle for the entire household and helps to form optimal living habits according to individual health needs.

[0283] The flow of the specific process in Example 1 will be described using FIG. 11.

[0284] Step 1:

[0285] The user inputs the basic cultural data for each household member into the terminal. The input data here includes age, gender, height, weight, allergy information, food preferences, etc. The terminal formats this data and prepares to send it to the server. As a specific operation, the user inputs the necessary information into the input form and clicks the "Send" button.

[0286] Step 2:

[0287] The terminal sends formatted basic cultural data to the server. The server temporarily stores the received data and creates a profile of each member. In this step, the data integrity is checked and any missing information is verified. The server then prepares to calculate nutritional requirements based on the input data.

[0288] Step 3:

[0289] The server calculates and analyzes the nutritional requirements of each household member based on stored basic cultural data. The server uses algorithms to calculate basal metabolic rate and the required intake of specific nutrients. Based on this input, it outputs the optimal energy expenditure and nutrient intake for maintaining health. Specific actions performed by the server include applying existing nutrition calculation formulas and reflecting the data in individual profiles.

[0290] Step 4:

[0291] The server uses a generative AI model to generate a meal plan based on the analyzed nutritional requirements. The AI ​​model is input with a prompt such as, "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy weekly meal plan for him." The AI ​​model then suggests and outputs nutritionally balanced recipes, ingredient lists, and cooking times. The server then provides these suggestions to the user as a weekly meal plan.

[0292] Step 5:

[0293] The user inputs daily activity information obtained from a smartwatch or fitness tracker into the device. The device then converts this information into a data format for transmission to the server. Specifically, it uses an activity tracking app to acquire data and imports that information into the device app.

[0294] Step 6:

[0295] Based on the activity information received by the server, it evaluates the exercise level of each household member. The server aggregates the data and uses an algorithm to analyze daily exercise volume and patterns. Based on the calculated exercise level, it generates an individualized exercise plan and provides it to the user. At this stage, the server suggests specific exercises to supplement any insufficient exercise.

[0296] Step 7:

[0297] The server uses a generative AI model to develop and deliver educational content for children. This content includes quizzes and game-based learning materials, which the server sends to the user's device and notifies them. Users and their families can access this content via their devices and use it as an opportunity for learning and entertainment.

[0298] (Application Example 1)

[0299] 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."

[0300] There is a need to efficiently manage the health status of each family member and provide exercise and nutritional suggestions tailored to individual needs. Furthermore, there is a need for educational content that allows children to learn about health in an enjoyable way. However, conventional systems struggle to comprehensively meet these requirements, and the provision of services integrated with home devices is insufficient.

[0301] 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.

[0302] In this invention, the server includes an acquisition means for inputting basic attribute information for each household member, an analysis means for analyzing nutritional requirements based on the basic attribute information, and a generation means for generating a diet plan based on the analysis result. As a result, it becomes possible to perform health management using household mechanical devices, and it becomes possible to provide individually optimized nutrition and exercise plans. In addition, by using an interaction means equipped with a voice recognition function, it becomes possible to provide information through natural interaction with the user, and it is possible to consider making it available while enjoying learning content for children.

[0303] The "household member" refers to each individual belonging to a household and is an object that requires individual health management.

[0304] The "basic attribute information" refers to data such as an individual's age, gender, height, weight, allergy information, and food preferences, and is basic data used for nutritional analysis and formulation of exercise plans.

[0305] The "nutritional requirement" indicates the nutrients and calorie intake necessary for maintaining the health of each household member, and by analyzing it, it becomes possible to formulate an optimal diet plan.

[0306] The "analysis means" refers to a function for calculating and analyzing nutritional requirements based on the input basic attribute information, and is a process for generating an appropriate diet plan.

[0307] The "generation means" refers to a process or system for formulating a diet plan provided to each member based on the result obtained from the analysis means.

[0308] The "activity information" refers to data related to an individual's exercise amount and activity status obtained from a smartwatch, fitness tracker, etc., and is information necessary for proposing an exercise plan.

[0309] The "exercise plan" is a plan for proposing individually optimized exercise content and schedule based on the activity information of household members.

[0310] "Supplying means" refers to a system or process that provides members with generated learning content and meal plans, and includes providing diverse information, including learning content for children, in an easy-to-understand manner.

[0311] "Household medical devices" refer to equipment that can be used within the home and have functions to provide information and interact with others for health management.

[0312] "Dialogue methods" refer to processes and functions that use speech recognition technology to engage in natural interactions with users and provide them with necessary information.

[0313] This invention is a system designed to support health management within the home, efficiently collecting and analyzing health data for each household member and presenting an optimal nutrition and exercise plan. The embodiments of this system are described in detail below.

[0314] First, users input basic attribute information for each household member using a terminal. This information includes age, gender, height, weight, allergy information, and food preferences. This data is sent to a server and used as basic data for analyzing nutritional requirements.

[0315] The server analyzes each member's nutritional requirements based on the received basic attribute information. This process includes calculating each individual's basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients. Based on the analysis results, the server uses a generative AI model to generate a meal plan optimized for each member. This meal plan includes specific recipes and a list of necessary ingredients.

[0316] Furthermore, users transmit activity information obtained from smartwatches and fitness trackers to the server via their devices. Based on this activity information, the server evaluates each member's exercise level and proposes a personalized exercise plan. This exercise plan includes specific advice for maintaining the health of household members.

[0317] For children's learning, the server generates educational content in the form of games and quizzes, which are then delivered through the device. This allows children to learn about health-related knowledge in an enjoyable way.

[0318] For example, based on a prompt such as, "Please suggest a healthy dessert recipe that a 12-year-old child can enjoy," the system will suggest meals and snacks suitable for children. Similarly, through a prompt such as, "Please create a one-week meal plan for a man in his 30s, taking calories and nutritional value into consideration," an individualized nutrition plan will be provided.

[0319] The hardware uses a Raspberry Pi as a home device, and the software employs a generative AI model built with Python and TensorFlow. General-purpose speech processing software is used for speech recognition, enabling efficient health management within the home through voice interaction with the user.

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] Users use a terminal to enter basic attribute information of household members. This information includes age, gender, height, weight, allergy information, and food preferences. The entered data must be recorded accurately and in detail, as it will be used as initial settings in the system. This information is sent to the server and stored in the database.

[0323] Step 2:

[0324] Based on the received basic attribute information, the server uses a generating AI model to analyze the nutritional requirements of each member. Specifically, it calculates the basal metabolic rate and required calorie intake, and identifies the required intake of specific nutrients. This analysis is performed using a Python program and TensorFlow, and the output is data on the optimal nutritional requirements for each member.

[0325] Step 3:

[0326] The server uses an AI model based on the analysis results to generate a meal plan optimized for each member. The generated plan includes specific recipes, cooking times, and a list of necessary ingredients. This output is sent to the terminal and made available to the user.

[0327] Step 4:

[0328] Users input activity information obtained from smartwatches or fitness trackers into the device. This data includes steps taken, calories burned, and heart rate. The entered activity data is sent to a server and serves as the basis for evaluating exercise levels.

[0329] Step 5:

[0330] The server analyzes the input activity information and assesses each member's exercise level. Based on this assessment, an individual exercise plan is generated. The exercise plan includes the type and frequency of exercise to be performed, and incorporates advice to promote the user's health maintenance.

[0331] Step 6:

[0332] To generate learning content for children, the server utilizes a generation AI model to create educational content in game and quiz formats. This content is delivered and accessible via the user's device. The content is designed to allow children to learn about health in an enjoyable way.

[0333] Step 7:

[0334] The generated meal plans, exercise plans, and educational content are notified to the user via the device, supporting them in managing their health at home. Users can access the system interactively using voice recognition and request more detailed information or additional instructions.

[0335] 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.

[0336] This invention combines an emotional engine with a system that supports healthy living at home to achieve even more personalized health management. The system begins by inputting basic attribute data for each family member and analyzing their nutritional needs based on that data.

[0337] First, the user uses their device to input basic attribute data for each family member. This data is sent to a server, which analyzes each member's nutritional needs. Specifically, it calculates the required calorie intake and the required amounts of specific nutrients.

[0338] Based on these results, the server uses a generative AI model to create an appropriate meal plan and presents it to the user via the terminal. The user also inputs activity data into the terminal, and the server analyzes this data to provide appropriate exercise plans and health advice.

[0339] Furthermore, this system is equipped with an emotion engine that recognizes the user's emotional state. Based on the data from this emotion engine, the server can adjust the suggested meal menus and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, the system will suggest menus using ingredients with relaxing effects and exercise plans that promote relaxation.

[0340] Furthermore, educational content for children will be customized using emotional data. Specifically, content that is more engaging and enjoyable to learn from will be provided according to the child's emotional state, making it possible to increase their interest in health.

[0341] For example, if the emotional engine detects stress signals when parents are busy in a particular household, the server suggests a simple, healthy meal that can be prepared quickly, and recommends moderate exercise and meditation exercises to reduce stress. Furthermore, if a child is feeling bored, it provides educational content in the form of games that encourage active physical movement.

[0342] In this way, this system, which combines emotional engines, comprehensively supports the mental and physical health of the entire family.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] The user enters basic attribute data for each household member (e.g., age, gender, weight, height, allergy information, food preferences) into the device. The device then sends this data to the server.

[0346] Step 2:

[0347] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. This calculation includes required calorie intake and target intake of specific nutrients, providing an analysis tailored to each individual's health condition.

