System

Abstract

To provide a system.SOLUTION: A system includes: first means for a user to input user's own weight data; second means which generates a first prompt sentence for outputting a first proposal content indicating menus and exercises optimal for the user based on the inputted present weight data and past weight data of the user in a database; third means for generating the first proposal content by inputting the generated first prompt sentence to a generative AI model; and fourth means for transmitting the generated first proposal content to a terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] It is difficult to self-manage the diet and exercise necessary to achieve one's ideal weight and body shape in daily life. Calculating the calories that suit oneself, planning a menu, and ordering ingredients for delivery is also time-consuming. Furthermore, if one gains weight or finds cooking a hassle, it is difficult to make the appropriate decisions on one's own. [Means for solving the problem]

[0005] This system manages daily weight and supports the diet and exercise necessary to achieve an ideal weight and body shape. It calculates the calories appropriate for each individual and even allows for menu planning and delivery of ingredients. Even if a person gains weight, it flexibly supports them by creating optimal menus and exercise plans. It also recommends nearby healthy restaurants for people who find cooking a hassle. [Brief explanation of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13]FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] The system of the present invention collects the user's weight data daily and provides dietary and exercise support to help them achieve their ideal weight and body shape based on that data. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[0029] "Example 2"

[0030] Even if the user gains weight, the system of the present invention will flexibly consider optimal menus and exercises to support the user. For example, if the user gains weight, the system will suggest low-calorie menus and recommend moderate exercise. This means that the user does not need to take appropriate measures on their own, and can manage their health with the support of the system.

[0031] "Example 3"

[0032] For people who don't like to cook, the system of this invention recommends nearby healthy restaurants and cafes based on the user's location information. This allows users to eat healthy meals without having to cook themselves.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters weight data into the system.

[0036] Step 2: The system calculates the appropriate calories for the user based on that data.

[0037] Step 3: The system suggests a menu based on the calculation results.

[0038] Step 4: The system delivers the ingredients needed for the proposed meal.

[0039] "Example 2"

[0040] Step 1: The user enters weight data into the system.

[0041] Step 2: The system detects that you have gained weight.

[0042] Step 3: The system suggests low-calorie meals.

[0043] Step 4: The system recommends moderate exercise.

[0044] "Example 3"

[0045] Step 1: The user inputs into the system that cooking is a hassle.

[0046] Step 2: The system recommends nearby healthy restaurants and cafes based on the user's location.

[0047] Example 1

[0048] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0049] Health management is an important issue in modern society, but many people find it difficult to manage their daily weight and plan appropriate meals and exercise. There are also few systems that calculate optimal calorie intake based on individual weight data and suggest menus based on that calculation. Furthermore, there are limited ways to easily obtain the ingredients needed for the suggested menus. A comprehensive system that can solve these problems is needed.

[0050] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0051] In this invention, the server includes means for collecting user weight data daily, means for calculating calories appropriate for the user based on the collected weight data, means for generating menus based on the calculation results, means for creating a list of ingredients required for the generated menus, and means for delivering ingredients based on the ingredient list. This allows users to efficiently manage their daily weight, obtain optimal calorie intake and menus based on their individual weight data, and easily obtain the necessary ingredients.

[0052] "User weight data" refers to the weight data that a user measures daily and enters into the system.

[0053] A "calorie calculation means" is an algorithm or software that calculates a user's appropriate daily calorie intake based on the user's weight data.

[0054] A "means for generating a menu" is an algorithm or software that creates a meal menu appropriate for the user based on the calculated calorie intake.

[0055] The "means for creating an ingredient list" refers to an algorithm or software for listing the ingredients and their quantities required for the generated menu.

[0056] "Means for delivering ingredients" refers to a service or system for delivering ingredients needed by the user based on the created ingredient list.

[0057] "A means of flexibly planning and supporting optimal meal plans and exercise even when weight gain occurs" refers to algorithms and software that dynamically adjust and provide optimal meal menus and exercise plans according to changes in the user's weight.

[0058] The "means for recommending nearby healthy restaurants" refers to algorithms and software that search for and recommend nearby restaurants that serve healthy meals to users who don't like to cook.

[0059] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[0060] Hardware and software used

[0061] server

[0062] The server collects weight data sent by users daily. This data is entered by the user through a dedicated application. The server calculates the appropriate calorie intake for the user based on the collected weight data. This calculation is performed using the Python (registered trademark) NumPy library. Based on the calculation results, the server generates a meal plan appropriate for the user. This meal plan generation uses the generative AI model GPT-4 (registered trademark). The server then creates a list of ingredients required for the generated meal plan and sends an order to a partner food delivery service. A REST API is used for this order processing.

[0063] Terminal

[0064] The device provides an interface for users to input weight data. Users input weight data into a dedicated application using a device such as a smartphone or tablet. The device uses the HTTPS protocol to send the input data to the server. The device also has the function of displaying calorie calculation results and meal suggestions received from the server. Users can check the suggested meals through the device and order the necessary ingredients.

[0065] user

[0066] Every day, users enter their weight data into a dedicated application. This application runs on devices such as smartphones and tablets. When users enter their weight data, the data is sent to a server. The server returns calorie calculation results and menu suggestions, which the user can then review. The user can then prepare meals based on the suggested menu and order the necessary ingredients.

[0067] Specific examples

[0068] Example 1: User weight data entry

[0069] The user weighs themselves in the morning and enters "70 kg" into the dedicated application. The device then sends this data to the server.

[0070] Example 2: Calorie counting and meal suggestions

[0071] The server receives the user's weight data (70 kg) and calculates the appropriate calorie intake using Python's NumPy library. For example, if the calculation result is 2000 kcal, the server uses GPT-4 to generate a meal plan based on 2000 kcal.

[0072] Example 3: Ordering ingredients

[0073] The server creates a list of ingredients needed for the generated menu and sends an order to a partner food delivery service. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via a REST API.

[0074] Prompt Sentence Examples

[0075] "If the user's weight data is 70 kg, calculate the appropriate calorie intake and suggest a meal plan based on that calorie intake. The plan should include breakfast, lunch, and dinner menus."

[0076] In this way, a system is created that calculates calories and suggests meals based on the user's weight data, and delivers the necessary ingredients.

[0077] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0078] Step 1:

[0079] The user weighs themselves every morning and enters their weight into a dedicated application. For example, the user enters "70 kg." This input data is saved on the device. The input data is the user's weight information and serves as the basis for subsequent processing.

[0080] Step 2:

[0081] The terminal sends the weight data entered by the user to the server. This transmission uses the HTTPS protocol. For example, the terminal encrypts the data "70kg" and sends it to the server. The input is the user's weight data, and the output is the encrypted data sent to the server.

[0082] Step 3:

[0083] The server calculates the appropriate calorie intake for the user based on the received weight data. This calculation uses Python's NumPy library. For example, the server receives data of "70 kg" and calculates the appropriate calorie intake as "2000 kcal." The input is weight data, and the output is calorie intake.

[0084] Step 4:

[0085] The server generates a menu appropriate for the user based on the calculated calorie intake. This menu generation uses the generative AI model GPT-4. For example, the server suggests breakfast, lunch, and dinner menus based on "2000 kcal." The input is the calorie intake, and the output is a menu.

[0086] Step 5:

[0087] The server creates a list of ingredients required for the generated menu. For example, if breakfast includes "oatmeal," lunch includes "chicken breast and broccoli," and dinner includes "brown rice and stir-fried vegetables," the server lists each ingredient and its quantity. The input is the menu, and the output is the ingredient list.

[0088] Step 6:

[0089] The server places an order for the created ingredient list with a partner food delivery service. This order processing uses a REST API. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via the API. The input is the ingredient list, and the output is the order data sent to the food delivery service.

[0090] Step 7:

[0091] The device displays the calorie calculation results and menu suggestions received from the server to the user. The user can check the suggested menu through the device and order the necessary ingredients. For example, the user opens the application and checks the menu displayed as "Today's Menu." The input is data from the server, and the output is the information displayed to the user.

[0092] (Application example 1)

[0093] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0094] Health management is an important issue in modern society, but for many people, individually managing their weight, selecting appropriate meals, and planning exercise is a heavy burden. Furthermore, there is a lack of systems that consistently calculate calories, suggest menus, and even procure the ingredients, making it difficult to maintain health management. To solve these issues, a system is needed that calculates appropriate calories based on the user's weight data, suggests menus based on the calculation results, and automatically orders the necessary ingredients.

[0095] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0096] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for calculating appropriate calories based on the user's weight data and proposing menus based on the calculation results, and a means for automatically ordering the necessary ingredients based on the proposed menu, thereby enabling users to consistently manage their daily weight, select appropriate meals, and procure ingredients.

[0097] A "weight management tool" is a device or software that collects and records a user's daily weight data.

[0098] "Means to support diet, exercise, etc." refers to devices and software that provide users with diet and exercise plans necessary to achieve their ideal weight and body shape and assist them in carrying them out.

[0099] A "calorie calculation means" is a device or software that calculates a person's appropriate daily calorie intake based on the user's weight data.

[0100] "Means that enable the process from planning a menu to delivering the ingredients" refers to devices or software that create a list of ingredients based on a proposed menu and deliver them to the user.

[0101] "Means for calculating appropriate calorie intake based on user's weight data" refers to a device or software that calculates the appropriate calorie intake for a person based on weight data entered by the user.

[0102] The "means for suggesting a menu based on the calculation results" refers to a device or software that suggests a meal menu suitable for the user based on the calculated calorie intake.

[0103] "Means for automatically ordering ingredients based on a proposed menu" refers to a device or software that automatically lists ingredients needed for a proposed menu and allows ordering online.

[0104] As an embodiment of the present invention, the following system can be constructed.

[0105] System Overview

[0106] This system collects the user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system has the function of inputting the user's weight data, calculating the appropriate calorie intake based on that data, proposing menus based on the calculation results, and automatically ordering the ingredients needed for those menus.

[0107] Hardware and software used

[0108] Hardware:

[0109] Smartphone: Used by users to input weight data and check menu suggestions and order status.

[0110] Server: Stores user weight data, calculates calories, suggests meals, and processes food orders.

[0111] software:

[0112] Python: A programming language used to implement server-side programs.

[0113] Requests library: The Python library used to send HTTP requests.

[0114] Database: Used to store user weight data and meal plan information.

[0115] Data processing and calculation

[0116] Server Action:

[0117] 1. Entering weight data: When a user enters weight data using a smartphone, the data is sent to the server and stored in a database.

[0118] 2. Calorie Calculation: The server calculates the appropriate daily calorie intake for the user based on the stored weight data. For example, based on the latest weight data, it calculates that 2000 calories is appropriate.

[0119] 3. Meal Suggestion: Based on the calculated calorie intake, the server will suggest suitable meal plans for the user, such as salad, grilled chicken, and fruit.

[0120] 4. Ingredients ordering: Based on the proposed menu, the server will list the necessary ingredients and place the order online. Once the order is successful, the user will be notified.

[0121] Specific examples

[0122] When a user inputs their weight of 70 kg, the server saves that data and calculates the appropriate calorie intake. For example, if it calculates that 2,000 calories is appropriate, it will suggest a menu of salad, grilled chicken, fruit, etc., and automatically order the necessary ingredients. If the order is successful, a notification will be sent to the user's smartphone and the ingredients will be delivered.

[0123] Prompt Sentence Examples

[0124] The following prompts can be used for the generative AI model:

[0125] Create an application that inputs a user's weight data, calculates the appropriate calorie intake based on that data, suggests a meal plan based on the calculation results, and delivers the ingredients needed for that meal. Specifically, this application has the functionality to store a user's weight, calculate the appropriate calorie intake, suggest a meal plan, and order the ingredients.

[0126] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0127] Step 1:

[0128] Entering weight data

[0129] The user inputs weight data using a smartphone. The input weight data is sent from the smartphone to a server. The server stores the received weight data in a database.

[0130] Input: User weight data

[0131] Output: Weight data stored in the database

[0132] Step 2:

[0133] Calorie Counting

[0134] The server retrieves the latest weight data stored in the database and calculates the appropriate daily calorie intake for the user based on the retrieved weight data. For example, if the latest weight data is 70 kg, it calculates that 2000 calories is appropriate.

[0135] Input: Weight data retrieved from the database

[0136] Output: Calculated calorie intake

[0137] Step 3:

[0138] Menu suggestions

[0139] The server then proposes meal plans suitable for the user based on the calculated calorie intake. For example, based on a 2000 calorie intake, it may suggest salad, grilled chicken, and fruit. The proposed plan is then sent to the user's smartphone.

[0140] Input: Calculated calorie intake

[0141] Output: Suggested menu

[0142] Step 4:

[0143] Ordering ingredients

[0144] The server lists the ingredients needed based on the proposed menu, and the ingredients are ordered online. Once the order is successfully placed, a notification is sent to the user's smartphone.

[0145] Input: Suggested menu

[0146] Output: Ordered ingredients and notification

[0147] Step 5:

[0148] Receive notifications

[0149] The user will be notified on their smartphone that the order has been placed successfully, and will then wait for the food to be delivered.

[0150] Input: Order successful notification

[0151] Output: User notification

[0152] By following the above steps, users can consistently manage their daily weight, select appropriate meals, and procure ingredients.

[0153] Example 2

[0154] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0155] Conventional health management systems require users to make appropriate decisions on their own, making it difficult to flexibly suggest optimal diets and exercises when weight gain occurs. Furthermore, the lack of specific suggestions based on weight data management and fluctuations makes it difficult for users to effectively manage their health.

[0156] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for inputting weight data, a means for transmitting and saving the input weight data, a means for detecting weight fluctuations, a means for sending prompts to the generative AI model to suggest optimal menus and exercises, and a means for transmitting and displaying the suggested contents. This allows the user to automatically receive optimal menus and exercises according to their weight gain or loss, thereby achieving effective health management.

[0157] The "weight management means" is a function for recording and saving the user's daily weight data.

[0158] "Means to support diet, exercise, etc." is a function that provides the user with the diet and exercise plans necessary to achieve their ideal weight and body shape.

[0159] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[0160] "Means that enable the process from planning a menu to delivering the ingredients" refers to a function that allows the necessary ingredients to be ordered and delivered based on the proposed menu.

[0161] The "means for inputting weight data" is an interface that allows a user to input their weight into the system.

[0162] The "means for transmitting and saving input weight data" is a function for transmitting weight data input by the user to a server and saving it in a database.

[0163] The "means for detecting weight fluctuations" is a function that compares past weight data with current weight data to determine whether weight has increased or decreased.

[0164] "Means for sending prompt text to the generative AI model to suggest optimal menus and exercises" refers to a function that sends prompt text to the generative AI model and generates optimal menus and exercises according to the user's weight fluctuations.

[0165] The "means for transmitting and displaying the proposed content" is a function for transmitting the generated menu and exercise proposal content to the user's terminal and displaying it.

[0166] The present invention is a system for supporting a user's weight management, and is implemented using a server, a terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0167] Hardware and software used

[0168] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[0169] Software: Generative AI models (e.g., GPT-4), database management systems (e.g., MySQL®), health management applications

[0170] Program processing

[0171] 1. Entering user weight data

[0172] The user uses the terminal to input weight data into the health management application.

[0173] Example: A user enters "Weight: 70kg" into a smartphone app.

[0174] 2. Data transmission and storage

[0175] The terminal transmits the input weight data to the server.

[0176] The server stores the received data in a database.

[0177] Example: The device sends the data "Weight: 70kg" to the server, which then stores the data in a MySQL database.

[0178] 3. Detect weight fluctuations

[0179] The server compares the data with past weight data in the database to detect weight gain or loss.

[0180] Example: The server retrieves the previous weight data (e.g., 68 kg) from the database and compares it with the current weight data (70 kg) to detect an increase of 2 kg.

[0181] 4. Menu and exercise suggestions using generative AI models

[0182] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[0183] Example prompt: "The user has gained 2 kg. Please suggest low-calorie meals and moderate exercise."

[0184] 5. Submitting and Displaying Proposals

[0185] Based on the prompt, the generative AI model suggests low-calorie meals and moderate exercise.

[0186] The server transmits the generated proposal to the user's terminal.

[0187] The terminal displays the received proposal content in the health management application.

[0188] Example: A generative AI model generates a suggestion such as, "For a low-calorie meal, we suggest a salad and grilled chicken breast. For exercise, we recommend 30 minutes of walking." The server then sends the suggestion to the user's device, which then displays it in the app.

[0189] In this way, the system supports users in implementing appropriate dietary and exercise programs even if they gain weight. This system provides a means for achieving effective health management without the need for users to take appropriate measures on their own.

[0190] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0191] Step 1:

[0192] Entering user weight data

[0193] The user opens the health management application and enters the latest weight data.

[0194] Input: A user enters "Weight: 70kg" into an app on their smartphone.

[0195] Output: The entered weight data is temporarily saved in the application.

[0196] Specific behavior: The user enters "70kg" into the app's input field and presses the submit button.

[0197] Step 2:

[0198] Data transmission and storage

[0199] The terminal transmits the input weight data to the server.

[0200] The server stores the received data in a database.

[0201] Input: Data "Weight: 70kg" sent from the device.

[0202] Output: The data "Weight: 70kg" is saved in the server database.

[0203] Specific operation: The device sends the data "Weight: 70kg" to the server, and the server stores the data in a MySQL database.

[0204] Step 3:

[0205] Detect weight fluctuations

[0206] The server compares the data with past weight data in the database to detect weight gain or loss.

[0207] Input: Past weight data (e.g. 68kg) and current weight data (70kg) retrieved from the database.

[0208] Output: Result: weight increased by 2 kg.

[0209] Specific operation: The server retrieves the previous weight data (68 kg) from the database and detects a 2 kg increase compared to the current weight data (70 kg).

[0210] Step 4:

[0211] Menu and exercise suggestions using generative AI models

[0212] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[0213] Input: Prompt: "User has gained 2kg. Please suggest low-calorie meals and moderate exercise."

[0214] Output: Recommendations from the generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[0215] How it works: The server sends a prompt to a generative AI model (e.g., GPT-4), which then generates suggestions based on it.

[0216] Step 5:

[0217] Submitting and viewing suggestions

[0218] The server transmits the generated proposal to the user's terminal.

[0219] The terminal displays the received proposal content in the health management application.

[0220] Input: Recommendations from a generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[0221] Output: The suggestion displayed on the user's device.

[0222] Specific operation: The server sends the generated suggestions to the user's device, and the device displays the suggestions in the app.

[0223] (Application example 2)

[0224] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0225] In modern society, daily weight management, proper diet, and exercise are important for maintaining an ideal weight and body shape. However, many people find it difficult to do these things on their own, and as a result, they often neglect their health management. Also, if weight gain occurs, they are unable to take appropriate measures quickly, which increases health risks. Furthermore, for people who find cooking a hassle, it is difficult to maintain a healthy diet. A system that can solve these problems is needed.

[0226] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting the diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for proposing low-calorie menus based on weight data, a means for proposing moderate exercise plans, a means for displaying information on stores offering ingredients based on the proposed menus and fitness programs based on the exercise plans, and a means for periodically notifying users of reminders to measure weight and exercise. This allows users to manage their health with the support of the system, without having to take appropriate measures on their own.

[0227] "Weight management means" is a function that records the user's daily weight data and saves it as history.

[0228] "Means to support diet, exercise, etc." refers to a function that provides users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[0229] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[0230] "Means that enable the process from planning a menu to delivering the ingredients" refers to the function of ordering and delivering the necessary ingredients based on the proposed menu.

[0231] "Means for suggesting low-calorie menus" is a function that suggests low-calorie meal menus based on the user's weight data.

[0232] The "means for proposing an exercise plan" is a function that suggests an appropriate exercise plan based on the user's weight data.

[0233] The "means for displaying store information" is a function that displays information about stores that offer related ingredients and fitness programs based on the proposed menu or exercise plan.

[0234] "Means for notifying reminders" refers to a function that periodically notifies users of reminders to measure their weight or exercise.

[0235] The system for implementing the present invention provides an application that integrates multiple functions to support a user's weight management. A specific embodiment of this system will be described below.

[0236] System configuration

[0237] The system consists of an application installed on the user's smartphone and a cloud server. The smartphone application provides the user interface and communicates with the server to send and receive data.

[0238] Hardware and software used

[0239] Smartphone: A device that allows users to input their daily weight and view suggested meal plans and exercise plans.

[0240] Cloud server: Stores user weight data and processes the data to calculate calories, propose menus, and suggest exercise plans.

[0241] Database: A database for storing the user's weight history, suggested meal plans, and exercise plans.

[0242] Generative AI model: An AI model that generates optimal meal plans and exercise plans based on the user's weight data.

[0243] Data processing and calculation

[0244] 1. Weight data input and management: Users input their daily weight through a smartphone application, and this data is sent to a cloud server and stored in a database.

[0245] 2. Calorie calculation: The server calculates the required calorie intake based on the user's weight data and activity level.

[0246] 3. Meal Suggestion: Using a generative AI model, low-calorie meal suggestions are made based on the user's weight data. These suggestions are displayed in the smartphone application.

[0247] 4. Exercise plan suggestions: Similarly, generative AI models are used to suggest appropriate exercise plans, which are also displayed in the smartphone application.

[0248] 5. Display of store information: Based on the proposed menu or exercise plan, information on stores that offer related ingredients and fitness programs will be displayed.

[0249] 6. Reminder notification: The server periodically sends reminders to the user's smartphone to measure weight or exercise.

[0250] Specific examples

[0251] For example, if a user enters their weight as 70 kg, the system will display "Your weight has been recorded as 70 kg." The system will then suggest "Today's recommended menu: Salad" and "Today's recommended exercise: Walking." It will then display information about nearby stores that offer ingredients based on the suggested menu and fitness programs based on the exercise plan. Finally, it will provide periodic reminders to measure weight and exercise.

[0252] Prompt Sentence Examples

[0253] Create a Python program that records the user's weight when they input it, and suggests low-calorie meals and a moderate exercise plan. Also add a function to display the weight history.

[0254] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0255] Step 1:

[0256] The user starts the smartphone application and inputs their daily weight. The input weight data is sent from the smartphone device to the cloud server. The server receives this data and stores it in a database. The input data is the user's weight (e.g., 70 kg), and the output is the weight data stored in the database.

[0257] Step 2:

[0258] The server calculates the user's calorie intake needs based on the stored weight data. The calculation uses data such as the user's weight, age, gender, and activity level. The input data is the user's weight data and other personal information, and the output is the calculated calorie intake.

