system

Abstract

A system is provided.SOLUTION: The system includes a means for inputting and storing basic information of a user, a means for calculating a calorie and a PFC value of a food by using an image recognition algorithm, a means for calculating and displaying a daily proper calorie intake and a PFC balance, and a means for displaying a remaining calorie and a PFC amount which can be taken daily in real time.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] Health management is an important issue in modern society, and there is a particular need to properly manage dietary calories and PFC (protein, fat, carbohydrates). However, conventional methods are time-consuming and difficult to obtain accurate information. For example, it is necessary to manually check the calorie content of food, and it is cumbersome to calculate it every time a meal is eaten. This has led to the problem that users cannot easily maintain their health management. [Means for solving the problem]

[0005] The present invention provides a system that allows users to easily manage their dietary calories and PFC through smart glasses. Specifically, the system consists of the following means:

[0006] a means for inputting and storing basic user information;

[0007] A means for calculating the calorie and PFC value of food using an image recognition algorithm;

[0008] A means for calculating and displaying the appropriate daily calorie intake and PFC balance;

[0009] The system includes a means for displaying the remaining calories and PFC intake available for the day in real time.

[0010] This allows users to easily calculate calories and PFC and manage their health by simply scanning an image of food with the smart glasses each time they eat.In addition, the appropriate calorie intake and PFC balance are displayed in real time, making it easier to manage dietary intake in daily life.

[0011] The "means for inputting and saving basic user information" is a function for inputting data such as the user's height, weight, and body fat percentage into the application and saving it on the server or in local storage.

[0012] "Means for calculating food calories and PFC values ​​using image recognition algorithms" refers to a function that analyzes images of food taken with smart glasses or a camera, and uses an algorithm that recognizes the type and quantity of food to calculate the corresponding calorie and PFC (protein, fat, carbohydrate) values.

[0013] "Means for calculating and displaying the appropriate daily calorie intake and PFC balance" is a function that calculates the appropriate daily calorie intake and PFC balance for a user based on the user's basic information, and visually displays the results on the application.

[0014] "Means for displaying the remaining calories and PFC amount available for daily intake in real time" is a function that successively updates the calorie and PFC values ​​of the food consumed by the user and displays the remaining calories available for daily intake and the remaining amount of each nutrient (PFC) to the user in real time.

[0015] "Means for acquiring and storing image data of food using smart glasses" refers to a function that uses the camera function built into smart glasses to take images of the food the user is consuming and stores the image data on a server or in local storage.

[0016] "Means for calculating the appropriate daily calorie intake and PFC balance based on basic information" is a function that uses an algorithm to calculate the total calories needed per day and PFC balance based on basic information such as the user's height, weight, and body fat percentage.

[0017] In this way, by having each of the means function in an integrated manner, it is possible to provide a system that allows users to easily manage the calories and PFC of their meals on a daily basis. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0039] The present invention relates to a system that allows users to easily manage the calories and PFC (protein, fat, carbohydrates) of their meals using an application linked to smart glasses. The following describes in detail the embodiments of this system.

[0040] Enter basic user information

[0041] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0042] Smart Glasses and Food Scanning

[0043] The user wears the smart glasses while eating. The camera in the smart glasses captures images of the meal. The image data captured by the camera is sent from the smart glasses to a server.

[0044] Image Recognition and Calorie Counting

[0045] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, it retrieves the calorie and PFC information for each food item from a database and totals them.

[0046] Calorie and PFC value display

[0047] The server sends the calculation results to the smart glasses and the app, which uses the received data to subtract the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0048] Real-time management

[0049] The smart glasses display the calculation results on a HUD (Head-Up Display) so that the user can check them directly in front of their eyes, allowing them to manage calories and nutrients in real time every time they eat.

[0050] Specific examples

[0051] Initial Setup

[0052] User: For example, enter your height (170cm), weight (70kg), and body fat percentage (20%) into the app.

[0053] App: Based on this, calculate your basal metabolic rate and set your daily calorie intake to 2,500 kcal. Save this information on the server.

[0054] Calculating calories in meals

[0055] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0056] Smart glasses: The camera scans the food and sends the image data to a server.

[0057] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0058] Display of calorie intake and PFC amount

[0059] App: Calculate the remaining calorie intake as 2,010 kcal and update the required PFC amount at the same time.

[0060] Smart Glasses: Display "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" on the HUD.

[0061] By implementing the system in this manner, the user can easily manage their daily diet and help maintain a healthy lifestyle.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[0065] Step 2:

[0066] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on the server.

[0067] Step 3:

[0068] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[0069] Step 4:

[0070] The smart glasses compress the captured image data and send it to a server via Wi-Fi or Bluetooth.

[0071] Step 5:

[0072] The server analyzes the received image data and uses an image recognition algorithm to identify the type and quantity of food.

[0073] Step 6:

[0074] The server retrieves the calorie and PFC values ​​of the food from the database based on the recognized food, and calculates the total value.

[0075] Step 7:

[0076] The server encodes the calculation results in JSON format and sends them to the smart glasses and app using an API.

[0077] Step 8:

[0078] Based on the calorie and PFC information received, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates the remaining calories available for intake and the amount of PFC required.

[0079] Step 9:

[0080] The smart glasses display the calculation results on the HUD and show the user in real time the following format: "Remaining calories: XXXX kcal, Protein requirements: XX g, Fat: XX g, Carbohydrates: XX g."

[0081] In this way, through a series of processing steps, users can easily manage their diet and maintain a healthy lifestyle.

[0082] Example 1

[0083] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0084] In modern society, effective dietary management is an important element of maintaining health and dieting for many people. However, managing calories and nutritional components (protein, fat, carbohydrates) requires checking the calorie content of each individual ingredient, which is time-consuming and laborious. Furthermore, real-time management is difficult, and it often does not become a continuous habit. Therefore, there is a need for a system that allows users to easily and accurately manage their own dietary content.

[0085] 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.

[0086] In this invention, the server includes a means for inputting and storing basic information such as a user's height, weight, and body fat percentage, a means for analyzing the type and amount of food using an image recognition algorithm to calculate calorie and nutrient values, and a means for calculating and displaying the appropriate daily calorie intake and nutrient balance. This allows users to easily record their diet using a smart device and check the calorie and nutrient balance on the spot.

[0087] "Basic information such as the user's height, weight, and body fat percentage" is data that indicates the user's physical characteristics, and is basic information for individual calorie balance and nutritional management.

[0088] An "image recognition algorithm" is a technology that analyzes image data acquired by a camera or other device and automatically identifies specific objects or features, and is used to identify the type and quantity of food.

[0089] "Calorie and nutritional values" is data that indicates the amount of energy (calories) and major nutrients (protein, fat, carbohydrates) contained in a food.

[0090] "Appropriate daily calorie intake and nutritional balance" refers to the total calories and balance of major nutrients that should be consumed in a day, calculated based on the user's physical characteristics and activity level.

[0091] "Wearable device" is a general term for electronic devices that can be worn, and in this case refers to a device that has the function of acquiring image data of food.

[0092] A "server" is a computer system that receives, stores, and analyzes data sent by users over a network and provides the necessary information.

[0093] This invention relates to a system that allows a user to easily and accurately manage the calories and nutritional components (protein, fat, carbohydrates) of their meals in order to maintain a healthy lifestyle. The following describes in detail the mode for implementing this system.

[0094] Enter basic user information

[0095] First, users download and install the smartphone app. When they launch the app, they are prompted to enter basic personal information such as height, weight, and body fat percentage. This data is used to calculate each user's calorie consumption and nutritional balance. The entered information is sent to a server via the app and saved.

[0096] Smart Glasses and Food Scanning

[0097] The user wears smart glasses as a wearable device while eating. The smart glasses are equipped with a high-resolution camera that captures images of the food. The captured image data is sent to a server in real time via the smart glasses.

[0098] Image Recognition and Calorie Counting

[0099] The server receives the transmitted image data and analyzes the type and quantity of food using an image recognition algorithm, which uses, for example, "image recognition software" to analyze the food pixel by pixel and identify the calorie and nutritional information for each food item.

[0100] Calculation and display of daily calorie and nutritional balance

[0101] Based on the analysis results, the server extracts calorie and nutritional information for each food item from the database, adds them up, calculates the appropriate daily calorie intake and nutritional balance, and sends the results to the smart glasses and smartphone app.

[0102] Display of remaining calorie intake and nutritional information in real time

[0103] The smart glasses display the calculation results using a HUD (Head-Up Display), allowing users to manage calories and nutritional information in real time with each meal. The app also calculates the remaining calories and nutritional information available for the day and displays it for easy viewing by the user.

[0104] Specific examples

[0105] Initial Setup

[0106] For example, the user enters their height of 170 cm, weight of 70 kg, and body fat percentage of 20% into the app.

[0107] The app calculates the basal metabolic rate based on the input data and sets the appropriate daily calorie intake at 2,500 kcal. This information is stored on a server.

[0108] Calculating calories in meals

[0109] The user wears the smart glasses while eating a lunch of salad, grilled chicken, and rice.

[0110] The smart glasses use a camera to scan the food and send the image data to a server.

[0111] Using an image recognition algorithm, the server determines that the salad is 40 kcal, the grilled chicken is 250 kcal, and the rice is 200 kcal, totaling 490 kcal. This is then sent to the app and smart glasses.

[0112] Display of calorie intake and nutritional information

[0113] The app will calculate the remaining calorie intake as 2,010 kcal and simultaneously update the nutritional requirements.

[0114] The smart glasses display the following information on the HUD: "Remaining calories: 2,010kcal, required protein: 80g, fat: 60g, carbohydrates: 250g."

[0115] Prompt Sentence Examples

[0116] Examples of input prompts for a generative AI model include:

[0117] "Please explain the specific usage of a system that uses a wearable device to manage the calories and nutritional components (protein, fat, carbohydrates) of meals."

[0118] By implementing the present invention in the above manner, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle.

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

[0120] Step 1:

[0121] Users download and install the smartphone app. When they launch the app, a screen appears where they can enter basic information such as their height, weight, and body fat percentage. The information they enter is sent to a server via the app and saved.

[0122] Input: Basic information such as height, weight, and body fat percentage

[0123] Output: Basic information data stored on the server

[0124] Step 2:

[0125] The server calculates the appropriate daily calorie intake and nutritional balance based on the received basic information. This calculation uses a basal metabolic rate calculation algorithm. The calculation results are stored in the server database.

[0126] Input: User's basic information (height, weight, body fat percentage, etc.)

[0127] Output: Proper daily calorie intake and nutritional balance

[0128] Step 3:

[0129] When a user eats, they wear smart glasses as a wearable device. The smart glasses' camera captures images of the food they are eating and transmits the image data to a server in real time.

[0130] Input: Food image data acquired through a camera

[0131] Output: Food image data sent to the server

[0132] Step 4:

[0133] The server analyzes the type and quantity of food using an image recognition algorithm based on the received image data. This algorithm uses, for example, "image recognition software." Based on the data obtained by image recognition, the server retrieves calorie and nutritional information for each food from a database.

[0134] Input: Food image data

[0135] Output: Food type and quantity, along with corresponding calorie and nutritional information

[0136] Step 5:

[0137] The server calculates the calorie and nutritional information for each food based on the analysis results. It then compares the calorie and nutritional information with the recommended daily intake and subtracts the amount already consumed. The calculation results are sent from the server to the smart glasses and smartphone app.

[0138] Input: Food type and quantity, as well as calorie and nutritional information

[0139] Output: Calories consumed and remaining, and nutritional information

[0140] Step 6:

[0141] The smart glasses use a HUD (Head-Up Display) to display the calculation results in real time, allowing users to check the calorie and nutritional balance of each meal. The same data is also displayed on a smartphone app, making daily dietary management easier.

[0142] Input: Calorie and nutritional information sent from the server

[0143] Output: Calorie and nutritional information displayed on HUD and smartphone app

[0144] (Application example 1)

[0145] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0146] As modern consumers lead busy lives, there is a growing need for easy and accurate management of the calories and PFC (protein, fat, carbohydrates) of their meals. While the popularity of food delivery services has increased options, making healthy choices can be challenging. Therefore, there is a need for a system that provides real-time calorie and PFC information to help users maintain healthy eating habits.

[0147] 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.

[0148] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calories and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying in real time the calories and PFC values ​​of foods ordered by the user through a digital device, and means for using an image capture device to capture and transmit images of the foods to the server, thereby enabling the user to understand the contents of their meals in real time and appropriately manage their calorie intake and nutrient balance.

[0149] The "means for inputting and storing basic user information" refers to a mechanism for inputting basic information such as a user's height, weight, and body fat percentage via a digital device and storing that data on a server.

[0150] The "means for calculating the calorie and PFC values ​​of food using an image recognition algorithm" is an algorithm that analyzes the type and quantity of food from the captured image and calculates the calories, protein, fat, and carbohydrates by referring to a database.

[0151] "Means for calculating and displaying the appropriate daily calorie intake and PFC balance" refers to a mechanism that calculates the appropriate daily calorie intake and PFC (protein, lipid, carbohydrate) balance based on the user's basic information and displays it to the user.

[0152] The "means for displaying the remaining calorie and PFC intake amount for the day in real time" is a mechanism that calculates the remaining calorie and PFC intake amount from the calorie and PFC intake amount for the day in real time and displays them to the user.

[0153] "Means for calculating and displaying in real time the calorie and PFC values ​​of food ordered by a user through a digital device" refers to a mechanism that calculates the calories and PFC values ​​of food ordered using a food delivery application and displays the results in real time.

[0154] "Means for using an image capture device to capture images of food and transmit them to a server" refers to a mechanism for using a digital device with a camera to capture images of food and transmit the data to a server.

[0155] This invention is a system that allows users to easily manage dietary calories and PFC (protein, fat, carbohydrates) by linking with a digital device. The system includes means for inputting and saving basic user information, means for calculating food calories and PFC values ​​using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying the calorie and PFC values ​​of foods ordered by the user through the digital device in real time, and means for using an image capture device to capture images of foods and send them to a server.

[0156] Each means of this system has the following specific configuration.

[0157] server

[0158] The server contains a database (such as MySQL (registered trademark)) for storing basic user information, software (such as TENSORFLOW (registered trademark)) for executing image recognition algorithms, and a system for real-time communication (such as Firebase). Basic information (height, weight, body fat percentage, etc.) entered by the user from their smartphone is sent to the server and stored in the database.

[0159] Example of user information entry

[0160] A user uses a smartphone app to enter their height of 170 cm, weight of 70 kg, and body fat percentage of 20%.

[0161] The server receives this information and stores it in a database.

[0162] Image Recognition and Calorie Counting

[0163] The server receives image data of food sent from smart glasses or smartphone cameras, analyzes the type and quantity of food using image recognition algorithms such as TensorFlow, and based on the analysis results, retrieves the calorie and PFC information of the food from the database and calculates the total value.

[0164] Example of calorie calculation for meals

[0165] A user wears smart glasses and captures an image of their lunch (salad, grilled chicken, and rice).

[0166] The smart glasses send the image data to a server.

[0167] The server analyzes the image and determines that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, for a total of 490kcal.

[0168] Real-time display using digital devices

[0169] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are calculated in real time and the information is displayed on the smartphone app and smart glasses.

[0170] Examples of digital device use

[0171] A user orders grilled salmon and salad through a food delivery app.

[0172] The smart glasses receive the order information and send it to the server.

[0173] The server calculates calories and PFC values ​​and displays them in real time on the smart glasses.

[0174] Smart glasses: "Grilled salmon 200kcal, salad 50kcal, total 250kcal" displayed on the HUD.

[0175] Example prompts for generative AI models

[0176] A user orders grilled salmon and salad for lunch and scans it with the smart glasses. Image recognition algorithms calculate the calories and nutritional information and display it to the user in real time.

[0177] By implementing the system in this manner, the user can grasp the contents of his / her meals in real time and appropriately manage the balance of calorie intake and nutrients.

[0178] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0179] Step 1:

[0180] Entering and saving user information

[0181] The user installs the smartphone app and enters basic information (height, weight, body fat percentage, etc.).

[0182] The server receives the entered data and saves it in a database (e.g., MySQL).

[0183] Input: Basic information such as the user's height, weight, and body fat percentage.

[0184] Output: Basic information of the user stored in the database.

[0185] Data processing and calculation: The storage process of the basic information entered.

[0186] Step 2:

[0187] Food image capture and transmission

[0188] The user wears the smart glasses and captures images of their meal.

[0189] The image data acquired by the smart glasses is sent to the server.

[0190] Input: Food image data.

