system

Abstract

A system is provided.SOLUTION: This system is provided with a means for inputting the taste of meal, allergy information and the data of life habit and transmitting them to a server, a means for preparing a user profile based on the received information and storing it in a database, and a means for collecting action data. A means for updating a profile, a means for sending information on ingredients in a refrigerator to a server, a means for generating a weekly cooking plan based on a user profile and the information on the ingredients in the refrigerator, a means for generating a purchase list of missing ingredients and cookware, a means for sending the purchase list to a user terminal as a reminder message, and a means for sending recipe information selected by the user to the server; The system includes a means for transmitting appropriate information to a server, a means for generating a guide corresponding to a progress situation and providing it to a user, and a means for generating a message for promoting sharing to an SNS after the end of cooking and transmitting it to the terminal of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Despite today's hectic lifestyles, many users desire an efficient and enjoyable cooking experience, yet the current situation is that the same dishes are often repeated at home every week. Furthermore, the increase in eating out and the use of processed foods has led to an imbalance in nutrition, and an increasing number of people lack basic cooking skills and knowledge. This has resulted in food waste and an inability to accommodate diverse dietary habits. Furthermore, selecting safe ingredients and recipes for users with allergies is also a challenge. [Means for solving the problem]

[0005] This invention is a system that suggests optimal ingredients and dishes based on a user's lifestyle and individual preferences. Specifically, it provides a means for inputting data on the user's dietary preferences, allergy information, and lifestyle habits, and sending the input information to a server. It also provides a means for creating a user profile based on the received information and saving it in a database, and a means for collecting user behavior data and updating the profile.

[0006] The system includes a means for recognizing information about ingredients in the refrigerator and sending it to a server, thereby providing a means for generating a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator, and a means for generating a shopping list for ingredients and cooking utensils that are running low and sending it to the user's terminal as a reminder message.

[0007] Furthermore, the system includes means for transmitting recipe information selected by the user from the suggested recipes to the server, monitoring the cooking progress in real time, and transmitting appropriate information to the server.In this way, a system is provided which includes means for generating and providing a guide according to the cooking progress to the user, and means for generating and sending a message to the user's device after cooking is completed, encouraging the user to share the cooking on social media.

[0008] "User's dietary preferences" refer to the types of foods and cuisines that a user likes to eat.

[0009] "Allergy Information" means information about specific foods or ingredients that a user cannot consume.

[0010] "Lifestyle data" refers to information about a user's daily activity patterns and schedules.

[0011] "Server" means the central system that receives, processes, stores and transmits information from User Devices.

[0012] A "user profile" is an individual data set created based on a user's dietary preferences, allergy information, and lifestyle data.

[0013] "Database" means a system for structured storage of user profiles and other related information.

[0014] "Behavioral data" refers to information about the dishes a user actually makes and the ingredients they purchase.

[0015] "Refrigerator food information" refers to data about food items currently stored in the user's refrigerator.

[0016] A "meal plan" is a list of meal suggestions for a certain period of time (usually a week) that is generated based on the user's profile and the ingredients in the refrigerator.

[0017] A "shopping list" is a list of ingredients and cooking equipment that are in short supply based on a cooking plan.

[0018] A "reminder message" is a message that notifies users of important information or actions.

[0019] "Recipe information" refers to information about the ingredients and steps required to make a particular dish.

[0020] "Progress" refers to the current stage or state of a user's cooking progress.

[0021] A "guide" is an instruction or advice given as the cooking progresses.

[0022] "Messages encouraging sharing on social media" are messages encouraging users to post their completed dishes on social networking services. [Brief explanation of the drawings]

[0023] [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

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[0045] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[0046] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[0047] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the cooking process of the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. After the dish is complete, the server sends a message to the device such as "Share this dish on social media" to encourage the user to share it.

[0048] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. It is expected that this invention will help solve many of the problems facing modern society.

[0049] The processing flow will be explained below.

[0050] Step 1:

[0051] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[0052] Step 2:

[0053] The terminal transmits the input information to the server.

[0054] Step 3:

[0055] The server creates a user profile based on the received information and stores it in a database.

[0056] Step 4:

[0057] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[0058] Step 5:

[0059] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[0060] Step 6:

[0061] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0062] Step 7:

[0063] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[0064] Step 8:

[0065] The server sends the shopping list as a reminder message to the user's terminal.

[0066] Step 9:

[0067] The user selects the recipe they like from the suggested recipes.

[0068] Step 10:

[0069] The terminal transmits the selected recipe information to the server.

[0070] Step 11:

[0071] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[0072] Step 12:

[0073] The server generates audio and video guides according to the progress and sends them to the device.