[0259] Step 3:

[0260] The server uses a generative AI model to suggest low-calorie meals based on the user's weight data. The AI ​​model generates optimal meals based on past data and nutritional information. The input data is the user's weight data and calorie intake, and the output is a suggested meal (e.g., salad).

[0261] Step 4:

[0262] The server uses a generative AI model to suggest a suitable exercise plan based on the user's weight data. The AI ​​model generates an optimal exercise plan taking into account the user's weight and activity level. The input data is the user's weight data and activity level, and the output is a suggested exercise plan (e.g., walking).

[0263] Step 5:

[0264] The server displays information about restaurants that offer related ingredients and fitness programs based on the proposed menu and exercise plan. The restaurant information is selected based on the user's location information and the content of the proposal. The input data is the proposed menu and exercise plan, and the output is related restaurant information.

[0265] Step 6:

[0266] The server periodically sends reminders to the user's smartphone to measure weight and exercise. The reminders are scheduled based on the user's settings. The input data are the user's settings and weight data, and the output is the reminder notification sent to the smartphone.

[0267] Example 3

[0268] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0269] In modern society, it is difficult to maintain a healthy diet in a busy daily life. This is especially true for those who do not like to cook or who do not have time. Another issue is the lack of support for weight management and achieving an ideal body shape. Another problem is the amount of effort required for health management, such as individual calorie calculations and food delivery.

[0270] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary for achieving an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring user location information, a means for searching for nearby healthy restaurants based on the acquired location information, and a means for providing the search results to the user. This enables the user to eat healthy meals without having to cook for themselves, and also provides support for weight management and achieving an ideal body shape.

[0271] "Weight management means" is a function for recording the user's daily weight and tracking fluctuations.

[0272] "Means to support diet, exercise, etc." is a function that provides the user with the meal plans and exercise programs necessary to achieve their ideal weight and body shape.

[0273] The "calorie calculation means" is a function that calculates the required calorie intake based on information such as the user's weight, height, age, and gender.

[0274] The "means for enabling delivery of ingredients from a menu" is a function that lists the ingredients required based on the menu selected by the user and delivers the ingredients to a location specified by the user.

[0275] "Means for obtaining location information" refers to a function that obtains the user's current location using GPS or other location information technology.

[0276] The "means for searching for nearby healthy restaurants" is a function that searches a database for healthy restaurants within a certain range from the user's current location based on the acquired location information.

[0277] The "means for providing search results to the user" is a function for transmitting information about the searched healthy restaurants to the user's terminal and displaying it.

[0278] This invention is a system that helps users maintain a healthy lifestyle by managing their weight on a daily basis, providing support for achieving an ideal weight and body shape, calculating calories, planning menus and delivering ingredients, and recommending nearby healthy restaurants.

[0279] Hardware and software used

[0280] Hardware: Smartphones (e.g., iPhone, Android devices), GPS devices

[0281] Software: GPS function, dedicated application, server (e.g., AWS (registered trademark), Google (registered trademark) Cloud)

[0282] Program processing

[0283] Subject: Server

[0284] The server receives the user's location information. The location information is obtained from the user's smartphone or GPS device. The server then references a database to search for healthy restaurants closest to the user's current location. This database includes information such as restaurant locations, menus, and ratings. Based on the search results, the server creates a list of healthy restaurants that are best suited to the user and sends it to the user's device.

[0285] Subject: Terminal

[0286] The device acquires the user's location information and sends it to the server. The location information is acquired using the smartphone's GPS function. After receiving the list of recommended healthy restaurants from the server, the device displays the list to the user. The user can select a restaurant of interest from the displayed list and check detailed information.

[0287] Subject: User

[0288] The user launches the app on their smartphone and allows location sharing. The app then requests nearby healthy restaurants based on the user's current location from the server. After receiving the recommendation list from the server, the user reviews the list and selects a restaurant that interests them. They then review the details of the selected restaurant and decide whether to visit.

[0289] Specific examples

[0290] When a user launches the smartphone app and allows location sharing, the device uses its GPS function to obtain its current location. The obtained location information is sent to a server, which then references a database to search for nearby healthy restaurants. For example, if the user is in Shibuya Ward, Tokyo, the server will create a list of healthy restaurants in Shibuya Ward and send it to the user's device. The user can then select a restaurant, such as "Shibuya Healthy Cafe" or "Natural Restaurant Shibuya," from the received list and check detailed information.

[0291] Example prompts to input to the generative AI model

[0292] "Please explain the system that recommends nearby healthy restaurants based on the user's current location. Please clearly state what kind of data processing and calculations are performed, including the names of specific hardware and software." The flow of the identification process in Example 3 will be explained using Figure 15.

[0293] Step 1:

[0294] The user launches the app and allows location sharing. The user launches the app on their smartphone and a pop-up appears requesting location sharing. When the user selects "Allow," the app starts acquiring location information. The input is the user's permission, and the output is the start of location information acquisition.

[0295] Step 2:

[0296] The device uses the GPS function to obtain the user's current location. The device uses the smartphone's GPS function to obtain the user's current location. Specifically, the device receives signals from GPS satellites and calculates latitude and longitude information. The input is the GPS signal, and the output is latitude and longitude information.

[0297] Step 3:

[0298] The device sends the acquired location information to the server. The device sends the acquired latitude and longitude information to the server. The HTTPS protocol is used for transmission to ensure data security. The input is latitude and longitude information, and the output is transmission to the server.

[0299] Step 4:

[0300] The server searches a database based on the received location information to list nearby healthy restaurants. The server searches the database based on the received location information. The database contains restaurant location information, menus, ratings, etc. The server lists healthy restaurants within a certain range from the user's current location. The input is location information, and the output is a list of restaurants.

[0301] Step 5:

[0302] The server sends the information about the listed restaurants to the terminal. The server sends the information about the listed restaurants to the terminal. The data sent is in JSON format and includes the restaurant's name, address, rating, part of the menu, etc. The input is a list of restaurants, and the output is what is sent to the terminal.

[0303] Step 6:

[0304] The device displays the received list of restaurants to the user. The device displays the received list of restaurants to the user. The app interface displays a list of restaurant names, ratings, distances, etc. The input is a list of restaurants, and the output is what is displayed to the user.

[0305] Step 7:

[0306] The user selects a restaurant of interest from the list and checks the details. The user selects a restaurant of interest from the list. Once selected, the app displays detailed information about the restaurant. The detailed information includes menu photos, opening hours, contact information, etc. The input is the user's selection and the output is the display of detailed information.

[0307] (Application example 3)

[0308] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0309] In modern society, people who lead busy lives find it difficult to plan and execute appropriate diets and exercises to maintain their health. Furthermore, for those who don't like cooking, the options for healthy meals are limited. Furthermore, the process of finding nearby healthy restaurants, ordering, and having food delivered can be cumbersome. There is a need for a system that can solve these problems and allow users to easily live a healthy lifestyle.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0311] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring the user's location information and listing nearby healthy restaurants, a means for ordering food from the listed restaurants and using delivery services, and a means for suggesting optimal menus based on the user's health status and goals. This allows the user to easily eat healthy meals without having to cook for themselves.

[0312] "Weight management tools" are features that allow users to record their daily weight and track fluctuations.

[0313] "Means to support diet, exercise, etc." refers to a function that provides meal plans and exercise plans necessary for users to achieve their ideal weight and body shape.

[0314] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's physical information and activity level.

[0315] "A means to enable the delivery of ingredients from a menu" is a function that lists the necessary ingredients based on the menu selected by the user and provides a service to deliver them.

[0316] "Means for obtaining location information" refers to a function that obtains the user's current location using technology such as GPS.

[0317] The "means of listing nearby healthy restaurants" is a function that searches for nearby restaurants that offer healthy menus based on the user's location information and displays them as a list.

[0318] "Means for ordering food and using delivery services" refers to the ability to select food from listed restaurants, order online, and use delivery services.

[0319] "Means to suggest optimal menus based on health status and goals" refers to a function that suggests optimal meal menus based on the user's health status and goals such as dieting and muscle building.

[0320] A system for carrying out the present invention includes the following means for supporting a user's health management.

[0321] 1. Program Generation

[0322] The system manages the user's daily weight and supports diet and exercise to achieve an ideal weight and body shape. It also calculates the user's calorie intake and enables everything from meal planning to food delivery. It also obtains the user's location information, lists nearby healthy restaurants, enables food ordering, and makes delivery services available. It also suggests optimal menus based on the user's health status and goals.

[0323] 2. Program processing explanation

[0324] Hardware used:

[0325] Smartphone (iOS or Android)

[0326] Software used:

[0327] Python

[0328] Geopy library (location information acquisition)

[0329] Requests library (API requests)

[0330] Google Places API (getting restaurant information)

[0331] Data processing and calculation:

[0332] The server first uses the Geopy library to obtain the user's location. Then, it uses the Google Places API to search for nearby healthy restaurants based on the obtained latitude and longitude. The search results are displayed as a list to the user, allowing the user to order food from the restaurant of their choice and use delivery services. It also calculates calories based on the user's input data to suggest optimal menus based on the user's health status and goals.

[0333] 3. Examples and prompts

[0334] Examples:

[0335] If the user is in Shibuya Ward, Tokyo, the system will display a list of nearby healthy restaurants. If the user indicates that they are on a diet, the system will suggest low-calorie options.

[0336] Example prompt sentence:

[0337] Write a Python program that gets the user's location and lists nearby healthy restaurants. Use the Geopy library to get the location and the Google Places API to get the restaurant information. Based on the user's latitude and longitude, search for healthy restaurants within a 1500 meter radius and display their information.

[0338] In this way, users can easily eat healthy meals without having to cook for themselves.

[0339] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0340] Step 1:

[0341] The server obtains the user's location information. Specifically, it obtains the latitude and longitude of the current location using the device's GPS function. The input is a location request from the user's device, and the output is the obtained latitude and longitude data.

[0342] Step 2:

[0343] The server uses the Google Places API to search for nearby healthy restaurants based on the acquired latitude and longitude. The input is the latitude and longitude data acquired in step 1, and the output is a list of restaurants as search results. Specifically, the server sends an API request and analyzes the response.

[0344] Step 3:

[0345] The server displays the search results to the user as a list. The input is the restaurant list obtained in step 2, and the output is the restaurant list displayed on the user's device. Specifically, the server formats the list and displays it on the user interface.

[0346] Step 4:

[0347] The user selects a restaurant from the list and orders food. The input is the user's selection, and the output is information about the selected restaurant and food. The specific operation is to accept the selection through a user interface.

[0348] Step 5:

[0349] The server receives the user's order information and arranges for a delivery service. The input is the order information obtained in step 4, and the output is a request to the delivery service. Specifically, it calls the delivery service's API and sends the order information.

[0350] Step 6:

[0351] The server proposes the optimal menu based on the user's health condition and goals. The input is data about the user's health condition and goals, and the output is the proposed menu. Specifically, the server calculates calories based on the user's input data and selects an appropriate menu.

[0352] Step 7:

[0353] The server presents the proposed menu to the user. The input is the menu information obtained in step 6, and the output is the menu displayed on the user's device. Specifically, the server formats the menu and displays it in the user interface.

[0354] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0355] "Example 1"

[0356] One embodiment of the present invention includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, behavioral patterns, etc. For example, if the user feels stressed, the emotion engine feeds that information back to the system, which then suggests exercises and meals that promote relaxation.

[0357] "Example 2"

[0358] The emotion engine also adjusts diet and exercise support based on the user's emotions. For example, when a user feels joy, the emotion engine feeds that information back to the system, which then suggests diet and exercise to maintain that joy. This allows users to manage their health in line with their emotions.

[0359] "Example 3"

[0360] Furthermore, the emotion engine recommends nearby healthy restaurants based on the user's emotions. For example, if the user is feeling down, the emotion engine will feed that information back into the system, and the system will suggest restaurants that serve healthy meals to lift the user's spirits. This allows users to make food choices that match their emotions.

[0361] The processing flow of each embodiment will be described below.

[0362] "Example 1"

[0363] Step 1: Collect data from users' tone of voice, facial expressions, behavioral patterns, etc.

[0364] Step 2: Send the collected data to the emotion engine.

[0365] Step 3: The emotion engine analyzes the user's emotions from the collected data.

[0366] Step 4: The analysis results are fed back to the system, which then suggests exercises and meals to the user that promote relaxation.

[0367] "Example 2"

[0368] Step 1: Analyze user emotion data with the emotion engine.

[0369] Step 2: The analysis results are fed back to the system, which then adjusts diet and exercise support based on the user's emotions.

[0370] Step 3: The system suggests diet and exercise recommendations to the user to maintain that joy.

[0371] "Example 3"

[0372] Step 1: Analyze user emotion data with the emotion engine.

[0373] Step 2: The analysis results are fed back to the system, which then recommends nearby healthy restaurants based on the user's emotions.

[0374] Step 3: The system suggests restaurants that offer healthy meals to boost the user's mood.

[0375] Example 1

[0376] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] In modern society, maintaining an ideal weight and body shape requires daily weight management, proper diet, and exercise support. However, it is difficult for many people to consistently do these things, and stress and emotional fluctuations in particular can affect health management. In addition, procuring ingredients and planning menus can be time-consuming, making continuous health management difficult.

[0378] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for sensing the user's tone of voice, facial expressions, and behavioral patterns, a means for analyzing the sensed data and identifying the user's emotional state, and a means for suggesting exercises and meals that promote relaxation based on the user's emotional state. This enables the user to consistently manage their health and receive support that also addresses stress and emotional fluctuations.

[0379] "Means for managing daily weight" refers to devices and software that allow users to measure their weight daily and record and save that data.

[0380] "Means to support the diet, exercise, etc. necessary to achieve an individual's ideal weight and body shape" refers to systems and algorithms that provide appropriate diet and exercise plans based on the user's health goals.

[0381] "Means for calculating calories appropriate for each individual" refers to a calculation function that calculates the amount of calories needed per day based on the user's weight data and other health information.

[0382] "Means that enable the process from planning a menu to delivering the ingredients" refers to a system or service that identifies the necessary ingredients based on the menu proposed to the user and delivers them to the user.

[0383] "Means for detecting a user's tone of voice, facial expression, and behavioral patterns" refers to devices or software that use sensors such as cameras and microphones to detect a user's tone of voice, facial expression, and behavioral patterns in real time.

[0384] "Means for analyzing the sensed data and identifying the user's emotional state" refers to an algorithm or analytical engine for analyzing the sensed data and identifying the user's emotional state.

[0385] "Means for suggesting exercises and meals that promote relaxation based on the user's emotional state" refers to a system or algorithm that suggests exercises and meals aimed at stress reduction and relaxation based on the user's emotional state.

[0386] MODE FOR CARRYING OUT THE INVENTION

[0387] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the calories appropriate for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[0388] Hardware and software used

[0389] This system uses the following hardware and software:

[0390] Hardware: smartphone, computer, camera, microphone

[0391] Software: Dedicated applications, databases (MySQL and PostgreSQL (registered trademark)), Python, NumPy, TENSORFLOW (registered trademark), OpenCV (registered trademark), Google Cloud Speech-to-Text API

[0392] Data processing and calculation

[0393] The server receives the weight data entered by the user and stores it in a database. The server then calculates the appropriate calorie intake for the user based on the stored data. This calculation is performed using Python's NumPy library. Based on the calculation results, the server then suggests a meal plan suitable for the user. This meal plan is proposed using a machine learning model (for example, using TensorFlow).

[0394] The server then identifies the ingredients needed for the proposed meal and sends an order to a partner food delivery service, so that the user can receive the ingredients at home.

[0395] Meanwhile, the device uses a camera and microphone to detect the user's tone of voice, facial expressions, and behavioral patterns. This data is sent to the emotion engine, which analyzes the data and identifies the user's emotional state. This analysis is performed using OpenCV and the Google Cloud Speech-to-Text API. If the emotion engine determines that the user is feeling stressed, the information is fed back to the server, which then uses the information to suggest exercises and meals that will promote relaxation for the user.

[0396] Specific examples

[0397] As a concrete example, consider the case where a user weighs themselves in the morning and enters that data into the system. When the user enters the weight data, the server receives and stores the data. The server then calculates the appropriate daily calorie intake based on the user's weight data. For example, if the user weighs 70 kg, the server calculates the daily calorie intake to be 2000 kcal. The server then proposes a meal plan based on 2000 kcal and orders the necessary ingredients from a food delivery service.

[0398] If the user is feeling stressed, the emotion engine analyzes the information and sends it back to the server, which then suggests relaxation exercises such as yoga or meditation.

[0399] Prompt Sentence Examples

[0400] Example prompts to input to a generative AI model:

[0401] Enter the user's weight data, then calculate the user's appropriate calorie intake and suggest meals based on the results. Also, if the user is feeling stressed, suggest exercises and meals that promote relaxation.

[0402] In this way, the system provides comprehensive support for the user's health management.

[0403] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0404] Step 1:

[0405] The user inputs weight data. The user measures their weight on a scale every morning and enters the weight data into a dedicated smartphone app. The input weight data is saved on the device.

[0406] Step 2:

[0407] The terminal sends the entered weight data to the server. The terminal encrypts the entered weight data using SSL / TLS and sends it to the server via the Internet. The input is weight data, and the output is encrypted data.

[0408] Step 3:

[0409] The server receives the weight data and stores it in a database. The server stores the received weight data in a database. A relational database such as MySQL or PostgreSQL is used for the database. The input is encrypted weight data, and the output is the data stored in the database.

[0410] Step 4:

[0411] The server calculates the calorie intake based on the stored weight data. The server uses Python's NumPy library to calculate the appropriate daily calorie intake based on the stored weight data. For example, it calculates 2000 kcal for a user weighing 70 kg. The input is weight data and the output is calorie intake.

[0412] Step 5:

[0413] The server uses TensorFlow to suggest a menu suitable for the user based on the calculation results. For example, it suggests oatmeal for breakfast, salad for lunch, and grilled chicken for dinner. The input is calorie intake, and the output is a menu suggestion.

[0414] Step 6:

[0415] The server identifies the ingredients needed for the proposed meal and sends an order to the food delivery service. The server identifies the ingredients needed for the proposed meal (oatmeal, lettuce, chicken breast, etc.) and sends an order to the partner food delivery service. The input is the meal and the output is the food order.

[0416] Step 7:

[0417] The device senses the user's tone of voice, facial expressions, and behavioral patterns. The device uses a built-in camera and microphone to sense the user's tone of voice, facial expressions, and behavioral patterns in real time. The input is the user's voice, facial expressions, and behavioral patterns, and the output is the sensed data.

[0418] Step 8:

[0419] The device sends the sensed data to the emotion engine. The device sends the sensed data to the emotion engine in real time. The data includes the user's tone of voice and changes in facial expression. The input is the sensed data, and the output is the data sent to the emotion engine.

[0420] Step 9:

[0421] The emotion engine analyzes the user's emotional state. The emotion engine uses OpenCV and the Google Cloud Speech-to-Text API to analyze the user's emotional state. For example, it determines if the user is feeling stressed. The input is the sensed data, and the output is the analysis result.

[0422] Step 10:

[0423] The emotion engine feeds back the analysis results to the server. The emotion engine feeds back the analysis results to the server. The fed back data indicates that the user is feeling stressed. The input is the analysis results, and the output is the data fed back to the server.

[0424] Step 11:

[0425] The server suggests exercises and meals that promote relaxation based on the user's emotional state. If the server learns that the user is feeling stressed, it suggests relaxation exercises such as yoga or meditation, or meals that are effective in reducing stress, such as chamomile tea. The input is the feedback data, and the output is suggestions that promote relaxation.

[0426] (Application example 1)

[0427] Next, a description will be given of Application Example 1 of Embodiment Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0428] Conventional weight management systems can collect a user's weight data and calculate calories and suggest meals, but they lack support that takes into account the user's emotional state. Furthermore, they do not deliver the ingredients needed for the suggested meals or suggest relaxation activities based on the user's emotions, making it difficult for users to continuously manage their health.

[0429] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0430] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for planning a menu and delivering the ingredients, a means for analyzing the user's emotions, a means for suggesting exercise and meals that promote relaxation based on the results of the emotion analysis, and a means including an application to be installed on a smartphone. This provides comprehensive support for the user's weight management and emotional state, enabling continuous health management.

[0431] A "weight management tool" is a device or software that collects and records a user's daily weight data.

[0432] "Means to support diet, exercise, etc." refers to devices or software that provide users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[0433] A "calorie calculation means" is a device or software that calculates an appropriate calorie intake for an individual based on the user's weight data.

[0434] "Means that enable the planning and delivery of ingredients" refers to devices or software that automatically order the necessary ingredients based on the proposed menu and deliver them to the user's home.

[0435] "Means for analyzing emotions" refers to devices or software that analyze emotions from the user's tone of voice, facial expressions, behavioral patterns, etc.

[0436] The "means for suggesting exercises and meals that promote relaxation" refers to a device or software that suggests exercises and meals that promote relaxation to the user based on the results of emotion analysis.

[0437] "Applications installed on smartphones" refers to software installed on smartphones to provide users with functions such as weight management, emotion analysis, calorie calculation, meal suggestions, and food ordering.

[0438] The system for implementing this invention collects weight data and emotional data of the user and provides dietary and exercise support to achieve an ideal weight and body shape. It also includes a function to automatically order ingredients needed for the suggested menu and have them delivered to the user's home.

[0439] Hardware and Software Configuration

[0440] Hardware:

[0441] Smartphone (camera, microphone)

[0442] Server (for data processing)

[0443] software:

[0444] Python

[0445] EmotionEngine (emotion analysis library)

[0446] FoodDeliveryService (API for ordering ingredients)

[0447] Data processing and calculation

[0448] Weight data collection:

[0449] Users input their weight data through a smartphone application, which is then sent to a server and recorded as their daily weight data.

[0450] Emotional Data Analysis:

[0451] The user's tone of voice and facial expression data are collected using the smartphone's camera and microphone, and the collected data is analyzed using the Emotion Engine to identify the user's emotional state.

[0452] Calorie Count:

[0453] The server calculates the required calorie intake based on the user's weight data, and the calculation results serve as a benchmark for the user to aim for their ideal weight and body shape.

[0454] Menu suggestions:

[0455] The server then suggests appropriate meals based on the calculated calories, taking into account the user's health and emotional state.

[0456] Ingredients Order:

[0457] The necessary ingredients based on the proposed menu are automatically ordered through the FoodDeliveryService, and the ordered ingredients are delivered to the user's home.

[0458] Relaxation Suggestions:

[0459] Based on the results of the emotion analysis, the server will suggest exercises and meals that promote relaxation to the user, thereby reducing stress and supporting health management.