[0191] Output: Image data sent to the server.

[0192] Data processing and calculation: Processing of image data for transmission.

[0193] Step 3:

[0194] Image Recognition and Calorie Counting

[0195] The server uses an image recognition algorithm (such as TensorFlow) to analyze the image data it receives.

[0196] Based on the analysis results, the calorie and PFC information of the food is obtained from the database and the total value is calculated.

[0197] Input: Food image data.

[0198] Output: Calories and PFC information.

[0199] Data processing and calculation: Image analysis and calculation of calories and PFC values.

[0200] Step 4:

[0201] Real-time display

[0202] The server sends the calculation results to the smart glasses and smartphone app.

[0203] The smart glasses and smartphone app display the received data.

[0204] Input: Calories and PFC information.

[0205] Output: Calorie and PFC information displayed on smart glasses and smartphone app.

[0206] Data processing and calculation: Data transmission and display processing.

[0207] Step 5:

[0208] Food delivery app integration

[0209] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are sent to the server.

[0210] Based on the order data received by the server, the calories and PFC values ​​are calculated in real time and sent to the smart glasses and smartphone app.

[0211] Input: Order data from a food delivery app.

[0212] Output: Calories and PFC information.

[0213] Data processing and calculation: Analysis of food delivery information and calculation of calories and PFC values.

[0214] Step 6:

[0215] Save and update final data

[0216] The server continuously updates the user's daily calorie intake and PFC amount and stores them in a database.

[0217] Users can check their intake status through the app.

[0218] Input: Calorie intake and PFC information.

[0219] Output: The updated database.

[0220] Data processing and calculation: Updating and storing intake status.

[0221] The above are the specific processing steps of the system that realizes the application example.

[0222] 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.

[0223] The present invention relates to a system that allows a user to easily manage the calories and PFC (protein, fat, carbohydrates) of their diet using an application and an emotion engine linked to smart glasses, and further recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[0224] Enter basic user information

[0225] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0226] Smart Glasses and Food Scanning

[0227] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the contents of the meal. The acquired image data is sent from the smart glasses to a server.

[0228] Image Recognition and Calorie Counting

[0229] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[0230] Recognizing user emotions with an emotion engine

[0231] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[0232] Calorie and PFC value display

[0233] The server sends the calculation results and emotion data obtained from the emotion engine to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie intake and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0234] Emotional diet management

[0235] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, providing advice such as "refill your energy when you're tired" or "recommend foods that have a relaxing effect when you're under a lot of stress."

[0236] Real-time management

[0237] The smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that can be viewed directly in front of the user's eyes, allowing users to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[0238] Specific examples

[0239] Initial Setup

[0240] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[0241] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[0242] Calculating calories in meals

[0243] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0244] Smart glasses: The camera scans the food and sends the image data to a server.

[0245] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0246] Emotion recognition and display of calories and PFC amount

[0247] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, it also displays food advice that will help them relax.

[0248] Smart Glasses: The HUD displays "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Consume foods that are effective in reducing stress."

[0249] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[0250] The processing flow will be explained below.

[0251] Step 1:

[0252] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[0253] Step 2:

[0254] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on a server.

[0255] Step 3:

[0256] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[0257] Step 4:

[0258] The smart glasses compress the captured image data and send it to a server using Wi-Fi or Bluetooth.

[0259] Step 5:

[0260] The server analyzes the received image data and uses image recognition algorithms to identify the type and quantity of food.

[0261] Step 6:

[0262] The server retrieves the calorie and PFC values ​​of the food from the database based on the identified food and calculates the total value.

[0263] Step 7:

[0264] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is then sent to a server.

[0265] Step 8:

[0266] The server transmits the calculated calories and PFC values, as well as the emotion data obtained from the emotion engine, to the smart glasses and the app.

[0267] Step 9:

[0268] Based on the received calorie and PFC information, the app subtracts the ingested calories and PFC from the appropriate daily calorie and PFC balance, calculates the remaining calorie intake and required PFC amount, and generates dietary advice based on the user's emotional state.

[0269] Step 10:

[0270] The smart glasses display advice based on the calculation results and emotions on a HUD that the user can see in their line of sight, such as "Remaining calorie intake: 2,010kcal, Protein requirement: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[0271] In this way, through a series of processing steps, the user can easily manage their diet and receive advice according to their emotional state, thereby maintaining a healthy lifestyle.

[0272] Example 2

[0273] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0274] In modern society, many people recognize the importance of daily dietary management, but it is difficult to keep track of calorie and nutrient intake. Furthermore, although a user's emotional state often influences food choices and intake, there are no tools to centrally manage these. This makes it difficult for users to manage themselves and maintain a healthy lifestyle and mental stability.

[0275] 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.

[0276] In this invention, the server includes means for inputting and saving basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for analyzing and acquiring the user's emotional state using an emotion engine, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, and means for adjusting the calorie and PFC display and dietary advice based on the user's emotional state. This allows the user to easily understand their calorie and nutrient intake and manage their diet in accordance with their emotional state.

[0277] "Basic user information" refers to personal data necessary for calculating calories and PFC balance, such as the user's height, weight, and body fat percentage.

[0278] "Image recognition algorithm" is a programming technology for recognizing the type and quantity of food and analyzing its calorie and PFC values.

[0279] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0280] "Appropriate daily calorie intake and PFC balance" refers to the balance of calories, protein, fat, and carbohydrates required for the user to maintain a healthy lifestyle.

[0281] "Display in real time" means that information is displayed immediately in a state that the user can see directly in front of their eyes.

[0282] "Dietary advice" is a recommendation to encourage better dietary choices based on the user's emotional state.

[0283] "Smart glasses" are devices worn by users that use a camera to scan the contents of a meal and display information on a HUD (Head-Up Display).

[0284] A "calorie" is a unit of heat obtained from food and used by the body as energy.

[0285] "PFC" is an abbreviation for protein, fat, and carbohydrate, which are the major nutrients found in food.

[0286] The present invention provides a system that allows users to easily manage their dietary calories and PFC (protein, fat, carbohydrates) using an application and emotion engine linked to smart glasses, and also recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[0287] Enter basic user information

[0288] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0289] Smart Glasses and Food Scanning

[0290] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the food contents. The acquired image data is sent from the smart glasses to a server.

[0291] Image Recognition and Calorie Counting

[0292] The server receives the image data and analyzes the type and quantity of food using an image recognition algorithm, such as TensorFlow or OpenCV. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[0293] Recognizing user emotions with an emotion engine

[0294] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[0295] Calorie and PFC value display

[0296] The server sends the calculation results and emotional data to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0297] Emotional diet management

[0298] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, offering advice such as "refuel when you're tired" or "choose foods that will help you relax when you're stressed."

[0299] Real-time management

[0300] Smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that users can see directly in front of their eyes, allowing them to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[0301] Specific examples

[0302] Initial Setup

[0303] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[0304] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[0305] Calculating calories in meals

[0306] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0307] Smart glasses: The camera scans the food and sends the image data to a server.

[0308] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0309] Emotion recognition and display of calories and PFC amount

[0310] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, the app also advises them to eat foods that have a relaxing effect.

[0311] Smart Glasses: The HUD displays the following advice: "Remaining calories: 2,010kcal, Protein requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[0312] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[0313] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0314] Step 1:

[0315] Users install the smartphone app and enter basic information.

[0316] Specific operation: The user launches the app and enters their height, weight, body fat percentage, etc. on the profile screen.

[0317] Input: Personal data such as height, weight, and body fat percentage

[0318] Data processing: The app formats the entered information for sending to a database.

[0319] Output: Basic user information in JSON format

[0320] Step 2:

[0321] The app sends the user's basic information to the server.

[0322] Specific behavior: The app sends JSON formatted data to the server as an HTTP request.

[0323] Input: Basic user information data in JSON format

[0324] Data calculation: The server analyzes the received data and stores it in a database.

[0325] Output: Basic information stored in the database

[0326] Step 3:

[0327] The server calculates the appropriate daily calorie intake and PFC balance.

[0328] Specific operation: The server retrieves user information from the database and uses an algorithm to calculate basal metabolic rate and daily calorie intake.

[0329] Input: User data such as height, weight, and body fat percentage

[0330] Data calculation: Calculation of basal metabolic rate and proper calorie balance

[0331] Output: Daily calorie intake and PFC balance

[0332] Step 4:

[0333] When the user eats, they wear the smart glasses and the camera scans the food.

[0334] Specific operation: Point the smart glasses camera at the food and take a picture of it.

[0335] Input: Food image data

[0336] Data processing: The smart glasses format the acquired image data for transmission to the server.

[0337] Output: Image data is prepared for transmission to the server

[0338] Step 5:

[0339] The server receives the image data and uses image recognition algorithms to analyze the type and quantity of food.

[0340] Specific operation: The server uses TensorFlow and OpenCV to identify the type and quantity of food from the image.

[0341] Input: Food image data

[0342] Data processing: Food analysis using image recognition algorithms

[0343] Output: Analyzed food type and quantity data

[0344] Step 6:

[0345] The server retrieves the calorie and PFC information for each food item from the database and calculates the total value.

[0346] Specific operation: The server refers to the food database and obtains the calories and PFC value for each food item.

[0347] Input: Data on the type and quantity of food analyzed

[0348] Data calculation: Calculate the total calories and PFC value of each food.

[0349] Output: Total calories and PFC value

[0350] Step 7:

[0351] The smart glasses and app use an emotion engine to analyze the user's emotional state and send the data to a server.

[0352] How it works: The app and smart glasses capture the user's facial expressions and tone of voice and analyze emotional data.

[0353] Input: User's facial expression data, voice data

[0354] Data processing: Real-time analysis using emotion engine

[0355] Output: Parsed emotion data

[0356] Step 8:

[0357] The server sends the calculation results and emotion data to the smart glasses and app.

[0358] Specific operation: The server sends the total calories, PFC value, and emotion data to the smart glasses and app.

[0359] Input: Total calories, PFC value, emotional data

[0360] Data processing: Format of transmitted data

[0361] Output: Data displayed on the smart glasses and in the app

[0362] Step 9:

[0363] The app and smart glasses provide dietary advice that reflects the user's emotions.

[0364] How it works: The app and smart glasses adjust the calorie and PFC display and provide dietary advice based on the user's emotional state.

[0365] Input: Total calories, PFC value, emotional data

[0366] Data Computing: Emotion-Based Advice Generation

[0367] Output: Meal advice displayed on HUD or app

[0368] Step 10:

[0369] The smart glasses display real-time advice on the HUD.

[0370] Specific operation: The smart glasses display advice based on calculation results and emotions on the HUD.

[0371] Input: Dietary advice data

[0372] Data processing: HUD display format

[0373] Output: Advice information at your fingertips

[0374] In this way, users can receive real-time calorie and nutrient management and emotion-based dietary advice.

[0375] (Application example 2)

[0376] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0377] Modern dietary management faces the challenge of easily and effectively managing calorie and nutrient intake. When choosing meals at restaurants or brick-and-mortar stores, it is difficult to obtain real-time nutritional information on the foods on offer, making it difficult to maintain appropriate intake. Dietary management that takes into account the user's emotional state is also important, and this lack of awareness needs to be addressed.

[0378] 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.

[0379] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for recognizing the user's emotions and reflecting them in dietary management, and visual display means for presenting information in real time when selecting foods in a physical store. This makes it possible to obtain calorie and nutrient information in real time even when selecting meals in a physical store, and also enables appropriate dietary management that takes the user's emotional state into consideration.

[0380] "User" refers to a person who uses the system to manage their diet.

[0381] "Basic information" refers to personal data such as height, weight, and body fat percentage entered by the user.

[0382] "Image recognition algorithm" refers to a calculation method for analyzing image data acquired by a camera and identifying the type and quantity of food.

[0383] "Calories" refers to the amount of energy contained in food and is expressed in kcal.

[0384] "PFC" refers to the three major nutrients: protein, fat, and carbohydrates.

[0385] "Smart glasses" are eyeglass-type wearable devices that incorporate functions such as a camera and a head-up display (HUD).

[0386] "Server" means a computer system that processes information sent by users and stores and provides necessary data.

[0387] An "emotion engine" refers to software or algorithms that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[0388] "Visual display device" refers to a display device that allows a user to view information in real time.

[0389] "Brick and mortar" refers to a food and beverage establishment that is located in a physical location, such as a cafe or restaurant.

[0390] To implement this invention, a user must first install an application on their smartphone and enter their basic information (height, weight, body fat percentage, etc.) Based on this basic information, the application calculates the appropriate daily calorie intake and PFC balance for each user and saves the results on a server.

[0391] Next, the user wears the smart glasses while eating. The smart glasses are equipped with a camera that can scan the contents of the meal. The captured image data is sent to a server in real time. The server uses an image recognition algorithm (e.g., TensorFlow or OpenCV) to analyze the type and quantity of food, retrieve the calorie and PFC values ​​of each food from a database, and calculate the total value.

[0392] Furthermore, the smart glasses are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is sent to a server, which then generates appropriate dietary advice based on this data. For example, if the user is feeling stressed, it will recommend foods that have a relaxing effect.

[0393] The calculation results and emotion analysis data from the server are displayed on a smartphone app and the smart glasses' HUD (head-up display). Users can check their calorie intake and PFC balance, as well as advice based on their emotional state, in real time while eating.

[0394] Examples:

[0395] If a user chooses a "chicken sandwich" and a "coffee" at a cafe, they put on the smart glasses and scan the food items. The server calculates the calories and PFC of the food items and displays them on the smart glasses' HUD as "Chicken sandwich: 350kcal, protein: 20g, fat: 10g, carbohydrates: 40g" and "Coffee (black): 5kcal, protein: 0g, fat: 0g, carbohydrates: 0g." At the same time, if the emotion engine determines that the user is looking for a relaxing experience, the HUD will also display advice such as "The chicken sandwich is a good choice, but how about some herbal tea for a relaxing effect?"

[0396] Example prompt sentence:

[0397] "Please analyze the types and quantities of food in this image. I'm looking for information on calories, protein, fat, and carbohydrates for each food item."

[0398] The system allows users to make healthy and emotionally relevant food choices in brick-and-mortar restaurants.

[0399] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0400] Step 1:

[0401] The user installs the application on their smartphone and enters basic information (height, weight, body fat percentage, etc.).

[0402] Input: User information such as height, weight, and body fat percentage

[0403] Output: Data on appropriate daily calorie intake and PFC balance

[0404] How it works: Based on the basic information entered, the application calculates the basal metabolic rate, daily calorie intake and PFC balance, and saves them on the server.

[0405] Step 2:

[0406] The user wears the smart glasses while eating, and the camera in the smart glasses scans the contents of the meal.

[0407] Input: Image data of meal contents

[0408] Output: Image data sent to the server

[0409] How it works: The camera in the smart glasses captures the food you eat and sends the image data to a server in real time.

[0410] Step 3:

[0411] The server uses an image recognition algorithm to analyze the transmitted image data.

[0412] Input: Image data of meal contents

[0413] Output: Data on food type and quantity

[0414] How it works: The server uses image recognition algorithms (such as TensorFlow or OpenCV) to identify the type and quantity of food and retrieves the calorie and PFC values ​​for each from a database.

[0415] Step 4:

[0416] The server adds up the calories and PFC values ​​of the food items it has acquired and sends the results to the smart glasses and smartphone app.

[0417] Input: data on food type and quantity, calories and PFC values

[0418] Output: Total calories and PFC value data

[0419] How it works: The server sums the calories and PFC values ​​of each food item retrieved from the database and sends the results to the smart glasses and smartphone app.

[0420] Step 5:

[0421] The smart glasses and app use an emotion engine to analyze the user's emotional state and send it to the server.

[0422] Input: User facial expressions and tone of voice

[0423] Output: Data about emotional state

[0424] How it works: The emotion engine analyzes the user's facial expressions and tone of voice and sends that data to the server.

[0425] Step 6:

[0426] The server generates appropriate dietary management advice for the user based on the emotion data.

[0427] Input: Data about emotional state

[0428] Output: Dietary advice

[0429] Operation: The server generates the necessary dietary advice (e.g., recommendations for foods with a relaxing effect) based on the emotional data.

[0430] Step 7:

[0431] The server displays the calculation results and emotion analysis data on the smart glasses' HUD and smartphone app.

[0432] Input: Total calories and PFC value data, dietary advice

[0433] Output: Information displayed on the smart glasses HUD and smartphone app

[0434] How it works: The server sends the calculation results and generated advice to the smart glasses HUD and smartphone app, allowing users to view the information in real time.