[0074] Step 13:

[0075] The device provides audio and video guidance to the user.

[0076] Step 14:

[0077] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[0078] Step 15:

[0079] The completed dish is shared on social media based on the message provided by the user.

[0080] This process allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[0081] Example 1

[0082] 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."

[0083] Conventional meal management systems struggle to provide personalized meal plans that comprehensively reflect a user's dietary preferences, allergies, and lifestyle habits. Furthermore, they lack systems that effectively utilize information about ingredients in the refrigerator, monitor the cooking progress in real time, and provide appropriate guidance. Furthermore, they lack functionality for continuously collecting and updating user behavior data and encouraging users to share their cooking on social media after cooking is complete.

[0084] 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.

[0085] In this invention, the server includes a means for monitoring the user's process of handling ingredients and cooking in real time and providing audio or video guidance as needed, a means for using an AI camera to recognize ingredient information in the refrigerator, and a means for automatically updating the shopping list based on information from the user's device, thereby enabling the creation of cooking plans based on the user's individual information, real-time cooking support, and efficient ingredient management.

[0086] "User" refers to a person who uses the system to provide personal information such as dietary preferences, allergy information, and lifestyle habits.

[0087] A "device" is an electronic device, such as a smartphone or tablet, that a user uses to enter information and receive reminders and guidance.

[0088] A "server" is a computer system that manages data sent by users and performs profile generation, cooking plan creation, real-time monitoring, etc.

[0089] A "user profile" is a data set constructed based on a user's dietary preferences, allergy information, lifestyle habits, etc.

[0090] A "database" is a data management system for storing user profile information, ingredient information, and the like.

[0091] "Information about ingredients in the refrigerator" is data about the types and quantities of ingredients stored in the refrigerator.

[0092] An "AI camera" is a camera system that uses image recognition technology to recognize information about ingredients in a refrigerator.

[0093] A "meal plan" is a weekly meal plan that is suggested based on the user's profile and the ingredients in their fridge.

[0094] A "shopping list" is a list of ingredients and equipment needed to execute a cooking plan, and is a list of items that the user must assemble.

[0095] A "reminding message" is a message that notifies the user of ingredients or equipment that need to be purchased.

[0096] "Recipe information" refers to detailed cooking instructions and ingredient information for the proposed recipe.

[0097] "Real-time monitoring" is the process of checking the user's cooking process in real time and understanding the status.

[0098] "Guides" are audio and video instructions provided to users as they progress through the cooking process.

[0099] "Sharing on social media" refers to the act of posting photos and information about the finished dish on a social networking service.

[0100] The following describes an embodiment of the present invention. The present invention is a system that provides personalized cooking plans based on a user's dietary preferences, allergy information, and lifestyle data, provides real-time assistance during cooking, and ultimately reduces food waste and improves the user's nutritional balance.

[0101] Hardware and software used

[0102] 1. Device: An electronic device such as a smartphone or tablet where users enter information and receive reminders and guidance.

[0103] 2. Server: A computer system that uses cloud services (e.g., AWS, Google Cloud) to manage the data sent by users and perform functions such as generating profiles, creating cooking plans, and real-time monitoring.

[0104] 3. AI Camera: This uses the device's built-in camera and image recognition software (e.g., TensorFlow, OpenCV) to recognize information about ingredients in the refrigerator.

[0105] 4. Database: A SQL or NoSQL database (e.g., MySQL, MongoDB) to store user profile information and ingredient information.

[0106] 5. Generative AI model: A language model (e.g., OpenAI GPT-4) to generate guides and messages based on prompts.

[0107] Example of a system

[0108] For example, the following shows a case where the AI ​​camera recognizes the chicken and vegetables in the user's refrigerator and sends the information to the server.

[0109] User information entry and submission

[0110] Using a smartphone app, users input data such as their dietary preferences, allergy information, and lifestyle habits. For example, they can enter information such as "I have a nut allergy" or "I like high-protein meals." The device then sends this information to a server, which then creates a user profile based on the information entered and stores it in a database.

[0111] Recognizing ingredients in the refrigerator

[0112] The user opens the refrigerator door and takes a picture of the inside with the AI ​​camera on their smartphone. The AI ​​camera recognizes ingredients such as chicken and cabbage and sends information such as "there is chicken and cabbage in the refrigerator" to the server.

[0113] Generate a meal plan

[0114] The server generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator, suggesting recipes such as "teriyaki chicken" and "stir-fried cabbage and chicken."

[0115] Missing item list and reminder messages

[0116] The server generates a list of missing ingredients and utensils needed to execute the cooking plan and sends a shopping list to the user's device as a reminder message, such as "You need to buy soy sauce and sugar."