[0348] Step 3:

[0349] Based on the analysis results, the server uses a generative AI model to create meal plans tailored to each family member. These meal plans are adjusted according to individual nutritional needs and preferences, and include weekly recipes, cooking times, and lists of necessary ingredients.

[0350] Step 4:

[0351] Users input activity data collected by smartwatches and fitness trackers into their devices, or, if direct transmission is possible, the data is automatically sent to the server. The device is responsible for transmitting this data to the server.

[0352] Step 5:

[0353] The server analyzes activity data and evaluates the exercise level of each household member. Based on the evaluation results, it generates exercise plans and health advice tailored to each member's needs and proposes them to the user via the device.

[0354] Step 6:

[0355] The server activates an emotion engine to recognize the user's emotions, analyzing the user's facial expressions and voice data. It identifies the emotional state and tracks stress levels and emotional changes.

[0356] Step 7:

[0357] The server uses data from the emotion engine to adjust meal plans and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, it will suggest relaxation-promoting meals and lighter exercise plans.

[0358] Step 8:

[0359] The server generates educational content for children based on emotional data. Specifically, it provides games and quizzes customized to the child's mood and interests.

[0360] Step 9:

[0361] The device displays generated meal plans, exercise plans, and educational content to the user. The user can then use these suggestions to plan and carry out healthy activities at home.

[0362] (Example 2)

[0363] 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".

[0364] There is a growing need for more individualized health management within the family, enabling health maintenance tailored to the nutritional and emotional states of each member. However, conventional systems have been insufficient in considering emotional states, making it difficult to provide optimal diets and exercises for each individual. Furthermore, there is a lack of customization of educational content, particularly for children, and efforts are needed to capture their interest.

[0365] 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.

[0366] In this invention, the server includes means for inputting basic attribute information for each household member, means for evaluating nutritional requirements based on the attribute information, and means for recognizing emotional states. This makes it possible to provide each household member with more precise and emotionally sensitive nutritional management and exercise plans. Furthermore, it is possible to conduct health education while attracting the interest of children by generating and providing educational information for them.

[0367] "Household members" refers to individual people who live together within a specific household, and each of them is responsible for managing their own health.

[0368] "Basic attribute information" refers to information necessary for health management, such as age, gender, weight, height, and activity level of each household member.

[0369] "Nutritional requirements" refer to the amount of calories and various nutrients that household members need to maintain their health.

[0370] "Methods of evaluation" refers to the process of analyzing nutritional requirements using the input basic attribute information and calculating the appropriate amount of nutrients and calories needed.

[0371] A "meal plan" refers to a menu of meals that household members should consume, based on their assessed nutritional requirements.

[0372] "Activity status" refers to the types of exercise and physical activity that household members engage in on a daily basis, and is information related to maintaining health.

[0373] An "exercise plan" refers to exercise guidelines or programs designed to promote health, based on the activity levels of household members.

[0374] "Emotional state" refers to the emotional health of family members, including stress and mood swings.

[0375] "Means of recognizing emotional states" refers to technical methods for understanding the emotional states of family members and adjusting proposals based on those states.

[0376] "Educational information" refers specifically to content provided for children to promote learning and health awareness.

[0377] This invention provides a system that personalizes health management for each member of a household. This system uses emotion engine technology to recognize the user's emotional state and adjust meal plans and exercise plans accordingly.

[0378] First, users input basic attribute information for each household member through a terminal used at home. This information includes age, gender, weight, height, and lifestyle. The terminal sends this information to a server. Upon receiving this information, the server uses specialized nutritional analysis software to evaluate the nutritional requirements of each household member. Based on this evaluation, an individualized meal plan is generated, utilizing tools such as OpenAI's generative AI model.

[0379] The server then receives activity data from household members and uses it to create an exercise plan. An emotion engine is used to adjust the plan, taking into account the user's emotional state. The emotional state is inferred from voice input and screen interactions, and relaxation-enhancing exercises are suggested as needed.

[0380] As a concrete example, the server runs an AI model based on the prompt "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis. Please suggest a healthy dinner menu suitable for a high-stress situation," and generates a result.

[0381] In this way, the present invention utilizes an emotional engine and is designed to ensure that each member of a household receives optimal health management.

[0382] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0383] Step 1:

[0384] Users use a home terminal to input basic attribute information for each household member. This information includes age, gender, weight, height, and activity level. This information is formatted as digital data and sent from the terminal to the server.

[0385] Step 2:

[0386] The server analyzes the received attribute information and uses nutritional analysis software to evaluate the nutritional requirements of each member. During this process, the necessary calories and nutrients (protein, fat, carbohydrates, etc.) are calculated based on age and activity level. The output generates nutritional information necessary for each member.

[0387] Step 3:

[0388] The server inputs prompt sentences into the generating AI model based on the nutritional requirements assessment results. For example, it might input a sentence like, "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis; suggest a nutritionally balanced meal plan." The generating AI model then generates individual meal plans based on the input prompt sentences. This results in the output of the optimal meal menu for each member.

[0389] Step 4:

[0390] Users input their exercise and daily activity data into the device. This includes daily steps, type of exercise, and duration. The device then sends this activity data back to the server.

[0391] Step 5:

[0392] The server analyzes the transmitted activity data and proposes an exercise plan tailored to the lifestyle of each household member. This analysis assesses the need for excess calorie expenditure and muscle strengthening. As output, an individual exercise plan is generated.

[0393] Step 6:

[0394] The server uses an emotion engine to recognize the user's emotional state. Based on the input data, the user's stress level and emotional changes are analyzed. This emotional data is used to adaptively adjust suggested meal plans and exercise plans. As output, emotionally sensitive advice is provided.

[0395] Step 7:

[0396] The server generates educational content for children based on their emotional state. Specifically, it selects health education materials and games that are likely to interest children. This provides content that is fun to learn while raising children's health awareness.

[0397] (Application Example 2)

[0398] 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 as the "terminal".

[0399] In modern society, personal health management is a crucial issue, but achieving effective health management tailored to each family's and individual's lifestyle and emotional state is difficult. Therefore, there is a need for systems that provide more personalized health promotion services.

[0400] 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.

[0401] In this invention, the server includes an input means for inputting basic attribute information for each household member, an emotion recognition means for recognizing and analyzing an individual's emotional state, and an adjustment means for adjusting and providing health promotion plans based on the emotional state. This enables personalized health management tailored to the lifestyle and emotional state of each household.

[0402] "Basic attribute information for each household member" refers to individual data such as age, gender, weight, and height for each member of the household.

[0403] "Nutritional needs" refer to the requirements regarding the intake of specific nutrients and calories necessary for maintaining an individual's health.

[0404] "Analysis means" refers to a method or apparatus for analyzing necessary nutritional needs based on the input basic attribute information.

[0405] "Generating means" refers to a method or apparatus for creating an individualized meal plan according to the analysis results.

[0406] "Activity information" refers to data about the exercise and activities that household members engage in on a daily basis.

[0407] "Proposed means" refers to a method or apparatus for providing an appropriate exercise plan based on activity information.

[0408] "Educational resources" is a general term for learning and educational materials and content provided to children.

[0409] "Emotion recognition means" refers to a method or device for detecting and analyzing an individual's emotional state.

[0410] "Adjustment means" refers to a method or apparatus for appropriately modifying and providing the proposed content in accordance with the recognized emotional state.

[0411] A "means for proposing health events" refers to a method or device for presenting events or activities that promote health improvement in accordance with the living environment of residents.

[0412] This invention realizes a system to support health management in the home. The system begins by inputting basic attribute information for each family member into a terminal and sending it to a server. This basic attribute information includes the age, gender, weight, and height of each family member. Once this data is sent to the server, the server uses a generative AI model to analyze the nutritional needs of each member and generates a meal plan based on that analysis.

[0413] The server also receives activity information from household members and proposes personalized exercise plans based on this information. This activity information includes daily exercise habits and activity levels. Furthermore, the system uses emotion recognition tools to detect and analyze the user's emotional state. This can be done using software such as OpenCV or the Emotion-Recognition API. Based on this emotional data, the server adjusts health promotion suggestions and provides an appropriate health management plan.

[0414] To give a specific example, if a user inputs their activity information using a device and the emotion recognition system detects "stress," the server will adjust and provide meal and activity suggestions that are appropriate for the user's emotional state. For example, suggestions might include "meals using ingredients effective for relaxation" or "exercise aimed at stress relief."

[0415] An example of a prompt message used as input to a generative AI model is, "Based on the user's emotional state, please suggest the most suitable relaxation method."

[0416] In this way, the system provides a way to comprehensively manage the health status of the entire household.

[0417] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0418] Step 1:

[0419] The user uses a device to enter basic attribute information for family members. This information includes data such as age, gender, weight, and height. The entered data is temporarily stored on the device.

[0420] Step 2:

[0421] The terminal sends the entered basic attribute information to the server. After receiving this information, the server uses a generative AI model to analyze the nutritional needs. The nutritional needs analysis involves data processing to calculate the required calories and the required amounts of specific nutrients.

[0422] Step 3:

[0423] The server generates a personalized meal plan based on the analysis results. This generation utilizes historical data and the latest nutritional information, and the generating AI model creates prompts to design the optimal meal plan.

[0424] Step 4:

[0425] Users input daily activity information into their devices. This includes data on exercise levels and activity types. This information is sent to a server to supplement health management.