[0460] Specific examples

[0461] For example, if a user inputs their weight of 75 kg and provides voice and facial expression data, the server will suggest a 2,000 calorie meal and automatically order salad, chicken breast, and brown rice. If the server also analyzes that the user is feeling stressed, it will suggest yoga or herbal tea to promote relaxation.

[0462] Prompt Sentence Examples

[0463] An example of a prompt for the generative AI model is as follows:

[0464] Develop an application that calculates calories and suggests meals to help users achieve their ideal weight and shape based on their weight and emotional data. Also, include a function to automatically order ingredients for the suggested meals and have them delivered to the user's home.

[0465] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0466] Step 1:

[0467] The user inputs weight data through a smartphone application.

[0468] Input: User weight data

[0469] Output: Weight data sent to the server

[0470] Specific behavior: When a user enters their weight in the application's input form and presses the submit button, the data is sent to the server.

[0471] Step 2:

[0472] The server records daily weight data.

[0473] Input: Weight data submitted by the user

[0474] Output: Weight data stored in the database

[0475] Specific operation: The server stores the received weight data in a database and records daily weight fluctuations.

[0476] Step 3:

[0477] The user collects voice and facial expression data using the camera and microphone on their smartphone.

[0478] Input: User's voice and facial expression data

[0479] Output: Voice and facial expression data sent to the server

[0480] What it does: The user launches the application, which uses the camera and microphone to record their voice and facial expressions, and then sends that data to the server.

[0481] Step 4:

[0482] The server analyzes the emotional data using EmotionEngine.

[0483] Input: User's voice and facial expression data

[0484] Output: Parsed emotion data

[0485] Specific operation: The server inputs the received voice and facial expression data into the Emotion Engine, performs emotion analysis, and obtains the results.

[0486] Step 5:

[0487] The server calculates calories based on the user's weight data.

[0488] Input: User weight data

[0489] Output: Calculated calorie intake

[0490] Specific operation: The server applies a calorie calculation algorithm based on weight data to calculate the required calorie intake.

[0491] Step 6:

[0492] The server will suggest a menu based on the calculated calories.

[0493] Input: Calculated calorie intake

[0494] Output: Suggested menu

[0495] Specific operation: The server generates an appropriate menu based on the calorie intake and suggests it to the user.

[0496] Step 7:

[0497] The server automatically orders the necessary ingredients based on the proposed menu through the FoodDeliveryService.

[0498] Input: Suggested menu

[0499] Output: Ordered ingredients

[0500] What happens: The server sends the proposed menu to the FoodDeliveryService, which automatically orders the necessary ingredients.

[0501] Step 8:

[0502] The server suggests exercises and meals that promote relaxation based on the results of emotion analysis.

[0503] Input: Parsed emotion data

[0504] Output: Suggestions for exercise and meals to promote relaxation

[0505] Specific operation: Based on the results of emotion analysis, the server suggests exercises and meals that promote relaxation to the user.

[0506] Example 2

[0507] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0508] Conventional health management systems require users to make appropriate decisions on their own, and provide insufficient support for weight management and emotional support. Furthermore, they do not provide dietary or exercise recommendations that reflect the user's emotions, making it difficult to address individual needs. Furthermore, they do not provide prompt and appropriate measures in the event of weight gain, making it difficult for users to effectively manage their health.

[0509] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0510] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for collecting user emotion data, a means for adjusting meal and exercise suggestions based on the collected emotion data, a means for generating optimal menu and exercise plans using a generative AI model, and a means for notifying the user of the generated suggestions to their terminal. This eliminates the need for the user to take appropriate measures on their own, and enables effective health management with the support of the system.

[0511] "Means for managing daily weight" is a function that allows users to input their daily weight and record, save, and manage that data.

[0512] "Means to support the diet, exercise, etc. necessary to achieve an individual's ideal weight and body shape" is a function that provides appropriate diet and exercise plans to help users achieve their ideal weight and body shape.

[0513] The "means for calculating calories appropriate for each individual" is a function that calculates the optimal calorie intake for each individual based on information such as the user's weight, age, sex, and activity level.

[0514] The "means for enabling delivery of ingredients from a menu" is a function for listing the ingredients required based on a proposed menu and delivering those ingredients to the user.

[0515] "Means for collecting user emotional data" refers to a function for inputting or automatically detecting the user's emotional state, and collecting and saving that data.

[0516] The "means for adjusting diet and exercise suggestions based on collected emotion data" is a function for adjusting diet and exercise suggestions in consideration of the collected emotion data of the user.

[0517] "Means for generating optimal menus and exercise plans using a generative AI model" refers to a function that uses a generative AI model to analyze a user's weight data and emotional data and generate optimal menus and exercise plans.

[0518] "Means for notifying the user of the generated suggestions" is a function for notifying the user of the generated menu and exercise plan on a device such as a smartphone or tablet.

[0519] This invention is a system for managing a user's weight and supporting their health based on their emotions. The system uses a server, user devices (smartphones, tablets, PCs), a generative AI model, an emotion engine, and a database management system (DBMS).

[0520] Hardware and software used

[0521] Hardware: Servers, user devices (smartphones, tablets, PCs)

[0522] Software: Generative AI model, emotion engine, database management system (DBMS)

[0523] Specific operation of the system

[0524] 1. Data Collection

[0525] The user inputs their weight, and the device sends this data to the server.

[0526] The emotion engine collects user emotion data, for example, by allowing the user to select an emotion within the app, or by automatically detecting emotions using emotion recognition technology.

[0527] 2. Data transmission and storage

[0528] The device sends the entered weight data to the server, which then stores the received data in a database.

[0529] 3. Data analysis

[0530] The server retrieves weight data and emotion data from the database and analyzes them using a generative AI model.

[0531] 4. Proposal generation

[0532] The server uses the generative AI model to suggest low-calorie meals and moderate exercise to the user, and the emotion engine adjusts the suggestions based on the user's emotional data.

[0533] 5. Suggestion Notification and Feedback

[0534] The server sends the generated menu and exercise plan to the user's device, where the user receives and executes the suggestions.

[0535] Specific examples

[0536] Weight data entry: The user enters their weight into the smartphone app.

[0537] Emotion data collection: User selects "joy" within the app.

[0538] Data analysis: The server detects weight gain and uses a generative AI model to generate low-calorie meals.

[0539] Recommendation: The server suggests a "low-calorie salad and grilled chicken breast" and recommends "30 minutes of walking" as moderate exercise.

[0540] Emotion regulation: The emotion engine suggests exercising while listening to your favorite music to maintain your "joy."

[0541] Prompt Sentence Examples

[0542] "Please generate a program that suggests low-calorie meals and moderate exercise if the user has gained weight. Also, please add a function that adjusts the suggestions based on the user's emotional data."

[0543] This system allows users to manage their health with the support of the system, without the need to take appropriate measures on their own.

[0544] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0545] Step 1:

[0546] A user opens a smartphone app and inputs their weight. The input weight data is temporarily stored on the device. The input data is in a format such as "Weight: 70kg". The device sends this data to the server. The output is the weight data sent to the server.

[0547] Step 2:

[0548] The server stores the weight data received from the terminal in a database. The input is the weight data sent from the terminal, and the output is the weight data stored in the database. Specifically, the server stores the data using a database management system (DBMS).

[0549] Step 3:

[0550] The user selects an emotion within the app, or emotion recognition technology is used to automatically detect the emotion. The emotion data is in the form of "happiness" or "sadness," etc. The device sends this emotion data to the server. The output is the emotion data sent to the server.

[0551] Step 4:

[0552] The server stores the emotion data received from the device in a database. The input is the emotion data sent from the device, and the output is the emotion data stored in the database. Specifically, the server stores the data using a database management system (DBMS).

[0553] Step 5:

[0554] The server retrieves weight data and emotion data from the database. The input is the weight data and emotion data stored in the database, and the output is the retrieved data. Specifically, the server retrieves the data using an SQL query.

[0555] Step 6:

[0556] The server uses the generative AI model to analyze the acquired weight data and emotional data. The input is the acquired weight data and emotional data, and the output is the analysis results. Specifically, the server inputs the data into the generative AI model and generates an optimal menu and exercise plan.

[0557] Step 7:

[0558] The server uses the generative AI model to suggest low-calorie meals and moderate exercise to the user. The emotion engine takes into account the user's emotional data and adjusts the suggestions. The input is the analysis results and emotional data, and the output is the adjusted suggestions. Specifically, the server works by linking the generative AI model and the emotion engine to generate the suggestions.

[0559] Step 8:

[0560] The server notifies the user's device of the menu and exercise plan it has generated. The input is the adjusted proposal, and the output is the notification sent to the user's device. Specifically, the server uses a notification API to send the proposal to the user's device.

[0561] Step 9:

[0562] The user receives the suggestions and executes them. The input is the suggestion notified to the terminal, and the output is the result of the user's execution. Specifically, the user creates a menu based on the suggested exercise plan and executes it.

[0563] (Application example 2)

[0564] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0565] In modern society, individual health management is an important issue. However, for many people, planning their own daily weight management, meals, and exercise is a burden, and it is particularly difficult to respond appropriately to emotional fluctuations. Furthermore, for people who find cooking a hassle, it is difficult to maintain a healthy diet. Furthermore, there is a lack of easy access to the suggested meals, which makes it difficult to continue health management.

[0566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0567] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for recognizing the user's emotions and adjusting diet and exercise based on those emotions, a means for ordering suggested meals via a delivery service, and a means for suggesting appropriate exercise and tracking progress. This allows the user to receive suggestions for optimal diet and exercise based on their weight and emotions and easily carry out those suggestions.

[0568] A "weight management tool" is a tool for recording a user's daily weight and tracking fluctuations.

[0569] "Means to support diet, exercise, etc." refers to means that provide users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[0570] A "calorie calculation means" is a means for calculating calorie needs based on a user's weight and activity level.

[0571] "Means that enable the planning of a menu and the delivery of ingredients" refers to a means of ordering and delivering the necessary ingredients based on a proposed menu.

[0572] "Means for recognizing emotions" refers to a means for detecting the user's emotions and feeding that information back to the system.

[0573] The "means for adjusting diet and exercise" is a means for appropriately changing the diet and exercise content based on the user's emotions.

[0574] "Means of ordering through a delivery service" refers to means of ordering the suggested meal using a delivery service.

[0575] "Means for suggesting exercises and tracking progress" refers to means for suggesting appropriate exercises to users and tracking their progress.

[0576] The following system configuration is used as an embodiment of the present invention.

[0577] System Configuration

[0578] Hardware

[0579] Smartphone: A device that allows users to input their daily weight and recognize emotions.

[0580] Server: A central system for processing and storing data.

[0581] software

[0582] EmotionEngine: An emotion recognition library for recognizing user emotions.

[0583] FoodSuggestion: A library that suggests meals based on the user's weight and emotions.

[0584] DeliveryService: An API for ordering suggested meals through a delivery service.

[0585] ExerciseSuggestion: A library that suggests appropriate exercises to users and tracks their progress.

[0586] Data processing and calculation

[0587] Obtaining the user's weight and emotions

[0588] Users input their daily weight using their smartphone, and EmotionEngine recognizes the user's emotions through the smartphone's camera and microphone, sending the user's weight and emotion data to the server.

[0589] Diet and exercise suggestions

[0590] The server uses the FoodSuggestion library to suggest optimal meals based on the user's weight and emotions, and the ExerciseSuggestion library to suggest moderate exercise. These suggestions are displayed on the smartphone.

[0591] Delivery orders

[0592] If the user decides to order a suggested meal, the order is placed through the DeliveryService API on their smartphone, which then delivers the suggested meal to the user.

[0593] Specific examples

[0594] User weight and emotions

[0595] User weight: 70kg

[0596] User Emotion: Delight

[0597] Prompt Sentence Examples

[0598] The user weighs 70 kg and feels happy. Suggest low-calorie meals, encourage moderate exercise, and allow the user to order the suggested meals via a delivery service.

[0599] In this way, a system can be realized that suggests optimal diet and exercise based on the user's weight and emotions, and provides them through a delivery service, allowing users to easily manage their health according to their weight and emotions.

[0600] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0601] Step 1:

[0602] The user inputs their daily weight using a smartphone, and the input weight data is sent from the smartphone to the server.

[0603] Input: User's weight

[0604] Output: Weight data sent to the server

[0605] Step 2:

[0606] The user recognizes emotions using the smartphone's camera and microphone, and the EmotionEngine analyzes the emotions and sends the results to the server.

[0607] Input: User's facial image or voice data

[0608] Output: Emotion data sent to the server

[0609] Step 3:

[0610] The server uses the FoodSuggestion library to suggest optimal meals based on the received weight and emotion data, and the suggested meal data is sent to the smartphone.

[0611] Input: Weight data, Emotion data

[0612] Output: Meal suggestion data sent to smartphone

[0613] Step 4:

[0614] The server uses the ExerciseSuggestion library to suggest appropriate exercises based on the received weight data, and the suggested exercise data is sent to the smartphone.

[0615] Input: Weight data

[0616] Output: Exercise suggestion data sent to smartphone

[0617] Step 5:

[0618] The user checks the suggested meals on their smartphone and places an order through the delivery service, which then sends the order data via the DeliveryService API.

[0619] Input: Meal suggestion data, user ordering instructions

[0620] Output: Order data sent to the delivery service

[0621] Step 6:

[0622] The delivery service receives the order and delivers the suggested meal to the user.

[0623] Input: Order data

[0624] Output: Meal delivered to user

[0625] Step 7:

[0626] The user performs the suggested exercise and enters their progress into their smartphone, which then sends the progress data to the server.

[0627] Input: User's exercise progress data

[0628] Output: Exercise progress data sent to the server

[0629] Step 8:

[0630] The server updates the user's exercise history based on the received exercise progress data and reflects it in the next exercise suggestion.

[0631] Input: Exercise progress data

[0632] Output: Updated exercise history data

[0633] Example 3

[0634] Next, a description will be given of a third embodiment of the third embodiment. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0635] In modern society, maintaining a healthy diet in a busy daily life is difficult. Choosing the right meal is even more difficult for people who find cooking a hassle or whose food choices are affected by emotional fluctuations. Conventional systems do not suggest meals that take into account the user's location information or emotional state, and therefore do not provide sufficient support for maintaining the user's health.

[0636] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0637] In this invention, the server includes means for acquiring user location information, means for searching for nearby healthy restaurants, means for analyzing the user's emotional state, means for recommending restaurants based on the emotional state, and means for notifying the user of information about the recommended restaurants, thereby enabling the user to easily find the optimal healthy restaurant based on their location information and emotional state.

[0638] A "weight management tool" is a device or software that records a user's daily weight and tracks fluctuations.

[0639] A "diet and exercise support tool" is a device or software that provides a user with the diet and exercise plan they need to achieve their ideal weight and shape.

[0640] The "calorie calculation means" is a device or software that calculates the required calorie intake based on the user's physical information and activity level.

[0641] "Means that enable the delivery of ingredients from a menu" refers to a device or software that provides a service that lists the ingredients needed based on the menu selected by the user and delivers those ingredients to the user.

[0642] "Means for obtaining user location information" refers to devices or software that use GPS or other location information technology to identify the user's current location.

[0643] The "means for searching for nearby healthy restaurants" is a device or software that searches for nearby restaurants that offer healthy meals based on the user's location information.

[0644] "Means for analyzing the user's emotional state" refers to a device or software that analyzes the user's input and behavioral data to determine the user's current emotional state.

[0645] The "means for recommending restaurants based on emotional state" is a device or software that selects and recommends optimal healthy restaurants in consideration of the user's emotional state.

[0646] The "means for notifying the user of information about the recommended store" is a device or software that notifies the user's terminal of information about the selected store.

[0647] This invention is a system that allows users to easily select healthy meals. The system recommends optimal healthy restaurants taking into account the user's location information and emotional state. Specific embodiments of this system are described below.

[0648] Hardware and software used

[0649] Hardware: Smartphone, GPS module, server

[0650] Software: Mobile applications, location APIs (e.g., Google Maps API), sentiment analysis engines, database management systems (DBMS)

[0651] Program processing procedure

[0652] 1. Obtaining user location information

[0653] The user launches a mobile application on their smartphone.

[0654] The device (smartphone) uses the built-in GPS module to obtain the user's current location.

[0655] The terminal transmits the acquired location information to the server.

[0656] 2. Find healthy restaurants near you

[0657] The server uses a location API to collect information about healthy restaurants and cafes near the user's current location.

[0658] The server stores the collected information in a database.

[0659] 3. Emotion analysis

[0660] The user inputs their emotional state within the application, or an emotion analysis engine analyzes the user's text or voice input to determine the emotion.

[0661] The terminal transmits the determined emotion information to the server.

[0662] 4. Store Recommendations

[0663] The server receives feedback from the sentiment analysis engine and selects the best healthy restaurants based on the user's emotional state.

[0664] The server sends information about the selected store to the user's smartphone.

[0665] 5. Notice to Users

[0666] The terminal notifies the user of information about the recommended store.

[0667] The user can select a store to visit based on the displayed information.

[0668] Specific examples

[0669] For example, if a user types "I'm tired today" into the application, the sentiment analysis engine will determine the emotion as "fatigue." Based on this information, the server will recommend healthy cafes with a relaxing atmosphere.

[0670] Prompt Sentence Examples

[0671] "If a user feels tired, describe a system that recommends healthy cafes with a relaxing atmosphere."

[0672] This system allows the user to select the most suitable meal to suit his / her emotional state. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0673] Step 1:

[0674] Obtaining user location information

[0675] The user launches a mobile application on their smartphone.

[0676] The device (smartphone) uses the built-in GPS module to obtain the user's current location.

[0677] Input: User application launch operation

[0678] Output: User's current location (latitude and longitude)

[0679] What it does: When a user opens the app, the message "Getting your current location" is displayed. Once the GPS has determined the location, the message "Location acquired" is displayed.

[0680] The terminal transmits the acquired location information to the server.

[0681] Step 2:

[0682] Find healthy restaurants near you

[0683] The server uses a location API to collect information about healthy restaurants and cafes near the user's current location.

[0684] Input: User's current location

[0685] Output: A list of nearby healthy restaurants

[0686] What it does: Once the server receives your location, it displays the message "Searching for nearby healthy restaurants." After a few seconds, it displays the message "Search completed."

[0687] The server stores the collected information in a database.

[0688] Step 3:

[0689] Emotion analysis

[0690] The user inputs their emotional state within the application, or an emotion analysis engine analyzes the user's text or voice input to determine the emotion.

[0691] Input: User emotional state input (text or voice)

[0692] Output: Determined emotion information

[0693] Specific behavior: When a user enters "I'm tired today," the emotion analysis engine determines it as "fatigue," and the message "Emotion information analyzed" is displayed.

[0694] The terminal transmits the determined emotion information to the server.

[0695] Step 4:

[0696] Store recommendation

[0697] The server receives feedback from the sentiment analysis engine and selects the best healthy restaurants based on the user's emotional state.

[0698] Input: Determined emotion information, list of nearby healthy restaurants

[0699] Output: Recommended store information

[0700] Specific behavior: When the server receives the emotion information, it displays the message "Selecting restaurants based on your emotions." After a few seconds, it displays the message "Recommended restaurants found."

[0701] The server sends information about the selected store to the user's smartphone.

[0702] Step 5:

[0703] User Notification

[0704] The terminal notifies the user of information about the recommended store.

[0705] Input: Recommended store information

[0706] Output: A message to inform the user

[0707] Specific operation: A notification will appear on the user's smartphone saying, "Here are some recommended shops," along with detailed information.

[0708] The user can select a store to visit based on the displayed information.

[0709] (Application example 3)

[0710] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0711] In modern society, many people find it difficult to eat healthy meals in their busy daily lives. For those who find cooking a hassle, preparing healthy meals themselves is even more difficult. Furthermore, there are no systems that can help users choose meals based on their emotional state. To solve these challenges, a system is needed that can recommend nearby healthy restaurants and easily order delivery based on the user's location and emotional state.

[0712] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0713] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring the user's location information, a means for analyzing the user's emotions, a means for recommending nearby healthy restaurants, and a means for ordering delivery directly from the recommended restaurants. This allows the user to eat healthy meals without having to cook for themselves, and also enables them to select meals according to their emotional state.

[0714] A "weight management tool" is a device or software that records a user's daily weight and tracks fluctuations.

[0715] "Means to support diet, exercise, etc." refers to devices or software that provide users with the meal plans and exercise programs they need to achieve their ideal weight and body shape.

[0716] A "calorie-counting means" is a device or software that calculates the user's calorie intake needs based on their weight and activity level.

[0717] "Means that enable the process from planning a menu to delivering the ingredients" refers to devices or software that automatically order and deliver the necessary ingredients based on the menu selected by the user.

[0718] "Means for obtaining location information" refers to devices or software that obtain the user's current location using technology such as GPS.

[0719] "Means for analyzing emotions" refers to devices or software that analyze the user's emotional state from facial expressions, voice, etc.

[0720] The "means for recommending nearby healthy restaurants" is a device or software that recommends nearby restaurants that serve healthy meals based on the user's location information and emotional state.

[0721] A "delivery ordering method" is a device or software that allows you to order food directly from a recommended restaurant and request delivery.

[0722] The system for carrying out the present invention is configured by combining multiple pieces of hardware and software to support the health management of a user. Specific embodiments are described below.

[0723] Hardware Configuration

[0724] 1. Smartphone: Equipped with GPS to obtain the user's location, and a camera and microphone to analyze emotions.

[0725] 2. Server: A central processing unit for data processing and analysis.

[0726] 3. Network: An internet connection for data communication between your smartphone and the server.

[0727] Software Configuration

[0728] 1. Location acquisition software: Uses the geopy library to acquire the user's current location.

[0729] 2. Emotion analysis software: Use the emotion_recognition library to analyze emotions from the user's facial expressions and voice.

[0730] 3. Restaurant search software: Use the restaurant_finder library to find nearby healthy eateries.

[0731] 4. Delivery ordering software: Provides an interface for ordering delivery directly from recommended restaurants.

[0732] Data processing and calculation

[0733] 1. Obtaining location information: The smartphone's GPS function is used to obtain the user's current location. The obtained location information is sent to the server.

[0734] 2. Emotion analysis: The smartphone camera and microphone are used to capture the user's facial expressions and voice, and the emotion_recognition library is used to analyze their emotions. The analysis results are sent to the server.

[0735] 3. Restaurant recommendation: Based on the location information and the results of sentiment analysis, the server uses the restaurant_finder library to search for nearby healthy restaurants and recommend them to the user.

[0736] 4. Order delivery: Provides an interface for users to select meals from recommended restaurants and order delivery. The order information is sent to the restaurant via the server.