[0117] Recipe selection and cooking assistance

[0118] The user selects "Teriyaki Chicken" from the suggested recipes and sends the information to the server. When the user starts cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the chicken over" and provides instructions to the user via voice.

[0119] Promoting social media sharing

[0120] After the dish is ready, the server generates a message such as "Share this dish on social media" and sends it to the user's device. The user taps the message to post it on social media.

[0121] Prompt Sentence Examples

[0122] 1. "Please suggest recipes based on the user's dietary preferences and allergy information."

[0123] 2. "Generate recipes using the chicken and vegetables in your fridge and guide you as you progress."

[0124] 3. "After cooking, please generate a message to share on social media."

[0125] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. This invention can help solve many of the problems facing modern society.

[0126] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0127] Step 1:

[0128] Users use a smartphone app to input their preferences, allergy information, and lifestyle data. The input information is personalized data about the user's preferences and allergies. Once the user has completed the input, the device sends it to the server. Specifically, the user enters information such as "I have a nut allergy" or "I like high-protein meals" into the input form and taps the "Submit" button.

[0129] Input: User-entered preferences, allergy information, and lifestyle data

[0130] Output: User data sent to the server

[0131] Step 2:

[0132] The server creates a user profile based on the received data and stores it in a database. This profile generation involves analyzing the user's input data and processing it to classify it into appropriate categories. Specifically, the server generates profile information such as "User A has a nut allergy and prefers a high-protein diet" and stores it in the database.

[0133] Input: User data sent to the server

[0134] Output: User profile stored in database

[0135] Step 3:

[0136] The user opens the refrigerator door and takes a picture of the inside of the refrigerator with the AI ​​camera on their smartphone. The AI ​​camera uses image recognition technology to automatically recognize the ingredients inside the refrigerator. The recognized ingredient information is sent from the device to the server. Specifically, the user takes a picture of chicken or cabbage with the camera, and the AI ​​camera recognizes them as "chicken" and "cabbage."

[0137] Input: Image data of the inside of the refrigerator

[0138] Output: Ingredient information sent to the server

[0139] Step 4:

[0140] The server generates a weekly cooking plan based on the received ingredient information and the user profile created earlier. This involves data calculations to select the optimal menu by comparing the ingredient information with the user's preferences. Specifically, the server suggests recipes such as "Teriyaki Chicken" and "Stir-fried Cabbage and Chicken."

[0141] Input: Ingredient information and user profile sent to the server

[0142] Output: Weekly meal plan

[0143] Step 5:

[0144] The server generates a list of ingredients and utensils needed to execute the cooking plan and sends it to the user's device as a reminder message. Specifically, the server creates a list such as "You need to buy soy sauce and sugar" and sends a message to the user's smartphone.

[0145] Enter: Weekly Meal Plan

[0146] Output: Shopping list sent as reminder messages

[0147] Step 6:

[0148] The user selects the desired dish from the suggested recipes, and the device sends that information to the server. Specifically, the user selects "Teriyaki Chicken" in the app and taps the "Select" button.

[0149] Input: Recipe information selected by the user

[0150] Output: Selected recipe information sent to the server

[0151] Step 7:

[0152] When the user starts cooking, the AI ​​camera monitors the cooking process in real time. The server provides appropriate guidance based on the recognized progress. Specifically, the AI ​​camera monitors the cooking of the chicken, and the server generates a voice prompt such as "Please turn the chicken over" and sends the instruction to the device.

[0153] Input: Real-time video of the cooking process

[0154] Output: Audio prompts provided to the user

[0155] Step 8:

[0156] Once the dish is ready, the server generates a message to share it on social media and sends it to the user's device. Specifically, the server generates a message such as "Share this dish on social media" and sends it to the user's smartphone.

[0157] Input: Notification of cooking completion

[0158] Output: Message encouraging social media sharing

[0159] The above are the specific processing steps of the program of this system.

[0160] (Application example 1)

[0161] 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."

[0162] In modern life, it is difficult to receive recipe suggestions that suit individual dietary preferences, allergies, and lifestyle habits. Furthermore, it is often inconvenient when certain ingredients or cooking equipment are lacking. Furthermore, without real-time monitoring of cooking progress or guidance, mistakes are likely to occur during the cooking process, making it difficult to have an efficient cooking experience. Furthermore, there are few systems that allow users to receive individually customized suggestions when selecting delivery menus. There is a need for an appropriate system to solve these issues.

[0163] 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.