[0426] Step 5:

[0427] After receiving activity information, the server proposes an exercise plan. This process involves data calculations based on the input activity data to select appropriate exercises. This results in a training plan optimized for the user.

[0428] Step 6:

[0429] The device analyzes the user's emotional state through emotion recognition mechanisms. Using camera and sensor data, it identifies emotions using the Emotion-Recognition API. This result is sent to a server and used to adjust health promotion recommendations based on the emotional state.

[0430] Step 7:

[0431] After receiving emotional data, the server adjusts health management suggestions based on that data and provides them to the user. For example, a generative AI model might generate a prompt such as, "Please suggest the best relaxation methods based on the user's emotional state," and then suggest meals and activities appropriate to the user's emotional state.

[0432] Step 8:

[0433] Users can review meal plans, exercise plans, and health management suggestions based on their emotional state, received through their device, and use them to maintain their daily health. This output serves as concrete action guidelines for improving daily lifestyle habits.

[0434] 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.

[0435] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0436] 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.

[0437] [Third Embodiment]

[0438] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0439] 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.

[0440] 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).

[0441] 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.

[0442] 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.

[0443] 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).

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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".

[0450] This invention provides a system that supports a healthy lifestyle in the home. The following describes each component of the system and the processes it performs.

[0451] First, the user uses a device to input basic attribute data for each household member, such as age, gender, height, weight, allergy information, and food preferences. This data is sent from the device to the server, which then receives it.

[0452] Next, the server calculates and analyzes each member's nutritional needs based on the received basic attribute data. This analysis includes calculating basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients.

[0453] Based on this analysis, the server uses a generative AI model to generate healthy meal plans tailored to each member. These plans are suggested weekly and include specific recipes, cooking times, and a list of necessary ingredients.

[0454] Users input activity data obtained from smartwatches and fitness trackers back into the device, which then sends it to a server. The server analyzes this activity data and assesses the exercise level of each household member. Furthermore, exercise plans and health maintenance advice are suggested based on these analysis results. This allows each member to manage their health according to their individual needs.

[0455] Furthermore, the server generates educational content for children at home. This content is presented in the form of games and quizzes, allowing children to learn about health while having fun. The device notifies the user of the generated content, making it accessible to the children.

[0456] For example, in one family where the child doesn't particularly like vegetables, the server suggests recipes that make vegetables delicious and provides educational content that makes eating them fun. Also, even if parents are busy, the system provides simple exercise plans to prevent a sedentary lifestyle and support their health.

[0457] In this way, "Healthy Family AI" is a system that provides comprehensive support for a healthy lifestyle for the entire family.

[0458] The following describes the processing flow.

[0459] Step 1:

[0460] The user enters basic attribute data for each household member (age, gender, height, weight, allergy information, food preferences, etc.) into the terminal. The terminal verifies the entered data, checks that the format is correct, and then sends it to the server.

[0461] Step 2:

[0462] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. Specifically, it calculates basal metabolic rate and recommended calorie intake, and identifies the necessary nutrient intake.

[0463] Step 3:

[0464] Based on the results of the nutrition needs analysis, the server uses a generative AI model to generate appropriate meal plans. These plans take into account each member's preferences and nutritional needs, and include weekly recipes, cooking times, and ingredient lists.

[0465] Step 4:

[0466] The user inputs activity data obtained from a smartwatch or fitness tracker into the device. The device then sends this data to the server.

[0467] Step 5:

[0468] The server receives activity data, analyzes it, and assesses the exercise level of each household member. Based on the assessment, it generates exercise plans and health maintenance advice tailored to each member's needs.

[0469] Step 6:

[0470] The server generates educational content for children. Specifically, it creates games and quizzes that make learning about health information fun. This content is provided for educational purposes within the home.

[0471] Step 7:

[0472] The device displays generated meal plans, exercise plans, and educational content to the user. The user reviews these and uses them to promote a healthy lifestyle at home.

[0473] (Example 1)

[0474] 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."

[0475] In modern families, managing the health of each member is important, but developing individualized nutrition and exercise plans is difficult. Furthermore, there is limited content available to educate children about healthy habits. These circumstances make maintaining overall family health challenging.

[0476] 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.

[0477] In this invention, the server includes means for calculating and analyzing nutritional requirements based on basic cultural data for each household member, means for proposing personalized exercise plans based on individual activity information, and means for generating and providing educational materials. This makes it possible to provide nutritional management and exercise plans tailored to each member while also providing educational content that is fun to learn from.

[0478] "Family members" refers to individual members belonging to the same household, and includes multiple groups of different ages and genders.

[0479] "Basic cultural data" refers to attribute information about household members, such as age, gender, height, weight, allergy information, and food preferences. This data forms the basis for nutrition and health management.

[0480] "Nutritional requirements" refer to the amount of nutrients necessary for maintaining physical health and activity, and are calculated based on individual attributes.

[0481] "Device for providing" refers to hardware or software that provides meal plans and exercise suggestions tailored to each household member based on calculated nutritional requirements.

[0482] "Activity information" refers to data about physical activity obtained from smart devices, including information such as the number of steps taken and exercise time.

[0483] An "individualized exercise plan" refers to an optimized exercise schedule proposed based on the activity information of each household member.

[0484] "Educational materials" refer to content created to make learning about health, nutrition, and exercise fun, and are provided in the form of games or quizzes.

[0485] This invention is designed as a system to support health management within the home. Specific embodiments of the invention are described below.

[0486] The user enters basic cultural data for each household member into a terminal. This terminal is a standard computer or smart device equipped with an interface for entering information. This data includes each member's age, gender, height, weight, allergy information, and food preferences.

[0487] The terminal sends the entered information to the server. The server is deployed on a cloud-based computing platform or within a local network and analyzes the received data. The server calculates nutritional requirements based on basic cultural data. This includes algorithms for calculating basal metabolic rate and the required intake of individual nutrients.

[0488] The server generates meal plans using a generative AI model. Based on the prompt, the AI ​​model suggests appropriate meal recipes, lists of necessary ingredients, cooking times, and more. For example, a prompt might be: "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy meal plan for him for one week."

[0489] Furthermore, users can input activity information from smartwatches and fitness trackers into the device. The device sends this information to a server, which then proposes a personalized exercise plan based on that data. This ensures that each member receives a healthy exercise plan tailored to their needs.

[0490] Furthermore, the server generates educational materials for children at home, and the device notifies them. These educational materials include games and quizzes about health and nutrition, making learning fun for children. The device notifies the user of the generated content, providing an environment where children can access it.

[0491] This system provides comprehensive support for a healthy lifestyle for the entire family, helping to create optimal lifestyle habits tailored to individual health needs.

[0492] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0493] Step 1:

[0494] The user enters basic cultural data for each household member into the terminal. This data includes age, gender, height, weight, allergy information, and food preferences. The terminal formats this data and prepares it for transmission to the server. Specifically, the user enters the required information into the input form and clicks the "Submit" button.

[0495] Step 2:

[0496] The terminal sends formatted basic cultural data to the server. The server temporarily stores the received data and creates a profile of each member. In this step, the data integrity is checked and any missing information is verified. The server then prepares to calculate nutritional requirements based on the input data.

[0497] Step 3:

[0498] The server calculates and analyzes the nutritional requirements of each household member based on stored basic cultural data. The server uses algorithms to calculate basal metabolic rate and the required intake of specific nutrients. Based on this input, it outputs the optimal energy expenditure and nutrient intake for maintaining health. Specific actions performed by the server include applying existing nutrition calculation formulas and reflecting the data in individual profiles.

[0499] Step 4:

[0500] The server uses a generative AI model to generate a meal plan based on the analyzed nutritional requirements. The AI ​​model is input with a prompt such as, "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy weekly meal plan for him." The AI ​​model then suggests and outputs nutritionally balanced recipes, ingredient lists, and cooking times. The server then provides these suggestions to the user as a weekly meal plan.

[0501] Step 5:

[0502] The user inputs daily activity information obtained from a smartwatch or fitness tracker into the device. The device then converts this information into a data format for transmission to the server. Specifically, it uses an activity tracking app to acquire data and imports that information into the device app.

[0503] Step 6:

[0504] Based on the activity information received by the server, it evaluates the exercise level of each household member. The server aggregates the data and uses an algorithm to analyze daily exercise volume and patterns. Based on the calculated exercise level, it generates an individualized exercise plan and provides it to the user. At this stage, the server suggests specific exercises to supplement any insufficient exercise.

[0505] Step 7:

[0506] The server uses a generative AI model to develop and deliver educational content for children. This content includes quizzes and game-based learning materials, which the server sends to the user's device and notifies them. Users and their families can access this content via their devices and use it as an opportunity for learning and entertainment.

[0507] (Application Example 1)

[0508] 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."

[0509] There is a need to efficiently manage the health status of each family member and provide exercise and nutritional suggestions tailored to individual needs. Furthermore, there is a need for educational content that allows children to learn about health in an enjoyable way. However, conventional systems struggle to comprehensively meet these requirements, and the provision of services integrated with home devices is insufficient.

[0510] 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.

[0511] In this invention, the server includes an acquisition means for inputting basic attribute information for each household member, an analysis means for analyzing nutritional requirements based on the basic attribute information, and a generation means for generating a meal plan based on the analysis results. This enables health management using a home appliance and allows for the provision of individually optimized nutrition and exercise plans. Furthermore, by using a dialogue means equipped with voice recognition functionality, information can be provided through natural dialogue with the user, and consideration can be given to making learning content for children enjoyable to use.