[0435] Through these steps, users can make their dining choices in brick-and-mortar stores healthier and more emotionally relevant.

[0436] 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.

[0437] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0438] 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.

[0439] [Second embodiment]

[0440] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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).

[0446] 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.

[0447] 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.

[0448] 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.

[0449] 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.

[0450] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0451] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0452] The present invention relates to a system that allows users to easily manage the calories and PFC (protein, fat, carbohydrates) of their meals using an application linked to smart glasses. The following describes in detail the embodiments of this system.

[0453] Enter basic user information

[0454] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0455] Smart Glasses and Food Scanning

[0456] The user wears the smart glasses while eating. The camera in the smart glasses captures images of the meal. The image data captured by the camera is sent from the smart glasses to a server.

[0457] Image Recognition and Calorie Counting

[0458] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, it retrieves the calorie and PFC information for each food item from a database and totals them.

[0459] Calorie and PFC value display

[0460] The server sends the calculation results to the smart glasses and the app, which uses the received data to subtract the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0461] Real-time management

[0462] The smart glasses display the calculation results on a HUD (Head-Up Display) so that the user can check them directly in front of their eyes, allowing them to manage calories and nutrients in real time every time they eat.

[0463] Specific examples

[0464] Initial Setup

[0465] User: For example, enter your height (170cm), weight (70kg), and body fat percentage (20%) into the app.

[0466] App: Based on this, calculate your basal metabolic rate and set your daily calorie intake to 2,500 kcal. Save this information on the server.

[0467] Calculating calories in meals

[0468] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0469] Smart glasses: The camera scans the food and sends the image data to a server.

[0470] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0471] Display of calorie intake and PFC amount

[0472] App: Calculate the remaining calorie intake as 2,010 kcal and update the required PFC amount at the same time.

[0473] Smart Glasses: Display "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" on the HUD.

[0474] By implementing the system in this manner, the user can easily manage their daily diet and help maintain a healthy lifestyle.

[0475] The processing flow will be explained below.

[0476] Step 1:

[0477] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[0478] Step 2:

[0479] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on the server.

[0480] Step 3:

[0481] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[0482] Step 4:

[0483] The smart glasses compress the captured image data and send it to a server via Wi-Fi or Bluetooth.

[0484] Step 5:

[0485] The server analyzes the received image data and uses an image recognition algorithm to identify the type and quantity of food.

[0486] Step 6:

[0487] The server retrieves the calorie and PFC values ​​of the food from the database based on the recognized food, and calculates the total value.

[0488] Step 7:

[0489] The server encodes the calculation results in JSON format and sends them to the smart glasses and app using an API.

[0490] Step 8:

[0491] Based on the calorie and PFC information received, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates the remaining calories available for intake and the amount of PFC required.

[0492] Step 9:

[0493] The smart glasses display the calculation results on the HUD and show the user in real time the following format: "Remaining calories: XXXX kcal, Protein requirements: XX g, Fat: XX g, Carbohydrates: XX g."

[0494] In this way, through a series of processing steps, users can easily manage their diet and maintain a healthy lifestyle.

[0495] Example 1

[0496] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0497] In modern society, effective dietary management is an important element of maintaining health and dieting for many people. However, managing calories and nutritional components (protein, fat, carbohydrates) requires checking the calorie content of each individual ingredient, which is time-consuming and laborious. Furthermore, real-time management is difficult, and it often does not become a continuous habit. Therefore, there is a need for a system that allows users to easily and accurately manage their own dietary content.

[0498] 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.

[0499] In this invention, the server includes a means for inputting and storing basic information such as a user's height, weight, and body fat percentage, a means for analyzing the type and amount of food using an image recognition algorithm to calculate calorie and nutrient values, and a means for calculating and displaying the appropriate daily calorie intake and nutrient balance. This allows users to easily record their diet using a smart device and check the calorie and nutrient balance on the spot.

[0500] "Basic information such as the user's height, weight, and body fat percentage" is data that indicates the user's physical characteristics, and is basic information for individual calorie balance and nutritional management.

[0501] An "image recognition algorithm" is a technology that analyzes image data acquired by a camera or other device and automatically identifies specific objects or features, and is used to identify the type and quantity of food.

[0502] "Calorie and nutritional values" is data that indicates the amount of energy (calories) and major nutrients (protein, fat, carbohydrates) contained in a food.

[0503] "Appropriate daily calorie intake and nutritional balance" refers to the total calories and balance of major nutrients that should be consumed in a day, calculated based on the user's physical characteristics and activity level.

[0504] "Wearable device" is a general term for electronic devices that can be worn, and in this case refers to a device that has the function of acquiring image data of food.

[0505] A "server" is a computer system that receives, stores, and analyzes data sent by users over a network and provides the necessary information.

[0506] This invention relates to a system that allows a user to easily and accurately manage the calories and nutritional components (protein, fat, carbohydrates) of their meals in order to maintain a healthy lifestyle. The following describes in detail the mode for implementing this system.

[0507] Enter basic user information

[0508] First, users download and install the smartphone app. When they launch the app, they are prompted to enter basic personal information such as height, weight, and body fat percentage. This data is used to calculate each user's calorie consumption and nutritional balance. The entered information is sent to a server via the app and saved.

[0509] Smart Glasses and Food Scanning

[0510] The user wears smart glasses as a wearable device while eating. The smart glasses are equipped with a high-resolution camera that captures images of the food. The captured image data is sent to a server in real time via the smart glasses.

[0511] Image Recognition and Calorie Counting

[0512] The server receives the transmitted image data and analyzes the type and quantity of food using an image recognition algorithm, which uses, for example, "image recognition software" to analyze the food pixel by pixel and identify the calorie and nutritional information for each food item.

[0513] Calculation and display of daily calorie and nutritional balance

[0514] Based on the analysis results, the server extracts calorie and nutritional information for each food item from the database, adds them up, calculates the appropriate daily calorie intake and nutritional balance, and sends the results to the smart glasses and smartphone app.

[0515] Display of remaining calorie intake and nutritional information in real time

[0516] The smart glasses display the calculation results using a HUD (Head-Up Display), allowing users to manage calories and nutritional information in real time with each meal. The app also calculates the remaining calories and nutritional information available for the day and displays it for easy viewing by the user.

[0517] Specific examples

[0518] Initial Setup

[0519] For example, the user enters their height of 170 cm, weight of 70 kg, and body fat percentage of 20% into the app.

[0520] The app calculates the basal metabolic rate based on the input data and sets the appropriate daily calorie intake at 2,500 kcal. This information is stored on a server.

[0521] Calculating calories in meals

[0522] The user wears the smart glasses while eating a lunch of salad, grilled chicken, and rice.

[0523] The smart glasses use a camera to scan the food and send the image data to a server.

[0524] Using an image recognition algorithm, the server determines that the salad is 40 kcal, the grilled chicken is 250 kcal, and the rice is 200 kcal, totaling 490 kcal. This is then sent to the app and smart glasses.

[0525] Display of calorie intake and nutritional information

[0526] The app will calculate the remaining calorie intake as 2,010 kcal and simultaneously update the nutritional requirements.

[0527] The smart glasses display the following information on the HUD: "Remaining calories: 2,010kcal, required protein: 80g, fat: 60g, carbohydrates: 250g."

[0528] Prompt Sentence Examples

[0529] Examples of input prompts for a generative AI model include:

[0530] "Please explain the specific usage of a system that uses a wearable device to manage the calories and nutritional components (protein, fat, carbohydrates) of meals."

[0531] By implementing the present invention in the above manner, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle.

[0532] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0533] Step 1:

[0534] Users download and install the smartphone app. When they launch the app, a screen appears where they can enter basic information such as their height, weight, and body fat percentage. The information they enter is sent to a server via the app and saved.

[0535] Input: Basic information such as height, weight, and body fat percentage

[0536] Output: Basic information data stored on the server

[0537] Step 2:

[0538] The server calculates the appropriate daily calorie intake and nutritional balance based on the received basic information. This calculation uses a basal metabolic rate calculation algorithm. The calculation results are stored in the server database.

[0539] Input: User's basic information (height, weight, body fat percentage, etc.)

[0540] Output: Proper daily calorie intake and nutritional balance

[0541] Step 3:

[0542] When a user eats, they wear smart glasses as a wearable device. The smart glasses' camera captures images of the food they are eating and transmits the image data to a server in real time.

[0543] Input: Food image data acquired through a camera

[0544] Output: Food image data sent to the server

[0545] Step 4:

[0546] The server analyzes the type and quantity of food using an image recognition algorithm based on the received image data. This algorithm uses, for example, "image recognition software." Based on the data obtained by image recognition, the server retrieves calorie and nutritional information for each food from a database.

[0547] Input: Food image data

[0548] Output: Food type and quantity, along with corresponding calorie and nutritional information

[0549] Step 5:

[0550] The server calculates the calorie and nutritional information for each food based on the analysis results. It then compares the calorie and nutritional information with the recommended daily intake and subtracts the amount already consumed. The calculation results are sent from the server to the smart glasses and smartphone app.

[0551] Input: Food type and quantity, as well as calorie and nutritional information

[0552] Output: Calories consumed and remaining, and nutritional information

[0553] Step 6:

[0554] The smart glasses use a HUD (Head-Up Display) to display the calculation results in real time, allowing users to check the calorie and nutritional balance of each meal. The same data is also displayed on a smartphone app, making daily dietary management easier.

[0555] Input: Calorie and nutritional information sent from the server

[0556] Output: Calorie and nutritional information displayed on HUD and smartphone app

[0557] (Application example 1)

[0558] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0559] As modern consumers lead busy lives, there is a growing need for easy and accurate management of the calories and PFC (protein, fat, carbohydrates) of their meals. While the popularity of food delivery services has increased options, making healthy choices can be challenging. Therefore, there is a need for a system that provides real-time calorie and PFC information to help users maintain healthy eating habits.

[0560] 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.

[0561] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calories and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying in real time the calories and PFC values ​​of foods ordered by the user through a digital device, and means for using an image capture device to capture and transmit images of the foods to the server, thereby enabling the user to understand the contents of their meals in real time and appropriately manage their calorie intake and nutrient balance.

[0562] The "means for inputting and storing basic user information" refers to a mechanism for inputting basic information such as a user's height, weight, and body fat percentage via a digital device and storing that data on a server.

[0563] The "means for calculating the calorie and PFC values ​​of food using an image recognition algorithm" is an algorithm that analyzes the type and quantity of food from the captured image and calculates the calories, protein, fat, and carbohydrates by referring to a database.

[0564] "Means for calculating and displaying the appropriate daily calorie intake and PFC balance" refers to a mechanism that calculates the appropriate daily calorie intake and PFC (protein, lipid, carbohydrate) balance based on the user's basic information and displays it to the user.

[0565] The "means for displaying the remaining calorie and PFC intake amount for the day in real time" is a mechanism that calculates the remaining calorie and PFC intake amount from the calorie and PFC intake amount for the day in real time and displays them to the user.

[0566] "Means for calculating and displaying in real time the calorie and PFC values ​​of food ordered by a user through a digital device" refers to a mechanism that calculates the calories and PFC values ​​of food ordered using a food delivery application and displays the results in real time.

[0567] "Means for using an image capture device to capture images of food and transmit them to a server" refers to a mechanism for using a digital device with a camera to capture images of food and transmit the data to a server.

[0568] This invention is a system that allows users to easily manage dietary calories and PFC (protein, fat, carbohydrates) by linking with a digital device. The system includes means for inputting and saving basic user information, means for calculating food calories and PFC values ​​using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying the calorie and PFC values ​​of foods ordered by the user through the digital device in real time, and means for using an image capture device to capture images of foods and send them to a server.

[0569] Each means of this system has the following specific configuration.

[0570] server

[0571] The server contains a database (e.g., MySQL) for storing basic user information, software (e.g., TensorFlow) for running image recognition algorithms, and a system for real-time communication (e.g., Firebase). Basic information (e.g., height, weight, body fat percentage) entered by the user on their smartphone is sent to the server and stored in the database.

[0572] Example of user information entry

[0573] A user uses a smartphone app to enter their height of 170 cm, weight of 70 kg, and body fat percentage of 20%.

[0574] The server receives this information and stores it in a database.

[0575] Image Recognition and Calorie Counting

[0576] The server receives image data of food sent from smart glasses or smartphone cameras, analyzes the type and quantity of food using image recognition algorithms such as TensorFlow, and based on the analysis results, retrieves the calorie and PFC information of the food from the database and calculates the total value.

[0577] Example of calorie calculation for meals

[0578] A user wears smart glasses and captures an image of their lunch (salad, grilled chicken, and rice).

[0579] The smart glasses send the image data to a server.

[0580] The server analyzes the image and determines that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, for a total of 490kcal.

[0581] Real-time display using digital devices

[0582] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are calculated in real time and the information is displayed on the smartphone app and smart glasses.

[0583] Examples of digital device use

[0584] A user orders grilled salmon and salad through a food delivery app.

[0585] The smart glasses receive the order information and send it to the server.

[0586] The server calculates calories and PFC values ​​and displays them in real time on the smart glasses.

[0587] Smart glasses: "Grilled salmon 200kcal, salad 50kcal, total 250kcal" displayed on the HUD.

[0588] Example prompts for generative AI models

[0589] A user orders grilled salmon and salad for lunch and scans it with the smart glasses. Image recognition algorithms calculate the calories and nutritional information and display it to the user in real time.

[0590] By implementing the system in this manner, the user can grasp the contents of his / her meals in real time and appropriately manage the balance of calorie intake and nutrients.

[0591] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0592] Step 1:

[0593] Entering and saving user information

[0594] The user installs the smartphone app and enters basic information (height, weight, body fat percentage, etc.).

[0595] The server receives the entered data and saves it in a database (e.g., MySQL).

[0596] Input: Basic information such as the user's height, weight, and body fat percentage.

[0597] Output: Basic information of the user stored in the database.

[0598] Data processing and calculation: The storage process of the basic information entered.

[0599] Step 2:

[0600] Food image capture and transmission

[0601] The user wears the smart glasses and captures images of their meal.

[0602] The image data acquired by the smart glasses is sent to the server.

[0603] Input: Food image data.

[0604] Output: Image data sent to the server.

[0605] Data processing and calculation: Processing of image data for transmission.

[0606] Step 3:

[0607] Image Recognition and Calorie Counting

[0608] The server uses an image recognition algorithm (such as TensorFlow) to analyze the image data it receives.

[0609] Based on the analysis results, the calorie and PFC information of the food is obtained from the database and the total value is calculated.

[0610] Input: Food image data.

[0611] Output: Calories and PFC information.

[0612] Data processing and calculation: Image analysis and calculation of calories and PFC values.

[0613] Step 4:

[0614] Real-time display

[0615] The server sends the calculation results to the smart glasses and smartphone app.

[0616] The smart glasses and smartphone app display the received data.

[0617] Input: Calories and PFC information.

[0618] Output: Calorie and PFC information displayed on smart glasses and smartphone app.

[0619] Data processing and calculation: Data transmission and display processing.

[0620] Step 5:

[0621] Food delivery app integration

[0622] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are sent to the server.

[0623] Based on the order data received by the server, the calories and PFC values ​​are calculated in real time and sent to the smart glasses and smartphone app.

[0624] Input: Order data from a food delivery app.

[0625] Output: Calories and PFC information.

[0626] Data processing and calculation: Analysis of food delivery information and calculation of calories and PFC values.

[0627] Step 6:

[0628] Save and update final data

[0629] The server continuously updates the user's daily calorie intake and PFC amount and stores them in a database.

[0630] Users can check their intake status through the app.

[0631] Input: Calorie intake and PFC information.

[0632] Output: The updated database.

[0633] Data processing and calculation: Updating and storing intake status.

[0634] The above are the specific processing steps of the system that realizes the application example.

[0635] 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.

[0636] The present invention relates to a system that allows a user to easily manage the calories and PFC (protein, fat, carbohydrates) of their diet using an application and an emotion engine linked to smart glasses, and further recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[0637] Enter basic user information

[0638] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0639] Smart Glasses and Food Scanning

[0640] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the contents of the meal. The acquired image data is sent from the smart glasses to a server.

[0641] Image Recognition and Calorie Counting

[0642] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[0643] Recognizing user emotions with an emotion engine

[0644] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[0645] Calorie and PFC value display

[0646] The server sends the calculation results and emotion data obtained from the emotion engine to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie intake and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0647] Emotional diet management

[0648] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, providing advice such as "refill your energy when you're tired" or "recommend foods that have a relaxing effect when you're under a lot of stress."