[0737] Specific examples

[0738] For example, if a user is tired from work, the system will analyze their emotions using the smartphone's camera and microphone to detect that they are feeling stressed. It will then use GPS to find the user's current location and recommend nearby cafes that offer healthy meals in a relaxing environment. The user can then order delivery directly from the recommended cafes.

[0739] Prompt Sentence Examples

[0740] "Recommend nearby healthy restaurants based on the user's location and emotions."

[0741] "When users are feeling down, suggest places that serve healthy meals to lift their spirits."

[0742] The above is a specific embodiment for carrying out the present invention.

[0743] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0744] Step 1:

[0745] Obtaining location information

[0746] The device (smartphone) uses its GPS function to obtain the user's current location. The input is location data from the GPS sensor, and the output is latitude and longitude information. This location information is sent to the server.

[0747] Step 2:

[0748] Sentiment analysis

[0749] The device (smartphone) uses a camera and microphone to capture the user's facial expressions and voice. The input is video and audio data from the camera and microphone, and the output is the emotion analysis result. The emotion_recognition library is used to analyze the user's emotions from this data and send the results to the server.

[0750] Step 3:

[0751] Restaurant search

[0752] The server uses the restaurant_finder library to search for nearby healthy restaurants based on the location information obtained in step 1 and the sentiment analysis results obtained in step 2. The input is the location information and the sentiment analysis results, and the output is a list of recommended restaurants.

[0753] Step 4:

[0754] Restaurant recommendations

[0755] The server recommends the list of restaurants obtained in step 3 to the user. The input is a list of recommended restaurants, and the output is a recommendation list displayed on the user's device. The user can select from this list.

[0756] Step 5:

[0757] Delivery orders

[0758] The user uses the terminal to select a meal from the recommended restaurant and order delivery. The input is the user's selected meal and order information, and the output is the order information sent to the restaurant. This information is sent to the restaurant via the server.

[0759] The above are the specific processing steps of this system.

[0760] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0761] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0762] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0763] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0764] [Second embodiment]

[0765] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0766] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0767] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0768] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0769] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0770] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0771] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0772] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0773] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0774] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0775] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0776] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0777] "Example 1"

[0778] The system of the present invention collects the user's weight data daily and provides dietary and exercise support to help them achieve their ideal weight and body shape based on that data. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[0779] "Example 2"

[0780] Even if the user gains weight, the system of the present invention will flexibly consider optimal menus and exercises to support the user. For example, if the user gains weight, the system will suggest low-calorie menus and recommend moderate exercise. This means that the user does not need to take appropriate measures on their own, and can manage their health with the support of the system.

[0781] "Example 3"

[0782] For people who don't like to cook, the system of this invention recommends nearby healthy restaurants and cafes based on the user's location information. This allows users to eat healthy meals without having to cook themselves.

[0783] The processing flow of each embodiment will be described below.

[0784] "Example 1"

[0785] Step 1: The user enters weight data into the system.

[0786] Step 2: The system calculates the appropriate calories for the user based on that data.

[0787] Step 3: The system suggests a menu based on the calculation results.

[0788] Step 4: The system delivers the ingredients needed for the proposed meal.

[0789] "Example 2"

[0790] Step 1: The user enters weight data into the system.

[0791] Step 2: The system detects that you have gained weight.

[0792] Step 3: The system suggests low-calorie meals.

[0793] Step 4: The system recommends moderate exercise.

[0794] "Example 3"

[0795] Step 1: The user inputs into the system that cooking is a hassle.

[0796] Step 2: The system recommends nearby healthy restaurants and cafes based on the user's location.

[0797] Example 1

[0798] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0799] Health management is an important issue in modern society, but many people find it difficult to manage their daily weight and plan appropriate meals and exercise. There are also few systems that calculate optimal calorie intake based on individual weight data and suggest menus based on that calculation. Furthermore, there are limited ways to easily obtain the ingredients needed for the suggested menus. A comprehensive system that can solve these problems is needed.

[0800] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0801] In this invention, the server includes means for collecting user weight data daily, means for calculating calories appropriate for the user based on the collected weight data, means for generating menus based on the calculation results, means for creating a list of ingredients required for the generated menus, and means for delivering ingredients based on the ingredient list. This allows users to efficiently manage their daily weight, obtain optimal calorie intake and menus based on their individual weight data, and easily obtain the necessary ingredients.

[0802] "User weight data" refers to the weight data that a user measures daily and enters into the system.

[0803] A "calorie calculation means" is an algorithm or software that calculates a user's appropriate daily calorie intake based on the user's weight data.

[0804] A "means for generating a menu" is an algorithm or software that creates a meal menu appropriate for the user based on the calculated calorie intake.

[0805] The "means for creating an ingredient list" refers to an algorithm or software for listing the ingredients and their quantities required for the generated menu.

[0806] "Means for delivering ingredients" refers to a service or system for delivering ingredients needed by the user based on the created ingredient list.

[0807] "A means of flexibly planning and supporting optimal meal plans and exercise even when weight gain occurs" refers to algorithms and software that dynamically adjust and provide optimal meal menus and exercise plans according to changes in the user's weight.

[0808] The "means for recommending nearby healthy restaurants" refers to algorithms and software that search for and recommend nearby restaurants that serve healthy meals to users who don't like to cook.

[0809] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[0810] Hardware and software used

[0811] server

[0812] The server collects weight data sent by users daily. This data is entered by the user through a dedicated application. The server calculates the appropriate calorie intake for the user based on the collected weight data. This calculation is performed using Python's NumPy library. Based on the calculation results, the server generates a meal plan appropriate for the user. This meal plan is generated using the generative AI model GPT-4. The server then creates a list of ingredients required for the generated meal plan and sends an order to a partner food delivery service. A REST API is used to process this order.

[0813] Terminal

[0814] The device provides an interface for users to input weight data. Users input weight data into a dedicated application using a device such as a smartphone or tablet. The device uses the HTTPS protocol to send the input data to the server. The device also has the function of displaying calorie calculation results and meal suggestions received from the server. Users can check the suggested meals through the device and order the necessary ingredients.

[0815] user

[0816] Every day, users enter their weight data into a dedicated application. This application runs on devices such as smartphones and tablets. When users enter their weight data, the data is sent to a server. The server returns calorie calculation results and menu suggestions, which the user can then review. The user can then prepare meals based on the suggested menu and order the necessary ingredients.

[0817] Specific examples

[0818] Example 1: User weight data entry

[0819] The user weighs themselves in the morning and enters "70 kg" into the dedicated application. The device then sends this data to the server.

[0820] Example 2: Calorie counting and meal suggestions

[0821] The server receives the user's weight data (70 kg) and calculates the appropriate calorie intake using Python's NumPy library. For example, if the calculation result is 2000 kcal, the server uses GPT-4 to generate a meal plan based on 2000 kcal.

[0822] Example 3: Ordering ingredients

[0823] The server creates a list of ingredients needed for the generated menu and sends an order to a partner food delivery service. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via a REST API.

[0824] Prompt Sentence Examples

[0825] "If the user's weight data is 70 kg, calculate the appropriate calorie intake and suggest a meal plan based on that calorie intake. The plan should include breakfast, lunch, and dinner menus."

[0826] In this way, a system is created that calculates calories and suggests meals based on the user's weight data, and delivers the necessary ingredients.

[0827] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0828] Step 1:

[0829] The user weighs themselves every morning and enters their weight into a dedicated application. For example, the user enters "70 kg." This input data is saved on the device. The input data is the user's weight information and serves as the basis for subsequent processing.

[0830] Step 2:

[0831] The terminal sends the weight data entered by the user to the server. This transmission uses the HTTPS protocol. For example, the terminal encrypts the data "70kg" and sends it to the server. The input is the user's weight data, and the output is the encrypted data sent to the server.

[0832] Step 3:

[0833] The server calculates the appropriate calorie intake for the user based on the received weight data. This calculation uses Python's NumPy library. For example, the server receives data of "70 kg" and calculates the appropriate calorie intake as "2000 kcal." The input is weight data, and the output is calorie intake.

[0834] Step 4:

[0835] The server generates a menu appropriate for the user based on the calculated calorie intake. This menu generation uses the generative AI model GPT-4. For example, the server suggests breakfast, lunch, and dinner menus based on "2000 kcal." The input is the calorie intake, and the output is a menu.

[0836] Step 5:

[0837] The server creates a list of ingredients required for the generated menu. For example, if breakfast includes "oatmeal," lunch includes "chicken breast and broccoli," and dinner includes "brown rice and stir-fried vegetables," the server lists each ingredient and its quantity. The input is the menu, and the output is the ingredient list.

[0838] Step 6:

[0839] The server places an order for the created ingredient list with a partner food delivery service. This order processing uses a REST API. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via the API. The input is the ingredient list, and the output is the order data sent to the food delivery service.

[0840] Step 7:

[0841] The device displays the calorie calculation results and menu suggestions received from the server to the user. The user can check the suggested menu through the device and order the necessary ingredients. For example, the user opens the application and checks the menu displayed as "Today's Menu." The input is data from the server, and the output is the information displayed to the user.

[0842] (Application example 1)

[0843] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0844] Health management is an important issue in modern society, but for many people, individually managing their weight, selecting appropriate meals, and planning exercise is a heavy burden. Furthermore, there is a lack of systems that consistently calculate calories, suggest menus, and even procure the ingredients, making it difficult to maintain health management. To solve these issues, a system is needed that calculates appropriate calories based on the user's weight data, suggests menus based on the calculation results, and automatically orders the necessary ingredients.

[0845] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0846] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for calculating appropriate calories based on the user's weight data and proposing menus based on the calculation results, and a means for automatically ordering the necessary ingredients based on the proposed menu, thereby enabling users to consistently manage their daily weight, select appropriate meals, and procure ingredients.

[0847] A "weight management tool" is a device or software that collects and records a user's daily weight data.

[0848] "Means to support diet, exercise, etc." refers to devices and software that provide users with diet and exercise plans necessary to achieve their ideal weight and body shape and assist them in carrying them out.

[0849] A "calorie calculation means" is a device or software that calculates a person's appropriate daily calorie intake based on the user's weight data.

[0850] "Means that enable the process from planning a menu to delivering the ingredients" refers to devices or software that create a list of ingredients based on a proposed menu and deliver them to the user.

[0851] "Means for calculating appropriate calorie intake based on user's weight data" refers to a device or software that calculates the appropriate calorie intake for a person based on weight data entered by the user.

[0852] The "means for suggesting a menu based on the calculation results" refers to a device or software that suggests a meal menu suitable for the user based on the calculated calorie intake.

[0853] "Means for automatically ordering ingredients based on a proposed menu" refers to a device or software that automatically lists ingredients needed for a proposed menu and allows ordering online.

[0854] As an embodiment of the present invention, the following system can be constructed.

[0855] System Overview

[0856] This system collects the user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system has the function of inputting the user's weight data, calculating the appropriate calorie intake based on that data, proposing menus based on the calculation results, and automatically ordering the ingredients needed for those menus.

[0857] Hardware and software used

[0858] Hardware:

[0859] Smartphone: Used by users to input weight data and check menu suggestions and order status.

[0860] Server: Stores user weight data, calculates calories, suggests meals, and processes food orders.

[0861] software:

[0862] Python: A programming language used to implement server-side programs.

[0863] Requests library: The Python library used to send HTTP requests.

[0864] Database: Used to store user weight data and meal plan information.

[0865] Data processing and calculation

[0866] Server Action:

[0867] 1. Entering weight data: When a user enters weight data using a smartphone, the data is sent to the server and stored in a database.

[0868] 2. Calorie Calculation: The server calculates the appropriate daily calorie intake for the user based on the stored weight data. For example, based on the latest weight data, it calculates that 2000 calories is appropriate.

[0869] 3. Meal Suggestion: Based on the calculated calorie intake, the server will suggest suitable meal plans for the user, such as salad, grilled chicken, and fruit.

[0870] 4. Ingredients ordering: Based on the proposed menu, the server will list the necessary ingredients and place the order online. Once the order is successful, the user will be notified.

[0871] Specific examples

[0872] When a user inputs their weight of 70 kg, the server saves that data and calculates the appropriate calorie intake. For example, if it calculates that 2,000 calories is appropriate, it will suggest a menu of salad, grilled chicken, fruit, etc., and automatically order the necessary ingredients. If the order is successful, a notification will be sent to the user's smartphone and the ingredients will be delivered.

[0873] Prompt Sentence Examples

[0874] The following prompts can be used for the generative AI model:

[0875] Create an application that inputs a user's weight data, calculates the appropriate calorie intake based on that data, suggests a meal plan based on the calculation results, and delivers the ingredients needed for that meal. Specifically, this application has the functionality to store a user's weight, calculate the appropriate calorie intake, suggest a meal plan, and order the ingredients.

[0876] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0877] Step 1:

[0878] Entering weight data

[0879] The user inputs weight data using a smartphone. The input weight data is sent from the smartphone to a server. The server stores the received weight data in a database.

[0880] Input: User weight data

[0881] Output: Weight data stored in the database

[0882] Step 2:

[0883] Calorie Counting

[0884] The server retrieves the latest weight data stored in the database and calculates the appropriate daily calorie intake for the user based on the retrieved weight data. For example, if the latest weight data is 70 kg, it calculates that 2000 calories is appropriate.

[0885] Input: Weight data retrieved from the database

[0886] Output: Calculated calorie intake

[0887] Step 3:

[0888] Menu suggestions

[0889] The server then proposes meal plans suitable for the user based on the calculated calorie intake. For example, based on a 2000 calorie intake, it may suggest salad, grilled chicken, and fruit. The proposed plan is then sent to the user's smartphone.

[0890] Input: Calculated calorie intake

[0891] Output: Suggested menu

[0892] Step 4:

[0893] Ordering ingredients

[0894] The server lists the ingredients needed based on the proposed menu, and the ingredients are ordered online. Once the order is successfully placed, a notification is sent to the user's smartphone.

[0895] Input: Suggested menu

[0896] Output: Ordered ingredients and notification

[0897] Step 5:

[0898] Receive notifications

[0899] The user will be notified on their smartphone that the order has been placed successfully, and will then wait for the food to be delivered.

[0900] Input: Order successful notification

[0901] Output: User notification

[0902] By following the above steps, users can consistently manage their daily weight, select appropriate meals, and procure ingredients.

[0903] Example 2

[0904] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0905] Conventional health management systems require users to make appropriate decisions on their own, making it difficult to flexibly suggest optimal diets and exercises when weight gain occurs. Furthermore, the lack of specific suggestions based on weight data management and fluctuations makes it difficult for users to effectively manage their health.

[0906] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for inputting weight data, a means for transmitting and saving the input weight data, a means for detecting weight fluctuations, a means for sending prompts to the generative AI model to suggest optimal menus and exercises, and a means for transmitting and displaying the suggested contents. This allows the user to automatically receive optimal menus and exercises according to their weight gain or loss, thereby achieving effective health management.

[0907] The "weight management means" is a function for recording and saving the user's daily weight data.

[0908] "Means to support diet, exercise, etc." is a function that provides the user with the diet and exercise plans necessary to achieve their ideal weight and body shape.

[0909] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[0910] "Means that enable the process from planning a menu to delivering the ingredients" refers to a function that allows the necessary ingredients to be ordered and delivered based on the proposed menu.

[0911] The "means for inputting weight data" is an interface that allows a user to input their weight into the system.

[0912] The "means for transmitting and saving input weight data" is a function for transmitting weight data input by the user to a server and saving it in a database.

[0913] The "means for detecting weight fluctuations" is a function that compares past weight data with current weight data to determine whether weight has increased or decreased.

[0914] "Means for sending prompt text to the generative AI model to suggest optimal menus and exercises" refers to a function that sends prompt text to the generative AI model and generates optimal menus and exercises according to the user's weight fluctuations.

[0915] The "means for transmitting and displaying the proposed content" is a function for transmitting the generated menu and exercise proposal content to the user's terminal and displaying it.

[0916] The present invention is a system for supporting a user's weight management, and is implemented using a server, a terminal, and a generative AI model. A specific embodiment of this system will be described below.

[0917] Hardware and software used

[0918] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[0919] Software: generative AI models (e.g., GPT-4), database management systems (e.g., MySQL), health management applications

[0920] Program processing

[0921] 1. Entering user weight data

[0922] The user uses the terminal to input weight data into the health management application.

[0923] Example: A user enters "Weight: 70kg" into a smartphone app.

[0924] 2. Data transmission and storage

[0925] The terminal transmits the input weight data to the server.

[0926] The server stores the received data in a database.

[0927] Example: The device sends the data "Weight: 70kg" to the server, which then stores the data in a MySQL database.

[0928] 3. Detect weight fluctuations

[0929] The server compares the data with past weight data in the database to detect weight gain or loss.

[0930] Example: The server retrieves the previous weight data (e.g., 68 kg) from the database and compares it with the current weight data (70 kg) to detect an increase of 2 kg.

[0931] 4. Menu and exercise suggestions using generative AI models

[0932] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[0933] Example prompt: "The user has gained 2 kg. Please suggest low-calorie meals and moderate exercise."

[0934] 5. Submitting and Displaying Proposals

[0935] Based on the prompt, the generative AI model suggests low-calorie meals and moderate exercise.

[0936] The server transmits the generated proposal to the user's terminal.

[0937] The terminal displays the received proposal content in the health management application.

[0938] Example: A generative AI model generates a suggestion such as, "For a low-calorie meal, we suggest a salad and grilled chicken breast. For exercise, we recommend 30 minutes of walking." The server then sends the suggestion to the user's device, which then displays it in the app.

[0939] In this way, the system supports users in implementing appropriate dietary and exercise programs even if they gain weight. This system provides a means for achieving effective health management without the need for users to take appropriate measures on their own.

[0940] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0941] Step 1:

[0942] Entering user weight data

[0943] The user opens the health management application and enters the latest weight data.

[0944] Input: A user enters "Weight: 70kg" into an app on their smartphone.

[0945] Output: The entered weight data is temporarily saved in the application.

[0946] Specific behavior: The user enters "70kg" into the app's input field and presses the submit button.

[0947] Step 2:

[0948] Data transmission and storage

[0949] The terminal transmits the input weight data to the server.

[0950] The server stores the received data in a database.

[0951] Input: Data "Weight: 70kg" sent from the device.

[0952] Output: The data "Weight: 70kg" is saved in the server database.

[0953] Specific operation: The device sends the data "Weight: 70kg" to the server, and the server stores the data in a MySQL database.

[0954] Step 3:

[0955] Detect weight fluctuations

[0956] The server compares the data with past weight data in the database to detect weight gain or loss.

[0957] Input: Past weight data (e.g. 68kg) and current weight data (70kg) retrieved from the database.

[0958] Output: Result: weight increased by 2 kg.

[0959] Specific operation: The server retrieves the previous weight data (68 kg) from the database and detects a 2 kg increase compared to the current weight data (70 kg).

[0960] Step 4:

[0961] Menu and exercise suggestions using generative AI models

[0962] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[0963] Input: Prompt: "User has gained 2kg. Please suggest low-calorie meals and moderate exercise."

[0964] Output: Recommendations from the generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[0965] How it works: The server sends a prompt to a generative AI model (e.g., GPT-4), which then generates suggestions based on it.

[0966] Step 5:

[0967] Submitting and viewing suggestions

[0968] The server transmits the generated proposal to the user's terminal.

[0969] The terminal displays the received proposal content in the health management application.

[0970] Input: Recommendations from a generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[0971] Output: The suggestion displayed on the user's device.

[0972] Specific operation: The server sends the generated suggestions to the user's device, and the device displays the suggestions in the app.

[0973] (Application example 2)

[0974] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0975] In modern society, daily weight management, proper diet, and exercise are important for maintaining an ideal weight and body shape. However, many people find it difficult to do these things on their own, and as a result, they often neglect their health management. Also, if weight gain occurs, they are unable to take appropriate measures quickly, which increases health risks. Furthermore, for people who find cooking a hassle, it is difficult to maintain a healthy diet. A system that can solve these problems is needed.

[0976] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting the diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for proposing low-calorie menus based on weight data, a means for proposing moderate exercise plans, a means for displaying information on stores offering ingredients based on the proposed menus and fitness programs based on the exercise plans, and a means for periodically notifying users of reminders to measure weight and exercise. This allows users to manage their health with the support of the system, without having to take appropriate measures on their own.

[0977] "Weight management means" is a function that records the user's daily weight data and saves it as history.

[0978] "Means to support diet, exercise, etc." refers to a function that provides users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[0979] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[0980] "Means that enable the process from planning a menu to delivering the ingredients" refers to the function of ordering and delivering the necessary ingredients based on the proposed menu.

[0981] "Means for suggesting low-calorie menus" is a function that suggests low-calorie meal menus based on the user's weight data.

[0982] The "means for proposing an exercise plan" is a function that suggests an appropriate exercise plan based on the user's weight data.

[0983] The "means for displaying store information" is a function that displays information about stores that offer related ingredients and fitness programs based on the proposed menu or exercise plan.

[0984] "Means for notifying reminders" refers to a function that periodically notifies users of reminders to measure their weight or exercise.

[0985] The system for implementing the present invention provides an application that integrates multiple functions to support a user's weight management. A specific embodiment of this system will be described below.

[0986] System configuration

[0987] The system consists of an application installed on the user's smartphone and a cloud server. The smartphone application provides the user interface and communicates with the server to send and receive data.

[0988] Hardware and software used

[0989] Smartphone: A device that allows users to input their daily weight and view suggested meal plans and exercise plans.

[0990] Cloud server: Stores user weight data and processes the data to calculate calories, propose menus, and suggest exercise plans.

[0991] Database: A database for storing the user's weight history, suggested meal plans, and exercise plans.

[0992] Generative AI model: An AI model that generates optimal meal plans and exercise plans based on the user's weight data.

[0993] Data processing and calculation

[0994] 1. Weight data input and management: Users input their daily weight through a smartphone application, and this data is sent to a cloud server and stored in a database.

[0995] 2. Calorie calculation: The server calculates the required calorie intake based on the user's weight data and activity level.

[0996] 3. Meal Suggestion: Using a generative AI model, low-calorie meal suggestions are made based on the user's weight data. These suggestions are displayed in the smartphone application.

[0997] 4. Exercise plan suggestions: Similarly, generative AI models are used to suggest appropriate exercise plans, which are also displayed in the smartphone application.

[0998] 5. Display of store information: Based on the proposed menu or exercise plan, information on stores that offer related ingredients and fitness programs will be displayed.

[0999] 6. Reminder notification: The server periodically sends reminders to the user's smartphone to measure weight or exercise.