[0512] "Family members" refers to each individual belonging to a household, and each of them is responsible for managing their own health.

[0513] "Basic attribute information" refers to data such as an individual's age, gender, height, weight, allergy information, and food preferences, and is fundamental data used for nutritional analysis and exercise plan development.

[0514] "Nutritional requirements" refer to the amount of nutrients and calories needed to maintain the health of each household member, and analyzing these requirements makes it possible to create an optimal meal plan.

[0515] "Analysis means" refers to a function that calculates and analyzes nutritional requirements based on the input basic attribute information, and is a process for generating an appropriate meal plan.

[0516] "Generation means" refers to the process or system for formulating meal plans to be provided to each member based on the results obtained from the analysis means.

[0517] "Activity information" refers to data on an individual's exercise volume and activity status obtained from smartwatches, fitness trackers, etc., and is necessary information for suggesting exercise plans.

[0518] An "exercise plan" is a plan that proposes individually optimized exercise content and schedules based on the activity information of each household member.

[0519] "Supplying means" refers to a system or process that provides members with generated learning content and meal plans, and includes providing diverse information, including learning content for children, in an easy-to-understand manner.

[0520] "Household medical devices" refer to equipment that can be used within the home and have functions to provide information and interact with others for health management.

[0521] "Dialogue methods" refer to processes and functions that use speech recognition technology to engage in natural interactions with users and provide them with necessary information.

[0522] This invention is a system designed to support health management within the home, efficiently collecting and analyzing health data for each household member and presenting an optimal nutrition and exercise plan. The embodiments are described in detail below.

[0523] First, users input basic attribute information for each household member using a terminal. This information includes age, gender, height, weight, allergy information, and food preferences. This data is sent to a server and used as basic data for analyzing nutritional requirements.

[0524] The server analyzes each member's nutritional requirements based on the received basic attribute information. This process includes calculating each individual's basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients. Based on the analysis results, the server uses a generative AI model to generate a meal plan optimized for each member. This meal plan includes specific recipes and a list of necessary ingredients.

[0525] Furthermore, users transmit activity information obtained from smartwatches and fitness trackers to the server via their devices. Based on this activity information, the server evaluates each member's exercise level and proposes a personalized exercise plan. This exercise plan includes specific advice for maintaining the health of household members.

[0526] For children's learning, the server generates educational content in the form of games and quizzes, which are then delivered through the device. This allows children to learn about health-related knowledge in an enjoyable way.

[0527] For example, based on a prompt such as, "Please suggest a healthy dessert recipe that a 12-year-old child can enjoy," the system will suggest meals and snacks suitable for children. Similarly, through a prompt such as, "Please create a one-week meal plan for a man in his 30s, taking calories and nutritional value into consideration," an individualized nutrition plan will be provided.

[0528] The hardware uses a Raspberry Pi as the home device, and the software employs a generative AI model built with Python and TensorFlow. General-purpose speech processing software is used for speech recognition, enabling efficient health management within the home through voice interaction with the user.

[0529] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0530] Step 1:

[0531] Users use a terminal to enter basic attribute information of household members. This information includes age, gender, height, weight, allergy information, and food preferences. The entered data must be recorded accurately and in detail, as it will be used as initial settings in the system. This information is sent to the server and stored in the database.

[0532] Step 2:

[0533] Based on the received basic attribute information, the server uses a generating AI model to analyze the nutritional requirements of each member. Specifically, it calculates the basal metabolic rate and required calorie intake, and identifies the required intake of specific nutrients. This analysis is performed using a Python program and TensorFlow, and the output is data on the optimal nutritional requirements for each member.

[0534] Step 3:

[0535] The server uses an AI model based on the analysis results to generate a meal plan optimized for each member. The generated plan includes specific recipes, cooking times, and a list of necessary ingredients. This output is sent to the terminal and made available to the user.

[0536] Step 4:

[0537] Users input activity information obtained from smartwatches or fitness trackers into the device. This data includes steps taken, calories burned, and heart rate. The entered activity data is sent to a server and serves as the basis for evaluating exercise levels.

[0538] Step 5:

[0539] The server analyzes the input activity information and assesses each member's exercise level. Based on this assessment, an individual exercise plan is generated. The exercise plan includes the type and frequency of exercise to be performed, and incorporates advice to promote the user's health maintenance.

[0540] Step 6:

[0541] To generate learning content for children, the server utilizes a generation AI model to create educational content in game and quiz formats. This content is delivered and accessible via the user's device. The content is designed to allow children to learn about health in an enjoyable way.

[0542] Step 7:

[0543] The generated meal plans, exercise plans, and educational content are notified to the user via the device, supporting them in managing their health at home. Users can access the system interactively using voice recognition and request more detailed information or additional instructions.

[0544] 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.

[0545] This invention combines an emotional engine with a system that supports healthy living at home to achieve even more personalized health management. The system begins by inputting basic attribute data for each family member and analyzing their nutritional needs based on that data.

[0546] First, the user uses their device to input basic attribute data for each family member. This data is sent to a server, which analyzes each member's nutritional needs. Specifically, it calculates the required calorie intake and the required amounts of specific nutrients.

[0547] Based on these results, the server uses a generative AI model to create an appropriate meal plan and presents it to the user via the terminal. The user also inputs activity data into the terminal, and the server analyzes this data to provide appropriate exercise plans and health advice.

[0548] Furthermore, this system is equipped with an emotion engine that recognizes the user's emotional state. Based on the data from this emotion engine, the server can adjust the suggested meal menus and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, the system will suggest menus using ingredients with relaxing effects and exercise plans that promote relaxation.

[0549] Furthermore, educational content for children will be customized using emotional data. Specifically, content that is more engaging and enjoyable to learn from will be provided according to the child's emotional state, making it possible to increase their interest in health.

[0550] For example, if the emotional engine detects stress signals when parents are busy in a particular household, the server suggests a simple, healthy meal that can be prepared quickly, and recommends moderate exercise and meditation exercises to reduce stress. Furthermore, if a child is feeling bored, it provides educational content in the form of games that encourage active physical movement.

[0551] In this way, this system, which combines emotional engines, comprehensively supports the mental and physical health of the entire family.

[0552] The following describes the processing flow.

[0553] Step 1:

[0554] The user enters basic attribute data for each household member (e.g., age, gender, weight, height, allergy information, food preferences) into the device. The device then sends this data to the server.

[0555] Step 2:

[0556] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. This calculation includes required calorie intake and target intake of specific nutrients, providing an analysis tailored to each individual's health condition.

[0557] Step 3:

[0558] Based on the analysis results, the server uses a generative AI model to create meal plans tailored to each family member. These meal plans are adjusted according to individual nutritional needs and preferences, and include weekly recipes, cooking times, and lists of necessary ingredients.

[0559] Step 4:

[0560] Users input activity data collected by smartwatches and fitness trackers into their devices, or, if direct transmission is possible, the data is automatically sent to the server. The device is responsible for transmitting this data to the server.

[0561] Step 5:

[0562] The server analyzes activity data and evaluates the exercise level of each household member. Based on the evaluation results, it generates exercise plans and health advice tailored to each member's needs and proposes them to the user via the device.

[0563] Step 6:

[0564] The server activates an emotion engine to recognize the user's emotions, analyzing the user's facial expressions and voice data. It identifies the emotional state and tracks stress levels and emotional changes.

[0565] Step 7:

[0566] The server uses data from the emotion engine to adjust meal plans and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, it will suggest relaxation-promoting meals and lighter exercise plans.

[0567] Step 8:

[0568] The server generates educational content for children based on emotional data. Specifically, it provides games and quizzes customized to the child's mood and interests.

[0569] Step 9:

[0570] The device displays generated meal plans, exercise plans, and educational content to the user. The user can then use these suggestions to plan and carry out healthy activities at home.

[0571] (Example 2)

[0572] 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."

[0573] There is a growing need for more individualized health management within the family, enabling health maintenance tailored to the nutritional and emotional states of each member. However, conventional systems have been insufficient in considering emotional states, making it difficult to provide optimal diets and exercises for each individual. Furthermore, there is a lack of customization of educational content, particularly for children, and efforts are needed to capture their interest.

[0574] 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.

[0575] In this invention, the server includes means for inputting basic attribute information for each household member, means for evaluating nutritional requirements based on the attribute information, and means for recognizing emotional states. This makes it possible to provide each household member with more precise and emotionally sensitive nutritional management and exercise plans. Furthermore, it is possible to conduct health education while attracting the interest of children by generating and providing educational information for them.

[0576] "Household members" refers to individual people who live together within a specific household, and each of them is responsible for managing their own health.

[0577] "Basic attribute information" refers to information necessary for health management, such as age, gender, weight, height, and activity level of each household member.

[0578] "Nutritional requirements" refer to the amount of calories and various nutrients that household members need to maintain their health.

[0579] "Methods of evaluation" refers to the process of analyzing nutritional requirements using the input basic attribute information and calculating the appropriate amount of nutrients and calories needed.

[0580] A "meal plan" refers to a menu of meals that household members should consume, based on their assessed nutritional requirements.

[0581] "Activity status" refers to the types of exercise and physical activity that household members engage in on a daily basis, and is information related to maintaining health.

[0582] An "exercise plan" refers to exercise guidelines or programs designed to promote health, based on the activity levels of household members.

[0583] "Emotional state" refers to the emotional health of family members, including stress and mood swings.