[0649] Real-time management

[0650] The smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that can be viewed directly in front of the user's eyes, allowing users to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[0651] Specific examples

[0652] Initial Setup

[0653] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[0654] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[0655] Calculating calories in meals

[0656] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0657] Smart glasses: The camera scans the food and sends the image data to a server.

[0658] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0659] Emotion recognition and display of calories and PFC amount

[0660] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, it also displays food advice that will help them relax.

[0661] Smart Glasses: The HUD displays "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Consume foods that are effective in reducing stress."

[0662] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[0663] The processing flow will be explained below.

[0664] Step 1:

[0665] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[0666] Step 2:

[0667] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on a server.

[0668] Step 3:

[0669] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[0670] Step 4:

[0671] The smart glasses compress the captured image data and send it to a server using Wi-Fi or Bluetooth.

[0672] Step 5:

[0673] The server analyzes the received image data and uses image recognition algorithms to identify the type and quantity of food.

[0674] Step 6:

[0675] The server retrieves the calorie and PFC values ​​of the food from the database based on the identified food and calculates the total value.

[0676] Step 7:

[0677] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is then sent to a server.

[0678] Step 8:

[0679] The server transmits the calculated calories and PFC values, as well as the emotion data obtained from the emotion engine, to the smart glasses and the app.

[0680] Step 9:

[0681] Based on the received calorie and PFC information, the app subtracts the ingested calories and PFC from the appropriate daily calorie and PFC balance, calculates the remaining calorie intake and required PFC amount, and generates dietary advice based on the user's emotional state.

[0682] Step 10:

[0683] The smart glasses display advice based on the calculation results and emotions on a HUD that the user can see in their line of sight, such as "Remaining calorie intake: 2,010kcal, Protein requirement: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[0684] In this way, through a series of processing steps, the user can easily manage their diet and receive advice according to their emotional state, thereby maintaining a healthy lifestyle.

[0685] Example 2

[0686] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0687] In modern society, many people recognize the importance of daily dietary management, but it is difficult to keep track of calorie and nutrient intake. Furthermore, although a user's emotional state often influences food choices and intake, there are no tools to centrally manage these. This makes it difficult for users to manage themselves and maintain a healthy lifestyle and mental stability.

[0688] 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.

[0689] In this invention, the server includes means for inputting and saving basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for analyzing and acquiring the user's emotional state using an emotion engine, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, and means for adjusting the calorie and PFC display and dietary advice based on the user's emotional state. This allows the user to easily understand their calorie and nutrient intake and manage their diet in accordance with their emotional state.

[0690] "Basic user information" refers to personal data necessary for calculating calories and PFC balance, such as the user's height, weight, and body fat percentage.

[0691] "Image recognition algorithm" is a programming technology for recognizing the type and quantity of food and analyzing its calorie and PFC values.

[0692] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[0693] "Appropriate daily calorie intake and PFC balance" refers to the balance of calories, protein, fat, and carbohydrates required for the user to maintain a healthy lifestyle.

[0694] "Display in real time" means that information is displayed immediately in a state that the user can see directly in front of their eyes.

[0695] "Dietary advice" is a recommendation to encourage better dietary choices based on the user's emotional state.

[0696] "Smart glasses" are devices worn by users that use a camera to scan the contents of a meal and display information on a HUD (Head-Up Display).

[0697] A "calorie" is a unit of heat obtained from food and used by the body as energy.

[0698] "PFC" is an abbreviation for protein, fat, and carbohydrate, which are the major nutrients found in food.

[0699] The present invention provides a system that allows users to easily manage their dietary calories and PFC (protein, fat, carbohydrates) using an application and emotion engine linked to smart glasses, and also recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[0700] Enter basic user information

[0701] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0702] Smart Glasses and Food Scanning

[0703] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the food contents. The acquired image data is sent from the smart glasses to a server.

[0704] Image Recognition and Calorie Counting

[0705] The server receives the image data and analyzes the type and quantity of food using an image recognition algorithm, such as TensorFlow or OpenCV. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[0706] Recognizing user emotions with an emotion engine

[0707] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[0708] Calorie and PFC value display

[0709] The server sends the calculation results and emotional data to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0710] Emotional diet management

[0711] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, offering advice such as "refuel when you're tired" or "choose foods that will help you relax when you're stressed."

[0712] Real-time management

[0713] Smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that users can see directly in front of their eyes, allowing them to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[0714] Specific examples

[0715] Initial Setup

[0716] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[0717] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[0718] Calculating calories in meals

[0719] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0720] Smart glasses: The camera scans the food and sends the image data to a server.

[0721] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0722] Emotion recognition and display of calories and PFC amount

[0723] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, the app also advises them to eat foods that have a relaxing effect.

[0724] Smart Glasses: The HUD displays the following advice: "Remaining calories: 2,010kcal, Protein requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[0725] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[0726] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0727] Step 1:

[0728] Users install the smartphone app and enter basic information.

[0729] Specific operation: The user launches the app and enters their height, weight, body fat percentage, etc. on the profile screen.

[0730] Input: Personal data such as height, weight, and body fat percentage

[0731] Data processing: The app formats the entered information for sending to a database.

[0732] Output: Basic user information in JSON format

[0733] Step 2:

[0734] The app sends the user's basic information to the server.

[0735] Specific behavior: The app sends JSON formatted data to the server as an HTTP request.

[0736] Input: Basic user information data in JSON format

[0737] Data calculation: The server analyzes the received data and stores it in a database.

[0738] Output: Basic information stored in the database

[0739] Step 3:

[0740] The server calculates the appropriate daily calorie intake and PFC balance.

[0741] Specific operation: The server retrieves user information from the database and uses an algorithm to calculate basal metabolic rate and daily calorie intake.

[0742] Input: User data such as height, weight, and body fat percentage

[0743] Data calculation: Calculation of basal metabolic rate and proper calorie balance

[0744] Output: Daily calorie intake and PFC balance

[0745] Step 4:

[0746] When the user eats, they wear the smart glasses and the camera scans the food.

[0747] Specific operation: Point the smart glasses camera at the food and take a picture of it.

[0748] Input: Food image data

[0749] Data processing: The smart glasses format the acquired image data for transmission to the server.

[0750] Output: Image data is prepared for transmission to the server

[0751] Step 5:

[0752] The server receives the image data and uses image recognition algorithms to analyze the type and quantity of food.

[0753] Specific operation: The server uses TensorFlow and OpenCV to identify the type and quantity of food from the image.

[0754] Input: Food image data

[0755] Data processing: Food analysis using image recognition algorithms

[0756] Output: Analyzed food type and quantity data

[0757] Step 6:

[0758] The server retrieves the calorie and PFC information for each food item from the database and calculates the total value.

[0759] Specific operation: The server refers to the food database and obtains the calories and PFC value for each food item.

[0760] Input: Data on the type and quantity of food analyzed

[0761] Data calculation: Calculate the total calories and PFC value of each food.

[0762] Output: Total calories and PFC value

[0763] Step 7:

[0764] The smart glasses and app use an emotion engine to analyze the user's emotional state and send the data to a server.

[0765] How it works: The app and smart glasses capture the user's facial expressions and tone of voice and analyze emotional data.

[0766] Input: User's facial expression data, voice data

[0767] Data processing: Real-time analysis using emotion engine

[0768] Output: Parsed emotion data

[0769] Step 8:

[0770] The server sends the calculation results and emotion data to the smart glasses and app.

[0771] Specific operation: The server sends the total calories, PFC value, and emotion data to the smart glasses and app.

[0772] Input: Total calories, PFC value, emotional data

[0773] Data processing: Format of transmitted data

[0774] Output: Data displayed on the smart glasses and in the app

[0775] Step 9:

[0776] The app and smart glasses provide dietary advice that reflects the user's emotions.

[0777] How it works: The app and smart glasses adjust the calorie and PFC display and provide dietary advice based on the user's emotional state.

[0778] Input: Total calories, PFC value, emotional data

[0779] Data Computing: Emotion-Based Advice Generation

[0780] Output: Meal advice displayed on HUD or app

[0781] Step 10:

[0782] The smart glasses display real-time advice on the HUD.

[0783] Specific operation: The smart glasses display advice based on calculation results and emotions on the HUD.

[0784] Input: Dietary advice data

[0785] Data processing: HUD display format

[0786] Output: Advice information at your fingertips

[0787] In this way, users can receive real-time calorie and nutrient management and emotion-based dietary advice.

[0788] (Application example 2)

[0789] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0790] Modern dietary management faces the challenge of easily and effectively managing calorie and nutrient intake. When choosing meals at restaurants or brick-and-mortar stores, it is difficult to obtain real-time nutritional information on the foods on offer, making it difficult to maintain appropriate intake. Dietary management that takes into account the user's emotional state is also important, and this lack of awareness needs to be addressed.

[0791] 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.

[0792] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for recognizing the user's emotions and reflecting them in dietary management, and visual display means for presenting information in real time when selecting foods in a physical store. This makes it possible to obtain calorie and nutrient information in real time even when selecting meals in a physical store, and also enables appropriate dietary management that takes the user's emotional state into consideration.

[0793] "User" refers to a person who uses the system to manage their diet.

[0794] "Basic information" refers to personal data such as height, weight, and body fat percentage entered by the user.

[0795] "Image recognition algorithm" refers to a calculation method for analyzing image data acquired by a camera and identifying the type and quantity of food.

[0796] "Calories" refers to the amount of energy contained in food and is expressed in kcal.

[0797] "PFC" refers to the three major nutrients: protein, fat, and carbohydrates.

[0798] "Smart glasses" are eyeglass-type wearable devices that incorporate functions such as a camera and a head-up display (HUD).

[0799] "Server" means a computer system that processes information sent by users and stores and provides necessary data.

[0800] An "emotion engine" refers to software or algorithms that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[0801] "Visual display device" refers to a display device that allows a user to view information in real time.

[0802] "Brick and mortar" refers to a food and beverage establishment that is located in a physical location, such as a cafe or restaurant.

[0803] To implement this invention, a user must first install an application on their smartphone and enter their basic information (height, weight, body fat percentage, etc.) Based on this basic information, the application calculates the appropriate daily calorie intake and PFC balance for each user and saves the results on a server.

[0804] Next, the user wears the smart glasses while eating. The smart glasses are equipped with a camera that can scan the contents of the meal. The captured image data is sent to a server in real time. The server uses an image recognition algorithm (e.g., TensorFlow or OpenCV) to analyze the type and quantity of food, retrieve the calorie and PFC values ​​of each food from a database, and calculate the total value.

[0805] Furthermore, the smart glasses are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is sent to a server, which then generates appropriate dietary advice based on this data. For example, if the user is feeling stressed, it will recommend foods that have a relaxing effect.

[0806] The calculation results and emotion analysis data from the server are displayed on a smartphone app and the smart glasses' HUD (head-up display). Users can check their calorie intake and PFC balance, as well as advice based on their emotional state, in real time while eating.

[0807] Examples:

[0808] If a user chooses a "chicken sandwich" and a "coffee" at a cafe, they put on the smart glasses and scan the food items. The server calculates the calories and PFC of the food items and displays them on the smart glasses' HUD as "Chicken sandwich: 350kcal, protein: 20g, fat: 10g, carbohydrates: 40g" and "Coffee (black): 5kcal, protein: 0g, fat: 0g, carbohydrates: 0g." At the same time, if the emotion engine determines that the user is looking for a relaxing experience, the HUD will also display advice such as "The chicken sandwich is a good choice, but how about some herbal tea for a relaxing effect?"

[0809] Example prompt sentence:

[0810] "Please analyze the types and quantities of food in this image. I'm looking for information on calories, protein, fat, and carbohydrates for each food item."

[0811] The system allows users to make healthy and emotionally relevant food choices in brick-and-mortar restaurants.

[0812] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0813] Step 1:

[0814] The user installs the application on their smartphone and enters basic information (height, weight, body fat percentage, etc.).

[0815] Input: User information such as height, weight, and body fat percentage

[0816] Output: Data on appropriate daily calorie intake and PFC balance

[0817] How it works: Based on the basic information entered, the application calculates the basal metabolic rate, daily calorie intake and PFC balance, and saves them on the server.

[0818] Step 2:

[0819] The user wears the smart glasses while eating, and the camera in the smart glasses scans the contents of the meal.

[0820] Input: Image data of meal contents

[0821] Output: Image data sent to the server

[0822] How it works: The camera in the smart glasses captures the food you eat and sends the image data to a server in real time.

[0823] Step 3:

[0824] The server uses an image recognition algorithm to analyze the transmitted image data.

[0825] Input: Image data of meal contents

[0826] Output: Data on food type and quantity

[0827] How it works: The server uses image recognition algorithms (such as TensorFlow or OpenCV) to identify the type and quantity of food and retrieves the calorie and PFC values ​​for each from a database.

[0828] Step 4:

[0829] The server adds up the calories and PFC values ​​of the food items it has acquired and sends the results to the smart glasses and smartphone app.

[0830] Input: data on food type and quantity, calories and PFC values

[0831] Output: Total calories and PFC value data

[0832] How it works: The server sums the calories and PFC values ​​of each food item retrieved from the database and sends the results to the smart glasses and smartphone app.

[0833] Step 5:

[0834] The smart glasses and app use an emotion engine to analyze the user's emotional state and send it to the server.

[0835] Input: User facial expressions and tone of voice

[0836] Output: Data about emotional state

[0837] How it works: The emotion engine analyzes the user's facial expressions and tone of voice and sends that data to the server.

[0838] Step 6:

[0839] The server generates appropriate dietary management advice for the user based on the emotion data.

[0840] Input: Data about emotional state

[0841] Output: Dietary advice

[0842] Operation: The server generates the necessary dietary advice (e.g., recommendations for foods with a relaxing effect) based on the emotional data.

[0843] Step 7:

[0844] The server displays the calculation results and emotion analysis data on the smart glasses' HUD and smartphone app.

[0845] Input: Total calories and PFC value data, dietary advice

[0846] Output: Information displayed on the smart glasses HUD and smartphone app

[0847] How it works: The server sends the calculation results and generated advice to the smart glasses HUD and smartphone app, allowing users to view the information in real time.

[0848] Through these steps, users can make their dining choices in brick-and-mortar stores healthier and more emotionally relevant.

[0849] 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.

[0850] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0851] 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.

[0852] [Third embodiment]

[0853] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0854] 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.

[0855] 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).

[0856] 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.

[0857] 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.

[0858] 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).

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0865] The present invention relates to a system that allows users to easily manage the calories and PFC (protein, fat, carbohydrates) of their meals using an application linked to smart glasses. The following describes in detail the embodiments of this system.

[0866] Enter basic user information

[0867] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[0868] Smart Glasses and Food Scanning

[0869] The user wears the smart glasses while eating. The camera in the smart glasses captures images of the meal. The image data captured by the camera is sent from the smart glasses to a server.

[0870] Image Recognition and Calorie Counting

[0871] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, it retrieves the calorie and PFC information for each food item from a database and totals them.

[0872] Calorie and PFC value display

[0873] The server sends the calculation results to the smart glasses and the app, which uses the received data to subtract the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[0874] Real-time management

[0875] The smart glasses display the calculation results on a HUD (Head-Up Display) so that the user can check them directly in front of their eyes, allowing them to manage calories and nutrients in real time every time they eat.

[0876] Specific examples

[0877] Initial Setup

[0878] User: For example, enter your height (170cm), weight (70kg), and body fat percentage (20%) into the app.

[0879] App: Based on this, calculate your basal metabolic rate and set your daily calorie intake to 2,500 kcal. Save this information on the server.

[0880] Calculating calories in meals

[0881] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[0882] Smart glasses: The camera scans the food and sends the image data to a server.

[0883] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[0884] Display of calorie intake and PFC amount

[0885] App: Calculate the remaining calorie intake as 2,010 kcal and update the required PFC amount at the same time.

[0886] Smart Glasses: Display "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" on the HUD.

[0887] By implementing the system in this manner, the user can easily manage their daily diet and help maintain a healthy lifestyle.

[0888] The processing flow will be explained below.

[0889] Step 1:

[0890] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[0891] Step 2:

[0892] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on the server.

[0893] Step 3:

[0894] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[0895] Step 4:

[0896] The smart glasses compress the captured image data and send it to a server via Wi-Fi or Bluetooth.

[0897] Step 5:

[0898] The server analyzes the received image data and uses an image recognition algorithm to identify the type and quantity of food.

[0899] Step 6:

[0900] The server retrieves the calorie and PFC values ​​of the food from the database based on the recognized food, and calculates the total value.