[0164] In this invention, the server includes a means for generating an individually customized delivery menu based on a user profile and ingredient information, a means for providing the delivery menu to the user and receiving an order, and a means for transmitting recipe information selected by the user from the suggested recipes to the server. This allows users to receive customized cooking suggestions that suit their individual preferences, allergies, and lifestyles, and allows them to quickly identify missing ingredients and cooking utensils and receive reminders as a shopping list. Furthermore, the cooking progress is monitored in real time and audio or video guidance is provided as needed, providing an efficient and error-free cooking experience and allowing users to order a menu that meets their individual needs, even when ordering delivery.

[0165] A "user profile" is an individual data set created based on information such as a user's dietary preferences, allergy information, lifestyle habits, and behavioral data.

[0166] "Server" means a computing system that receives, processes, stores, and provides the necessary data to the User.

[0167] "Delivery Menu" means a meal or ingredient delivery option customized based on user profile and ingredient information.

[0168] "Cooking progress" is information that monitors the current stage of cooking in real time.

[0169] "Guide" means audio or video instructions provided to a user as they cook a dish.

[0170] "Ingredient information" is data relating to the types and quantities of ingredients present in the refrigerator.

[0171] A "reminder message" is a notification that prompts the user to purchase the necessary ingredients and cooking equipment.

[0172] A "suggested recipe" is a server-generated suggestion for how to cook a dish based on the user's profile and ingredient information.

[0173] "Ordering" means the act of a user purchasing a dish or ingredient selected from the delivery menu.

[0174] "SNS sharing message" is a notification that encourages the user to post the results of their cooking to a social networking service after they have finished cooking.

[0175] An "AI camera" is a camera that has the ability to recognize objects using artificial intelligence technology.

[0176] This invention is a system that provides individually customized meal suggestions and delivery menus based on a user's dietary preferences, allergy information, lifestyle habits, behavioral data, etc. Specifically, it is implemented in the following steps.

[0177] Program Generation

[0178] The server receives data on dietary preferences, allergies, and lifestyle habits entered from the user's device and creates a user profile based on this data. The created profile is stored in a database, and user behavior data is continuously collected and updated. Using this data, the server generates an individually customized delivery menu. In addition, information on ingredients in the refrigerator is recognized using an AI camera installed on the device and sent to the server.

[0179] Hardware and software used

[0180] 1. Server:

[0181] The server is built using Python and the Flask framework.

[0182] Machine learning libraries such as TensorFlow are used for data processing and AI models are executed.

[0183] 2. Terminal:

[0184] The user's smartphone or tablet.

[0185] An AI camera for recognizing food ingredient information.

[0186] Speakers and displays to provide audio and video guides.

[0187] Processing description

[0188] 1. Create a user profile:

[0189] The server receives the user's submitted data on preferences, allergies, and lifestyle habits and creates a user profile based on it, storing the information in a database for later use.

[0190] 2. Collecting ingredient information:

[0191] The AI ​​camera installed on the device recognizes the ingredients in the refrigerator and sends that information to a server, which uses it to generate recipes and menus.

[0192] 3. Generate delivery menu:

[0193] The server generates an individually customized delivery menu based on the user profile and ingredient information, using a generative AI model to suggest the optimal menu.

[0194] 4. Cooking Progression Guide:

[0195] Based on the recipe information selected by the user, the server monitors the cooking progress in real time and generates appropriate guidance (audio or video).

[0196] 5. Sharing to social media:

[0197] After cooking is complete, the server generates a message encouraging sharing on social media and sends it to the user's device.

[0198] Specific examples

[0199] To give a specific example, let's say a user uses the AI ​​camera on their smartphone to recognize the chicken and vegetables in their refrigerator. The server generates a cooking plan for "Teriyaki Chicken" based on the user profile, and sends a reminder message to purchase any necessary condiments if they are missing. While cooking, the device provides voice guidance such as "Please turn the meat over," and once the dish is finished, the server sends the user a message saying, "Share this dish on social media."

[0200] Prompt Sentence Examples

[0201] Here are some example prompts to input to the generative AI model based on the following information:

[0202] User Preferences: Japanese, Gluten-Free

[0203] Allergy Information: Dairy

[0204] Lifestyle: Health conscious

[0205] Ingredients in the refrigerator: chicken, carrots, cabbage, ginger

[0206] Generate a weekly cooking plan based on the information below.

[0207] This system allows users to receive optimal meal suggestions and delivery menus tailored to their individual preferences, allergies, and lifestyles, as well as receive support during the cooking process, helping to realize an efficient and healthy diet.

[0208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0209] Step 1:

[0210] Creating and saving a user profile

[0211] Users use devices such as smartphones or tablets to input personal data such as preferences, allergy information, and lifestyle habits. This data is sent and received by a server, which creates a user profile. Specifically, an individual profile is stored in a database based on the user's preferences and allergy information. At this time, the database assigns each user a unique ID and centrally manages data related to that ID.