[0584] "Means of recognizing emotional states" refers to technical methods for understanding the emotional states of family members and adjusting proposals based on those states.

[0585] "Educational information" refers specifically to content provided for children to promote learning and health awareness.

[0586] This invention provides a system that personalizes health management for each member of a household. This system uses emotion engine technology to recognize the user's emotional state and adjust meal plans and exercise plans accordingly.

[0587] First, users input basic attribute information for each household member through a terminal used at home. This information includes age, gender, weight, height, and lifestyle. The terminal sends this information to a server. Upon receiving this information, the server uses specialized nutritional analysis software to evaluate the nutritional requirements of each household member. Based on this evaluation, an individualized meal plan is generated, utilizing tools such as OpenAI's generative AI model.

[0588] The server then receives activity data from household members and uses it to create an exercise plan. An emotion engine is used to adjust the plan, taking into account the user's emotional state. The emotional state is inferred from voice input and screen interactions, and relaxation-enhancing exercises are suggested as needed.

[0589] As a concrete example, the server runs an AI model based on the prompt "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis. Please suggest a healthy dinner menu suitable for a high-stress situation," and generates a result.

[0590] In this way, the present invention utilizes an emotional engine and is designed to ensure that each member of a household receives optimal health management.

[0591] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0592] Step 1:

[0593] Users use a home terminal to input basic attribute information for each household member. This information includes age, gender, weight, height, and activity level. This information is formatted as digital data and sent from the terminal to the server.

[0594] Step 2:

[0595] The server analyzes the received attribute information and uses nutritional analysis software to evaluate the nutritional requirements of each member. During this process, the necessary calories and nutrients (protein, fat, carbohydrates, etc.) are calculated based on age and activity level. The output generates nutritional information necessary for each member.

[0596] Step 3:

[0597] The server inputs prompt sentences into the generating AI model based on the nutritional requirements assessment results. For example, it might input a sentence like, "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis; suggest a nutritionally balanced meal plan." The generating AI model then generates individual meal plans based on the input prompt sentences. This results in the output of the optimal meal menu for each member.

[0598] Step 4:

[0599] Users input their exercise and daily activity data into the device. This includes daily steps, type of exercise, and duration. The device then sends this activity data back to the server.

[0600] Step 5:

[0601] The server analyzes the transmitted activity data and proposes an exercise plan tailored to the lifestyle of each household member. This analysis assesses the need for excess calorie expenditure and muscle strengthening. As output, an individual exercise plan is generated.

[0602] Step 6:

[0603] The server uses an emotion engine to recognize the user's emotional state. Based on the input data, the user's stress level and emotional changes are analyzed. This emotional data is used to adaptively adjust suggested meal plans and exercise plans. As output, emotionally sensitive advice is provided.

[0604] Step 7:

[0605] The server generates educational content for children based on their emotional state. Specifically, it selects health education materials and games that are likely to interest children. This provides content that is fun to learn while raising children's health awareness.

[0606] (Application Example 2)

[0607] 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."

[0608] In modern society, personal health management is a crucial issue, but achieving effective health management tailored to each family's and individual's lifestyle and emotional state is difficult. Therefore, there is a need for systems that provide more personalized health promotion services.

[0609] 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.

[0610] In this invention, the server includes an input means for inputting basic attribute information for each household member, an emotion recognition means for recognizing and analyzing an individual's emotional state, and an adjustment means for adjusting and providing health promotion plans based on the emotional state. This enables personalized health management tailored to the lifestyle and emotional state of each household.

[0611] "Basic attribute information for each household member" refers to individual data such as age, gender, weight, and height for each member of the household.

[0612] "Nutritional needs" refer to the requirements regarding the intake of specific nutrients and calories necessary for maintaining an individual's health.

[0613] "Analysis means" refers to a method or apparatus for analyzing necessary nutritional needs based on the input basic attribute information.

[0614] "Generating means" refers to a method or apparatus for creating an individualized meal plan according to the analysis results.

[0615] "Activity information" refers to data about the exercise and activities that household members engage in on a daily basis.

[0616] "Proposed means" refers to a method or apparatus for providing an appropriate exercise plan based on activity information.

[0617] "Educational resources" is a general term for learning and educational materials and content provided to children.

[0618] "Emotion recognition means" refers to a method or device for detecting and analyzing an individual's emotional state.

[0619] "Adjustment means" refers to a method or apparatus for appropriately modifying and providing the proposed content in accordance with the recognized emotional state.

[0620] A "means for proposing health events" refers to a method or device for presenting events or activities that promote health improvement in accordance with the living environment of residents.

[0621] This invention realizes a system to support health management in the home. The system begins by inputting basic attribute information for each family member into a terminal and sending it to a server. This basic attribute information includes the age, gender, weight, and height of each family member. Once this data is sent to the server, the server uses a generative AI model to analyze the nutritional needs of each member and generates a meal plan based on that analysis.

[0622] The server also receives activity information from household members and proposes personalized exercise plans based on this information. This activity information includes daily exercise habits and activity levels. Furthermore, the system uses emotion recognition tools to detect and analyze the user's emotional state. This can be done using software such as OpenCV or the Emotion-Recognition API. Based on this emotional data, the server adjusts health promotion suggestions and provides an appropriate health management plan.

[0623] To give a specific example, if a user inputs their activity information using a device and the emotion recognition system detects "stress," the server will adjust and provide meal and activity suggestions that are appropriate for the user's emotional state. For example, suggestions might include "meals using ingredients effective for relaxation" or "exercise aimed at stress relief."

[0624] An example of a prompt message used as input to a generative AI model is, "Based on the user's emotional state, please suggest the most suitable relaxation method."

[0625] In this way, the system provides a way to comprehensively manage the health status of the entire household.

[0626] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0627] Step 1:

[0628] The user uses a device to enter basic attribute information for family members. This information includes data such as age, gender, weight, and height. The entered data is temporarily stored on the device.

[0629] Step 2:

[0630] The terminal sends the entered basic attribute information to the server. After receiving this information, the server uses a generative AI model to analyze the nutritional needs. The nutritional needs analysis involves data processing to calculate the required calories and the required amounts of specific nutrients.

[0631] Step 3:

[0632] The server generates a personalized meal plan based on the analysis results. This generation utilizes historical data and the latest nutritional information, and the generating AI model creates prompts to design the optimal meal plan.

[0633] Step 4:

[0634] Users input daily activity information into their devices. This includes data on exercise levels and activity types. This information is sent to a server to supplement health management.

[0635] Step 5:

[0636] After receiving activity information, the server proposes an exercise plan. This process involves data calculations based on the input activity data to select appropriate exercises. This results in a training plan optimized for the user.

[0637] Step 6:

[0638] The device analyzes the user's emotional state through emotion recognition mechanisms. Using camera and sensor data, it identifies emotions using the Emotion-Recognition API. This result is sent to a server and used to adjust health promotion recommendations based on the emotional state.

[0639] Step 7:

[0640] After receiving emotional data, the server adjusts health management suggestions based on that data and provides them to the user. For example, a generative AI model might generate a prompt such as, "Please suggest the best relaxation methods based on the user's emotional state," and then suggest meals and activities appropriate to the user's emotional state.

[0641] Step 8:

[0642] Users can review meal plans, exercise plans, and health management suggestions based on their emotional state, received through their device, and use them to maintain their daily health. This output serves as concrete action guidelines for improving daily lifestyle habits.

[0643] 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.

[0644] 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.

[0645] 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.

[0646] [Fourth Embodiment]

[0647] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0648] 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.

[0649] 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).

[0650] 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.

[0651] 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.

[0652] 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).

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] 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".

[0660] This invention provides a system that supports a healthy lifestyle in the home. The following describes each component of the system and the processes it performs.

[0661] First, the user uses a device to input basic attribute data for each household member, such as age, gender, height, weight, allergy information, and food preferences. This data is sent from the device to the server, which then receives it.

[0662] Next, the server calculates and analyzes each member's nutritional needs based on the received basic attribute data. This analysis includes calculating basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients.

[0663] Based on this analysis, the server uses a generative AI model to generate healthy meal plans tailored to each member. These plans are suggested weekly and include specific recipes, cooking times, and a list of necessary ingredients.

[0664] Users input activity data obtained from smartwatches and fitness trackers back into the device, which then sends it to a server. The server analyzes this activity data and assesses the exercise level of each household member. Furthermore, exercise plans and health maintenance advice are suggested based on these analysis results. This allows each member to manage their health according to their individual needs.

[0665] Furthermore, the server generates educational content for children at home. This content is presented in the form of games and quizzes, allowing children to learn about health while having fun. The device notifies the user of the generated content, making it accessible to the children.

[0666] For example, in one family where the child doesn't particularly like vegetables, the server suggests recipes that make vegetables delicious and provides educational content that makes eating them fun. Also, even if parents are busy, the system provides simple exercise plans to prevent a sedentary lifestyle and support their health.

[0667] In this way, "Healthy Family AI" is a system that provides comprehensive support for a healthy lifestyle for the entire family.

[0668] The following describes the processing flow.

[0669] Step 1:

[0670] The user enters basic attribute data for each household member (age, gender, height, weight, allergy information, food preferences, etc.) into the terminal. The terminal verifies the entered data, checks that the format is correct, and then sends it to the server.

[0671] Step 2:

[0672] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. Specifically, it calculates basal metabolic rate and recommended calorie intake, and identifies the necessary nutrient intake.