[0901] Step 7:

[0902] The server encodes the calculation results in JSON format and sends them to the smart glasses and app using an API.

[0903] Step 8:

[0904] Based on the calorie and PFC information received, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates the remaining calories available for intake and the amount of PFC required.

[0905] Step 9:

[0906] The smart glasses display the calculation results on the HUD and show the user in real time the following format: "Remaining calories: XXXX kcal, Protein requirements: XX g, Fat: XX g, Carbohydrates: XX g."

[0907] In this way, through a series of processing steps, users can easily manage their diet and maintain a healthy lifestyle.

[0908] Example 1

[0909] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0910] In modern society, effective dietary management is an important element of maintaining health and dieting for many people. However, managing calories and nutritional components (protein, fat, carbohydrates) requires checking the calorie content of each individual ingredient, which is time-consuming and laborious. Furthermore, real-time management is difficult, and it often does not become a continuous habit. Therefore, there is a need for a system that allows users to easily and accurately manage their own dietary content.

[0911] 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.

[0912] In this invention, the server includes a means for inputting and storing basic information such as a user's height, weight, and body fat percentage, a means for analyzing the type and amount of food using an image recognition algorithm to calculate calorie and nutrient values, and a means for calculating and displaying the appropriate daily calorie intake and nutrient balance. This allows users to easily record their diet using a smart device and check the calorie and nutrient balance on the spot.

[0913] "Basic information such as the user's height, weight, and body fat percentage" is data that indicates the user's physical characteristics, and is basic information for individual calorie balance and nutritional management.

[0914] An "image recognition algorithm" is a technology that analyzes image data acquired by a camera or other device and automatically identifies specific objects or features, and is used to identify the type and quantity of food.

[0915] "Calorie and nutritional values" is data that indicates the amount of energy (calories) and major nutrients (protein, fat, carbohydrates) contained in a food.

[0916] "Appropriate daily calorie intake and nutritional balance" refers to the total calories and balance of major nutrients that should be consumed in a day, calculated based on the user's physical characteristics and activity level.

[0917] "Wearable device" is a general term for electronic devices that can be worn, and in this case refers to a device that has the function of acquiring image data of food.

[0918] A "server" is a computer system that receives, stores, and analyzes data sent by users over a network and provides the necessary information.

[0919] This invention relates to a system that allows a user to easily and accurately manage the calories and nutritional components (protein, fat, carbohydrates) of their meals in order to maintain a healthy lifestyle. The following describes in detail the mode for implementing this system.

[0920] Enter basic user information

[0921] First, users download and install the smartphone app. When they launch the app, they are prompted to enter basic personal information such as height, weight, and body fat percentage. This data is used to calculate each user's calorie consumption and nutritional balance. The entered information is sent to a server via the app and saved.

[0922] Smart Glasses and Food Scanning

[0923] The user wears smart glasses as a wearable device while eating. The smart glasses are equipped with a high-resolution camera that captures images of the food. The captured image data is sent to a server in real time via the smart glasses.

[0924] Image Recognition and Calorie Counting

[0925] The server receives the transmitted image data and analyzes the type and quantity of food using an image recognition algorithm, which uses, for example, "image recognition software" to analyze the food pixel by pixel and identify the calorie and nutritional information for each food item.

[0926] Calculation and display of daily calorie and nutritional balance

[0927] Based on the analysis results, the server extracts calorie and nutritional information for each food item from the database, adds them up, calculates the appropriate daily calorie intake and nutritional balance, and sends the results to the smart glasses and smartphone app.

[0928] Display of remaining calorie intake and nutritional information in real time

[0929] The smart glasses display the calculation results using a HUD (Head-Up Display), allowing users to manage calories and nutritional information in real time with each meal. The app also calculates the remaining calories and nutritional information available for the day and displays it for easy viewing by the user.

[0930] Specific examples

[0931] Initial Setup

[0932] For example, the user enters their height of 170 cm, weight of 70 kg, and body fat percentage of 20% into the app.

[0933] The app calculates the basal metabolic rate based on the input data and sets the appropriate daily calorie intake at 2,500 kcal. This information is stored on a server.

[0934] Calculating calories in meals

[0935] The user wears the smart glasses while eating a lunch of salad, grilled chicken, and rice.

[0936] The smart glasses use a camera to scan the food and send the image data to a server.

[0937] Using an image recognition algorithm, the server determines that the salad is 40 kcal, the grilled chicken is 250 kcal, and the rice is 200 kcal, totaling 490 kcal. This is then sent to the app and smart glasses.

[0938] Display of calorie intake and nutritional information

[0939] The app will calculate the remaining calorie intake as 2,010 kcal and simultaneously update the nutritional requirements.

[0940] The smart glasses display the following information on the HUD: "Remaining calories: 2,010kcal, required protein: 80g, fat: 60g, carbohydrates: 250g."

[0941] Prompt Sentence Examples

[0942] Examples of input prompts for a generative AI model include:

[0943] "Please explain the specific usage of a system that uses a wearable device to manage the calories and nutritional components (protein, fat, carbohydrates) of meals."

[0944] By implementing the present invention in the above manner, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle.

[0945] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0946] Step 1:

[0947] Users download and install the smartphone app. When they launch the app, a screen appears where they can enter basic information such as their height, weight, and body fat percentage. The information they enter is sent to a server via the app and saved.

[0948] Input: Basic information such as height, weight, and body fat percentage

[0949] Output: Basic information data stored on the server

[0950] Step 2:

[0951] The server calculates the appropriate daily calorie intake and nutritional balance based on the received basic information. This calculation uses a basal metabolic rate calculation algorithm. The calculation results are stored in the server database.

[0952] Input: User's basic information (height, weight, body fat percentage, etc.)

[0953] Output: Proper daily calorie intake and nutritional balance

[0954] Step 3:

[0955] When a user eats, they wear smart glasses as a wearable device. The smart glasses' camera captures images of the food they are eating and transmits the image data to a server in real time.

[0956] Input: Food image data acquired through a camera

[0957] Output: Food image data sent to the server

[0958] Step 4:

[0959] The server analyzes the type and quantity of food using an image recognition algorithm based on the received image data. This algorithm uses, for example, "image recognition software." Based on the data obtained by image recognition, the server retrieves calorie and nutritional information for each food from a database.

[0960] Input: Food image data

[0961] Output: Food type and quantity, along with corresponding calorie and nutritional information

[0962] Step 5:

[0963] The server calculates the calorie and nutritional information for each food based on the analysis results. It then compares the calorie and nutritional information with the recommended daily intake and subtracts the amount already consumed. The calculation results are sent from the server to the smart glasses and smartphone app.

[0964] Input: Food type and quantity, as well as calorie and nutritional information

[0965] Output: Calories consumed and remaining, and nutritional information

[0966] Step 6:

[0967] The smart glasses use a HUD (Head-Up Display) to display the calculation results in real time, allowing users to check the calorie and nutritional balance of each meal. The same data is also displayed on a smartphone app, making daily dietary management easier.

[0968] Input: Calorie and nutritional information sent from the server

[0969] Output: Calorie and nutritional information displayed on HUD and smartphone app

[0970] (Application example 1)

[0971] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0972] As modern consumers lead busy lives, there is a growing need for easy and accurate management of the calories and PFC (protein, fat, carbohydrates) of their meals. While the popularity of food delivery services has increased options, making healthy choices can be challenging. Therefore, there is a need for a system that provides real-time calorie and PFC information to help users maintain healthy eating habits.

[0973] 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.

[0974] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calories and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying in real time the calories and PFC values ​​of foods ordered by the user through a digital device, and means for using an image capture device to capture and transmit images of the foods to the server, thereby enabling the user to understand the contents of their meals in real time and appropriately manage their calorie intake and nutrient balance.

[0975] The "means for inputting and storing basic user information" refers to a mechanism for inputting basic information such as a user's height, weight, and body fat percentage via a digital device and storing that data on a server.

[0976] The "means for calculating the calorie and PFC values ​​of food using an image recognition algorithm" is an algorithm that analyzes the type and quantity of food from the captured image and calculates the calories, protein, fat, and carbohydrates by referring to a database.

[0977] "Means for calculating and displaying the appropriate daily calorie intake and PFC balance" refers to a mechanism that calculates the appropriate daily calorie intake and PFC (protein, lipid, carbohydrate) balance based on the user's basic information and displays it to the user.

[0978] The "means for displaying the remaining calorie and PFC intake amount for the day in real time" is a mechanism that calculates the remaining calorie and PFC intake amount from the calorie and PFC intake amount for the day in real time and displays them to the user.

[0979] "Means for calculating and displaying in real time the calorie and PFC values ​​of food ordered by a user through a digital device" refers to a mechanism that calculates the calories and PFC values ​​of food ordered using a food delivery application and displays the results in real time.

[0980] "Means for using an image capture device to capture images of food and transmit them to a server" refers to a mechanism for using a digital device with a camera to capture images of food and transmit the data to a server.

[0981] This invention is a system that allows users to easily manage dietary calories and PFC (protein, fat, carbohydrates) by linking with a digital device. The system includes means for inputting and saving basic user information, means for calculating food calories and PFC values ​​using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying the calorie and PFC values ​​of foods ordered by the user through the digital device in real time, and means for using an image capture device to capture images of foods and send them to a server.

[0982] Each means of this system has the following specific configuration.

[0983] server

[0984] The server contains a database (e.g., MySQL) for storing basic user information, software (e.g., TensorFlow) for running image recognition algorithms, and a system for real-time communication (e.g., Firebase). Basic information (e.g., height, weight, body fat percentage) entered by the user on their smartphone is sent to the server and stored in the database.

[0985] Example of user information entry

[0986] A user uses a smartphone app to enter their height of 170 cm, weight of 70 kg, and body fat percentage of 20%.

[0987] The server receives this information and stores it in a database.

[0988] Image Recognition and Calorie Counting

[0989] The server receives image data of food sent from smart glasses or smartphone cameras, analyzes the type and quantity of food using image recognition algorithms such as TensorFlow, and based on the analysis results, retrieves the calorie and PFC information of the food from the database and calculates the total value.

[0990] Example of calorie calculation for meals

[0991] A user wears smart glasses and captures an image of their lunch (salad, grilled chicken, and rice).

[0992] The smart glasses send the image data to a server.

[0993] The server analyzes the image and determines that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, for a total of 490kcal.

[0994] Real-time display using digital devices

[0995] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are calculated in real time and the information is displayed on the smartphone app and smart glasses.

[0996] Examples of digital device use

[0997] A user orders grilled salmon and salad through a food delivery app.

[0998] The smart glasses receive the order information and send it to the server.

[0999] The server calculates calories and PFC values ​​and displays them in real time on the smart glasses.

[1000] Smart glasses: "Grilled salmon 200kcal, salad 50kcal, total 250kcal" displayed on the HUD.

[1001] Example prompts for generative AI models

[1002] A user orders grilled salmon and salad for lunch and scans it with the smart glasses. Image recognition algorithms calculate the calories and nutritional information and display it to the user in real time.

[1003] By implementing the system in this manner, the user can grasp the contents of his / her meals in real time and appropriately manage the balance of calorie intake and nutrients.

[1004] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1005] Step 1:

[1006] Entering and saving user information

[1007] The user installs the smartphone app and enters basic information (height, weight, body fat percentage, etc.).

[1008] The server receives the entered data and saves it in a database (e.g., MySQL).

[1009] Input: Basic information such as the user's height, weight, and body fat percentage.

[1010] Output: Basic information of the user stored in the database.

[1011] Data processing and calculation: The storage process of the basic information entered.

[1012] Step 2:

[1013] Food image capture and transmission

[1014] The user wears the smart glasses and captures images of their meal.

[1015] The image data acquired by the smart glasses is sent to the server.

[1016] Input: Food image data.

[1017] Output: Image data sent to the server.

[1018] Data processing and calculation: Processing of image data for transmission.

[1019] Step 3:

[1020] Image Recognition and Calorie Counting

[1021] The server uses an image recognition algorithm (such as TensorFlow) to analyze the image data it receives.

[1022] Based on the analysis results, the calorie and PFC information of the food is obtained from the database and the total value is calculated.

[1023] Input: Food image data.

[1024] Output: Calories and PFC information.

[1025] Data processing and calculation: Image analysis and calculation of calories and PFC values.

[1026] Step 4:

[1027] Real-time display

[1028] The server sends the calculation results to the smart glasses and smartphone app.

[1029] The smart glasses and smartphone app display the received data.

[1030] Input: Calories and PFC information.

[1031] Output: Calorie and PFC information displayed on smart glasses and smartphone app.

[1032] Data processing and calculation: Data transmission and display processing.

[1033] Step 5:

[1034] Food delivery app integration

[1035] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are sent to the server.

[1036] Based on the order data received by the server, the calories and PFC values ​​are calculated in real time and sent to the smart glasses and smartphone app.

[1037] Input: Order data from a food delivery app.

[1038] Output: Calories and PFC information.

[1039] Data processing and calculation: Analysis of food delivery information and calculation of calories and PFC values.

[1040] Step 6:

[1041] Save and update final data

[1042] The server continuously updates the user's daily calorie intake and PFC amount and stores them in a database.

[1043] Users can check their intake status through the app.

[1044] Input: Calorie intake and PFC information.

[1045] Output: The updated database.

[1046] Data processing and calculation: Updating and storing intake status.

[1047] The above are the specific processing steps of the system that realizes the application example.

[1048] 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.

[1049] The present invention relates to a system that allows a user to easily manage the calories and PFC (protein, fat, carbohydrates) of their diet using an application and an emotion engine linked to smart glasses, and further recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[1050] Enter basic user information

[1051] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[1052] Smart Glasses and Food Scanning

[1053] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the contents of the meal. The acquired image data is sent from the smart glasses to a server.

[1054] Image Recognition and Calorie Counting

[1055] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[1056] Recognizing user emotions with an emotion engine

[1057] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[1058] Calorie and PFC value display

[1059] The server sends the calculation results and emotion data obtained from the emotion engine to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie intake and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[1060] Emotional diet management

[1061] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, providing advice such as "refill your energy when you're tired" or "recommend foods that have a relaxing effect when you're under a lot of stress."

[1062] Real-time management

[1063] The smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that can be viewed directly in front of the user's eyes, allowing users to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[1064] Specific examples

[1065] Initial Setup

[1066] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[1067] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[1068] Calculating calories in meals

[1069] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[1070] Smart glasses: The camera scans the food and sends the image data to a server.

[1071] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[1072] Emotion recognition and display of calories and PFC amount

[1073] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, it also displays food advice that will help them relax.

[1074] Smart Glasses: The HUD displays "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Consume foods that are effective in reducing stress."

[1075] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[1076] The processing flow will be explained below.

[1077] Step 1:

[1078] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[1079] Step 2:

[1080] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on a server.

[1081] Step 3:

[1082] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[1083] Step 4:

[1084] The smart glasses compress the captured image data and send it to a server using Wi-Fi or Bluetooth.

[1085] Step 5:

[1086] The server analyzes the received image data and uses image recognition algorithms to identify the type and quantity of food.

[1087] Step 6:

[1088] The server retrieves the calorie and PFC values ​​of the food from the database based on the identified food and calculates the total value.

[1089] Step 7:

[1090] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is then sent to a server.

[1091] Step 8:

[1092] The server transmits the calculated calories and PFC values, as well as the emotion data obtained from the emotion engine, to the smart glasses and the app.

[1093] Step 9:

[1094] Based on the received calorie and PFC information, the app subtracts the ingested calories and PFC from the appropriate daily calorie and PFC balance, calculates the remaining calorie intake and required PFC amount, and generates dietary advice based on the user's emotional state.

[1095] Step 10:

[1096] The smart glasses display advice based on the calculation results and emotions on a HUD that the user can see in their line of sight, such as "Remaining calorie intake: 2,010kcal, Protein requirement: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[1097] In this way, through a series of processing steps, the user can easily manage their diet and receive advice according to their emotional state, thereby maintaining a healthy lifestyle.

[1098] Example 2

[1099] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1100] In modern society, many people recognize the importance of daily dietary management, but it is difficult to keep track of calorie and nutrient intake. Furthermore, although a user's emotional state often influences food choices and intake, there are no tools to centrally manage these. This makes it difficult for users to manage themselves and maintain a healthy lifestyle and mental stability.

[1101] 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.

[1102] In this invention, the server includes means for inputting and saving basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for analyzing and acquiring the user's emotional state using an emotion engine, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, and means for adjusting the calorie and PFC display and dietary advice based on the user's emotional state. This allows the user to easily understand their calorie and nutrient intake and manage their diet in accordance with their emotional state.