[1000] Specific examples

[1001] For example, if a user enters their weight as 70 kg, the system will display "Your weight has been recorded as 70 kg." The system will then suggest "Today's recommended menu: Salad" and "Today's recommended exercise: Walking." It will then display information about nearby stores that offer ingredients based on the suggested menu and fitness programs based on the exercise plan. Finally, it will provide periodic reminders to measure weight and exercise.

[1002] Prompt Sentence Examples

[1003] Create a Python program that records the user's weight when they input it, and suggests low-calorie meals and a moderate exercise plan. Also add a function to display the weight history.

[1004] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1005] Step 1:

[1006] The user starts the smartphone application and inputs their daily weight. The input weight data is sent from the smartphone device to the cloud server. The server receives this data and stores it in a database. The input data is the user's weight (e.g., 70 kg), and the output is the weight data stored in the database.

[1007] Step 2:

[1008] The server calculates the user's calorie intake needs based on the stored weight data. The calculation uses data such as the user's weight, age, gender, and activity level. The input data is the user's weight data and other personal information, and the output is the calculated calorie intake.

[1009] Step 3:

[1010] The server uses a generative AI model to suggest low-calorie meals based on the user's weight data. The AI ​​model generates optimal meals based on past data and nutritional information. The input data is the user's weight data and calorie intake, and the output is a suggested meal (e.g., salad).

[1011] Step 4:

[1012] The server uses a generative AI model to suggest a suitable exercise plan based on the user's weight data. The AI ​​model generates an optimal exercise plan taking into account the user's weight and activity level. The input data is the user's weight data and activity level, and the output is a suggested exercise plan (e.g., walking).

[1013] Step 5:

[1014] The server displays information about restaurants that offer related ingredients and fitness programs based on the proposed menu and exercise plan. The restaurant information is selected based on the user's location information and the content of the proposal. The input data is the proposed menu and exercise plan, and the output is related restaurant information.

[1015] Step 6:

[1016] The server periodically sends reminders to the user's smartphone to measure weight and exercise. The reminders are scheduled based on the user's settings. The input data are the user's settings and weight data, and the output is the reminder notification sent to the smartphone.

[1017] Example 3

[1018] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1019] In modern society, it is difficult to maintain a healthy diet in a busy daily life. This is especially true for those who do not like to cook or who do not have time. Another issue is the lack of support for weight management and achieving an ideal body shape. Another problem is the amount of effort required for health management, such as individual calorie calculations and food delivery.

[1020] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary for achieving an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring user location information, a means for searching for nearby healthy restaurants based on the acquired location information, and a means for providing the search results to the user. This enables the user to eat healthy meals without having to cook for themselves, and also provides support for weight management and achieving an ideal body shape.

[1021] "Weight management means" is a function for recording the user's daily weight and tracking fluctuations.

[1022] "Means to support diet, exercise, etc." is a function that provides the user with the meal plans and exercise programs necessary to achieve their ideal weight and body shape.

[1023] The "calorie calculation means" is a function that calculates the required calorie intake based on information such as the user's weight, height, age, and gender.

[1024] The "means for enabling delivery of ingredients from a menu" is a function that lists the ingredients required based on the menu selected by the user and delivers the ingredients to a location specified by the user.

[1025] "Means for obtaining location information" refers to a function that obtains the user's current location using GPS or other location information technology.

[1026] The "means for searching for nearby healthy restaurants" is a function that searches a database for healthy restaurants within a certain range from the user's current location based on the acquired location information.

[1027] The "means for providing search results to the user" is a function for transmitting information about the searched healthy restaurants to the user's terminal and displaying it.

[1028] This invention is a system that helps users maintain a healthy lifestyle by managing their weight on a daily basis, providing support for achieving an ideal weight and body shape, calculating calories, planning menus and delivering ingredients, and recommending nearby healthy restaurants.

[1029] Hardware and software used

[1030] Hardware: Smartphones (e.g. iPhone, Android devices), GPS devices

[1031] Software: GPS function, dedicated application, server (e.g. AWS, Google Cloud)

[1032] Program processing

[1033] Subject: Server

[1034] The server receives the user's location information. The location information is obtained from the user's smartphone or GPS device. The server then references a database to search for healthy restaurants closest to the user's current location. This database includes information such as restaurant locations, menus, and ratings. Based on the search results, the server creates a list of healthy restaurants that are best suited to the user and sends it to the user's device.

[1035] Subject: Terminal

[1036] The device acquires the user's location information and sends it to the server. The location information is acquired using the smartphone's GPS function. After receiving the list of recommended healthy restaurants from the server, the device displays the list to the user. The user can select a restaurant of interest from the displayed list and check detailed information.

[1037] Subject: User

[1038] The user launches the app on their smartphone and allows location sharing. The app then requests nearby healthy restaurants based on the user's current location from the server. After receiving the recommendation list from the server, the user reviews the list and selects a restaurant that interests them. They then review the details of the selected restaurant and decide whether to visit.

[1039] Specific examples

[1040] When a user launches the smartphone app and allows location sharing, the device uses its GPS function to obtain its current location. The obtained location information is sent to a server, which then references a database to search for nearby healthy restaurants. For example, if the user is in Shibuya Ward, Tokyo, the server will create a list of healthy restaurants in Shibuya Ward and send it to the user's device. The user can then select a restaurant, such as "Shibuya Healthy Cafe" or "Natural Restaurant Shibuya," from the received list and check detailed information.

[1041] Example prompts to input to the generative AI model

[1042] "Please explain the system that recommends nearby healthy restaurants based on the user's current location. Please clearly state what kind of data processing and calculations are performed, including the names of specific hardware and software." The flow of the identification process in Example 3 will be explained using Figure 15.

[1043] Step 1:

[1044] The user launches the app and allows location sharing. The user launches the app on their smartphone and a pop-up appears requesting location sharing. When the user selects "Allow," the app starts acquiring location information. The input is the user's permission, and the output is the start of location information acquisition.

[1045] Step 2:

[1046] The device uses the GPS function to obtain the user's current location. The device uses the smartphone's GPS function to obtain the user's current location. Specifically, the device receives signals from GPS satellites and calculates latitude and longitude information. The input is the GPS signal, and the output is latitude and longitude information.

[1047] Step 3:

[1048] The device sends the acquired location information to the server. The device sends the acquired latitude and longitude information to the server. The HTTPS protocol is used for transmission to ensure data security. The input is latitude and longitude information, and the output is transmission to the server.

[1049] Step 4:

[1050] The server searches a database based on the received location information to list nearby healthy restaurants. The server searches the database based on the received location information. The database contains restaurant location information, menus, ratings, etc. The server lists healthy restaurants within a certain range from the user's current location. The input is location information, and the output is a list of restaurants.

[1051] Step 5:

[1052] The server sends the information about the listed restaurants to the terminal. The server sends the information about the listed restaurants to the terminal. The data sent is in JSON format and includes the restaurant's name, address, rating, part of the menu, etc. The input is a list of restaurants, and the output is what is sent to the terminal.

[1053] Step 6:

[1054] The device displays the received list of restaurants to the user. The device displays the received list of restaurants to the user. The app interface displays a list of restaurant names, ratings, distances, etc. The input is a list of restaurants, and the output is what is displayed to the user.

[1055] Step 7:

[1056] The user selects a restaurant of interest from the list and checks the details. The user selects a restaurant of interest from the list. Once selected, the app displays detailed information about the restaurant. The detailed information includes menu photos, opening hours, contact information, etc. The input is the user's selection and the output is the display of detailed information.

[1057] (Application example 3)

[1058] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1059] In modern society, people who lead busy lives find it difficult to plan and execute appropriate diets and exercises to maintain their health. Furthermore, for those who don't like cooking, the options for healthy meals are limited. Furthermore, the process of finding nearby healthy restaurants, ordering, and having food delivered can be cumbersome. There is a need for a system that can solve these problems and allow users to easily live a healthy lifestyle.

[1060] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1061] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring the user's location information and listing nearby healthy restaurants, a means for ordering food from the listed restaurants and using delivery services, and a means for suggesting optimal menus based on the user's health status and goals. This allows the user to easily eat healthy meals without having to cook for themselves.

[1062] "Weight management tools" are features that allow users to record their daily weight and track fluctuations.

[1063] "Means to support diet, exercise, etc." refers to a function that provides meal plans and exercise plans necessary for users to achieve their ideal weight and body shape.

[1064] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's physical information and activity level.

[1065] "A means to enable the delivery of ingredients from a menu" is a function that lists the necessary ingredients based on the menu selected by the user and provides a service to deliver them.

[1066] "Means for obtaining location information" refers to a function that obtains the user's current location using technology such as GPS.

[1067] The "means of listing nearby healthy restaurants" is a function that searches for nearby restaurants that offer healthy menus based on the user's location information and displays them as a list.

[1068] "Means for ordering food and using delivery services" refers to the ability to select food from listed restaurants, order online, and use delivery services.

[1069] "Means to suggest optimal menus based on health status and goals" refers to a function that suggests optimal meal menus based on the user's health status and goals such as dieting and muscle building.

[1070] A system for carrying out the present invention includes the following means for supporting a user's health management.

[1071] 1. Program Generation

[1072] The system manages the user's daily weight and supports diet and exercise to achieve an ideal weight and body shape. It also calculates the user's calorie intake and enables everything from meal planning to food delivery. It also obtains the user's location information, lists nearby healthy restaurants, enables food ordering, and makes delivery services available. It also suggests optimal menus based on the user's health status and goals.

[1073] 2. Program processing explanation

[1074] Hardware used:

[1075] Smartphone (iOS or Android)

[1076] Software used:

[1077] Python

[1078] Geopy library (location information acquisition)

[1079] Requests library (API requests)

[1080] Google Places API (getting restaurant information)

[1081] Data processing and calculation:

[1082] The server first uses the Geopy library to obtain the user's location. Then, it uses the Google Places API to search for nearby healthy restaurants based on the obtained latitude and longitude. The search results are displayed as a list to the user, allowing the user to order food from the restaurant of their choice and use delivery services. It also calculates calories based on the user's input data to suggest optimal menus based on the user's health status and goals.

[1083] 3. Examples and prompts

[1084] Examples:

[1085] If the user is in Shibuya Ward, Tokyo, the system will display a list of nearby healthy restaurants. If the user indicates that they are on a diet, the system will suggest low-calorie options.

[1086] Example prompt sentence:

[1087] Write a Python program that gets the user's location and lists nearby healthy restaurants. Use the Geopy library to get the location and the Google Places API to get the restaurant information. Based on the user's latitude and longitude, search for healthy restaurants within a 1500 meter radius and display their information.

[1088] In this way, users can easily eat healthy meals without having to cook for themselves.

[1089] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1090] Step 1:

[1091] The server obtains the user's location information. Specifically, it obtains the latitude and longitude of the current location using the device's GPS function. The input is a location request from the user's device, and the output is the obtained latitude and longitude data.

[1092] Step 2:

[1093] The server uses the Google Places API to search for nearby healthy restaurants based on the acquired latitude and longitude. The input is the latitude and longitude data acquired in step 1, and the output is a list of restaurants as search results. Specifically, the server sends an API request and analyzes the response.

[1094] Step 3:

[1095] The server displays the search results to the user as a list. The input is the restaurant list obtained in step 2, and the output is the restaurant list displayed on the user's device. Specifically, the server formats the list and displays it on the user interface.

[1096] Step 4:

[1097] The user selects a restaurant from the list and orders food. The input is the user's selection, and the output is information about the selected restaurant and food. The specific operation is to accept the selection through a user interface.

[1098] Step 5:

[1099] The server receives the user's order information and arranges for a delivery service. The input is the order information obtained in step 4, and the output is a request to the delivery service. Specifically, it calls the delivery service's API and sends the order information.

[1100] Step 6:

[1101] The server proposes the optimal menu based on the user's health condition and goals. The input is data about the user's health condition and goals, and the output is the proposed menu. Specifically, the server calculates calories based on the user's input data and selects an appropriate menu.

[1102] Step 7:

[1103] The server presents the proposed menu to the user. The input is the menu information obtained in step 6, and the output is the menu displayed on the user's device. Specifically, the server formats the menu and displays it in the user interface.

[1104] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1105] "Example 1"

[1106] One embodiment of the present invention includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, behavioral patterns, etc. For example, if the user feels stressed, the emotion engine feeds that information back to the system, which then suggests exercises and meals that promote relaxation.

[1107] "Example 2"

[1108] The emotion engine also adjusts diet and exercise support based on the user's emotions. For example, when a user feels joy, the emotion engine feeds that information back to the system, which then suggests diet and exercise to maintain that joy. This allows users to manage their health in line with their emotions.

[1109] "Example 3"

[1110] Furthermore, the emotion engine recommends nearby healthy restaurants based on the user's emotions. For example, if the user is feeling down, the emotion engine will feed that information back into the system, and the system will suggest restaurants that serve healthy meals to lift the user's spirits. This allows users to make food choices that match their emotions.

[1111] The processing flow of each embodiment will be described below.

[1112] "Example 1"

[1113] Step 1: Collect data from users' tone of voice, facial expressions, behavioral patterns, etc.

[1114] Step 2: Send the collected data to the emotion engine.

[1115] Step 3: The emotion engine analyzes the user's emotions from the collected data.

[1116] Step 4: The analysis results are fed back to the system, which then suggests exercises and meals to the user that promote relaxation.

[1117] "Example 2"

[1118] Step 1: Analyze user emotion data with the emotion engine.

[1119] Step 2: The analysis results are fed back to the system, which then adjusts diet and exercise support based on the user's emotions.

[1120] Step 3: The system suggests diet and exercise recommendations to the user to maintain that joy.

[1121] "Example 3"

[1122] Step 1: Analyze user emotion data with the emotion engine.

[1123] Step 2: The analysis results are fed back to the system, which then recommends nearby healthy restaurants based on the user's emotions.

[1124] Step 3: The system suggests restaurants that offer healthy meals to boost the user's mood.

[1125] Example 1

[1126] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1127] In modern society, maintaining an ideal weight and body shape requires daily weight management, proper diet, and exercise support. However, it is difficult for many people to consistently do these things, and stress and emotional fluctuations in particular can affect health management. In addition, procuring ingredients and planning menus can be time-consuming, making continuous health management difficult.

[1128] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for sensing the user's tone of voice, facial expressions, and behavioral patterns, a means for analyzing the sensed data and identifying the user's emotional state, and a means for suggesting exercises and meals that promote relaxation based on the user's emotional state. This enables the user to consistently manage their health and receive support that also addresses stress and emotional fluctuations.

[1129] "Means for managing daily weight" refers to devices and software that allow users to measure their weight daily and record and save that data.

[1130] "Means to support the diet, exercise, etc. necessary to achieve an individual's ideal weight and body shape" refers to systems and algorithms that provide appropriate diet and exercise plans based on the user's health goals.

[1131] "Means for calculating calories appropriate for each individual" refers to a calculation function that calculates the amount of calories needed per day based on the user's weight data and other health information.

[1132] "Means that enable the process from planning a menu to delivering the ingredients" refers to a system or service that identifies the necessary ingredients based on the menu proposed to the user and delivers them to the user.

[1133] "Means for detecting a user's tone of voice, facial expression, and behavioral patterns" refers to devices or software that use sensors such as cameras and microphones to detect a user's tone of voice, facial expression, and behavioral patterns in real time.

[1134] "Means for analyzing the sensed data and identifying the user's emotional state" refers to an algorithm or analytical engine for analyzing the sensed data and identifying the user's emotional state.

[1135] "Means for suggesting exercises and meals that promote relaxation based on the user's emotional state" refers to a system or algorithm that suggests exercises and meals aimed at stress reduction and relaxation based on the user's emotional state.

[1136] MODE FOR CARRYING OUT THE INVENTION

[1137] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the calories appropriate for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[1138] Hardware and software used

[1139] This system uses the following hardware and software:

[1140] Hardware: smartphone, computer, camera, microphone

[1141] Software: Dedicated applications, databases (MySQL and PostgreSQL), Python, NumPy, TensorFlow, OpenCV, Google Cloud Speech-to-Text API

[1142] Data processing and calculation

[1143] The server receives the weight data entered by the user and stores it in a database. The server then calculates the appropriate calorie intake for the user based on the stored data. This calculation is performed using Python's NumPy library. Based on the calculation results, the server then suggests a meal plan suitable for the user. This meal plan is proposed using a machine learning model (for example, using TensorFlow).

[1144] The server then identifies the ingredients needed for the proposed meal and sends an order to a partner food delivery service, so that the user can receive the ingredients at home.

[1145] Meanwhile, the device uses a camera and microphone to detect the user's tone of voice, facial expressions, and behavioral patterns. This data is sent to the emotion engine, which analyzes the data and identifies the user's emotional state. This analysis is performed using OpenCV and the Google Cloud Speech-to-Text API. If the emotion engine determines that the user is feeling stressed, the information is fed back to the server, which then uses the information to suggest exercises and meals that will promote relaxation for the user.

[1146] Specific examples

[1147] As a concrete example, consider the case where a user weighs themselves in the morning and enters that data into the system. When the user enters the weight data, the server receives and stores the data. The server then calculates the appropriate daily calorie intake based on the user's weight data. For example, if the user weighs 70 kg, the server calculates the daily calorie intake to be 2000 kcal. The server then proposes a meal plan based on 2000 kcal and orders the necessary ingredients from a food delivery service.

[1148] If the user is feeling stressed, the emotion engine analyzes the information and sends it back to the server, which then suggests relaxation exercises such as yoga or meditation.

[1149] Prompt Sentence Examples

[1150] Example prompts to input to a generative AI model:

[1151] Enter the user's weight data, then calculate the user's appropriate calorie intake and suggest meals based on the results. Also, if the user is feeling stressed, suggest exercises and meals that promote relaxation.

[1152] In this way, the system provides comprehensive support for the user's health management.

[1153] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1154] Step 1:

[1155] The user inputs weight data. The user measures their weight on a scale every morning and enters the weight data into a dedicated smartphone app. The input weight data is saved on the device.

[1156] Step 2:

[1157] The terminal sends the entered weight data to the server. The terminal encrypts the entered weight data using SSL / TLS and sends it to the server via the Internet. The input is weight data, and the output is encrypted data.

[1158] Step 3:

[1159] The server receives the weight data and stores it in a database. The server stores the received weight data in a database. A relational database such as MySQL or PostgreSQL is used for the database. The input is encrypted weight data, and the output is the data stored in the database.

[1160] Step 4:

[1161] The server calculates the calorie intake based on the stored weight data. The server uses Python's NumPy library to calculate the appropriate daily calorie intake based on the stored weight data. For example, it calculates 2000 kcal for a user weighing 70 kg. The input is weight data and the output is calorie intake.

[1162] Step 5:

[1163] The server uses TensorFlow to suggest a menu suitable for the user based on the calculation results. For example, it suggests oatmeal for breakfast, salad for lunch, and grilled chicken for dinner. The input is calorie intake, and the output is a menu suggestion.

[1164] Step 6:

[1165] The server identifies the ingredients needed for the proposed meal and sends an order to the food delivery service. The server identifies the ingredients needed for the proposed meal (oatmeal, lettuce, chicken breast, etc.) and sends an order to the partner food delivery service. The input is the meal and the output is the food order.

[1166] Step 7:

[1167] The device senses the user's tone of voice, facial expressions, and behavioral patterns. The device uses a built-in camera and microphone to sense the user's tone of voice, facial expressions, and behavioral patterns in real time. The input is the user's voice, facial expressions, and behavioral patterns, and the output is the sensed data.

[1168] Step 8:

[1169] The device sends the sensed data to the emotion engine. The device sends the sensed data to the emotion engine in real time. The data includes the user's tone of voice and changes in facial expression. The input is the sensed data, and the output is the data sent to the emotion engine.

[1170] Step 9:

[1171] The emotion engine analyzes the user's emotional state. The emotion engine uses OpenCV and the Google Cloud Speech-to-Text API to analyze the user's emotional state. For example, it determines if the user is feeling stressed. The input is the sensed data, and the output is the analysis result.

[1172] Step 10:

[1173] The emotion engine feeds back the analysis results to the server. The emotion engine feeds back the analysis results to the server. The fed back data indicates that the user is feeling stressed. The input is the analysis results, and the output is the data fed back to the server.

[1174] Step 11:

[1175] The server suggests exercises and meals that promote relaxation based on the user's emotional state. If the server learns that the user is feeling stressed, it suggests relaxation exercises such as yoga or meditation, or meals that are effective in reducing stress, such as chamomile tea. The input is the feedback data, and the output is suggestions that promote relaxation.

[1176] (Application example 1)

[1177] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1178] Conventional weight management systems can collect a user's weight data and calculate calories and suggest meals, but they lack support that takes into account the user's emotional state. Furthermore, they do not deliver the ingredients needed for the suggested meals or suggest relaxation activities based on the user's emotions, making it difficult for users to continuously manage their health.

[1179] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1180] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for planning a menu and delivering the ingredients, a means for analyzing the user's emotions, a means for suggesting exercise and meals that promote relaxation based on the results of the emotion analysis, and a means including an application to be installed on a smartphone. This provides comprehensive support for the user's weight management and emotional state, enabling continuous health management.

[1181] A "weight management tool" is a device or software that collects and records a user's daily weight data.

[1182] "Means to support diet, exercise, etc." refers to devices or software that provide users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[1183] A "calorie calculation means" is a device or software that calculates an appropriate calorie intake for an individual based on the user's weight data.

[1184] "Means that enable the planning and delivery of ingredients" refers to devices or software that automatically order the necessary ingredients based on the proposed menu and deliver them to the user's home.

[1185] "Means for analyzing emotions" refers to devices or software that analyze emotions from the user's tone of voice, facial expressions, behavioral patterns, etc.

[1186] The "means for suggesting exercises and meals that promote relaxation" refers to a device or software that suggests exercises and meals that promote relaxation to the user based on the results of emotion analysis.

[1187] "Applications installed on smartphones" refers to software installed on smartphones to provide users with functions such as weight management, emotion analysis, calorie calculation, meal suggestions, and food ordering.

[1188] The system for implementing this invention collects weight data and emotional data of the user and provides dietary and exercise support to achieve an ideal weight and body shape. It also includes a function to automatically order ingredients needed for the suggested menu and have them delivered to the user's home.

[1189] Hardware and Software Configuration

[1190] Hardware:

[1191] Smartphone (camera, microphone)

[1192] Server (for data processing)

[1193] software:

[1194] Python

[1195] EmotionEngine (emotion analysis library)

[1196] FoodDeliveryService (API for ordering ingredients)

[1197] Data processing and calculation

[1198] Weight data collection:

[1199] Users input their weight data through a smartphone application, which is then sent to a server and recorded as their daily weight data.