[0673] Step 3:

[0674] Based on the results of the nutrition needs analysis, the server uses a generative AI model to generate appropriate meal plans. These plans take into account each member's preferences and nutritional needs, and include weekly recipes, cooking times, and ingredient lists.

[0675] Step 4:

[0676] The user inputs activity data obtained from a smartwatch or fitness tracker into the device. The device then sends this data to the server.

[0677] Step 5:

[0678] The server receives activity data, analyzes it, and assesses the exercise level of each household member. Based on the assessment, it generates exercise plans and health maintenance advice tailored to each member's needs.

[0679] Step 6:

[0680] The server generates educational content for children. Specifically, it creates games and quizzes that make learning about health information fun. This content is provided for educational purposes within the home.

[0681] Step 7:

[0682] The device displays generated meal plans, exercise plans, and educational content to the user. The user reviews these and uses them to promote a healthy lifestyle at home.

[0683] (Example 1)

[0684] 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".

[0685] In modern families, managing the health of each member is important, but developing individualized nutrition and exercise plans is difficult. Furthermore, there is limited content available to educate children about healthy habits. These circumstances make maintaining overall family health challenging.

[0686] 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.

[0687] In this invention, the server includes means for calculating and analyzing nutritional requirements based on basic cultural data for each household member, means for proposing personalized exercise plans based on individual activity information, and means for generating and providing educational materials. This makes it possible to provide nutritional management and exercise plans tailored to each member while also providing educational content that is fun to learn from.

[0688] "Family members" refers to individual members belonging to the same household, and includes multiple groups of different ages and genders.

[0689] "Basic cultural data" refers to attribute information about household members, such as age, gender, height, weight, allergy information, and food preferences. This data forms the basis for nutrition and health management.

[0690] "Nutritional requirements" refer to the amount of nutrients necessary for maintaining physical health and activity, and are calculated based on individual attributes.

[0691] "Device for providing" refers to hardware or software that provides meal plans and exercise suggestions tailored to each household member based on calculated nutritional requirements.

[0692] "Activity information" refers to data about physical activity obtained from smart devices, including information such as the number of steps taken and exercise time.

[0693] An "individualized exercise plan" refers to an optimized exercise schedule proposed based on the activity information of each household member.

[0694] "Educational materials" refer to content created to make learning about health, nutrition, and exercise fun, and are provided in the form of games or quizzes.

[0695] This invention is designed as a system to support health management within the home. Specific embodiments of the invention are described below.

[0696] The user enters basic cultural data for each household member into a terminal. This terminal is a standard computer or smart device equipped with an interface for entering information. This data includes each member's age, gender, height, weight, allergy information, and food preferences.

[0697] The terminal sends the entered information to the server. The server is deployed on a cloud-based computing platform or within a local network and analyzes the received data. The server calculates nutritional requirements based on basic cultural data. This includes algorithms for calculating basal metabolic rate and the required intake of individual nutrients.

[0698] The server generates meal plans using a generative AI model. Based on the prompt, the AI ​​model suggests appropriate meal recipes, lists of necessary ingredients, cooking times, and more. For example, a prompt might be: "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy meal plan for him for one week."

[0699] Furthermore, users can input activity information from smartwatches and fitness trackers into the device. The device sends this information to a server, which then proposes a personalized exercise plan based on that data. This ensures that each member receives a healthy exercise plan tailored to their needs.

[0700] Furthermore, the server generates educational materials for children at home, and the device notifies them. These educational materials include games and quizzes about health and nutrition, making learning fun for children. The device notifies the user of the generated content, providing an environment where children can access it.

[0701] This system provides comprehensive support for a healthy lifestyle for the entire family, helping to create optimal lifestyle habits tailored to individual health needs.

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] The user enters basic cultural data for each household member into the terminal. This data includes age, gender, height, weight, allergy information, and food preferences. The terminal formats this data and prepares it for transmission to the server. Specifically, the user enters the required information into the input form and clicks the "Submit" button.

[0705] Step 2:

[0706] The terminal sends formatted basic cultural data to the server. The server temporarily stores the received data and creates a profile of each member. In this step, the data integrity is checked and any missing information is verified. The server then prepares to calculate nutritional requirements based on the input data.

[0707] Step 3:

[0708] The server calculates and analyzes the nutritional requirements of each household member based on stored basic cultural data. The server uses algorithms to calculate basal metabolic rate and the required intake of specific nutrients. Based on this input, it outputs the optimal energy expenditure and nutrient intake for maintaining health. Specific actions performed by the server include applying existing nutrition calculation formulas and reflecting the data in individual profiles.

[0709] Step 4:

[0710] The server uses a generative AI model to generate a meal plan based on the analyzed nutritional requirements. The AI ​​model is input with a prompt such as, "A 40-year-old male, 175cm tall, weighing 70kg, with no allergies, who likes Italian food. Please suggest a healthy weekly meal plan for him." The AI ​​model then suggests and outputs nutritionally balanced recipes, ingredient lists, and cooking times. The server then provides these suggestions to the user as a weekly meal plan.

[0711] Step 5:

[0712] The user inputs daily activity information obtained from a smartwatch or fitness tracker into the device. The device then converts this information into a data format for transmission to the server. Specifically, it uses an activity tracking app to acquire data and imports that information into the device app.

[0713] Step 6:

[0714] Based on the activity information received by the server, it evaluates the exercise level of each household member. The server aggregates the data and uses an algorithm to analyze daily exercise volume and patterns. Based on the calculated exercise level, it generates an individualized exercise plan and provides it to the user. At this stage, the server suggests specific exercises to supplement any insufficient exercise.

[0715] Step 7:

[0716] The server uses a generative AI model to develop and deliver educational content for children. This content includes quizzes and game-based learning materials, which the server sends to the user's device and notifies them. Users and their families can access this content via their devices and use it as an opportunity for learning and entertainment.

[0717] (Application Example 1)

[0718] 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".

[0719] There is a need to efficiently manage the health status of each family member and provide exercise and nutritional suggestions tailored to individual needs. Furthermore, there is a need for educational content that allows children to learn about health in an enjoyable way. However, conventional systems struggle to comprehensively meet these requirements, and the provision of services integrated with home devices is insufficient.

[0720] 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.

[0721] In this invention, the server includes an acquisition means for inputting basic attribute information for each household member, an analysis means for analyzing nutritional requirements based on the basic attribute information, and a generation means for generating a meal plan based on the analysis results. This enables health management using a home appliance and allows for the provision of individually optimized nutrition and exercise plans. Furthermore, by using a dialogue means equipped with voice recognition functionality, information can be provided through natural dialogue with the user, and consideration can be given to making learning content for children enjoyable to use.

[0722] "Family members" refers to each individual belonging to a household, and each of them is responsible for managing their own health.

[0723] "Basic attribute information" refers to data such as an individual's age, gender, height, weight, allergy information, and food preferences, and is fundamental data used for nutritional analysis and exercise plan development.

[0724] "Nutritional requirements" refer to the amount of nutrients and calories needed to maintain the health of each household member, and analyzing these requirements makes it possible to create an optimal meal plan.

[0725] "Analysis means" refers to a function that calculates and analyzes nutritional requirements based on the input basic attribute information, and is a process for generating an appropriate meal plan.

[0726] "Generation means" refers to the process or system for formulating meal plans to be provided to each member based on the results obtained from the analysis means.

[0727] "Activity information" refers to data on an individual's exercise volume and activity status obtained from smartwatches, fitness trackers, etc., and is necessary information for suggesting exercise plans.

[0728] An "exercise plan" is a plan that proposes individually optimized exercise content and schedules based on the activity information of each household member.

[0729] "Supplying means" refers to a system or process that provides members with generated learning content and meal plans, and includes providing diverse information, including learning content for children, in an easy-to-understand manner.

[0730] "Household medical devices" refer to equipment that can be used within the home and have functions to provide information and interact with others for health management.

[0731] "Dialogue methods" refer to processes and functions that use speech recognition technology to engage in natural interactions with users and provide them with necessary information.

[0732] This invention is a system designed to support health management within the home, efficiently collecting and analyzing health data for each household member and presenting an optimal nutrition and exercise plan. The embodiments are described in detail below.

[0733] First, users input basic attribute information for each household member using a terminal. This information includes age, gender, height, weight, allergy information, and food preferences. This data is sent to a server and used as basic data for analyzing nutritional requirements.

[0734] The server analyzes each member's nutritional requirements based on the received basic attribute information. This process includes calculating each individual's basal metabolic rate and required calorie intake, and also clarifies the required intake of specific nutrients. Based on the analysis results, the server uses a generative AI model to generate a meal plan optimized for each member. This meal plan includes specific recipes and a list of necessary ingredients.

[0735] Furthermore, users transmit activity information obtained from smartwatches and fitness trackers to the server via their devices. Based on this activity information, the server evaluates each member's exercise level and proposes a personalized exercise plan. This exercise plan includes specific advice for maintaining the health of household members.

[0736] For children's learning, the server generates educational content in the form of games and quizzes, which are then delivered through the device. This allows children to learn about health-related knowledge in an enjoyable way.

[0737] For example, based on a prompt such as, "Please suggest a healthy dessert recipe that a 12-year-old child can enjoy," the system will suggest meals and snacks suitable for children. Similarly, through a prompt such as, "Please create a one-week meal plan for a man in his 30s, taking calories and nutritional value into consideration," an individualized nutrition plan will be provided.