[0212] Input: User preferences, allergy information, lifestyle data

[0213] Data processing: Converting received data into a format and saving it to a database

[0214] Output: User profile creation and saving to database completed

[0215] Step 2:

[0216] Collecting information about ingredients in the refrigerator

[0217] The user takes a photo of the ingredients in the refrigerator using the AI ​​camera installed on the device. The device analyzes the image and recognizes the ingredient information. The recognized ingredient information is sent to the server and stored in an ingredient database. The AI ​​camera performs image analysis using machine learning models such as TensorFlow.

[0218] Input: Images of ingredients in the refrigerator

[0219] Data processing: Image analysis (machine learning model), food ingredient data extraction

[0220] Output: Recognized ingredients

[0221] Step 3:

[0222] Generate delivery menu

[0223] The server generates a personalized delivery menu based on the user profile and the ingredients in the refrigerator, using a generative AI model (e.g., GPT-3) to suggest menu items that suit the user's preferences and allergies.

[0224] Input: User profile, refrigerator ingredients information

[0225] Data processing: Menu generation using generative AI models

[0226] Output: Delivery menu suggestions

[0227] Step 4:

[0228] Generate shopping lists and send reminder messages

[0229] The server generates a shopping list of missing ingredients and cooking utensils based on the delivery menu and the information on ingredients in the refrigerator, and sends this shopping list to the user's device as a reminder message.

[0230] Input: Delivery menu, information on ingredients in the refrigerator

[0231] Data processing: Identifying necessary ingredients and equipment, and generating a shopping list

[0232] Output: Shopping list as reminder messages

[0233] Step 5:

[0234] Monitor cooking progress and provide guidance

[0235] Once the user selects a suggested recipe and begins cooking, the device monitors the cooking progress in real time. The server provides audio and video guidance to the user based on the progress. Instructions such as "Please turn the meat over" are sent to the device in real time, and the user follows them as they cook.

[0236] Input: User's cooking progress

[0237] Data processing: Real-time progress analysis, guide generation

[0238] Output: Audio and video guides

[0239] Step 6:

[0240] Encourage sharing on social media after cooking is complete

[0241] After the cooking is complete, the server generates a message prompting the user to share the cooking on social media and sends it to the user's device. The user receives this message and posts a photo of the cooking and a comment on the social media.

[0242] Input: Cooking completion information

[0243] Data processing: Generating SNS sharing messages

[0244] Output: SNS sharing message notification to user

[0245] 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.

[0246] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[0247] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[0248] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[0249] Furthermore, by combining it with an emotion engine, the system recognizes the user's emotional state and transmits that data to the server. The server then uses this emotional data to further personalize the user's cooking experience. Specifically, the system can adjust cooking suggestions and change the content and tone of guidance based on the user's progress based on the emotions recognized by the emotion engine.

[0250] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. Furthermore, if the user is feeling stressed, the guidance tone can be softened and instructions can be given in a gentler voice.

[0251] After the dish is complete, the server sends a message to the device, such as "Share this dish on social media," encouraging the user to share the joy of cooking. This system not only allows users to have an efficient and enjoyable cooking experience, but also reduces food waste and improves nutritional balance. This invention is expected to help solve many of the challenges facing modern society.

[0252] The processing flow will be explained below.

[0253] Step 1:

[0254] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[0255] Step 2:

[0256] The terminal transmits the input information to the server.

[0257] Step 3:

[0258] The server creates a user profile based on the received information and stores it in a database.

[0259] Step 4:

[0260] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[0261] Step 5:

[0262] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[0263] Step 6:

[0264] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0265] Step 7:

[0266] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[0267] Step 8:

[0268] The server sends the shopping list as a reminder message to the user's terminal.

[0269] Step 9:

[0270] The user selects the recipe they like from the suggested recipes.

[0271] Step 10:

[0272] The terminal transmits the selected recipe information to the server.

[0273] Step 11:

[0274] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, recognizing their emotional state.

[0275] Step 12:

[0276] The device transmits the recognized emotion data to the server.

[0277] Step 13:

[0278] The server uses the emotional data to personalize the user's cooking experience, adjusting the content and tone of the instructions depending on the cooking progress.

[0279] Step 14:

[0280] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[0281] Step 15:

[0282] The server generates audio and video guides according to the progress and sends them to the device.

[0283] Step 16:

[0284] The device provides users with audio and video guidance, and if the user is feeling stressed, the guidance tone will be softened and instructions will be given in a gentle voice.