[1200] Emotional Data Analysis:

[1201] The user's tone of voice and facial expression data are collected using the smartphone's camera and microphone, and the collected data is analyzed using the Emotion Engine to identify the user's emotional state.

[1202] Calorie Count:

[1203] The server calculates the required calorie intake based on the user's weight data, and the calculation results serve as a benchmark for the user to aim for their ideal weight and body shape.

[1204] Menu suggestions:

[1205] The server then suggests appropriate meals based on the calculated calories, taking into account the user's health and emotional state.

[1206] Ingredients Order:

[1207] The necessary ingredients based on the proposed menu are automatically ordered through the FoodDeliveryService, and the ordered ingredients are delivered to the user's home.

[1208] Relaxation Suggestions:

[1209] Based on the results of the emotion analysis, the server will suggest exercises and meals that promote relaxation to the user, thereby reducing stress and supporting health management.

[1210] Specific examples

[1211] For example, if a user inputs their weight of 75 kg and provides voice and facial expression data, the server will suggest a 2,000 calorie meal and automatically order salad, chicken breast, and brown rice. If the server also analyzes that the user is feeling stressed, it will suggest yoga or herbal tea to promote relaxation.

[1212] Prompt Sentence Examples

[1213] An example of a prompt for the generative AI model is as follows:

[1214] Develop an application that calculates calories and suggests meals to help users achieve their ideal weight and shape based on their weight and emotional data. Also, include a function to automatically order ingredients for the suggested meals and have them delivered to the user's home.

[1215] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1216] Step 1:

[1217] The user inputs weight data through a smartphone application.

[1218] Input: User weight data

[1219] Output: Weight data sent to the server

[1220] Specific behavior: When a user enters their weight in the application's input form and presses the submit button, the data is sent to the server.

[1221] Step 2:

[1222] The server records daily weight data.

[1223] Input: Weight data submitted by the user

[1224] Output: Weight data stored in the database

[1225] Specific operation: The server stores the received weight data in a database and records daily weight fluctuations.

[1226] Step 3:

[1227] The user collects voice and facial expression data using the camera and microphone on their smartphone.

[1228] Input: User's voice and facial expression data

[1229] Output: Voice and facial expression data sent to the server

[1230] What it does: The user launches the application, which uses the camera and microphone to record their voice and facial expressions, and then sends that data to the server.

[1231] Step 4:

[1232] The server analyzes the emotional data using EmotionEngine.

[1233] Input: User's voice and facial expression data

[1234] Output: Parsed emotion data

[1235] Specific operation: The server inputs the received voice and facial expression data into the Emotion Engine, performs emotion analysis, and obtains the results.

[1236] Step 5:

[1237] The server calculates calories based on the user's weight data.

[1238] Input: User weight data

[1239] Output: Calculated calorie intake

[1240] Specific operation: The server applies a calorie calculation algorithm based on weight data to calculate the required calorie intake.

[1241] Step 6:

[1242] The server will suggest a menu based on the calculated calories.

[1243] Input: Calculated calorie intake

[1244] Output: Suggested menu

[1245] Specific operation: The server generates an appropriate menu based on the calorie intake and suggests it to the user.

[1246] Step 7:

[1247] The server automatically orders the necessary ingredients based on the proposed menu through the FoodDeliveryService.

[1248] Input: Suggested menu

[1249] Output: Ordered ingredients

[1250] What happens: The server sends the proposed menu to the FoodDeliveryService, which automatically orders the necessary ingredients.

[1251] Step 8:

[1252] The server suggests exercises and meals that promote relaxation based on the results of emotion analysis.

[1253] Input: Parsed emotion data

[1254] Output: Suggestions for exercise and meals to promote relaxation

[1255] Specific operation: Based on the results of emotion analysis, the server suggests exercises and meals that promote relaxation to the user.

[1256] Example 2

[1257] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1258] Conventional health management systems require users to make appropriate decisions on their own, and provide insufficient support for weight management and emotional support. Furthermore, they do not provide dietary or exercise recommendations that reflect the user's emotions, making it difficult to address individual needs. Furthermore, they do not provide prompt and appropriate measures in the event of weight gain, making it difficult for users to effectively manage their health.

[1259] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1260] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for collecting user emotion data, a means for adjusting meal and exercise suggestions based on the collected emotion data, a means for generating optimal menu and exercise plans using a generative AI model, and a means for notifying the user of the generated suggestions to their terminal. This eliminates the need for the user to take appropriate measures on their own, and enables effective health management with the support of the system.

[1261] "Means for managing daily weight" is a function that allows users to input their daily weight and record, save, and manage that data.

[1262] "Means to support the diet, exercise, etc. necessary to achieve an individual's ideal weight and body shape" is a function that provides appropriate diet and exercise plans to help users achieve their ideal weight and body shape.

[1263] The "means for calculating calories appropriate for each individual" is a function that calculates the optimal calorie intake for each individual based on information such as the user's weight, age, sex, and activity level.

[1264] The "means for enabling delivery of ingredients from a menu" is a function for listing the ingredients required based on a proposed menu and delivering those ingredients to the user.

[1265] "Means for collecting user emotional data" refers to a function for inputting or automatically detecting the user's emotional state, and collecting and saving that data.

[1266] The "means for adjusting diet and exercise suggestions based on collected emotion data" is a function for adjusting diet and exercise suggestions in consideration of the collected emotion data of the user.

[1267] "Means for generating optimal menus and exercise plans using a generative AI model" refers to a function that uses a generative AI model to analyze a user's weight data and emotional data and generate optimal menus and exercise plans.

[1268] "Means for notifying the user of the generated suggestions" is a function for notifying the user of the generated menu and exercise plan on a device such as a smartphone or tablet.

[1269] This invention is a system for managing a user's weight and supporting their health based on their emotions. The system uses a server, user devices (smartphones, tablets, PCs), a generative AI model, an emotion engine, and a database management system (DBMS).

[1270] Hardware and software used

[1271] Hardware: Servers, user devices (smartphones, tablets, PCs)

[1272] Software: Generative AI model, emotion engine, database management system (DBMS)

[1273] Specific operation of the system

[1274] 1. Data Collection

[1275] The user inputs their weight, and the device sends this data to the server.

[1276] The emotion engine collects user emotion data, for example, by allowing the user to select an emotion within the app, or by automatically detecting emotions using emotion recognition technology.

[1277] 2. Data transmission and storage

[1278] The device sends the entered weight data to the server, which then stores the received data in a database.

[1279] 3. Data analysis

[1280] The server retrieves weight data and emotion data from the database and analyzes them using a generative AI model.

[1281] 4. Proposal generation

[1282] The server uses the generative AI model to suggest low-calorie meals and moderate exercise to the user, and the emotion engine adjusts the suggestions based on the user's emotional data.

[1283] 5. Suggestion Notification and Feedback

[1284] The server sends the generated menu and exercise plan to the user's device, where the user receives and executes the suggestions.

[1285] Specific examples

[1286] Weight data entry: The user enters their weight into the smartphone app.

[1287] Emotion data collection: User selects "joy" within the app.

[1288] Data analysis: The server detects weight gain and uses a generative AI model to generate low-calorie meals.

[1289] Recommendation: The server suggests a "low-calorie salad and grilled chicken breast" and recommends "30 minutes of walking" as moderate exercise.

[1290] Emotion regulation: The emotion engine suggests exercising while listening to your favorite music to maintain your "joy."

[1291] Prompt Sentence Examples

[1292] "Please generate a program that suggests low-calorie meals and moderate exercise if the user has gained weight. Also, please add a function that adjusts the suggestions based on the user's emotional data."

[1293] This system allows users to manage their health with the support of the system, without the need to take appropriate measures on their own.

[1294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1295] Step 1:

[1296] A user opens a smartphone app and inputs their weight. The input weight data is temporarily stored on the device. The input data is in a format such as "Weight: 70kg". The device sends this data to the server. The output is the weight data sent to the server.

[1297] Step 2:

[1298] The server stores the weight data received from the terminal in a database. The input is the weight data sent from the terminal, and the output is the weight data stored in the database. Specifically, the server stores the data using a database management system (DBMS).

[1299] Step 3:

[1300] The user selects an emotion within the app, or emotion recognition technology is used to automatically detect the emotion. The emotion data is in the form of "happiness" or "sadness," etc. The device sends this emotion data to the server. The output is the emotion data sent to the server.

[1301] Step 4:

[1302] The server stores the emotion data received from the device in a database. The input is the emotion data sent from the device, and the output is the emotion data stored in the database. Specifically, the server stores the data using a database management system (DBMS).

[1303] Step 5:

[1304] The server retrieves weight data and emotion data from the database. The input is the weight data and emotion data stored in the database, and the output is the retrieved data. Specifically, the server retrieves the data using an SQL query.

[1305] Step 6:

[1306] The server uses the generative AI model to analyze the acquired weight data and emotional data. The input is the acquired weight data and emotional data, and the output is the analysis results. Specifically, the server inputs the data into the generative AI model and generates an optimal menu and exercise plan.

[1307] Step 7:

[1308] The server uses the generative AI model to suggest low-calorie meals and moderate exercise to the user. The emotion engine takes into account the user's emotional data and adjusts the suggestions. The input is the analysis results and emotional data, and the output is the adjusted suggestions. Specifically, the server works by linking the generative AI model and the emotion engine to generate the suggestions.

[1309] Step 8:

[1310] The server notifies the user's device of the menu and exercise plan it has generated. The input is the adjusted proposal, and the output is the notification sent to the user's device. Specifically, the server uses a notification API to send the proposal to the user's device.

[1311] Step 9:

[1312] The user receives the suggestions and executes them. The input is the suggestion notified to the terminal, and the output is the result of the user's execution. Specifically, the user creates a menu based on the suggested exercise plan and executes it.

[1313] (Application example 2)

[1314] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1315] In modern society, individual health management is an important issue. However, for many people, planning their own daily weight management, meals, and exercise is a burden, and it is particularly difficult to respond appropriately to emotional fluctuations. Furthermore, for people who find cooking a hassle, it is difficult to maintain a healthy diet. Furthermore, there is a lack of easy access to the suggested meals, which makes it difficult to continue health management.

[1316] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1317] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for recognizing the user's emotions and adjusting diet and exercise based on those emotions, a means for ordering suggested meals via a delivery service, and a means for suggesting appropriate exercise and tracking progress. This allows the user to receive suggestions for optimal diet and exercise based on their weight and emotions and easily carry out those suggestions.

[1318] A "weight management tool" is a tool for recording a user's daily weight and tracking fluctuations.

[1319] "Means to support diet, exercise, etc." refers to means that provide users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[1320] A "calorie calculation means" is a means for calculating calorie needs based on a user's weight and activity level.

[1321] "Means that enable the planning of a menu and the delivery of ingredients" refers to a means of ordering and delivering the necessary ingredients based on a proposed menu.

[1322] "Means for recognizing emotions" refers to a means for detecting the user's emotions and feeding that information back to the system.

[1323] The "means for adjusting diet and exercise" is a means for appropriately changing the diet and exercise content based on the user's emotions.

[1324] "Means of ordering through a delivery service" refers to means of ordering the suggested meal using a delivery service.

[1325] "Means for suggesting exercises and tracking progress" refers to means for suggesting appropriate exercises to users and tracking their progress.

[1326] The following system configuration is used as an embodiment of the present invention.

[1327] System Configuration

[1328] Hardware

[1329] Smartphone: A device that allows users to input their daily weight and recognize emotions.

[1330] Server: A central system for processing and storing data.

[1331] software

[1332] EmotionEngine: An emotion recognition library for recognizing user emotions.

[1333] FoodSuggestion: A library that suggests meals based on the user's weight and emotions.

[1334] DeliveryService: An API for ordering suggested meals through a delivery service.

[1335] ExerciseSuggestion: A library that suggests appropriate exercises to users and tracks their progress.

[1336] Data processing and calculation

[1337] Obtaining the user's weight and emotions

[1338] Users input their daily weight using their smartphone, and EmotionEngine recognizes the user's emotions through the smartphone's camera and microphone, sending the user's weight and emotion data to the server.

[1339] Diet and exercise suggestions

[1340] The server uses the FoodSuggestion library to suggest optimal meals based on the user's weight and emotions, and the ExerciseSuggestion library to suggest moderate exercise. These suggestions are displayed on the smartphone.

[1341] Delivery orders

[1342] If the user decides to order a suggested meal, the order is placed through the DeliveryService API on their smartphone, which then delivers the suggested meal to the user.

[1343] Specific examples

[1344] User weight and emotions

[1345] User weight: 70kg

[1346] User Emotion: Delight

[1347] Prompt Sentence Examples

[1348] The user weighs 70 kg and feels happy. Suggest low-calorie meals, encourage moderate exercise, and allow the user to order the suggested meals via a delivery service.

[1349] In this way, a system can be realized that suggests optimal diet and exercise based on the user's weight and emotions, and provides them through a delivery service, allowing users to easily manage their health according to their weight and emotions.

[1350] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1351] Step 1:

[1352] The user inputs their daily weight using a smartphone, and the input weight data is sent from the smartphone to the server.

[1353] Input: User's weight

[1354] Output: Weight data sent to the server

[1355] Step 2:

[1356] The user recognizes emotions using the smartphone's camera and microphone, and the EmotionEngine analyzes the emotions and sends the results to the server.

[1357] Input: User's facial image or voice data

[1358] Output: Emotion data sent to the server

[1359] Step 3:

[1360] The server uses the FoodSuggestion library to suggest optimal meals based on the received weight and emotion data, and the suggested meal data is sent to the smartphone.

[1361] Input: Weight data, Emotion data

[1362] Output: Meal suggestion data sent to smartphone

[1363] Step 4:

[1364] The server uses the ExerciseSuggestion library to suggest appropriate exercises based on the received weight data, and the suggested exercise data is sent to the smartphone.

[1365] Input: Weight data

[1366] Output: Exercise suggestion data sent to smartphone

[1367] Step 5:

[1368] The user checks the suggested meals on their smartphone and places an order through the delivery service, which then sends the order data via the DeliveryService API.

[1369] Input: Meal suggestion data, user ordering instructions

[1370] Output: Order data sent to the delivery service

[1371] Step 6:

[1372] The delivery service receives the order and delivers the suggested meal to the user.

[1373] Input: Order data

[1374] Output: Meal delivered to user

[1375] Step 7:

[1376] The user performs the suggested exercise and enters their progress into their smartphone, which then sends the progress data to the server.

[1377] Input: User's exercise progress data

[1378] Output: Exercise progress data sent to the server

[1379] Step 8:

[1380] The server updates the user's exercise history based on the received exercise progress data and reflects it in the next exercise suggestion.

[1381] Input: Exercise progress data

[1382] Output: Updated exercise history data

[1383] Example 3

[1384] Next, a description will be given of Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1385] In modern society, maintaining a healthy diet in a busy daily life is difficult. Choosing the right meal is even more difficult for people who find cooking a hassle or whose food choices are affected by emotional fluctuations. Conventional systems do not suggest meals that take into account the user's location information or emotional state, and therefore do not provide sufficient support for maintaining the user's health.

[1386] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1387] In this invention, the server includes means for acquiring user location information, means for searching for nearby healthy restaurants, means for analyzing the user's emotional state, means for recommending restaurants based on the emotional state, and means for notifying the user of information about the recommended restaurants, thereby enabling the user to easily find the optimal healthy restaurant based on their location information and emotional state.

[1388] A "weight management tool" is a device or software that records a user's daily weight and tracks fluctuations.

[1389] A "diet and exercise support tool" is a device or software that provides a user with the diet and exercise plan they need to achieve their ideal weight and shape.

[1390] The "calorie calculation means" is a device or software that calculates the required calorie intake based on the user's physical information and activity level.

[1391] "Means that enable the delivery of ingredients from a menu" refers to a device or software that provides a service that lists the ingredients needed based on the menu selected by the user and delivers those ingredients to the user.

[1392] "Means for obtaining user location information" refers to devices or software that use GPS or other location information technology to identify the user's current location.

[1393] The "means for searching for nearby healthy restaurants" is a device or software that searches for nearby restaurants that offer healthy meals based on the user's location information.

[1394] "Means for analyzing the user's emotional state" refers to a device or software that analyzes the user's input and behavioral data to determine the user's current emotional state.

[1395] The "means for recommending restaurants based on emotional state" is a device or software that selects and recommends optimal healthy restaurants in consideration of the user's emotional state.

[1396] The "means for notifying the user of information about the recommended store" is a device or software that notifies the user's terminal of information about the selected store.

[1397] This invention is a system that allows users to easily select healthy meals. The system recommends optimal healthy restaurants taking into account the user's location information and emotional state. Specific embodiments of this system are described below.

[1398] Hardware and software used

[1399] Hardware: Smartphone, GPS module, server

[1400] Software: Mobile applications, location APIs (e.g., Google Maps API), sentiment analysis engines, database management systems (DBMS)

[1401] Program processing procedure

[1402] 1. Obtaining user location information

[1403] The user launches a mobile application on their smartphone.

[1404] The device (smartphone) uses the built-in GPS module to obtain the user's current location.

[1405] The terminal transmits the acquired location information to the server.

[1406] 2. Find healthy restaurants near you

[1407] The server uses a location API to collect information about healthy restaurants and cafes near the user's current location.

[1408] The server stores the collected information in a database.

[1409] 3. Emotion analysis

[1410] The user inputs their emotional state within the application, or an emotion analysis engine analyzes the user's text or voice input to determine the emotion.

[1411] The terminal transmits the determined emotion information to the server.

[1412] 4. Store Recommendations

[1413] The server receives feedback from the sentiment analysis engine and selects the best healthy restaurants based on the user's emotional state.

[1414] The server sends information about the selected store to the user's smartphone.

[1415] 5. Notice to Users

[1416] The terminal notifies the user of information about the recommended store.

[1417] The user can select a store to visit based on the displayed information.

[1418] Specific examples

[1419] For example, if a user types "I'm tired today" into the application, the sentiment analysis engine will determine the emotion as "fatigue." Based on this information, the server will recommend healthy cafes with a relaxing atmosphere.

[1420] Prompt Sentence Examples

[1421] "If a user feels tired, describe a system that recommends healthy cafes with a relaxing atmosphere."

[1422] This system allows the user to select the most suitable meal to suit his / her emotional state. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1423] Step 1:

[1424] Obtaining user location information

[1425] The user launches a mobile application on their smartphone.

[1426] The device (smartphone) uses the built-in GPS module to obtain the user's current location.

[1427] Input: User application launch operation

[1428] Output: User's current location (latitude and longitude)

[1429] What it does: When a user opens the app, the message "Getting your current location" is displayed. Once the GPS has determined the location, the message "Location acquired" is displayed.

[1430] The terminal transmits the acquired location information to the server.

[1431] Step 2:

[1432] Find healthy restaurants near you

[1433] The server uses a location API to collect information about healthy restaurants and cafes near the user's current location.

[1434] Input: User's current location

[1435] Output: A list of nearby healthy restaurants

[1436] What it does: Once the server receives your location, it displays the message "Searching for nearby healthy restaurants." After a few seconds, it displays the message "Search completed."

[1437] The server stores the collected information in a database.

[1438] Step 3:

[1439] Emotion analysis

[1440] The user inputs their emotional state within the application, or an emotion analysis engine analyzes the user's text or voice input to determine the emotion.

[1441] Input: User emotional state input (text or voice)

[1442] Output: Determined emotion information

[1443] Specific behavior: When a user enters "I'm tired today," the emotion analysis engine determines it as "fatigue," and the message "Emotion information analyzed" is displayed.

[1444] The terminal transmits the determined emotion information to the server.

[1445] Step 4:

[1446] Store recommendation

[1447] The server receives feedback from the sentiment analysis engine and selects the best healthy restaurants based on the user's emotional state.

[1448] Input: Determined emotion information, list of nearby healthy restaurants

[1449] Output: Recommended store information

[1450] Specific behavior: When the server receives the emotion information, it displays the message "Selecting restaurants based on your emotions." After a few seconds, it displays the message "Recommended restaurants found."

[1451] The server sends information about the selected store to the user's smartphone.

[1452] Step 5:

[1453] User Notification

[1454] The terminal notifies the user of information about the recommended store.

[1455] Input: Recommended store information

[1456] Output: A message to inform the user

[1457] Specific operation: A notification will appear on the user's smartphone saying, "Here are some recommended shops," along with detailed information.

[1458] The user can select a store to visit based on the displayed information.

[1459] (Application example 3)

[1460] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1461] In modern society, many people find it difficult to eat healthy meals in their busy daily lives. For those who find cooking a hassle, preparing healthy meals themselves is even more difficult. Furthermore, there are no systems that can help users choose meals based on their emotional state. To solve these challenges, a system is needed that can recommend nearby healthy restaurants and easily order delivery based on the user's location and emotional state.

[1462] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1463] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring the user's location information, a means for analyzing the user's emotions, a means for recommending nearby healthy restaurants, and a means for ordering delivery directly from the recommended restaurants. This allows the user to eat healthy meals without having to cook for themselves, and also enables them to select meals according to their emotional state.

[1464] A "weight management tool" is a device or software that records a user's daily weight and tracks fluctuations.

[1465] "Means to support diet, exercise, etc." refers to devices or software that provide users with the meal plans and exercise programs they need to achieve their ideal weight and body shape.

[1466] A "calorie-counting means" is a device or software that calculates the user's calorie intake needs based on their weight and activity level.

[1467] "Means that enable the process from planning a menu to delivering the ingredients" refers to devices or software that automatically order and deliver the necessary ingredients based on the menu selected by the user.

[1468] "Means for obtaining location information" refers to devices or software that obtain the user's current location using technology such as GPS.

[1469] "Means for analyzing emotions" refers to devices or software that analyze the user's emotional state from facial expressions, voice, etc.

[1470] The "means for recommending nearby healthy restaurants" is a device or software that recommends nearby restaurants that serve healthy meals based on the user's location information and emotional state.

[1471] A "delivery ordering method" is a device or software that allows you to order food directly from a recommended restaurant and request delivery.

[1472] The system for carrying out the present invention is configured by combining multiple pieces of hardware and software to support the health management of a user. Specific embodiments are described below.

[1473] Hardware Configuration

[1474] 1. Smartphone: Equipped with GPS to obtain the user's location, and a camera and microphone to analyze emotions.

[1475] 2. Server: A central processing unit for data processing and analysis.

[1476] 3. Network: An internet connection for data communication between your smartphone and the server.

[1477] Software Configuration

[1478] 1. Location acquisition software: Uses the geopy library to acquire the user's current location.