[0738] The hardware uses a Raspberry Pi as the home device, and the software employs a generative AI model built with Python and TensorFlow. General-purpose speech processing software is used for speech recognition, enabling efficient health management within the home through voice interaction with the user.

[0739] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0740] Step 1:

[0741] Users use a terminal to enter basic attribute information of household members. This information includes age, gender, height, weight, allergy information, and food preferences. The entered data must be recorded accurately and in detail, as it will be used as initial settings in the system. This information is sent to the server and stored in the database.

[0742] Step 2:

[0743] Based on the received basic attribute information, the server uses a generating AI model to analyze the nutritional requirements of each member. Specifically, it calculates the basal metabolic rate and required calorie intake, and identifies the required intake of specific nutrients. This analysis is performed using a Python program and TensorFlow, and the output is data on the optimal nutritional requirements for each member.

[0744] Step 3:

[0745] The server uses an AI model based on the analysis results to generate a meal plan optimized for each member. The generated plan includes specific recipes, cooking times, and a list of necessary ingredients. This output is sent to the terminal and made available to the user.

[0746] Step 4:

[0747] Users input activity information obtained from smartwatches or fitness trackers into the device. This data includes steps taken, calories burned, and heart rate. The entered activity data is sent to a server and serves as the basis for evaluating exercise levels.

[0748] Step 5:

[0749] The server analyzes the input activity information and assesses each member's exercise level. Based on this assessment, an individual exercise plan is generated. The exercise plan includes the type and frequency of exercise to be performed, and incorporates advice to promote the user's health maintenance.

[0750] Step 6:

[0751] To generate learning content for children, the server utilizes a generation AI model to create educational content in game and quiz formats. This content is delivered and accessible via the user's device. The content is designed to allow children to learn about health in an enjoyable way.

[0752] Step 7:

[0753] The generated meal plans, exercise plans, and educational content are notified to the user via the device, supporting them in managing their health at home. Users can access the system interactively using voice recognition and request more detailed information or additional instructions.

[0754] 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.

[0755] This invention combines an emotional engine with a system that supports healthy living at home to achieve even more personalized health management. The system begins by inputting basic attribute data for each family member and analyzing their nutritional needs based on that data.

[0756] First, the user uses their device to input basic attribute data for each family member. This data is sent to a server, which analyzes each member's nutritional needs. Specifically, it calculates the required calorie intake and the required amounts of specific nutrients.

[0757] Based on these results, the server uses a generative AI model to create an appropriate meal plan and presents it to the user via the terminal. The user also inputs activity data into the terminal, and the server analyzes this data to provide appropriate exercise plans and health advice.

[0758] Furthermore, this system is equipped with an emotion engine that recognizes the user's emotional state. Based on the data from this emotion engine, the server can adjust the suggested meal menus and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, the system will suggest menus using ingredients with relaxing effects and exercise plans that promote relaxation.

[0759] Furthermore, educational content for children will be customized using emotional data. Specifically, content that is more engaging and enjoyable to learn from will be provided according to the child's emotional state, making it possible to increase their interest in health.

[0760] For example, if the emotional engine detects stress signals when parents are busy in a particular household, the server suggests a simple, healthy meal that can be prepared quickly, and recommends moderate exercise and meditation exercises to reduce stress. Furthermore, if a child is feeling bored, it provides educational content in the form of games that encourage active physical movement.

[0761] In this way, this system, which combines emotional engines, comprehensively supports the mental and physical health of the entire family.

[0762] The following describes the processing flow.

[0763] Step 1:

[0764] The user enters basic attribute data for each household member (e.g., age, gender, weight, height, allergy information, food preferences) into the device. The device then sends this data to the server.

[0765] Step 2:

[0766] The server analyzes the received basic attribute data and calculates the nutritional needs of each household member. This calculation includes required calorie intake and target intake of specific nutrients, providing an analysis tailored to each individual's health condition.

[0767] Step 3:

[0768] Based on the analysis results, the server uses a generative AI model to create meal plans tailored to each family member. These meal plans are adjusted according to individual nutritional needs and preferences, and include weekly recipes, cooking times, and lists of necessary ingredients.

[0769] Step 4:

[0770] Users input activity data collected by smartwatches and fitness trackers into their devices, or, if direct transmission is possible, the data is automatically sent to the server. The device is responsible for transmitting this data to the server.

[0771] Step 5:

[0772] The server analyzes activity data and evaluates the exercise level of each household member. Based on the evaluation results, it generates exercise plans and health advice tailored to each member's needs and proposes them to the user via the device.

[0773] Step 6:

[0774] The server activates an emotion engine to recognize the user's emotions, analyzing the user's facial expressions and voice data. It identifies the emotional state and tracks stress levels and emotional changes.

[0775] Step 7:

[0776] The server uses data from the emotion engine to adjust meal plans and exercise plans to suit the user's emotional state. For example, if the user is feeling stressed, it will suggest relaxation-promoting meals and lighter exercise plans.

[0777] Step 8:

[0778] The server generates educational content for children based on emotional data. Specifically, it provides games and quizzes customized to the child's mood and interests.

[0779] Step 9:

[0780] The device displays generated meal plans, exercise plans, and educational content to the user. The user can then use these suggestions to plan and carry out healthy activities at home.

[0781] (Example 2)

[0782] 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".

[0783] There is a growing need for more individualized health management within the family, enabling health maintenance tailored to the nutritional and emotional states of each member. However, conventional systems have been insufficient in considering emotional states, making it difficult to provide optimal diets and exercises for each individual. Furthermore, there is a lack of customization of educational content, particularly for children, and efforts are needed to capture their interest.

[0784] 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.

[0785] In this invention, the server includes means for inputting basic attribute information for each household member, means for evaluating nutritional requirements based on the attribute information, and means for recognizing emotional states. This makes it possible to provide each household member with more precise and emotionally sensitive nutritional management and exercise plans. Furthermore, it is possible to conduct health education while attracting the interest of children by generating and providing educational information for them.

[0786] "Household members" refers to individual people who live together within a specific household, and each of them is responsible for managing their own health.

[0787] "Basic attribute information" refers to information necessary for health management, such as age, gender, weight, height, and activity level of each household member.

[0788] "Nutritional requirements" refer to the amount of calories and various nutrients that household members need to maintain their health.

[0789] "Methods of evaluation" refers to the process of analyzing nutritional requirements using the input basic attribute information and calculating the appropriate amount of nutrients and calories needed.

[0790] A "meal plan" refers to a menu of meals that household members should consume, based on their assessed nutritional requirements.

[0791] "Activity status" refers to the types of exercise and physical activity that household members engage in on a daily basis, and is information related to maintaining health.

[0792] An "exercise plan" refers to exercise guidelines or programs designed to promote health, based on the activity levels of household members.

[0793] "Emotional state" refers to the emotional health of family members, including stress and mood swings.

[0794] "Means of recognizing emotional states" refers to technical methods for understanding the emotional states of family members and adjusting proposals based on those states.

[0795] "Educational information" refers specifically to content provided for children to promote learning and health awareness.

[0796] This invention provides a system that personalizes health management for each member of a household. This system uses emotion engine technology to recognize the user's emotional state and adjust meal plans and exercise plans accordingly.

[0797] First, users input basic attribute information for each household member through a terminal used at home. This information includes age, gender, weight, height, and lifestyle. The terminal sends this information to a server. Upon receiving this information, the server uses specialized nutritional analysis software to evaluate the nutritional requirements of each household member. Based on this evaluation, an individualized meal plan is generated, utilizing tools such as OpenAI's generative AI model.

[0798] The server then receives activity data from household members and uses it to create an exercise plan. An emotion engine is used to adjust the plan, taking into account the user's emotional state. The emotional state is inferred from voice input and screen interactions, and relaxation-enhancing exercises are suggested as needed.

[0799] As a concrete example, the server runs an AI model based on the prompt "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis. Please suggest a healthy dinner menu suitable for a high-stress situation," and generates a result.

[0800] In this way, the present invention utilizes an emotional engine and is designed to ensure that each member of a household receives optimal health management.

[0801] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0802] Step 1:

[0803] Users use a home terminal to input basic attribute information for each household member. This information includes age, gender, weight, height, and activity level. This information is formatted as digital data and sent from the terminal to the server.

[0804] Step 2:

[0805] The server analyzes the received attribute information and uses nutritional analysis software to evaluate the nutritional requirements of each member. During this process, the necessary calories and nutrients (protein, fat, carbohydrates, etc.) are calculated based on age and activity level. The output generates nutritional information necessary for each member.

[0806] Step 3:

[0807] The server inputs prompt sentences into the generating AI model based on the nutritional requirements assessment results. For example, it might input a sentence like, "A 40-year-old male, 175cm tall, weighing 70kg, who exercises lightly on a daily basis; suggest a nutritionally balanced meal plan." The generating AI model then generates individual meal plans based on the input prompt sentences. This results in the output of the optimal meal menu for each member.

[0808] Step 4:

[0809] Users input their exercise and daily activity data into the device. This includes daily steps, type of exercise, and duration. The device then sends this activity data back to the server.

[0810] Step 5:

[0811] The server analyzes the transmitted activity data and proposes an exercise plan tailored to the lifestyle of each household member. This analysis assesses the need for excess calorie expenditure and muscle strengthening. As output, an individual exercise plan is generated.

[0812] Step 6:

[0813] The server uses an emotion engine to recognize the user's emotional state. Based on the input data, the user's stress level and emotional changes are analyzed. This emotional data is used to adaptively adjust suggested meal plans and exercise plans. As output, emotionally sensitive advice is provided.