[0285] Step 17:

[0286] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[0287] Step 18:

[0288] The finished dish is shared on social media based on a message provided by the user, which is also customized according to the user's emotional state.

[0289] This process allows users to have an efficient and enjoyable cooking experience, while receiving personalized support tailored to their individual emotional state.

[0290] Example 2

[0291] 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."

[0292] Currently, there are no systems that automatically generate personalized cooking plans based on dietary preferences, allergies, and lifestyle habits. There is also a lack of systems that can recognize ingredients in the refrigerator, list the necessary ingredients and cooking utensils, or provide guidance based on the cooking progress. Furthermore, technology that personalizes the cooking experience based on the user's emotional state is underdeveloped. Therefore, there is a need for systems that provide an efficient and enjoyable cooking experience, reduce food waste, and improve nutritional balance.

[0293] 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.

[0294] In this invention, the server includes: means for inputting data on a user's dietary preferences, allergy information, and lifestyle habits; means for transmitting the input information to the server; means for creating a user profile based on the received information and saving it to a database; means for collecting user behavior data and updating the profile; means for recognizing information about ingredients in the refrigerator and transmitting it to the server; means for generating a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator; means for generating a shopping list for missing ingredients and cooking utensils; means for transmitting the shopping list as a reminder message to the user's device; means for transmitting information about a recipe selected by the user from suggested recipes to the server; means for monitoring the cooking progress in real time and transmitting appropriate information to the server; means for generating and providing guidance based on the cooking progress; means for generating and providing a message encouraging sharing on social media after cooking is completed and transmitting it to the user's device; means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server; and means for adjusting the content and tone of the guidance provided based on the emotion data. This enables automatic generation of individual cooking plans, providing an efficient and enjoyable cooking experience, reducing food waste, and improving nutritional balance.

[0295] A "user" is a person who uses the system and provides data on dietary preferences, allergy information, and lifestyle habits.

[0296] A "server" is a computer system that receives, processes, stores, and performs various calculations on data.

[0297] "Terminal" means a device used by a user to enter data or receive notifications from the system, including a smartphone or tablet.

[0298] A "profile" is a data set that centralizes a user's unique information, including the user's dietary preferences, allergy information, lifestyle habits, and other behavioral data.

[0299] "Database" means the digital storage system in which the Server stores user profiles and other related information.

[0300] An "AI camera" is a camera that uses artificial intelligence to recognize ingredients in the refrigerator.

[0301] A "reminder message" is a notification message that prompts the user to take necessary action.

[0302] A "cooking plan" is a set of suggested cooking recipes and preparation plans based on a user profile and the ingredients in the refrigerator.

[0303] The "emotion engine" is a technology that analyzes a user's facial expressions and voice data to recognize their emotional state.

[0304] A "guide" is information containing instructions and advice that are generated as the cooking progresses and is provided in audio or video format.

[0305] The system collects data on a user's dietary preferences, allergies, and lifestyle habits, and provides personalized cooking plans based on that data. It also recognizes the ingredients in the refrigerator, provides a list of ingredients and cooking utensils needed, provides real-time cooking guidance, and personalizes the plan according to the user's emotional state.

[0306] Hardware and software used

[0307] Device: A smartphone or tablet where users enter information and receive instructions and guidance.

[0308] Server: A computer system that receives, processes, stores, and analyzes data.

[0309] AI camera: A camera used to recognize ingredients in the refrigerator.

[0310] Emotion engine: Technology for recognizing a user's emotional state by analyzing their facial expressions and voice data.

[0311] Specific details of data processing and calculation

[0312] 1. Data entry and submission

[0313] Device: Users enter their dietary preferences, allergy information, and lifestyle data through an app on their smartphone or tablet.

[0314] Server: Receives data sent from the device, creates a user profile, and stores it in a database.

[0315] 2. Recognition and transmission of food ingredient information

[0316] Terminal: An AI camera installed inside the refrigerator recognizes ingredients and sends that information to the server.

[0317] Server: Matches the received ingredient information with the user profile and generates an appropriate cooking plan.

[0318] 3. Generating a Cooking Plan

[0319] Server: Automatically generates a personalized weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0320] Server: Identifies missing ingredients and cooking equipment, creates a shopping list, and sends it to the user's device as a reminder message.

[0321] 4. Real-time cooking guide

[0322] User: Selects a suggested cooking recipe and sends the information to the server via the device.

[0323] Server: Monitors the cooking progress in real time and generates appropriate audio and video guides to send to the device.

[0324] 5. Recognizing and guiding emotional states

[0325] Emotion engine: Analyzes the user's facial expressions and voice data to recognize their emotional state.

[0326] Server: Based on emotional data, the content and tone of the guide can be adjusted to further personalize the user's cooking experience.