[1479] 2. Emotion analysis software: Use the emotion_recognition library to analyze emotions from the user's facial expressions and voice.

[1480] 3. Restaurant search software: Use the restaurant_finder library to find nearby healthy eateries.

[1481] 4. Delivery ordering software: Provides an interface for ordering delivery directly from recommended restaurants.

[1482] Data processing and calculation

[1483] 1. Obtaining location information: The smartphone's GPS function is used to obtain the user's current location. The obtained location information is sent to the server.

[1484] 2. Emotion analysis: The smartphone camera and microphone are used to capture the user's facial expressions and voice, and the emotion_recognition library is used to analyze their emotions. The analysis results are sent to the server.

[1485] 3. Restaurant recommendation: Based on the location information and the results of sentiment analysis, the server uses the restaurant_finder library to search for nearby healthy restaurants and recommend them to the user.

[1486] 4. Order delivery: Provides an interface for users to select meals from recommended restaurants and order delivery. The order information is sent to the restaurant via the server.

[1487] Specific examples

[1488] For example, if a user is tired from work, the system will analyze their emotions using the smartphone's camera and microphone to detect that they are feeling stressed. It will then use GPS to find the user's current location and recommend nearby cafes that offer healthy meals in a relaxing environment. The user can then order delivery directly from the recommended cafes.

[1489] Prompt Sentence Examples

[1490] "Recommend nearby healthy restaurants based on the user's location and emotions."

[1491] "When users are feeling down, suggest places that serve healthy meals to lift their spirits."

[1492] The above is a specific embodiment for carrying out the present invention.

[1493] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1494] Step 1:

[1495] Obtaining location information

[1496] The device (smartphone) uses its GPS function to obtain the user's current location. The input is location data from the GPS sensor, and the output is latitude and longitude information. This location information is sent to the server.

[1497] Step 2:

[1498] Sentiment analysis

[1499] The device (smartphone) uses a camera and microphone to capture the user's facial expressions and voice. The input is video and audio data from the camera and microphone, and the output is the emotion analysis result. The emotion_recognition library is used to analyze the user's emotions from this data and send the results to the server.

[1500] Step 3:

[1501] Restaurant search

[1502] The server uses the restaurant_finder library to search for nearby healthy restaurants based on the location information obtained in step 1 and the sentiment analysis results obtained in step 2. The input is the location information and the sentiment analysis results, and the output is a list of recommended restaurants.

[1503] Step 4:

[1504] Restaurant recommendations

[1505] The server recommends the list of restaurants obtained in step 3 to the user. The input is a list of recommended restaurants, and the output is a recommendation list displayed on the user's device. The user can select from this list.

[1506] Step 5:

[1507] Delivery orders

[1508] The user uses the terminal to select a meal from the recommended restaurant and order delivery. The input is the user's selected meal and order information, and the output is the order information sent to the restaurant. This information is sent to the restaurant via the server.

[1509] The above are the specific processing steps of this system.

[1510] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1511] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1512] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1513] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1514] [Third embodiment]

[1515] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1516] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1517] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1518] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1519] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1520] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1521] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1522] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1523] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1524] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1525] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1526] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1527] "Example 1"

[1528] The system of the present invention collects the user's weight data daily and provides dietary and exercise support to help them achieve their ideal weight and body shape based on that data. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[1529] "Example 2"

[1530] Even if the user gains weight, the system of the present invention will flexibly consider optimal menus and exercises to support the user. For example, if the user gains weight, the system will suggest low-calorie menus and recommend moderate exercise. This means that the user does not need to take appropriate measures on their own, and can manage their health with the support of the system.

[1531] "Example 3"

[1532] For people who don't like to cook, the system of this invention recommends nearby healthy restaurants and cafes based on the user's location information. This allows users to eat healthy meals without having to cook themselves.

[1533] The processing flow of each embodiment will be described below.

[1534] "Example 1"

[1535] Step 1: The user enters weight data into the system.

[1536] Step 2: The system calculates the appropriate calories for the user based on that data.

[1537] Step 3: The system suggests a menu based on the calculation results.

[1538] Step 4: The system delivers the ingredients needed for the proposed meal.

[1539] "Example 2"

[1540] Step 1: The user enters weight data into the system.

[1541] Step 2: The system detects that you have gained weight.

[1542] Step 3: The system suggests low-calorie meals.

[1543] Step 4: The system recommends moderate exercise.

[1544] "Example 3"

[1545] Step 1: The user inputs into the system that cooking is a hassle.

[1546] Step 2: The system recommends nearby healthy restaurants and cafes based on the user's location.

[1547] Example 1

[1548] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1549] Health management is an important issue in modern society, but many people find it difficult to manage their daily weight and plan appropriate meals and exercise. There are also few systems that calculate optimal calorie intake based on individual weight data and suggest menus based on that calculation. Furthermore, there are limited ways to easily obtain the ingredients needed for the suggested menus. A comprehensive system that can solve these problems is needed.

[1550] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1551] In this invention, the server includes means for collecting user weight data daily, means for calculating calories appropriate for the user based on the collected weight data, means for generating menus based on the calculation results, means for creating a list of ingredients required for the generated menus, and means for delivering ingredients based on the ingredient list. This allows users to efficiently manage their daily weight, obtain optimal calorie intake and menus based on their individual weight data, and easily obtain the necessary ingredients.

[1552] "User weight data" refers to the weight data that a user measures daily and enters into the system.

[1553] A "calorie calculation means" is an algorithm or software that calculates a user's appropriate daily calorie intake based on the user's weight data.

[1554] A "means for generating a menu" is an algorithm or software that creates a meal menu appropriate for the user based on the calculated calorie intake.

[1555] The "means for creating an ingredient list" refers to an algorithm or software for listing the ingredients and their quantities required for the generated menu.

[1556] "Means for delivering ingredients" refers to a service or system for delivering ingredients needed by the user based on the created ingredient list.

[1557] "A means of flexibly planning and supporting optimal meal plans and exercise even when weight gain occurs" refers to algorithms and software that dynamically adjust and provide optimal meal menus and exercise plans according to changes in the user's weight.

[1558] The "means for recommending nearby healthy restaurants" refers to algorithms and software that search for and recommend nearby restaurants that serve healthy meals to users who don't like to cook.

[1559] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the appropriate calorie intake for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[1560] Hardware and software used

[1561] server

[1562] The server collects weight data sent by users daily. This data is entered by the user through a dedicated application. The server calculates the appropriate calorie intake for the user based on the collected weight data. This calculation is performed using Python's NumPy library. Based on the calculation results, the server generates a meal plan appropriate for the user. This meal plan is generated using the generative AI model GPT-4. The server then creates a list of ingredients required for the generated meal plan and sends an order to a partner food delivery service. A REST API is used to process this order.

[1563] Terminal

[1564] The device provides an interface for users to input weight data. Users input weight data into a dedicated application using a device such as a smartphone or tablet. The device uses the HTTPS protocol to send the input data to the server. The device also has the function of displaying calorie calculation results and meal suggestions received from the server. Users can check the suggested meals through the device and order the necessary ingredients.

[1565] user

[1566] Every day, users enter their weight data into a dedicated application. This application runs on devices such as smartphones and tablets. When users enter their weight data, the data is sent to a server. The server returns calorie calculation results and menu suggestions, which the user can then review. The user can then prepare meals based on the suggested menu and order the necessary ingredients.

[1567] Specific examples

[1568] Example 1: User weight data entry

[1569] The user weighs themselves in the morning and enters "70 kg" into the dedicated application. The device then sends this data to the server.

[1570] Example 2: Calorie counting and meal suggestions

[1571] The server receives the user's weight data (70 kg) and calculates the appropriate calorie intake using Python's NumPy library. For example, if the calculation result is 2000 kcal, the server uses GPT-4 to generate a meal plan based on 2000 kcal.

[1572] Example 3: Ordering ingredients

[1573] The server creates a list of ingredients needed for the generated menu and sends an order to a partner food delivery service. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via a REST API.

[1574] Prompt Sentence Examples

[1575] "If the user's weight data is 70 kg, calculate the appropriate calorie intake and suggest a meal plan based on that calorie intake. The plan should include breakfast, lunch, and dinner menus."

[1576] In this way, a system is created that calculates calories and suggests meals based on the user's weight data, and delivers the necessary ingredients.

[1577] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1578] Step 1:

[1579] The user weighs themselves every morning and enters their weight into a dedicated application. For example, the user enters "70 kg." This input data is saved on the device. The input data is the user's weight information and serves as the basis for subsequent processing.

[1580] Step 2:

[1581] The terminal sends the weight data entered by the user to the server. This transmission uses the HTTPS protocol. For example, the terminal encrypts the data "70kg" and sends it to the server. The input is the user's weight data, and the output is the encrypted data sent to the server.

[1582] Step 3:

[1583] The server calculates the appropriate calorie intake for the user based on the received weight data. This calculation uses Python's NumPy library. For example, the server receives data of "70 kg" and calculates the appropriate calorie intake as "2000 kcal." The input is weight data, and the output is calorie intake.

[1584] Step 4:

[1585] The server generates a menu appropriate for the user based on the calculated calorie intake. This menu generation uses the generative AI model GPT-4. For example, the server suggests breakfast, lunch, and dinner menus based on "2000 kcal." The input is the calorie intake, and the output is a menu.

[1586] Step 5:

[1587] The server creates a list of ingredients required for the generated menu. For example, if breakfast includes "oatmeal," lunch includes "chicken breast and broccoli," and dinner includes "brown rice and stir-fried vegetables," the server lists each ingredient and its quantity. The input is the menu, and the output is the ingredient list.

[1588] Step 6:

[1589] The server places an order for the created ingredient list with a partner food delivery service. This order processing uses a REST API. For example, an ingredient list such as "200g chicken breast, 100g broccoli, 150g brown rice" is sent via the API. The input is the ingredient list, and the output is the order data sent to the food delivery service.

[1590] Step 7:

[1591] The device displays the calorie calculation results and menu suggestions received from the server to the user. The user can check the suggested menu through the device and order the necessary ingredients. For example, the user opens the application and checks the menu displayed as "Today's Menu." The input is data from the server, and the output is the information displayed to the user.

[1592] (Application example 1)

[1593] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1594] Health management is an important issue in modern society, but for many people, individually managing their weight, selecting appropriate meals, and planning exercise is a heavy burden. Furthermore, there is a lack of systems that consistently calculate calories, suggest menus, and even procure the ingredients, making it difficult to maintain health management. To solve these issues, a system is needed that calculates appropriate calories based on the user's weight data, suggests menus based on the calculation results, and automatically orders the necessary ingredients.

[1595] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1596] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for calculating appropriate calories based on the user's weight data and proposing menus based on the calculation results, and a means for automatically ordering the necessary ingredients based on the proposed menu, thereby enabling users to consistently manage their daily weight, select appropriate meals, and procure ingredients.

[1597] A "weight management tool" is a device or software that collects and records a user's daily weight data.

[1598] "Means to support diet, exercise, etc." refers to devices and software that provide users with diet and exercise plans necessary to achieve their ideal weight and body shape and assist them in carrying them out.

[1599] A "calorie calculation means" is a device or software that calculates a person's appropriate daily calorie intake based on the user's weight data.

[1600] "Means that enable the process from planning a menu to delivering the ingredients" refers to devices or software that create a list of ingredients based on a proposed menu and deliver them to the user.

[1601] "Means for calculating appropriate calorie intake based on user's weight data" refers to a device or software that calculates the appropriate calorie intake for a person based on weight data entered by the user.

[1602] The "means for suggesting a menu based on the calculation results" refers to a device or software that suggests a meal menu suitable for the user based on the calculated calorie intake.

[1603] "Means for automatically ordering ingredients based on a proposed menu" refers to a device or software that automatically lists ingredients needed for a proposed menu and allows ordering online.

[1604] As an embodiment of the present invention, the following system can be constructed.

[1605] System Overview

[1606] This system collects the user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system has the function of inputting the user's weight data, calculating the appropriate calorie intake based on that data, proposing menus based on the calculation results, and automatically ordering the ingredients needed for those menus.

[1607] Hardware and software used

[1608] Hardware:

[1609] Smartphone: Used by users to input weight data and check menu suggestions and order status.

[1610] Server: Stores user weight data, calculates calories, suggests meals, and processes food orders.

[1611] software:

[1612] Python: A programming language used to implement server-side programs.

[1613] Requests library: The Python library used to send HTTP requests.

[1614] Database: Used to store user weight data and meal plan information.

[1615] Data processing and calculation

[1616] Server Action:

[1617] 1. Entering weight data: When a user enters weight data using a smartphone, the data is sent to the server and stored in a database.

[1618] 2. Calorie Calculation: The server calculates the appropriate daily calorie intake for the user based on the stored weight data. For example, based on the latest weight data, it calculates that 2000 calories is appropriate.

[1619] 3. Meal Suggestion: Based on the calculated calorie intake, the server will suggest suitable meal plans for the user, such as salad, grilled chicken, and fruit.

[1620] 4. Ingredients ordering: Based on the proposed menu, the server will list the necessary ingredients and place the order online. Once the order is successful, the user will be notified.

[1621] Specific examples

[1622] When a user inputs their weight of 70 kg, the server saves that data and calculates the appropriate calorie intake. For example, if it calculates that 2,000 calories is appropriate, it will suggest a menu of salad, grilled chicken, fruit, etc., and automatically order the necessary ingredients. If the order is successful, a notification will be sent to the user's smartphone and the ingredients will be delivered.

[1623] Prompt Sentence Examples

[1624] The following prompts can be used for the generative AI model:

[1625] Create an application that inputs a user's weight data, calculates the appropriate calorie intake based on that data, suggests a meal plan based on the calculation results, and delivers the ingredients needed for that meal. Specifically, this application has the functionality to store a user's weight, calculate the appropriate calorie intake, suggest a meal plan, and order the ingredients.

[1626] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1627] Step 1:

[1628] Entering weight data

[1629] The user inputs weight data using a smartphone. The input weight data is sent from the smartphone to a server. The server stores the received weight data in a database.

[1630] Input: User weight data

[1631] Output: Weight data stored in the database

[1632] Step 2:

[1633] Calorie Counting

[1634] The server retrieves the latest weight data stored in the database and calculates the appropriate daily calorie intake for the user based on the retrieved weight data. For example, if the latest weight data is 70 kg, it calculates that 2000 calories is appropriate.

[1635] Input: Weight data retrieved from the database

[1636] Output: Calculated calorie intake

[1637] Step 3:

[1638] Menu suggestions

[1639] The server then proposes meal plans suitable for the user based on the calculated calorie intake. For example, based on a 2000 calorie intake, it may suggest salad, grilled chicken, and fruit. The proposed plan is then sent to the user's smartphone.

[1640] Input: Calculated calorie intake

[1641] Output: Suggested menu

[1642] Step 4:

[1643] Ordering ingredients

[1644] The server lists the ingredients needed based on the proposed menu, and the ingredients are ordered online. Once the order is successfully placed, a notification is sent to the user's smartphone.

[1645] Input: Suggested menu

[1646] Output: Ordered ingredients and notification

[1647] Step 5:

[1648] Receive notifications

[1649] The user will be notified on their smartphone that the order has been placed successfully, and will then wait for the food to be delivered.

[1650] Input: Order successful notification

[1651] Output: User notification

[1652] By following the above steps, users can consistently manage their daily weight, select appropriate meals, and procure ingredients.

[1653] Example 2

[1654] Next, a description will be given of Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1655] Conventional health management systems require users to make appropriate decisions on their own, making it difficult to flexibly suggest optimal diets and exercises when weight gain occurs. Furthermore, the lack of specific suggestions based on weight data management and fluctuations makes it difficult for users to effectively manage their health.

[1656] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for inputting weight data, a means for transmitting and saving the input weight data, a means for detecting weight fluctuations, a means for sending prompts to the generative AI model to suggest optimal menus and exercises, and a means for transmitting and displaying the suggested contents. This allows the user to automatically receive optimal menus and exercises according to their weight gain or loss, thereby achieving effective health management.

[1657] The "weight management means" is a function for recording and saving the user's daily weight data.

[1658] "Means to support diet, exercise, etc." is a function that provides the user with the diet and exercise plans necessary to achieve their ideal weight and body shape.

[1659] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[1660] "Means that enable the process from planning a menu to delivering the ingredients" refers to a function that allows the necessary ingredients to be ordered and delivered based on the proposed menu.

[1661] The "means for inputting weight data" is an interface that allows a user to input their weight into the system.

[1662] The "means for transmitting and saving input weight data" is a function for transmitting weight data input by the user to a server and saving it in a database.

[1663] The "means for detecting weight fluctuations" is a function that compares past weight data with current weight data to determine whether weight has increased or decreased.

[1664] "Means for sending prompt text to the generative AI model to suggest optimal menus and exercises" refers to a function that sends prompt text to the generative AI model and generates optimal menus and exercises according to the user's weight fluctuations.

[1665] The "means for transmitting and displaying the proposed content" is a function for transmitting the generated menu and exercise proposal content to the user's terminal and displaying it.

[1666] The present invention is a system for supporting a user's weight management, and is implemented using a server, a terminal, and a generative AI model. A specific embodiment of this system will be described below.

[1667] Hardware and software used

[1668] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[1669] Software: generative AI models (e.g., GPT-4), database management systems (e.g., MySQL), health management applications

[1670] Program processing

[1671] 1. Entering user weight data

[1672] The user uses the terminal to input weight data into the health management application.

[1673] Example: A user enters "Weight: 70kg" into a smartphone app.

[1674] 2. Data transmission and storage

[1675] The terminal transmits the input weight data to the server.

[1676] The server stores the received data in a database.

[1677] Example: The device sends the data "Weight: 70kg" to the server, which then stores the data in a MySQL database.

[1678] 3. Detect weight fluctuations

[1679] The server compares the data with past weight data in the database to detect weight gain or loss.

[1680] Example: The server retrieves the previous weight data (e.g., 68 kg) from the database and compares it with the current weight data (70 kg) to detect an increase of 2 kg.

[1681] 4. Menu and exercise suggestions using generative AI models

[1682] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[1683] Example prompt: "The user has gained 2 kg. Please suggest low-calorie meals and moderate exercise."

[1684] 5. Submitting and Displaying Proposals

[1685] Based on the prompt, the generative AI model suggests low-calorie meals and moderate exercise.

[1686] The server transmits the generated proposal to the user's terminal.

[1687] The terminal displays the received proposal content in the health management application.

[1688] Example: A generative AI model generates a suggestion such as, "For a low-calorie meal, we suggest a salad and grilled chicken breast. For exercise, we recommend 30 minutes of walking." The server then sends the suggestion to the user's device, which then displays it in the app.

[1689] In this way, the system supports users in implementing appropriate dietary and exercise programs even if they gain weight. This system provides a means for achieving effective health management without the need for users to take appropriate measures on their own.

[1690] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1691] Step 1:

[1692] Entering user weight data

[1693] The user opens the health management application and enters the latest weight data.

[1694] Input: A user enters "Weight: 70kg" into an app on their smartphone.

[1695] Output: The entered weight data is temporarily saved in the application.

[1696] Specific behavior: The user enters "70kg" into the app's input field and presses the submit button.

[1697] Step 2:

[1698] Data transmission and storage

[1699] The terminal transmits the input weight data to the server.

[1700] The server stores the received data in a database.

[1701] Input: Data "Weight: 70kg" sent from the device.

[1702] Output: The data "Weight: 70kg" is saved in the server database.

[1703] Specific operation: The device sends the data "Weight: 70kg" to the server, and the server stores the data in a MySQL database.

[1704] Step 3:

[1705] Detect weight fluctuations

[1706] The server compares the data with past weight data in the database to detect weight gain or loss.

[1707] Input: Past weight data (e.g. 68kg) and current weight data (70kg) retrieved from the database.

[1708] Output: Result: weight increased by 2 kg.

[1709] Specific operation: The server retrieves the previous weight data (68 kg) from the database and detects a 2 kg increase compared to the current weight data (70 kg).

[1710] Step 4:

[1711] Menu and exercise suggestions using generative AI models

[1712] The server sends prompts to the generative AI model to generate optimal menus and exercises.

[1713] Input: Prompt: "User has gained 2kg. Please suggest low-calorie meals and moderate exercise."

[1714] Output: Recommendations from the generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[1715] How it works: The server sends a prompt to a generative AI model (e.g., GPT-4), which then generates suggestions based on it.

[1716] Step 5:

[1717] Submitting and viewing suggestions

[1718] The server transmits the generated proposal to the user's terminal.

[1719] The terminal displays the received proposal content in the health management application.

[1720] Input: Recommendations from a generative AI model (e.g., "For a low-calorie meal, I suggest a salad with grilled chicken breast. For exercise, I recommend 30 minutes of walking.").

[1721] Output: The suggestion displayed on the user's device.

[1722] Specific operation: The server sends the generated suggestions to the user's device, and the device displays the suggestions in the app.

[1723] (Application example 2)

[1724] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1725] In modern society, daily weight management, proper diet, and exercise are important for maintaining an ideal weight and body shape. However, many people find it difficult to do these things on their own, and as a result, they often neglect their health management. Also, if weight gain occurs, they are unable to take appropriate measures quickly, which increases health risks. Furthermore, for people who find cooking a hassle, it is difficult to maintain a healthy diet. A system that can solve these problems is needed.

[1726] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting the diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for proposing low-calorie menus based on weight data, a means for proposing moderate exercise plans, a means for displaying information on stores offering ingredients based on the proposed menus and fitness programs based on the exercise plans, and a means for periodically notifying users of reminders to measure weight and exercise. This allows users to manage their health with the support of the system, without having to take appropriate measures on their own.

[1727] "Weight management means" is a function that records the user's daily weight data and saves it as history.

[1728] "Means to support diet, exercise, etc." refers to a function that provides users with the diet and exercise plans they need to achieve their ideal weight and body shape.

[1729] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's weight and activity level.

[1730] "Means that enable the process from planning a menu to delivering the ingredients" refers to the function of ordering and delivering the necessary ingredients based on the proposed menu.

[1731] "Means for suggesting low-calorie menus" is a function that suggests low-calorie meal menus based on the user's weight data.

[1732] The "means for proposing an exercise plan" is a function that suggests an appropriate exercise plan based on the user's weight data.

[1733] The "means for displaying store information" is a function that displays information about stores that offer related ingredients and fitness programs based on the proposed menu or exercise plan.

[1734] "Means for notifying reminders" refers to a function that periodically notifies users of reminders to measure their weight or exercise.

[1735] The system for implementing the present invention provides an application that integrates multiple functions to support a user's weight management. A specific embodiment of this system will be described below.