[1103] "Basic user information" refers to personal data necessary for calculating calories and PFC balance, such as the user's height, weight, and body fat percentage.

[1104] "Image recognition algorithm" is a programming technology for recognizing the type and quantity of food and analyzing its calorie and PFC values.

[1105] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1106] "Appropriate daily calorie intake and PFC balance" refers to the balance of calories, protein, fat, and carbohydrates required for the user to maintain a healthy lifestyle.

[1107] "Display in real time" means that information is displayed immediately in a state that the user can see directly in front of their eyes.

[1108] "Dietary advice" is a recommendation to encourage better dietary choices based on the user's emotional state.

[1109] "Smart glasses" are devices worn by users that use a camera to scan the contents of a meal and display information on a HUD (Head-Up Display).

[1110] A "calorie" is a unit of heat obtained from food and used by the body as energy.

[1111] "PFC" is an abbreviation for protein, fat, and carbohydrate, which are the major nutrients found in food.

[1112] The present invention provides a system that allows users to easily manage their dietary calories and PFC (protein, fat, carbohydrates) using an application and emotion engine linked to smart glasses, and also recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[1113] Enter basic user information

[1114] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[1115] Smart Glasses and Food Scanning

[1116] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the food contents. The acquired image data is sent from the smart glasses to a server.

[1117] Image Recognition and Calorie Counting

[1118] The server receives the image data and analyzes the type and quantity of food using an image recognition algorithm, such as TensorFlow or OpenCV. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[1119] Recognizing user emotions with an emotion engine

[1120] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[1121] Calorie and PFC value display

[1122] The server sends the calculation results and emotional data to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[1123] Emotional diet management

[1124] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, offering advice such as "refuel when you're tired" or "choose foods that will help you relax when you're stressed."

[1125] Real-time management

[1126] Smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that users can see directly in front of their eyes, allowing them to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[1127] Specific examples

[1128] Initial Setup

[1129] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[1130] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[1131] Calculating calories in meals

[1132] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[1133] Smart glasses: The camera scans the food and sends the image data to a server.

[1134] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[1135] Emotion recognition and display of calories and PFC amount

[1136] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, the app also advises them to eat foods that have a relaxing effect.

[1137] Smart Glasses: The HUD displays the following advice: "Remaining calories: 2,010kcal, Protein requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[1138] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[1139] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1140] Step 1:

[1141] Users install the smartphone app and enter basic information.

[1142] Specific operation: The user launches the app and enters their height, weight, body fat percentage, etc. on the profile screen.

[1143] Input: Personal data such as height, weight, and body fat percentage

[1144] Data processing: The app formats the entered information for sending to a database.

[1145] Output: Basic user information in JSON format

[1146] Step 2:

[1147] The app sends the user's basic information to the server.

[1148] Specific behavior: The app sends JSON formatted data to the server as an HTTP request.

[1149] Input: Basic user information data in JSON format

[1150] Data calculation: The server analyzes the received data and stores it in a database.

[1151] Output: Basic information stored in the database

[1152] Step 3:

[1153] The server calculates the appropriate daily calorie intake and PFC balance.

[1154] Specific operation: The server retrieves user information from the database and uses an algorithm to calculate basal metabolic rate and daily calorie intake.

[1155] Input: User data such as height, weight, and body fat percentage

[1156] Data calculation: Calculation of basal metabolic rate and proper calorie balance

[1157] Output: Daily calorie intake and PFC balance

[1158] Step 4:

[1159] When the user eats, they wear the smart glasses and the camera scans the food.

[1160] Specific operation: Point the smart glasses camera at the food and take a picture of it.

[1161] Input: Food image data

[1162] Data processing: The smart glasses format the acquired image data for transmission to the server.

[1163] Output: Image data is prepared for transmission to the server

[1164] Step 5:

[1165] The server receives the image data and uses image recognition algorithms to analyze the type and quantity of food.

[1166] Specific operation: The server uses TensorFlow and OpenCV to identify the type and quantity of food from the image.

[1167] Input: Food image data

[1168] Data processing: Food analysis using image recognition algorithms

[1169] Output: Analyzed food type and quantity data

[1170] Step 6:

[1171] The server retrieves the calorie and PFC information for each food item from the database and calculates the total value.

[1172] Specific operation: The server refers to the food database and obtains the calories and PFC value for each food item.

[1173] Input: Data on the type and quantity of food analyzed

[1174] Data calculation: Calculate the total calories and PFC value of each food.

[1175] Output: Total calories and PFC value

[1176] Step 7:

[1177] The smart glasses and app use an emotion engine to analyze the user's emotional state and send the data to a server.

[1178] How it works: The app and smart glasses capture the user's facial expressions and tone of voice and analyze emotional data.

[1179] Input: User's facial expression data, voice data

[1180] Data processing: Real-time analysis using emotion engine

[1181] Output: Parsed emotion data

[1182] Step 8:

[1183] The server sends the calculation results and emotion data to the smart glasses and app.

[1184] Specific operation: The server sends the total calories, PFC value, and emotion data to the smart glasses and app.

[1185] Input: Total calories, PFC value, emotional data

[1186] Data processing: Format of transmitted data

[1187] Output: Data displayed on the smart glasses and in the app

[1188] Step 9:

[1189] The app and smart glasses provide dietary advice that reflects the user's emotions.

[1190] How it works: The app and smart glasses adjust the calorie and PFC display and provide dietary advice based on the user's emotional state.

[1191] Input: Total calories, PFC value, emotional data

[1192] Data Computing: Emotion-Based Advice Generation

[1193] Output: Meal advice displayed on HUD or app

[1194] Step 10:

[1195] The smart glasses display real-time advice on the HUD.

[1196] Specific operation: The smart glasses display advice based on calculation results and emotions on the HUD.

[1197] Input: Dietary advice data

[1198] Data processing: HUD display format

[1199] Output: Advice information at your fingertips

[1200] In this way, users can receive real-time calorie and nutrient management and emotion-based dietary advice.

[1201] (Application example 2)

[1202] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1203] Modern dietary management faces the challenge of easily and effectively managing calorie and nutrient intake. When choosing meals at restaurants or brick-and-mortar stores, it is difficult to obtain real-time nutritional information on the foods on offer, making it difficult to maintain appropriate intake. Dietary management that takes into account the user's emotional state is also important, and this lack of awareness needs to be addressed.

[1204] 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.

[1205] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for recognizing the user's emotions and reflecting them in dietary management, and visual display means for presenting information in real time when selecting foods in a physical store. This makes it possible to obtain calorie and nutrient information in real time even when selecting meals in a physical store, and also enables appropriate dietary management that takes the user's emotional state into consideration.

[1206] "User" refers to a person who uses the system to manage their diet.

[1207] "Basic information" refers to personal data such as height, weight, and body fat percentage entered by the user.

[1208] "Image recognition algorithm" refers to a calculation method for analyzing image data acquired by a camera and identifying the type and quantity of food.

[1209] "Calories" refers to the amount of energy contained in food and is expressed in kcal.

[1210] "PFC" refers to the three major nutrients: protein, fat, and carbohydrates.

[1211] "Smart glasses" are eyeglass-type wearable devices that incorporate functions such as a camera and a head-up display (HUD).

[1212] "Server" means a computer system that processes information sent by users and stores and provides necessary data.

[1213] An "emotion engine" refers to software or algorithms that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[1214] "Visual display device" refers to a display device that allows a user to view information in real time.

[1215] "Brick and mortar" refers to a food and beverage establishment that is located in a physical location, such as a cafe or restaurant.

[1216] To implement this invention, a user must first install an application on their smartphone and enter their basic information (height, weight, body fat percentage, etc.) Based on this basic information, the application calculates the appropriate daily calorie intake and PFC balance for each user and saves the results on a server.

[1217] Next, the user wears the smart glasses while eating. The smart glasses are equipped with a camera that can scan the contents of the meal. The captured image data is sent to a server in real time. The server uses an image recognition algorithm (e.g., TensorFlow or OpenCV) to analyze the type and quantity of food, retrieve the calorie and PFC values ​​of each food from a database, and calculate the total value.

[1218] Furthermore, the smart glasses are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is sent to a server, which then generates appropriate dietary advice based on this data. For example, if the user is feeling stressed, it will recommend foods that have a relaxing effect.

[1219] The calculation results and emotion analysis data from the server are displayed on a smartphone app and the smart glasses' HUD (head-up display). Users can check their calorie intake and PFC balance, as well as advice based on their emotional state, in real time while eating.

[1220] Examples:

[1221] If a user chooses a "chicken sandwich" and a "coffee" at a cafe, they put on the smart glasses and scan the food items. The server calculates the calories and PFC of the food items and displays them on the smart glasses' HUD as "Chicken sandwich: 350kcal, protein: 20g, fat: 10g, carbohydrates: 40g" and "Coffee (black): 5kcal, protein: 0g, fat: 0g, carbohydrates: 0g." At the same time, if the emotion engine determines that the user is looking for a relaxing experience, the HUD will also display advice such as "The chicken sandwich is a good choice, but how about some herbal tea for a relaxing effect?"

[1222] Example prompt sentence:

[1223] "Please analyze the types and quantities of food in this image. I'm looking for information on calories, protein, fat, and carbohydrates for each food item."

[1224] The system allows users to make healthy and emotionally relevant food choices in brick-and-mortar restaurants.

[1225] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1226] Step 1:

[1227] The user installs the application on their smartphone and enters basic information (height, weight, body fat percentage, etc.).

[1228] Input: User information such as height, weight, and body fat percentage

[1229] Output: Data on appropriate daily calorie intake and PFC balance

[1230] How it works: Based on the basic information entered, the application calculates the basal metabolic rate, daily calorie intake and PFC balance, and saves them on the server.

[1231] Step 2:

[1232] The user wears the smart glasses while eating, and the camera in the smart glasses scans the contents of the meal.

[1233] Input: Image data of meal contents

[1234] Output: Image data sent to the server

[1235] How it works: The camera in the smart glasses captures the food you eat and sends the image data to a server in real time.

[1236] Step 3:

[1237] The server uses an image recognition algorithm to analyze the transmitted image data.

[1238] Input: Image data of meal contents

[1239] Output: Data on food type and quantity

[1240] How it works: The server uses image recognition algorithms (such as TensorFlow or OpenCV) to identify the type and quantity of food and retrieves the calorie and PFC values ​​for each from a database.

[1241] Step 4:

[1242] The server adds up the calories and PFC values ​​of the food items it has acquired and sends the results to the smart glasses and smartphone app.

[1243] Input: data on food type and quantity, calories and PFC values

[1244] Output: Total calories and PFC value data

[1245] How it works: The server sums the calories and PFC values ​​of each food item retrieved from the database and sends the results to the smart glasses and smartphone app.

[1246] Step 5:

[1247] The smart glasses and app use an emotion engine to analyze the user's emotional state and send it to the server.

[1248] Input: User facial expressions and tone of voice

[1249] Output: Data about emotional state

[1250] How it works: The emotion engine analyzes the user's facial expressions and tone of voice and sends that data to the server.

[1251] Step 6:

[1252] The server generates appropriate dietary management advice for the user based on the emotion data.

[1253] Input: Data about emotional state

[1254] Output: Dietary advice

[1255] Operation: The server generates the necessary dietary advice (e.g., recommendations for foods with a relaxing effect) based on the emotional data.

[1256] Step 7:

[1257] The server displays the calculation results and emotion analysis data on the smart glasses' HUD and smartphone app.

[1258] Input: Total calories and PFC value data, dietary advice

[1259] Output: Information displayed on the smart glasses HUD and smartphone app

[1260] How it works: The server sends the calculation results and generated advice to the smart glasses HUD and smartphone app, allowing users to view the information in real time.

[1261] Through these steps, users can make their dining choices in brick-and-mortar stores healthier and more emotionally relevant.

[1262] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1263] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1264] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1265] [Fourth embodiment]

[1266] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1267] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1268] 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).

[1269] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1270] 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.

[1271] 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).

[1272] 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.

[1273] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1274] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1275] 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.

[1276] 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.

[1277] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1278] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1279] The present invention relates to a system that allows users to easily manage the calories and PFC (protein, fat, carbohydrates) of their meals using an application linked to smart glasses. The following describes in detail the embodiments of this system.

[1280] Enter basic user information

[1281] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[1282] Smart Glasses and Food Scanning

[1283] The user wears the smart glasses while eating. The camera in the smart glasses captures images of the meal. The image data captured by the camera is sent from the smart glasses to a server.

[1284] Image Recognition and Calorie Counting

[1285] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, it retrieves the calorie and PFC information for each food item from a database and totals them.

[1286] Calorie and PFC value display

[1287] The server sends the calculation results to the smart glasses and the app, which uses the received data to subtract the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[1288] Real-time management

[1289] The smart glasses display the calculation results on a HUD (Head-Up Display) so that the user can check them directly in front of their eyes, allowing them to manage calories and nutrients in real time every time they eat.

[1290] Specific examples

[1291] Initial Setup

[1292] User: For example, enter your height (170cm), weight (70kg), and body fat percentage (20%) into the app.

[1293] App: Based on this, calculate your basal metabolic rate and set your daily calorie intake to 2,500 kcal. Save this information on the server.

[1294] Calculating calories in meals

[1295] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[1296] Smart glasses: The camera scans the food and sends the image data to a server.

[1297] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[1298] Display of calorie intake and PFC amount

[1299] App: Calculate the remaining calorie intake as 2,010 kcal and update the required PFC amount at the same time.

[1300] Smart Glasses: Display "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" on the HUD.

[1301] By implementing the system in this manner, the user can easily manage their daily diet and help maintain a healthy lifestyle.

[1302] The processing flow will be explained below.

[1303] Step 1:

[1304] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[1305] Step 2:

[1306] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on the server.

[1307] Step 3:

[1308] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[1309] Step 4:

[1310] The smart glasses compress the captured image data and send it to a server via Wi-Fi or Bluetooth.

[1311] Step 5:

[1312] The server analyzes the received image data and uses an image recognition algorithm to identify the type and quantity of food.

[1313] Step 6:

[1314] The server retrieves the calorie and PFC values ​​of the food from the database based on the recognized food, and calculates the total value.

[1315] Step 7:

[1316] The server encodes the calculation results in JSON format and sends them to the smart glasses and app using an API.

[1317] Step 8:

[1318] Based on the calorie and PFC information received, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates the remaining calories available for intake and the amount of PFC required.

[1319] Step 9:

[1320] The smart glasses display the calculation results on the HUD and show the user in real time the following format: "Remaining calories: XXXX kcal, Protein requirements: XX g, Fat: XX g, Carbohydrates: XX g."

[1321] In this way, through a series of processing steps, users can easily manage their diet and maintain a healthy lifestyle.

[1322] Example 1

[1323] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1324] In modern society, effective dietary management is an important element of maintaining health and dieting for many people. However, managing calories and nutritional components (protein, fat, carbohydrates) requires checking the calorie content of each individual ingredient, which is time-consuming and laborious. Furthermore, real-time management is difficult, and it often does not become a continuous habit. Therefore, there is a need for a system that allows users to easily and accurately manage their own dietary content.

[1325] 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.

[1326] In this invention, the server includes a means for inputting and storing basic information such as a user's height, weight, and body fat percentage, a means for analyzing the type and amount of food using an image recognition algorithm to calculate calorie and nutrient values, and a means for calculating and displaying the appropriate daily calorie intake and nutrient balance. This allows users to easily record their diet using a smart device and check the calorie and nutrient balance on the spot.

[1327] "Basic information such as the user's height, weight, and body fat percentage" is data that indicates the user's physical characteristics, and is basic information for individual calorie balance and nutritional management.

[1328] An "image recognition algorithm" is a technology that analyzes image data acquired by a camera or other device and automatically identifies specific objects or features, and is used to identify the type and quantity of food.

[1329] "Calorie and nutritional values" is data that indicates the amount of energy (calories) and major nutrients (protein, fat, carbohydrates) contained in a food.

[1330] "Appropriate daily calorie intake and nutritional balance" refers to the total calories and balance of major nutrients that should be consumed in a day, calculated based on the user's physical characteristics and activity level.

[1331] "Wearable device" is a general term for electronic devices that can be worn, and in this case refers to a device that has the function of acquiring image data of food.

[1332] A "server" is a computer system that receives, stores, and analyzes data sent by users over a network and provides the necessary information.

[1333] This invention relates to a system that allows a user to easily and accurately manage the calories and nutritional components (protein, fat, carbohydrates) of their meals in order to maintain a healthy lifestyle. The following describes in detail the mode for implementing this system.