[0327] Specific operation example

[0328] The user enters their preferred ingredients (e.g., chicken, tomato), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) on their smartphone and presses the send button. This data is sent to the server, which creates a user profile and uses an AI camera to identify ingredients in the refrigerator (e.g., 200g of chicken, 1 cabbage). Based on this information, the server generates a cooking plan such as "Teriyaki Chicken" and sends the user a shopping list of missing seasonings and ingredients as a reminder message. When the user selects a recipe and begins cooking, the server provides audio guidance such as "Please turn the meat over," adjusting the guidance tone according to the user's stress level as recognized by the emotion engine. When the dish is complete, a notification is displayed urging the user to "Share this dish on social media."

[0329] Examples of prompt statements

[0330] "Generate the perfect weekly cooking plan based on your preferences and allergies."

[0331] "Recognize the ingredients in your refrigerator and suggest cooking recipes based on them."

[0332] "Consider the user's emotional state and adjust the content and tone of your cooking progression guide."

[0333] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0334] Step 1:

[0335] Data Entry and Submission

[0336] Users use the device to input their food preferences (e.g., favorite foods), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) through an app on their smartphone or tablet. This input data is stored on the device and prepared for transmission.

[0337] Input: User preferences, allergy information, and lifestyle data.

[0338] Data processing: Validation and formatting of input data.

[0339] Output: Data ready to be sent to the server.

[0340] Step 2:

[0341] Data transmission and storage

[0342] The server receives the data sent from the device. Based on this, the server generates a user profile and stores it in a database. For example, the server creates a new profile and stores each attribute (preferences, allergies, lifestyle habits) in the database.

[0343] Input: User data sent from the device.

[0344] Data processing: A profile is generated based on user data and stored in a database.

[0345] Output: The updated user profile in the database.

[0346] Step 3:

[0347] Recognizing and transmitting information about ingredients in the refrigerator

[0348] An AI camera connected to the device recognizes the ingredients in the refrigerator and sends that information to a server. For example, the AI ​​camera recognizes that the refrigerator contains 200g of chicken and one cabbage.

[0349] Input: Video of food in the refrigerator.

[0350] Data processing: Extraction of food ingredient information through video analysis.

[0351] Output: Ingredient information sent to the server.

[0352] Step 4:

[0353] Generate a recipe plan and list missing ingredients

[0354] The server generates a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator. It lists ingredients, seasonings, and cooking utensils that are in short supply and generates a shopping list. For example, it suggests "teriyaki chicken" and prompts the user to purchase necessary seasonings (e.g., soy sauce and sugar).

[0355] Input: User profile, refrigerator food information.

[0356] Data processing: Generate an appropriate cooking plan based on user profile and ingredient information. List ingredients that are in short supply.

[0357] Output: Meal plan and shopping list.

[0358] Step 5:

[0359] Sending shopping list reminder messages

[0360] The server then sends the generated shopping list to the device as a reminder message. For example, the user's smartphone might receive a notification saying, "Please buy soy sauce and sugar."

[0361] Enter: Shopping List.

[0362] Data processing: Convert shopping lists into reminder messages.

[0363] Output: The reminder message sent to the user's device.

[0364] Step 6:

[0365] Select and submit a recipe

[0366] The user selects their favorite recipe from the multiple recipe suggestions and sends the information to the server via their device. For example, they select "Teriyaki Chicken."

[0367] Input: A suggested recipe.

[0368] Data processing: The selected recipe information is sent to the server.

[0369] Output: The selected recipe information sent to the server.

[0370] Step 7:

[0371] Monitor cooking progress and provide guidance

[0372] The server monitors the cooking progress in real time and generates appropriate guidance (e.g., "Please turn the meat over") and sends it to the device.

[0373] Input: Select recipe information and real-time progress data.

[0374] Data processing: Proceeding and generating guides.

[0375] Output: The guide sent to your device.

[0376] Step 8:

[0377] Recognizing and guiding emotional states

[0378] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotional state. The server then adjusts the content and tone of the guide based on this data. For example, if the user is feeling stressed, the tone of the guide will be changed to a gentler tone.

[0379] Input: User's facial expressions and voice data.

[0380] Data processing: Data analysis for emotional state recognition and guided adjustment.

[0381] Output: Adjusted guide.

[0382] Step 9:

[0383] Encourage sharing on social media after cooking is complete

[0384] When the dish is complete, the server sends a message to the device saying, "Share this dish on social media," encouraging the user to share the results of their cooking with others.

[0385] Input: Notification that the food is ready.

[0386] Data processing: Generating messages encouraging sharing on social media.

[0387] Output: The sharing prompt sent to the device.