[0814] Step 7:

[0815] The server generates educational content for children based on their emotional state. Specifically, it selects health education materials and games that are likely to interest children. This provides content that is fun to learn while raising children's health awareness.

[0816] (Application Example 2)

[0817] 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".

[0818] In modern society, personal health management is a crucial issue, but achieving effective health management tailored to each family's and individual's lifestyle and emotional state is difficult. Therefore, there is a need for systems that provide more personalized health promotion services.

[0819] 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.

[0820] In this invention, the server includes an input means for inputting basic attribute information for each household member, an emotion recognition means for recognizing and analyzing an individual's emotional state, and an adjustment means for adjusting and providing health promotion plans based on the emotional state. This enables personalized health management tailored to the lifestyle and emotional state of each household.

[0821] "Basic attribute information for each household member" refers to individual data such as age, gender, weight, and height for each member of the household.

[0822] "Nutritional needs" refer to the requirements regarding the intake of specific nutrients and calories necessary for maintaining an individual's health.

[0823] "Analysis means" refers to a method or apparatus for analyzing necessary nutritional needs based on the input basic attribute information.

[0824] "Generating means" refers to a method or apparatus for creating an individualized meal plan according to the analysis results.

[0825] "Activity information" refers to data about the exercise and activities that household members engage in on a daily basis.

[0826] "Proposed means" refers to a method or apparatus for providing an appropriate exercise plan based on activity information.

[0827] "Educational resources" is a general term for learning and educational materials and content provided to children.

[0828] "Emotion recognition means" refers to a method or device for detecting and analyzing an individual's emotional state.

[0829] "Adjustment means" refers to a method or apparatus for appropriately modifying and providing the proposed content in accordance with the recognized emotional state.

[0830] A "means for proposing health events" refers to a method or device for presenting events or activities that promote health improvement in accordance with the living environment of residents.

[0831] This invention realizes a system to support health management in the home. The system begins by inputting basic attribute information for each family member into a terminal and sending it to a server. This basic attribute information includes the age, gender, weight, and height of each family member. Once this data is sent to the server, the server uses a generative AI model to analyze the nutritional needs of each member and generates a meal plan based on that analysis.

[0832] The server also receives activity information from household members and proposes personalized exercise plans based on this information. This activity information includes daily exercise habits and activity levels. Furthermore, the system uses emotion recognition tools to detect and analyze the user's emotional state. This can be done using software such as OpenCV or the Emotion-Recognition API. Based on this emotional data, the server adjusts health promotion suggestions and provides an appropriate health management plan.

[0833] To give a specific example, if a user inputs their activity information using a device and the emotion recognition system detects "stress," the server will adjust and provide meal and activity suggestions that are appropriate for the user's emotional state. For example, suggestions might include "meals using ingredients effective for relaxation" or "exercise aimed at stress relief."

[0834] An example of a prompt message used as input to a generative AI model is, "Based on the user's emotional state, please suggest the most suitable relaxation method."

[0835] In this way, the system provides a way to comprehensively manage the health status of the entire household.

[0836] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0837] Step 1:

[0838] The user uses a device to enter basic attribute information for family members. This information includes data such as age, gender, weight, and height. The entered data is temporarily stored on the device.

[0839] Step 2:

[0840] The terminal sends the entered basic attribute information to the server. After receiving this information, the server uses a generative AI model to analyze the nutritional needs. The nutritional needs analysis involves data processing to calculate the required calories and the required amounts of specific nutrients.

[0841] Step 3:

[0842] The server generates a personalized meal plan based on the analysis results. This generation utilizes historical data and the latest nutritional information, and the generating AI model creates prompts to design the optimal meal plan.

[0843] Step 4:

[0844] Users input daily activity information into their devices. This includes data on exercise levels and activity types. This information is sent to a server to supplement health management.

[0845] Step 5:

[0846] After receiving activity information, the server proposes an exercise plan. This process involves data calculations based on the input activity data to select appropriate exercises. This results in a training plan optimized for the user.

[0847] Step 6:

[0848] The device analyzes the user's emotional state through emotion recognition mechanisms. Using camera and sensor data, it identifies emotions using the Emotion-Recognition API. This result is sent to a server and used to adjust health promotion recommendations based on the emotional state.

[0849] Step 7:

[0850] After receiving emotional data, the server adjusts health management suggestions based on that data and provides them to the user. For example, a generative AI model might generate a prompt such as, "Please suggest the best relaxation methods based on the user's emotional state," and then suggest meals and activities appropriate to the user's emotional state.

[0851] Step 8:

[0852] Users can review meal plans, exercise plans, and health management suggestions based on their emotional state, received through their device, and use them to maintain their daily health. This output serves as concrete action guidelines for improving daily lifestyle habits.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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.

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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."

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0874] The following is further disclosed regarding the embodiments described above.

[0875] (Claim 1)

[0876] An input method for entering basic attribute data for each household member,

[0877] An analytical method for analyzing nutritional needs based on the above basic attribute data,

[0878] A generation means for generating a meal menu based on the above analysis results,

[0879] An input method for entering and transmitting activity data,

[0880] A proposal method that suggests an exercise plan based on the above activity data,

[0881] A means of generating and providing educational content for children,

[0882] A system that includes this.

[0883] (Claim 2)

[0884] The system according to claim 1, which calculates the required intake of a specific nutrient based on the nutritional needs of each household member.

[0885] (Claim 3)

[0886] The system according to claim 1, which provides health maintenance advice based on the activity levels of household members.

[0887] "Example 1"

[0888] (Claim 1)

[0889] A device for inputting basic cultural data for each household member,

[0890] A device for calculating and analyzing nutritional requirements based on the above basic cultural data,

[0891] A device for creating and providing a meal plan based on the above-calculated and analyzed nutritional requirements,

[0892] A device for inputting and transmitting individual activity information,

[0893] A device that proposes an individualized exercise plan based on the above activity information,

[0894] A device that generates and provides educational materials,

[0895] A device that notifies users of the generated educational materials and makes them accessible to users,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, which calculates the required intake of a specific nutrient based on the nutritional requirements of each household member.

[0899] (Claim 3)

[0900] The system according to claim 1, which provides health maintenance guidance based on the physical activity levels of household members.

[0901] "Application Example 1"

[0902] (Claim 1)

[0903] A means of obtaining and inputting basic attribute information for each household member,

[0904] An analytical means for analyzing nutritional requirements based on the above basic attribute information,

[0905] A generation means for generating a meal plan based on the above analysis results,

[0906] A means of acquiring and transmitting activity information,

[0907] A proposal means for suggesting an exercise plan based on the above activity information,

[0908] A means of supplying and generating learning content for children,

[0909] A conversational means that manages health status using household machinery and provides information in a conversational format using voice recognition functionality,

[0910] A system that includes this.

[0911] (Claim 2)

[0912] The system according to claim 1, which calculates the required intake of a specific nutrient based on the nutritional requirements of each household member.

[0913] (Claim 3)

[0914] The system according to claim 1, which provides health maintenance advice based on the activity levels of household members.

[0915] "Example 2 of combining an emotion engine"

[0916] (Claim 1)

[0917] A means of inputting basic attribute information for each household member,

[0918] A means for evaluating nutritional requirements based on the above attribute information,

[0919] A means for generating a meal plan based on the above evaluation results,

[0920] A means of inputting and submitting activity status,

[0921] A means of proposing an exercise plan based on the above activity status,

[0922] Means of recognizing emotional states,

[0923] A means of adjusting the proposed content based on the above emotional state,

[0924] Means for generating and providing educational information for children,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, which calculates the essential intake of a specific nutrient based on the nutritional requirements of each household member.

[0928] (Claim 3)

[0929] The system according to claim 1, which provides health maintenance advice based on the activity status of household members.

[0930] "Application example 2 when combining with an emotional engine"

[0931] (Claim 1)

[0932] An input method for entering basic attribute information for each family member,

[0933] An analytical method for analyzing nutritional needs based on the above basic attribute information,

[0934] A generation means for generating a meal plan based on the above analysis results,

[0935] An input method for entering and submitting activity information,

[0936] A proposal means for suggesting an exercise plan based on the above activity information,

[0937] A means of generating and providing educational resources for children,

[0938] A means of recognizing and analyzing an individual's emotional state,

[0939] A means of adjusting and providing health promotion plans based on emotional state,

[0940] Event proposal methods that propose health events tailored to the living environment of residents,

[0941] A system that includes this.

[0942] (Claim 2)

[0943] The system according to claim 1, which calculates the required amount of a specific nutrient based on the nutritional needs of each household member.

[0944] (Claim 3)

[0945] The system according to claim 1, which provides health maintenance advice based on the activity level and emotional state of family members. [Explanation of Symbols]

[0946] 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 obtaining and inputting basic attribute information for each household member, An analytical means for analyzing nutritional requirements based on the above basic attribute information, A generation means for generating a meal plan based on the above analysis results, A means of acquiring and transmitting activity information, A proposal means for suggesting an exercise plan based on the above activity information, A means of supplying and generating learning content for children, A conversational means that manages health status using household machinery and provides information in a conversational format using voice recognition functionality, A system that includes this.

2. The system according to claim 1, which calculates the required intake of a specific nutrient based on the nutritional requirements of each household member.

3. The system according to claim 1, which provides health maintenance advice based on the activity levels of household members.

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