[1334] Enter basic user information

[1335] First, users download and install the smartphone app. When they launch the app, they are prompted to enter basic personal information such as height, weight, and body fat percentage. This data is used to calculate each user's calorie consumption and nutritional balance. The entered information is sent to a server via the app and saved.

[1336] Smart Glasses and Food Scanning

[1337] The user wears smart glasses as a wearable device while eating. The smart glasses are equipped with a high-resolution camera that captures images of the food. The captured image data is sent to a server in real time via the smart glasses.

[1338] Image Recognition and Calorie Counting

[1339] The server receives the transmitted image data and analyzes the type and quantity of food using an image recognition algorithm, which uses, for example, "image recognition software" to analyze the food pixel by pixel and identify the calorie and nutritional information for each food item.

[1340] Calculation and display of daily calorie and nutritional balance

[1341] Based on the analysis results, the server extracts calorie and nutritional information for each food item from the database, adds them up, calculates the appropriate daily calorie intake and nutritional balance, and sends the results to the smart glasses and smartphone app.

[1342] Display of remaining calorie intake and nutritional information in real time

[1343] The smart glasses display the calculation results using a HUD (Head-Up Display), allowing users to manage calories and nutritional information in real time with each meal. The app also calculates the remaining calories and nutritional information available for the day and displays it for easy viewing by the user.

[1344] Specific examples

[1345] Initial Setup

[1346] For example, the user enters their height of 170 cm, weight of 70 kg, and body fat percentage of 20% into the app.

[1347] The app calculates the basal metabolic rate based on the input data and sets the appropriate daily calorie intake at 2,500 kcal. This information is stored on a server.

[1348] Calculating calories in meals

[1349] The user wears the smart glasses while eating a lunch of salad, grilled chicken, and rice.

[1350] The smart glasses use a camera to scan the food and send the image data to a server.

[1351] Using an image recognition algorithm, the server determines that the salad is 40 kcal, the grilled chicken is 250 kcal, and the rice is 200 kcal, totaling 490 kcal. This is then sent to the app and smart glasses.

[1352] Display of calorie intake and nutritional information

[1353] The app will calculate the remaining calorie intake as 2,010 kcal and simultaneously update the nutritional requirements.

[1354] The smart glasses display the following information on the HUD: "Remaining calories: 2,010kcal, required protein: 80g, fat: 60g, carbohydrates: 250g."

[1355] Prompt Sentence Examples

[1356] Examples of input prompts for a generative AI model include:

[1357] "Please explain the specific usage of a system that uses a wearable device to manage the calories and nutritional components (protein, fat, carbohydrates) of meals."

[1358] By implementing the present invention in the above manner, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle.

[1359] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1360] Step 1:

[1361] Users download and install the smartphone app. When they launch the app, a screen appears where they can enter basic information such as their height, weight, and body fat percentage. The information they enter is sent to a server via the app and saved.

[1362] Input: Basic information such as height, weight, and body fat percentage

[1363] Output: Basic information data stored on the server

[1364] Step 2:

[1365] The server calculates the appropriate daily calorie intake and nutritional balance based on the received basic information. This calculation uses a basal metabolic rate calculation algorithm. The calculation results are stored in the server database.

[1366] Input: User's basic information (height, weight, body fat percentage, etc.)

[1367] Output: Proper daily calorie intake and nutritional balance

[1368] Step 3:

[1369] When a user eats, they wear smart glasses as a wearable device. The smart glasses' camera captures images of the food they are eating and transmits the image data to a server in real time.

[1370] Input: Food image data acquired through a camera

[1371] Output: Food image data sent to the server

[1372] Step 4:

[1373] The server analyzes the type and quantity of food using an image recognition algorithm based on the received image data. This algorithm uses, for example, "image recognition software." Based on the data obtained by image recognition, the server retrieves calorie and nutritional information for each food from a database.

[1374] Input: Food image data

[1375] Output: Food type and quantity, along with corresponding calorie and nutritional information

[1376] Step 5:

[1377] The server calculates the calorie and nutritional information for each food based on the analysis results. It then compares the calorie and nutritional information with the recommended daily intake and subtracts the amount already consumed. The calculation results are sent from the server to the smart glasses and smartphone app.

[1378] Input: Food type and quantity, as well as calorie and nutritional information

[1379] Output: Calories consumed and remaining, and nutritional information

[1380] Step 6:

[1381] The smart glasses use a HUD (Head-Up Display) to display the calculation results in real time, allowing users to check the calorie and nutritional balance of each meal. The same data is also displayed on a smartphone app, making daily dietary management easier.

[1382] Input: Calorie and nutritional information sent from the server

[1383] Output: Calorie and nutritional information displayed on HUD and smartphone app

[1384] (Application example 1)

[1385] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1386] As modern consumers lead busy lives, there is a growing need for easy and accurate management of the calories and PFC (protein, fat, carbohydrates) of their meals. While the popularity of food delivery services has increased options, making healthy choices can be challenging. Therefore, there is a need for a system that provides real-time calorie and PFC information to help users maintain healthy eating habits.

[1387] 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.

[1388] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calories and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying in real time the calories and PFC values ​​of foods ordered by the user through a digital device, and means for using an image capture device to capture and transmit images of the foods to the server, thereby enabling the user to understand the contents of their meals in real time and appropriately manage their calorie intake and nutrient balance.

[1389] The "means for inputting and storing basic user information" refers to a mechanism for inputting basic information such as a user's height, weight, and body fat percentage via a digital device and storing that data on a server.

[1390] The "means for calculating the calorie and PFC values ​​of food using an image recognition algorithm" is an algorithm that analyzes the type and quantity of food from the captured image and calculates the calories, protein, fat, and carbohydrates by referring to a database.

[1391] "Means for calculating and displaying the appropriate daily calorie intake and PFC balance" refers to a mechanism that calculates the appropriate daily calorie intake and PFC (protein, lipid, carbohydrate) balance based on the user's basic information and displays it to the user.

[1392] The "means for displaying the remaining calorie and PFC intake amount for the day in real time" is a mechanism that calculates the remaining calorie and PFC intake amount from the calorie and PFC intake amount for the day in real time and displays them to the user.

[1393] "Means for calculating and displaying in real time the calorie and PFC values ​​of food ordered by a user through a digital device" refers to a mechanism that calculates the calories and PFC values ​​of food ordered using a food delivery application and displays the results in real time.

[1394] "Means for using an image capture device to capture images of food and transmit them to a server" refers to a mechanism for using a digital device with a camera to capture images of food and transmit the data to a server.

[1395] This invention is a system that allows users to easily manage dietary calories and PFC (protein, fat, carbohydrates) by linking with a digital device. The system includes means for inputting and saving basic user information, means for calculating food calories and PFC values ​​using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for calculating and displaying the calorie and PFC values ​​of foods ordered by the user through the digital device in real time, and means for using an image capture device to capture images of foods and send them to a server.

[1396] Each means of this system has the following specific configuration.

[1397] server

[1398] The server contains a database (e.g., MySQL) for storing basic user information, software (e.g., TensorFlow) for running image recognition algorithms, and a system for real-time communication (e.g., Firebase). Basic information (e.g., height, weight, body fat percentage) entered by the user on their smartphone is sent to the server and stored in the database.

[1399] Example of user information entry

[1400] A user uses a smartphone app to enter their height of 170 cm, weight of 70 kg, and body fat percentage of 20%.

[1401] The server receives this information and stores it in a database.

[1402] Image Recognition and Calorie Counting

[1403] The server receives image data of food sent from smart glasses or smartphone cameras, analyzes the type and quantity of food using image recognition algorithms such as TensorFlow, and based on the analysis results, retrieves the calorie and PFC information of the food from the database and calculates the total value.

[1404] Example of calorie calculation for meals

[1405] A user wears smart glasses and captures an image of their lunch (salad, grilled chicken, and rice).

[1406] The smart glasses send the image data to a server.

[1407] The server analyzes the image and determines that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, for a total of 490kcal.

[1408] Real-time display using digital devices

[1409] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are calculated in real time and the information is displayed on the smartphone app and smart glasses.

[1410] Examples of digital device use

[1411] A user orders grilled salmon and salad through a food delivery app.

[1412] The smart glasses receive the order information and send it to the server.

[1413] The server calculates calories and PFC values ​​and displays them in real time on the smart glasses.

[1414] Smart glasses: "Grilled salmon 200kcal, salad 50kcal, total 250kcal" displayed on the HUD.

[1415] Example prompts for generative AI models

[1416] A user orders grilled salmon and salad for lunch and scans it with the smart glasses. Image recognition algorithms calculate the calories and nutritional information and display it to the user in real time.

[1417] By implementing the system in this manner, the user can grasp the contents of his / her meals in real time and appropriately manage the balance of calorie intake and nutrients.

[1418] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1419] Step 1:

[1420] Entering and saving user information

[1421] The user installs the smartphone app and enters basic information (height, weight, body fat percentage, etc.).

[1422] The server receives the entered data and saves it in a database (e.g., MySQL).

[1423] Input: Basic information such as the user's height, weight, and body fat percentage.

[1424] Output: Basic information of the user stored in the database.

[1425] Data processing and calculation: The storage process of the basic information entered.

[1426] Step 2:

[1427] Food image capture and transmission

[1428] The user wears the smart glasses and captures images of their meal.

[1429] The image data acquired by the smart glasses is sent to the server.

[1430] Input: Food image data.

[1431] Output: Image data sent to the server.

[1432] Data processing and calculation: Processing of image data for transmission.

[1433] Step 3:

[1434] Image Recognition and Calorie Counting

[1435] The server uses an image recognition algorithm (such as TensorFlow) to analyze the image data it receives.

[1436] Based on the analysis results, the calorie and PFC information of the food is obtained from the database and the total value is calculated.

[1437] Input: Food image data.

[1438] Output: Calories and PFC information.

[1439] Data processing and calculation: Image analysis and calculation of calories and PFC values.

[1440] Step 4:

[1441] Real-time display

[1442] The server sends the calculation results to the smart glasses and smartphone app.

[1443] The smart glasses and smartphone app display the received data.

[1444] Input: Calories and PFC information.

[1445] Output: Calorie and PFC information displayed on smart glasses and smartphone app.

[1446] Data processing and calculation: Data transmission and display processing.

[1447] Step 5:

[1448] Food delivery app integration

[1449] When a user places an order using a food delivery app, the calories and PFC value of the ordered food are sent to the server.

[1450] Based on the order data received by the server, the calories and PFC values ​​are calculated in real time and sent to the smart glasses and smartphone app.

[1451] Input: Order data from a food delivery app.

[1452] Output: Calories and PFC information.

[1453] Data processing and calculation: Analysis of food delivery information and calculation of calories and PFC values.

[1454] Step 6:

[1455] Save and update final data

[1456] The server continuously updates the user's daily calorie intake and PFC amount and stores them in a database.

[1457] Users can check their intake status through the app.

[1458] Input: Calorie intake and PFC information.

[1459] Output: The updated database.

[1460] Data processing and calculation: Updating and storing intake status.

[1461] The above are the specific processing steps of the system that realizes the application example.

[1462] 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.

[1463] The present invention relates to a system that allows a user to easily manage the calories and PFC (protein, fat, carbohydrates) of their diet using an application and an emotion engine linked to smart glasses, and further recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[1464] Enter basic user information

[1465] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[1466] Smart Glasses and Food Scanning

[1467] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the contents of the meal. The acquired image data is sent from the smart glasses to a server.

[1468] Image Recognition and Calorie Counting

[1469] The server receives the image data and uses an image recognition algorithm to analyze the type and quantity of food. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[1470] Recognizing user emotions with an emotion engine

[1471] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[1472] Calorie and PFC value display

[1473] The server sends the calculation results and emotion data obtained from the emotion engine to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie intake and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[1474] Emotional diet management

[1475] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, providing advice such as "refill your energy when you're tired" or "recommend foods that have a relaxing effect when you're under a lot of stress."

[1476] Real-time management

[1477] The smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that can be viewed directly in front of the user's eyes, allowing users to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[1478] Specific examples

[1479] Initial Setup

[1480] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[1481] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[1482] Calculating calories in meals

[1483] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[1484] Smart glasses: The camera scans the food and sends the image data to a server.

[1485] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[1486] Emotion recognition and display of calories and PFC amount

[1487] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, it also displays food advice that will help them relax.

[1488] Smart Glasses: The HUD displays "Remaining Calories: 2,010kcal, Protein Requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Consume foods that are effective in reducing stress."

[1489] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[1490] The processing flow will be explained below.

[1491] Step 1:

[1492] Users install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen.

[1493] Step 2:

[1494] The app calculates the basal metabolic rate based on the basic information entered, sets the appropriate daily calorie intake and PFC balance, and stores this information on a server.

[1495] Step 3:

[1496] When a user eats a meal, they wear the smart glasses and the contents of the meal are scanned with the smart glasses' camera.

[1497] Step 4:

[1498] The smart glasses compress the captured image data and send it to a server using Wi-Fi or Bluetooth.

[1499] Step 5:

[1500] The server analyzes the received image data and uses image recognition algorithms to identify the type and quantity of food.

[1501] Step 6:

[1502] The server retrieves the calorie and PFC values ​​of the food from the database based on the identified food and calculates the total value.

[1503] Step 7:

[1504] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is then sent to a server.

[1505] Step 8:

[1506] The server transmits the calculated calories and PFC values, as well as the emotion data obtained from the emotion engine, to the smart glasses and the app.

[1507] Step 9:

[1508] Based on the received calorie and PFC information, the app subtracts the ingested calories and PFC from the appropriate daily calorie and PFC balance, calculates the remaining calorie intake and required PFC amount, and generates dietary advice based on the user's emotional state.

[1509] Step 10:

[1510] The smart glasses display advice based on the calculation results and emotions on a HUD that the user can see in their line of sight, such as "Remaining calorie intake: 2,010kcal, Protein requirement: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[1511] In this way, through a series of processing steps, the user can easily manage their diet and receive advice according to their emotional state, thereby maintaining a healthy lifestyle.

[1512] Example 2

[1513] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1514] In modern society, many people recognize the importance of daily dietary management, but it is difficult to keep track of calorie and nutrient intake. Furthermore, although a user's emotional state often influences food choices and intake, there are no tools to centrally manage these. This makes it difficult for users to manage themselves and maintain a healthy lifestyle and mental stability.

[1515] 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.

[1516] In this invention, the server includes means for inputting and saving basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for analyzing and acquiring the user's emotional state using an emotion engine, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, and means for adjusting the calorie and PFC display and dietary advice based on the user's emotional state. This allows the user to easily understand their calorie and nutrient intake and manage their diet in accordance with their emotional state.

[1517] "Basic user information" refers to personal data necessary for calculating calories and PFC balance, such as the user's height, weight, and body fat percentage.

[1518] "Image recognition algorithm" is a programming technology for recognizing the type and quantity of food and analyzing its calorie and PFC values.

[1519] The "emotion engine" is a technology that analyzes a user's facial expressions and tone of voice to recognize the user's emotional state in real time.

[1520] "Appropriate daily calorie intake and PFC balance" refers to the balance of calories, protein, fat, and carbohydrates required for the user to maintain a healthy lifestyle.

[1521] "Display in real time" means that information is displayed immediately in a state that the user can see directly in front of their eyes.

[1522] "Dietary advice" is a recommendation to encourage better dietary choices based on the user's emotional state.

[1523] "Smart glasses" are devices worn by users that use a camera to scan the contents of a meal and display information on a HUD (Head-Up Display).

[1524] A "calorie" is a unit of heat obtained from food and used by the body as energy.

[1525] "PFC" is an abbreviation for protein, fat, and carbohydrate, which are the major nutrients found in food.

[1526] The present invention provides a system that allows users to easily manage their dietary calories and PFC (protein, fat, carbohydrates) using an application and emotion engine linked to smart glasses, and also recognizes the user's emotions and reflects them in dietary management. The following describes in detail an embodiment of this system.

[1527] Enter basic user information

[1528] Users first install the smartphone app and enter basic information such as height, weight, and body fat percentage on the profile screen. This calculates the appropriate daily calorie intake and PFC balance for each user. The app then stores this data on a server.

[1529] Smart Glasses and Food Scanning

[1530] When a user eats a meal, they wear the smart glasses and use the camera in the smart glasses to scan the food contents. The acquired image data is sent from the smart glasses to a server.

[1531] Image Recognition and Calorie Counting

[1532] The server receives the image data and analyzes the type and quantity of food using an image recognition algorithm, such as TensorFlow or OpenCV. Based on the analysis results, the server retrieves the calorie and PFC information for each food item from the database and calculates the total.