[1736] System configuration

[1737] The system consists of an application installed on the user's smartphone and a cloud server. The smartphone application provides the user interface and communicates with the server to send and receive data.

[1738] Hardware and software used

[1739] Smartphone: A device that allows users to input their daily weight and view suggested meal plans and exercise plans.

[1740] Cloud server: Stores user weight data and processes the data to calculate calories, propose menus, and suggest exercise plans.

[1741] Database: A database for storing the user's weight history, suggested meal plans, and exercise plans.

[1742] Generative AI model: An AI model that generates optimal meal plans and exercise plans based on the user's weight data.

[1743] Data processing and calculation

[1744] 1. Weight data input and management: Users input their daily weight through a smartphone application, and this data is sent to a cloud server and stored in a database.

[1745] 2. Calorie calculation: The server calculates the required calorie intake based on the user's weight data and activity level.

[1746] 3. Meal Suggestion: Using a generative AI model, low-calorie meal suggestions are made based on the user's weight data. These suggestions are displayed in the smartphone application.

[1747] 4. Exercise plan suggestions: Similarly, generative AI models are used to suggest appropriate exercise plans, which are also displayed in the smartphone application.

[1748] 5. Display of store information: Based on the proposed menu or exercise plan, information on stores that offer related ingredients and fitness programs will be displayed.

[1749] 6. Reminder notification: The server periodically sends reminders to the user's smartphone to measure weight or exercise.

[1750] Specific examples

[1751] For example, if a user enters their weight as 70 kg, the system will display "Your weight has been recorded as 70 kg." The system will then suggest "Today's recommended menu: Salad" and "Today's recommended exercise: Walking." It will then display information about nearby stores that offer ingredients based on the suggested menu and fitness programs based on the exercise plan. Finally, it will provide periodic reminders to measure weight and exercise.

[1752] Prompt Sentence Examples

[1753] Create a Python program that records the user's weight when they input it, and suggests low-calorie meals and a moderate exercise plan. Also add a function to display the weight history.

[1754] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1755] Step 1:

[1756] The user starts the smartphone application and inputs their daily weight. The input weight data is sent from the smartphone device to the cloud server. The server receives this data and stores it in a database. The input data is the user's weight (e.g., 70 kg), and the output is the weight data stored in the database.

[1757] Step 2:

[1758] The server calculates the user's calorie intake needs based on the stored weight data. The calculation uses data such as the user's weight, age, gender, and activity level. The input data is the user's weight data and other personal information, and the output is the calculated calorie intake.

[1759] Step 3:

[1760] The server uses a generative AI model to suggest low-calorie meals based on the user's weight data. The AI ​​model generates optimal meals based on past data and nutritional information. The input data is the user's weight data and calorie intake, and the output is a suggested meal (e.g., salad).

[1761] Step 4:

[1762] The server uses a generative AI model to suggest a suitable exercise plan based on the user's weight data. The AI ​​model generates an optimal exercise plan taking into account the user's weight and activity level. The input data is the user's weight data and activity level, and the output is a suggested exercise plan (e.g., walking).

[1763] Step 5:

[1764] The server displays information about restaurants that offer related ingredients and fitness programs based on the proposed menu and exercise plan. The restaurant information is selected based on the user's location information and the content of the proposal. The input data is the proposed menu and exercise plan, and the output is related restaurant information.

[1765] Step 6:

[1766] The server periodically sends reminders to the user's smartphone to measure weight and exercise. The reminders are scheduled based on the user's settings. The input data are the user's settings and weight data, and the output is the reminder notification sent to the smartphone.

[1767] Example 3

[1768] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1769] In modern society, it is difficult to maintain a healthy diet in a busy daily life. This is especially true for those who do not like to cook or who do not have time. Another issue is the lack of support for weight management and achieving an ideal body shape. Another problem is the amount of effort required for health management, such as individual calorie calculations and food delivery.

[1770] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary for achieving an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring user location information, a means for searching for nearby healthy restaurants based on the acquired location information, and a means for providing the search results to the user. This enables the user to eat healthy meals without having to cook for themselves, and also provides support for weight management and achieving an ideal body shape.

[1771] "Weight management means" is a function for recording the user's daily weight and tracking fluctuations.

[1772] "Means to support diet, exercise, etc." is a function that provides the user with the meal plans and exercise programs necessary to achieve their ideal weight and body shape.

[1773] The "calorie calculation means" is a function that calculates the required calorie intake based on information such as the user's weight, height, age, and gender.

[1774] The "means for enabling delivery of ingredients from a menu" is a function that lists the ingredients required based on the menu selected by the user and delivers the ingredients to a location specified by the user.

[1775] "Means for obtaining location information" refers to a function that obtains the user's current location using GPS or other location information technology.

[1776] The "means for searching for nearby healthy restaurants" is a function that searches a database for healthy restaurants within a certain range from the user's current location based on the acquired location information.

[1777] The "means for providing search results to the user" is a function for transmitting information about the searched healthy restaurants to the user's terminal and displaying it.

[1778] This invention is a system that helps users maintain a healthy lifestyle by managing their weight on a daily basis, providing support for achieving an ideal weight and body shape, calculating calories, planning menus and delivering ingredients, and recommending nearby healthy restaurants.

[1779] Hardware and software used

[1780] Hardware: Smartphones (e.g. iPhone, Android devices), GPS devices

[1781] Software: GPS function, dedicated application, server (e.g. AWS, Google Cloud)

[1782] Program processing

[1783] Subject: Server

[1784] The server receives the user's location information. The location information is obtained from the user's smartphone or GPS device. The server then references a database to search for healthy restaurants closest to the user's current location. This database includes information such as restaurant locations, menus, and ratings. Based on the search results, the server creates a list of healthy restaurants that are best suited to the user and sends it to the user's device.

[1785] Subject: Terminal

[1786] The device acquires the user's location information and sends it to the server. The location information is acquired using the smartphone's GPS function. After receiving the list of recommended healthy restaurants from the server, the device displays the list to the user. The user can select a restaurant of interest from the displayed list and check detailed information.

[1787] Subject: User

[1788] The user launches the app on their smartphone and allows location sharing. The app then requests nearby healthy restaurants based on the user's current location from the server. After receiving the recommendation list from the server, the user reviews the list and selects a restaurant that interests them. They then review the details of the selected restaurant and decide whether to visit.

[1789] Specific examples

[1790] When a user launches the smartphone app and allows location sharing, the device uses its GPS function to obtain its current location. The obtained location information is sent to a server, which then references a database to search for nearby healthy restaurants. For example, if the user is in Shibuya Ward, Tokyo, the server will create a list of healthy restaurants in Shibuya Ward and send it to the user's device. The user can then select a restaurant, such as "Shibuya Healthy Cafe" or "Natural Restaurant Shibuya," from the received list and check detailed information.

[1791] Example prompts to input to the generative AI model

[1792] "Please explain the system that recommends nearby healthy restaurants based on the user's current location. Please clearly state what kind of data processing and calculations are performed, including the names of specific hardware and software." The flow of the identification process in Example 3 will be explained using Figure 15.

[1793] Step 1:

[1794] The user launches the app and allows location sharing. The user launches the app on their smartphone and a pop-up appears requesting location sharing. When the user selects "Allow," the app starts acquiring location information. The input is the user's permission, and the output is the start of location information acquisition.

[1795] Step 2:

[1796] The device uses the GPS function to obtain the user's current location. The device uses the smartphone's GPS function to obtain the user's current location. Specifically, the device receives signals from GPS satellites and calculates latitude and longitude information. The input is the GPS signal, and the output is latitude and longitude information.

[1797] Step 3:

[1798] The device sends the acquired location information to the server. The device sends the acquired latitude and longitude information to the server. The HTTPS protocol is used for transmission to ensure data security. The input is latitude and longitude information, and the output is transmission to the server.

[1799] Step 4:

[1800] The server searches a database based on the received location information to list nearby healthy restaurants. The server searches the database based on the received location information. The database contains restaurant location information, menus, ratings, etc. The server lists healthy restaurants within a certain range from the user's current location. The input is location information, and the output is a list of restaurants.

[1801] Step 5:

[1802] The server sends the information about the listed restaurants to the terminal. The server sends the information about the listed restaurants to the terminal. The data sent is in JSON format and includes the restaurant's name, address, rating, part of the menu, etc. The input is a list of restaurants, and the output is what is sent to the terminal.

[1803] Step 6:

[1804] The device displays the received list of restaurants to the user. The device displays the received list of restaurants to the user. The app interface displays a list of restaurant names, ratings, distances, etc. The input is a list of restaurants, and the output is what is displayed to the user.

[1805] Step 7:

[1806] The user selects a restaurant of interest from the list and checks the details. The user selects a restaurant of interest from the list. Once selected, the app displays detailed information about the restaurant. The detailed information includes menu photos, opening hours, contact information, etc. The input is the user's selection and the output is the display of detailed information.

[1807] (Application example 3)

[1808] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1809] In modern society, people who lead busy lives find it difficult to plan and execute appropriate diets and exercises to maintain their health. Furthermore, for those who don't like cooking, the options for healthy meals are limited. Furthermore, the process of finding nearby healthy restaurants, ordering, and having food delivered can be cumbersome. There is a need for a system that can solve these problems and allow users to easily live a healthy lifestyle.

[1810] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1811] In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise necessary to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for acquiring the user's location information and listing nearby healthy restaurants, a means for ordering food from the listed restaurants and using delivery services, and a means for suggesting optimal menus based on the user's health status and goals. This allows the user to easily eat healthy meals without having to cook for themselves.

[1812] "Weight management tools" are features that allow users to record their daily weight and track fluctuations.

[1813] "Means to support diet, exercise, etc." refers to a function that provides meal plans and exercise plans necessary for users to achieve their ideal weight and body shape.

[1814] The "calorie calculation means" is a function that calculates the required calorie intake based on the user's physical information and activity level.

[1815] "A means to enable the delivery of ingredients from a menu" is a function that lists the necessary ingredients based on the menu selected by the user and provides a service to deliver them.

[1816] "Means for obtaining location information" refers to a function that obtains the user's current location using technology such as GPS.

[1817] The "means of listing nearby healthy restaurants" is a function that searches for nearby restaurants that offer healthy menus based on the user's location information and displays them as a list.

[1818] "Means for ordering food and using delivery services" refers to the ability to select food from listed restaurants, order online, and use delivery services.

[1819] "Means to suggest optimal menus based on health status and goals" refers to a function that suggests optimal meal menus based on the user's health status and goals such as dieting and muscle building.

[1820] A system for carrying out the present invention includes the following means for supporting a user's health management.

[1821] 1. Program Generation

[1822] The system manages the user's daily weight and supports diet and exercise to achieve an ideal weight and body shape. It also calculates the user's calorie intake and enables everything from meal planning to food delivery. It also obtains the user's location information, lists nearby healthy restaurants, enables food ordering, and makes delivery services available. It also suggests optimal menus based on the user's health status and goals.

[1823] 2. Program processing explanation

[1824] Hardware used:

[1825] Smartphone (iOS or Android)

[1826] Software used:

[1827] Python

[1828] Geopy library (location information acquisition)

[1829] Requests library (API requests)

[1830] Google Places API (getting restaurant information)

[1831] Data processing and calculation:

[1832] The server first uses the Geopy library to obtain the user's location. Then, it uses the Google Places API to search for nearby healthy restaurants based on the obtained latitude and longitude. The search results are displayed as a list to the user, allowing the user to order food from the restaurant of their choice and use delivery services. It also calculates calories based on the user's input data to suggest optimal menus based on the user's health status and goals.

[1833] 3. Examples and prompts

[1834] Examples:

[1835] If the user is in Shibuya Ward, Tokyo, the system will display a list of nearby healthy restaurants. If the user indicates that they are on a diet, the system will suggest low-calorie options.

[1836] Example prompt sentence:

[1837] Write a Python program that gets the user's location and lists nearby healthy restaurants. Use the Geopy library to get the location and the Google Places API to get the restaurant information. Based on the user's latitude and longitude, search for healthy restaurants within a 1500 meter radius and display their information.

[1838] In this way, users can easily eat healthy meals without having to cook for themselves.

[1839] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1840] Step 1:

[1841] The server obtains the user's location information. Specifically, it obtains the latitude and longitude of the current location using the device's GPS function. The input is a location request from the user's device, and the output is the obtained latitude and longitude data.

[1842] Step 2:

[1843] The server uses the Google Places API to search for nearby healthy restaurants based on the acquired latitude and longitude. The input is the latitude and longitude data acquired in step 1, and the output is a list of restaurants as search results. Specifically, the server sends an API request and analyzes the response.

[1844] Step 3:

[1845] The server displays the search results to the user as a list. The input is the restaurant list obtained in step 2, and the output is the restaurant list displayed on the user's device. Specifically, the server formats the list and displays it on the user interface.

[1846] Step 4:

[1847] The user selects a restaurant from the list and orders food. The input is the user's selection, and the output is information about the selected restaurant and food. The specific operation is to accept the selection through a user interface.

[1848] Step 5:

[1849] The server receives the user's order information and arranges for a delivery service. The input is the order information obtained in step 4, and the output is a request to the delivery service. Specifically, it calls the delivery service's API and sends the order information.

[1850] Step 6:

[1851] The server proposes the optimal menu based on the user's health condition and goals. The input is data about the user's health condition and goals, and the output is the proposed menu. Specifically, the server calculates calories based on the user's input data and selects an appropriate menu.

[1852] Step 7:

[1853] The server presents the proposed menu to the user. The input is the menu information obtained in step 6, and the output is the menu displayed on the user's device. Specifically, the server formats the menu and displays it in the user interface.

[1854] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1855] "Example 1"

[1856] One embodiment of the present invention includes an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's emotions from their tone of voice, facial expressions, behavioral patterns, etc. For example, if the user feels stressed, the emotion engine feeds that information back to the system, which then suggests exercises and meals that promote relaxation.

[1857] "Example 2"

[1858] The emotion engine also adjusts diet and exercise support based on the user's emotions. For example, when a user feels joy, the emotion engine feeds that information back to the system, which then suggests diet and exercise to maintain that joy. This allows users to manage their health in line with their emotions.

[1859] "Example 3"

[1860] Furthermore, the emotion engine recommends nearby healthy restaurants based on the user's emotions. For example, if the user is feeling down, the emotion engine will feed that information back into the system, and the system will suggest restaurants that serve healthy meals to lift the user's spirits. This allows users to make food choices that match their emotions.

[1861] The processing flow of each embodiment will be described below.

[1862] "Example 1"

[1863] Step 1: Collect data from users' tone of voice, facial expressions, behavioral patterns, etc.

[1864] Step 2: Send the collected data to the emotion engine.

[1865] Step 3: The emotion engine analyzes the user's emotions from the collected data.

[1866] Step 4: The analysis results are fed back to the system, which then suggests exercises and meals to the user that promote relaxation.

[1867] "Example 2"

[1868] Step 1: Analyze user emotion data with the emotion engine.

[1869] Step 2: The analysis results are fed back to the system, which then adjusts diet and exercise support based on the user's emotions.

[1870] Step 3: The system suggests diet and exercise recommendations to the user to maintain that joy.

[1871] "Example 3"

[1872] Step 1: Analyze user emotion data with the emotion engine.

[1873] Step 2: The analysis results are fed back to the system, which then recommends nearby healthy restaurants based on the user's emotions.

[1874] Step 3: The system suggests restaurants that offer healthy meals to boost the user's mood.

[1875] Example 1

[1876] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1877] In modern society, maintaining an ideal weight and body shape requires daily weight management, proper diet, and exercise support. However, it is difficult for many people to consistently do these things, and stress and emotional fluctuations in particular can affect health management. In addition, procuring ingredients and planning menus can be time-consuming, making continuous health management difficult.

[1878] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for managing daily weight, a means for supporting diet and exercise required to achieve an individual's ideal weight and body shape, a means for calculating calories appropriate for the individual, a means for enabling everything from menu planning to delivery of ingredients, a means for sensing the user's tone of voice, facial expressions, and behavioral patterns, a means for analyzing the sensed data and identifying the user's emotional state, and a means for suggesting exercises and meals that promote relaxation based on the user's emotional state. This enables the user to consistently manage their health and receive support that also addresses stress and emotional fluctuations.

[1879] "Means for managing daily weight" refers to devices and software that allow users to measure their weight daily and record and save that data.

[1880] "Means to support the diet, exercise, etc. necessary to achieve an individual's ideal weight and body shape" refers to systems and algorithms that provide appropriate diet and exercise plans based on the user's health goals.

[1881] "Means for calculating calories appropriate for each individual" refers to a calculation function that calculates the amount of calories needed per day based on the user's weight data and other health information.

[1882] "Means that enable the process from planning a menu to delivering the ingredients" refers to a system or service that identifies the necessary ingredients based on the menu proposed to the user and delivers them to the user.

[1883] "Means for detecting a user's tone of voice, facial expression, and behavioral patterns" refers to devices or software that use sensors such as cameras and microphones to detect a user's tone of voice, facial expression, and behavioral patterns in real time.

[1884] "Means for analyzing the sensed data and identifying the user's emotional state" refers to an algorithm or analytical engine for analyzing the sensed data and identifying the user's emotional state.

[1885] "Means for suggesting exercises and meals that promote relaxation based on the user's emotional state" refers to a system or algorithm that suggests exercises and meals aimed at stress reduction and relaxation based on the user's emotional state.

[1886] MODE FOR CARRYING OUT THE INVENTION

[1887] This invention is a system that collects a user's weight data daily and provides dietary and exercise support based on that data to help them achieve their ideal weight and body shape. Specifically, the system inputs the user's weight data and calculates the calories appropriate for the user based on that data. It also proposes a menu based on the calculation results and delivers the ingredients needed for that menu.

[1888] Hardware and software used

[1889] This system uses the following hardware and software:

[1890] Hardware: smartphone, computer, camera, microphone

[1891] Software: Dedicated applications, databases (MySQL and PostgreSQL), Python, NumPy, TensorFlow, OpenCV, Google Cloud Speech-to-Text API

[1892] Data processing and calculation

[1893] The server receives the weight data entered by the user and stores it in a database. The server then calculates the appropriate calorie intake for the user based on the stored data. This calculation is performed using Python's NumPy library. Based on the calculation results, the server then suggests a meal plan suitable for the user. This meal plan is proposed using a machine learning model (for example, using TensorFlow).

[1894] The server then identifies the ingredients needed for the proposed meal and sends an order to a partner food delivery service, so that the user can receive the ingredients at home.

[1895] Meanwhile, the device uses a camera and microphone to detect the user's tone of voice, facial expressions, and behavioral patterns. This data is sent to the emotion engine, which analyzes the data and identifies the user's emotional state. This analysis is performed using OpenCV and the Google Cloud Speech-to-Text API. If the emotion engine determines that the user is feeling stressed, the information is fed back to the server, which then uses the information to suggest exercises and meals that will promote relaxation for the user.

[1896] Specific examples

[1897] As a concrete example, consider the case where a user weighs themselves in the morning and enters that data into the system. When the user enters the weight data, the server receives and stores the data. The server then calculates the appropriate daily calorie intake based on the user's weight data. For example, if the user weighs 70 kg, the server calculates the daily calorie intake to be 2000 kcal. The server then proposes a meal plan based on 2000 kcal and orders the necessary ingredients from a food delivery service.

[1898] If the user is feeling stressed, the emotion engine analyzes the information and sends it back to the server, which then suggests relaxation exercises such as yoga or meditation.

[1899] Prompt Sentence Examples

[1900] Example prompts to input to a generative AI model:

[1901] Enter the user's weight data, then calculate the user's appropriate calorie intake and suggest meals based on the results. Also, if the user is feeling stressed, suggest exercises and meals that promote relaxation.

[1902] In this way, the system provides comprehensive support for the user's health management.

[1903] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1904] Step 1:

[1905] The user inputs weight data. The user measures their weight on a scale every morning and enters the weight data into a dedicated smartphone app. The input weight data is saved on the device.

[1906] Step 2:

[1907] The terminal sends the entered weight data to the server. The terminal encrypts the entered weight data using SSL / TLS and sends it to the server via the Internet. The input is weight data, and the output is encrypted data.

[1908] Step 3:

[1909] The server receives the weight data and stores it in a database. The server stores the received weight data in a database. A relational database such as MySQL or PostgreSQL is used for the database. The input is encrypted weight data, and the output is the data stored in the database.

[1910] Step 4:

[1911] The server calculates the calorie intake based on the stored weight data. The server uses Python's NumPy library to calculate the appropriate daily calorie intake based on the stored weight data. For example, it calculates 2000 kcal for a user weighing 70 kg. The input is weight data and the output is calorie intake.

[1912] Step 5:

[1913] The server uses TensorFlow to suggest a menu suitable for the user based on the calculation results. For example, it suggests oatmeal for breakfast, salad for lunch, and grilled chicken for dinner. The input is calorie intake, and the output is a menu suggestion.

[1914] Step 6:

[1915] The server identifies the ingredients needed for the proposed meal and sends an order to the food delivery service. The server identifies the ingredients needed for the proposed meal (oatmeal, lettuce, chicken breast, etc.) and sends an order to the partner food delivery service. The input is the meal and the output is the food order.

[1916] Step 7:

[1917] The device senses the user's tone of voice, facial expressions, and behavioral patterns. The device uses a built-in camera and microphone to sense the user's tone of voice, facial expressions, and behavioral patterns in real time. The input is the user's voice, facial expressions, and behavioral patterns, and the output is the sensed data.

[1918] Step 8:

[1919] The device sends the sensed data to the emotion engine. The device sends the sensed data to the emotio...

Claims

1. a first means for a user to input his / her weight data; A second means for generating a first prompt sentence for outputting a first suggestion content indicating an optimal menu and exercise for the user based on the input current weight data and the user's past weight data in a database; a third means for inputting the generated first prompt sentence into a generative AI model to generate the first suggestion content; A fourth means for transmitting the generated first proposal content to a terminal of the user; A system including:

2. and a fifth means for displaying, on a terminal of the user, information on a store that provides food ingredients related to a menu optimal for the user shown in the first proposal content or a fitness program related to an exercise optimal for the user, based on the first proposal content and location information of the user. The system of claim 1 .

3. a sixth means for analyzing an emotional state of the user from the tone of voice, facial expression, and behavioral patterns of the user using an emotion engine; The second means generates a second prompt sentence for outputting a second suggestion content indicating an exercise or a meal that promotes relaxation to the user based on the emotional state of the user; The third means inputs the generated second prompt sentence into a generative AI model to generate the second suggestion content.

3. A system according to claim 1 or 2.

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