[1533] Recognizing user emotions with an emotion engine

[1534] The smart glasses and app are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time, and the analyzed emotion data is sent to a server.

[1535] Calorie and PFC value display

[1536] The server sends the calculation results and emotional data to the smart glasses and app. Based on the received data, the app subtracts the calories and PFCs already ingested from the appropriate daily calorie and PFC balance, and calculates and displays the remaining calorie and PFC intake amounts.

[1537] Emotional diet management

[1538] The app and smart glasses adjust the calorie and PFC display based on the user's emotional state, offering advice such as "refuel when you're tired" or "choose foods that will help you relax when you're stressed."

[1539] Real-time management

[1540] Smart glasses display advice based on calculation results and emotions on a HUD (Head-Up Display) that users can see directly in front of their eyes, allowing them to receive advice based on calories, nutrients, and even their mental state in real time every time they eat.

[1541] Specific examples

[1542] Initial Setup

[1543] User: For example, enter the following data into the app: height 170cm, weight 70kg, body fat percentage 20%.

[1544] App: Calculates basal metabolic rate and sets the appropriate daily calorie intake as 2,500 kcal. Saves this information on the server.

[1545] Calculating calories in meals

[1546] User: Wears smart glasses while eating salad, grilled chicken, and rice for lunch.

[1547] Smart glasses: The camera scans the food and sends the image data to a server.

[1548] Server: Using an image recognition algorithm, the server analyzes the food to determine that the salad is 40kcal, the grilled chicken is 250kcal, and the rice is 200kcal, calculating a total of 490kcal, and sending the results to the app and smart glasses.

[1549] Emotion recognition and display of calories and PFC amount

[1550] App: Based on emotional data obtained from the user's facial expressions and tone of voice, the app calculates the remaining calorie intake as 2,010 kcal and updates the required PFC amount. If the user is feeling stressed, the app also advises them to eat foods that have a relaxing effect.

[1551] Smart Glasses: The HUD displays the following advice: "Remaining calories: 2,010kcal, Protein requirements: 80g, Fat: 60g, Carbohydrates: 250g" and "Eat foods that are effective in reducing stress."

[1552] By implementing it in this form, the user can easily manage their daily diet, which helps them maintain a healthy lifestyle and mental stability.

[1553] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1554] Step 1:

[1555] Users install the smartphone app and enter basic information.

[1556] Specific operation: The user launches the app and enters their height, weight, body fat percentage, etc. on the profile screen.

[1557] Input: Personal data such as height, weight, and body fat percentage

[1558] Data processing: The app formats the entered information for sending to a database.

[1559] Output: Basic user information in JSON format

[1560] Step 2:

[1561] The app sends the user's basic information to the server.

[1562] Specific behavior: The app sends JSON formatted data to the server as an HTTP request.

[1563] Input: Basic user information data in JSON format

[1564] Data calculation: The server analyzes the received data and stores it in a database.

[1565] Output: Basic information stored in the database

[1566] Step 3:

[1567] The server calculates the appropriate daily calorie intake and PFC balance.

[1568] Specific operation: The server retrieves user information from the database and uses an algorithm to calculate basal metabolic rate and daily calorie intake.

[1569] Input: User data such as height, weight, and body fat percentage

[1570] Data calculation: Calculation of basal metabolic rate and proper calorie balance

[1571] Output: Daily calorie intake and PFC balance

[1572] Step 4:

[1573] When the user eats, they wear the smart glasses and the camera scans the food.

[1574] Specific operation: Point the smart glasses camera at the food and take a picture of it.

[1575] Input: Food image data

[1576] Data processing: The smart glasses format the acquired image data for transmission to the server.

[1577] Output: Image data is prepared for transmission to the server

[1578] Step 5:

[1579] The server receives the image data and uses image recognition algorithms to analyze the type and quantity of food.

[1580] Specific operation: The server uses TensorFlow and OpenCV to identify the type and quantity of food from the image.

[1581] Input: Food image data

[1582] Data processing: Food analysis using image recognition algorithms

[1583] Output: Analyzed food type and quantity data

[1584] Step 6:

[1585] The server retrieves the calorie and PFC information for each food item from the database and calculates the total value.

[1586] Specific operation: The server refers to the food database and obtains the calories and PFC value for each food item.

[1587] Input: Data on the type and quantity of food analyzed

[1588] Data calculation: Calculate the total calories and PFC value of each food.

[1589] Output: Total calories and PFC value

[1590] Step 7:

[1591] The smart glasses and app use an emotion engine to analyze the user's emotional state and send the data to a server.

[1592] How it works: The app and smart glasses capture the user's facial expressions and tone of voice and analyze emotional data.

[1593] Input: User's facial expression data, voice data

[1594] Data processing: Real-time analysis using emotion engine

[1595] Output: Parsed emotion data

[1596] Step 8:

[1597] The server sends the calculation results and emotion data to the smart glasses and app.

[1598] Specific operation: The server sends the total calories, PFC value, and emotion data to the smart glasses and app.

[1599] Input: Total calories, PFC value, emotional data

[1600] Data processing: Format of transmitted data

[1601] Output: Data displayed on the smart glasses and in the app

[1602] Step 9:

[1603] The app and smart glasses provide dietary advice that reflects the user's emotions.

[1604] How it works: The app and smart glasses adjust the calorie and PFC display and provide dietary advice based on the user's emotional state.

[1605] Input: Total calories, PFC value, emotional data

[1606] Data Computing: Emotion-Based Advice Generation

[1607] Output: Meal advice displayed on HUD or app

[1608] Step 10:

[1609] The smart glasses display real-time advice on the HUD.

[1610] Specific operation: The smart glasses display advice based on calculation results and emotions on the HUD.

[1611] Input: Dietary advice data

[1612] Data processing: HUD display format

[1613] Output: Advice information at your fingertips

[1614] In this way, users can receive real-time calorie and nutrient management and emotion-based dietary advice.

[1615] (Application example 2)

[1616] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1617] Modern dietary management faces the challenge of easily and effectively managing calorie and nutrient intake. When choosing meals at restaurants or brick-and-mortar stores, it is difficult to obtain real-time nutritional information on the foods on offer, making it difficult to maintain appropriate intake. Dietary management that takes into account the user's emotional state is also important, and this lack of awareness needs to be addressed.

[1618] 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.

[1619] In this invention, the server includes means for inputting and storing basic information about the user, means for calculating the calorie and PFC values ​​of foods using an image recognition algorithm, means for calculating and displaying the appropriate daily calorie intake and PFC balance, means for displaying the remaining daily calorie and PFC intake in real time, means for recognizing the user's emotions and reflecting them in dietary management, and visual display means for presenting information in real time when selecting foods in a physical store. This makes it possible to obtain calorie and nutrient information in real time even when selecting meals in a physical store, and also enables appropriate dietary management that takes the user's emotional state into consideration.

[1620] "User" refers to a person who uses the system to manage their diet.

[1621] "Basic information" refers to personal data such as height, weight, and body fat percentage entered by the user.

[1622] "Image recognition algorithm" refers to a calculation method for analyzing image data acquired by a camera and identifying the type and quantity of food.

[1623] "Calories" refers to the amount of energy contained in food and is expressed in kcal.

[1624] "PFC" refers to the three major nutrients: protein, fat, and carbohydrates.

[1625] "Smart glasses" are eyeglass-type wearable devices that incorporate functions such as a camera and a head-up display (HUD).

[1626] "Server" means a computer system that processes information sent by users and stores and provides necessary data.

[1627] An "emotion engine" refers to software or algorithms that analyze a user's facial expressions and tone of voice to recognize their emotional state.

[1628] "Visual display device" refers to a display device that allows a user to view information in real time.

[1629] "Brick and mortar" refers to a food and beverage establishment that is located in a physical location, such as a cafe or restaurant.

[1630] To implement this invention, a user must first install an application on their smartphone and enter their basic information (height, weight, body fat percentage, etc.) Based on this basic information, the application calculates the appropriate daily calorie intake and PFC balance for each user and saves the results on a server.

[1631] Next, the user wears the smart glasses while eating. The smart glasses are equipped with a camera that can scan the contents of the meal. The captured image data is sent to a server in real time. The server uses an image recognition algorithm (e.g., TensorFlow or OpenCV) to analyze the type and quantity of food, retrieve the calorie and PFC values ​​of each food from a database, and calculate the total value.

[1632] Furthermore, the smart glasses are equipped with an emotion engine that analyzes the user's facial expressions and tone of voice to recognize their emotional state in real time. The analyzed emotion data is sent to a server, which then generates appropriate dietary advice based on this data. For example, if the user is feeling stressed, it will recommend foods that have a relaxing effect.

[1633] The calculation results and emotion analysis data from the server are displayed on a smartphone app and the smart glasses' HUD (head-up display). Users can check their calorie intake and PFC balance, as well as advice based on their emotional state, in real time while eating.

[1634] Examples:

[1635] If a user chooses a "chicken sandwich" and a "coffee" at a cafe, they put on the smart glasses and scan the food items. The server calculates the calories and PFC of the food items and displays them on the smart glasses' HUD as "Chicken sandwich: 350kcal, protein: 20g, fat: 10g, carbohydrates: 40g" and "Coffee (black): 5kcal, protein: 0g, fat: 0g, carbohydrates: 0g." At the same time, if the emotion engine determines that the user is looking for a relaxing experience, the HUD will also display advice such as "The chicken sandwich is a good choice, but how about some herbal tea for a relaxing effect?"

[1636] Example prompt sentence:

[1637] "Please analyze the types and quantities of food in this image. I'm looking for information on calories, protein, fat, and carbohydrates for each food item."

[1638] The system allows users to make healthy and emotionally relevant food choices in brick-and-mortar restaurants.

[1639] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1640] Step 1:

[1641] The user installs the application on their smartphone and enters basic information (height, weight, body fat percentage, etc.).

[1642] Input: User information such as height, weight, and body fat percentage

[1643] Output: Data on appropriate daily calorie intake and PFC balance

[1644] How it works: Based on the basic information entered, the application calculates the basal metabolic rate, daily calorie intake and PFC balance, and saves them on the server.

[1645] Step 2:

[1646] The user wears the smart glasses while eating, and the camera in the smart glasses scans the contents of the meal.

[1647] Input: Image data of meal contents

[1648] Output: Image data sent to the server

[1649] How it works: The camera in the smart glasses captures the food you eat and sends the image data to a server in real time.

[1650] Step 3:

[1651] The server uses an image recognition algorithm to analyze the transmitted image data.

[1652] Input: Image data of meal contents

[1653] Output: Data on food type and quantity

[1654] How it works: The server uses image recognition algorithms (such as TensorFlow or OpenCV) to identify the type and quantity of food and retrieves the calorie and PFC values ​​for each from a database.

[1655] Step 4:

[1656] The server adds up the calories and PFC values ​​of the food items it has acquired and sends the results to the smart glasses and smartphone app.

[1657] Input: data on food type and quantity, calories and PFC values

[1658] Output: Total calories and PFC value data

[1659] How it works: The server sums the calories and PFC values ​​of each food item retrieved from the database and sends the results to the smart glasses and smartphone app.

[1660] Step 5:

[1661] The smart glasses and app use an emotion engine to analyze the user's emotional state and send it to the server.

[1662] Input: User facial expressions and tone of voice

[1663] Output: Data about emotional state

[1664] How it works: The emotion engine analyzes the user's facial expressions and tone of voice and sends that data to the server.

[1665] Step 6:

[1666] The server generates appropriate dietary management advice for the user based on the emotion data.

[1667] Input: Data about emotional state

[1668] Output: Dietary advice

[1669] Operation: The server generates the necessary dietary advice (e.g., recommendations for foods with a relaxing effect) based on the emotional data.

[1670] Step 7:

[1671] The server displays the calculation results and emotion analysis data on the smart glasses' HUD and smartphone app.

[1672] Input: Total calories and PFC value data, dietary advice

[1673] Output: Information displayed on the smart glasses HUD and smartphone app

[1674] How it works: The server sends the calculation results and generated advice to the smart glasses HUD and smartphone app, allowing users to view the information in real time.

[1675] Through these steps, users can make their dining choices in brick-and-mortar stores healthier and more emotionally relevant.

[1676] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1677] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1678] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1679] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1680] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1681] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1682] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1683] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1684] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1685] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1686] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1687] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1688] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1689] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1690] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1691] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1692] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1693] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1694] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1695] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1696] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1697] The following is further disclosed regarding the above embodiment.

[1698] (Claim 1)

[1699] a means for inputting and storing basic user information;

[1700] A means for calculating the calorie and PFC value of food using an image recognition algorithm;

[1701] A means for calculating and displaying the appropriate daily calorie intake and PFC balance;

[1702] A system including a means for displaying the remaining calorie and PFC intake amounts available for the day in real time.

[1703] (Claim 2)

[1704] The system of claim 1, wherein smart glasses are used to acquire and store image data of food.

[1705] (Claim 3)

[1706] The system according to claim 1, which calculates the appropriate daily calorie intake and PFC balance based on basic information.

[1707] "Example 1"

[1708] (Claim 1)

[1709] A means to input and save basic information such as the user's height, weight, and body fat percentage;

[1710] means for analyzing the type and quantity of food using an image recognition algorithm and calculating calorie and nutritional values;

[1711] A means for calculating and displaying the appropriate daily calorie intake and nutritional balance;

[1712] The system includes a means for displaying the remaining calorie and nutrient intake amount for the day in real time.

[1713] (Claim 2)

[1714] 2. The system according to claim 1, wherein image data of food is acquired using a wearable device and transmitted to a server.

[1715] (Claim 3)

[1716] 2. The system according to claim 1, which calculates the appropriate daily calorie intake and nutritional balance based on the user's physical information.

[1717] "Application Example 1"

[1718] (Claim 1)

[1719] a means for inputting and storing basic user information;

[1720] A means for calculating the calorie and PFC value of food using an image recognition algorithm;

[1721] A means for calculating and displaying the appropriate daily calorie intake and PFC balance;

[1722] A means for displaying the remaining calories and PFC intake available for the day in real time;

[1723] means for calculating and displaying in real time the calorie and PFC values ​​of food ordered by a user through a digital device;

[1724] A system including means for using an image capture device to capture and transmit images of the food product to a server.

[1725] (Claim 2)

[1726] The system of claim 1, wherein smart glasses are used to acquire and store image data of food.

[1727] (Claim 3)

[1728] The system according to claim 1, which calculates the appropriate daily calorie intake and PFC balance based on basic information.

[1729] "Example 2: Combining Emotion Engines"

[1730] (Claim 1)

[1731] a means for inputting and storing basic user information;

[1732] A means for calculating the calorie and PFC value of food using an image recognition algorithm;

[1733] means for analyzing and acquiring the emotional state of a user by an emotion engine;

[1734] A means for calculating and displaying the appropriate daily calorie intake and PFC balance;

[1735] A means for displaying the remaining calories and PFC intake available for the day in real time;

[1736] A system including means for adjusting calorie and PFC display and dietary advice based on the user's emotional state.

[1737] (Claim 2)

[1738] The system of claim 1, wherein smart glasses are used to acquire and store image data of food.

[1739] (Claim 3)

[1740] The system according to claim 1, which calculates the appropriate daily calorie intake and PFC balance based on basic information.

[1741] "Application example 2 when combining emotion engines"

[1742] (Claim 1)

[1743] a means for inputting and storing basic user information;

[1744] A means for calculating the calorie and PFC value of food using an image recognition algorithm;

[1745] A means for calculating and displaying the appropriate daily calorie intake and PFC balance;

[1746] A means for displaying the remaining calories and PFC intake available for the day in real time;

[1747] A means for recognizing the user's emotions and reflecting them in dietary management;

[1748] A system including a visual display means for presenting real-time information during food selection in a brick-and-mortar store.

[1749] (Claim 2)

[1750] The system of claim 1, wherein smart glasses are used to acquire and store image data of food.

[1751] (Claim 3)

[1752] The system according to claim 1, which calculates the appropriate daily calorie intake and PFC balance based on basic information. [Explanation of symbols]

[1753] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting and storing basic user information; A means for calculating the calorie and PFC value of food using an image recognition algorithm; A means for calculating and displaying the appropriate daily calorie intake and PFC balance; A system including a means for displaying the remaining calorie and PFC intake amounts available for the day in real time.

2. The system of claim 1 , wherein smart glasses are used to acquire and store image data of food.

3. The system according to claim 1, which calculates the appropriate daily calorie intake and PFC balance based on basic information.

Images