[0388] (Application example 2)

[0389] 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."

[0390] Conventional cooking assistance systems lack personalized recipe suggestions based on users' dietary preferences and allergy information, and have problems such as shortages of certain ingredients and tedious recipe planning. Furthermore, the content and tone of the cooking assistance could not be adjusted according to the user's emotional state, which often caused stress during the cooking process. Furthermore, purchasing missing ingredients was a manual process, preventing the establishment of an efficient supply chain.

[0391] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server, means for adjusting the content and tone of the guidance based on the emotion, means for ordering missing ingredients and cooking utensils, and means for generating prompt sentences with instruction content according to the emotion using a generative AI model. This enables personalized recipe suggestions for the user, enabling flexible cooking support according to emotions and efficient ingredient procurement.

[0392] "User dietary preferences" refer to the types of foods or cuisines that a particular user prefers to eat.

[0393] "Allergy information" refers to information that indicates a user's allergic reaction to a particular food or ingredient.

[0394] "Lifestyle habits" refers to the activities and behavioral patterns that a user engages in on a daily basis.

[0395] "Server" means a centralized computer system that receives and processes information from users and provides necessary data.

[0396] A "user profile" is an individual data set created based on information such as a user's food preferences, allergy information, and lifestyle habits.

[0397] A "database" is a system for systematically storing and managing information such as user profiles.

[0398] "Behavioral data" refers to data about a user's daily behavior, including information such as meal times and frequency, and the dishes they choose.

[0399] "Information about ingredients in the refrigerator" is information about the food and ingredients currently stored in the user's refrigerator.

[0400] A "cooking plan" is a cooking schedule for a specific period (for example, a week) that is created based on the user's profile and the ingredients in the refrigerator.

[0401] A "shopping list" is a list that is generated when specific ingredients or cooking equipment are in short supply based on a cooking plan.

[0402] A "remind message" is a message that notifies the user of important information or suggestions.

[0403] "Recipe information" refers to information about how to make the dish selected by the user and the ingredients needed.

[0404] "Cooking progress" refers to the current state of the user's cooking process.

[0405] "Guide" means instructions or advice provided to the user as they proceed with their cooking.

[0406] "Sharing on social media" refers to posting photos and information about the dishes created by users on social networking services.

[0407] The "emotion engine" is a system for recognizing a user's emotional state from their facial expressions and behavior.

[0408] A "generative AI model" is a machine learning algorithm that generates personalized content or instructions based on data.

[0409] A "prompt" is a document that provides specific instructions or guidelines generated by a generative AI model.

[0410] This invention is a system that provides personalized meal plans based on a user's dietary preferences, allergy information, lifestyle habits, and emotional state, and efficiently procures ingredients in cooperation with food delivery services. The system includes a user terminal, a server, an AI camera in the refrigerator, and an emotion engine.

[0411] First, the user enters data on their dietary preferences, allergies, and lifestyle habits through their device. This data is then sent to the server, which then creates a user profile based on that data and stores it in a database. The device also continuously collects user behavior data, which the server uses to update the profile.

[0412] Next, the refrigerator's AI camera recognizes the ingredients in the refrigerator and sends the information to a server. The server generates a weekly cooking plan based on this information and the user's profile. The cooking plan identifies any shortages of necessary ingredients or cooking equipment and generates a shopping list. This list is then sent to the user's device as a reminder message.

[0413] Once cooking begins, the user device sends the selected recipe information to the server, which monitors the cooking progress in real time. The server generates appropriate guidance based on the cooking progress and provides it to the user via audio and video. In addition, the emotion engine recognizes the user's emotional state and sends that data to the server to adjust the content and tone of the guidance. For example, if the user is feeling stressed, the server will provide instructions in a calmer tone.

[0414] After cooking is complete, the server sends a message to the user's device encouraging them to share the cooking experience on social media. This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[0415] The server generates a prompt like this:

[0416] Suggest recipes using the chicken and broccoli the user has in their fridge. If the user becomes stressed during the cooking process, calm the guide's tone and provide specific audio instructions.

[0417] This invention uses the Python Requests library to communicate with the server, and utilizes the server API to update profiles, update refrigerator contents, generate cooking plans, acquire emotions, and generate guides. This enables personalized recipe suggestions for users, enabling flexible cooking support based on emotions and efficient ingredient procurement.

[0418] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0419] Step 1:

[0420] Users input data such as dietary preferences, allergy information, and lifestyle habits into their device. The device then structures the data and sends it to the server, which then creates a user profile based on the data and stores it in a database.

[0421] Step 2:

[0422] The AI ​​camera recognizes the information about ingredients in the refrigerator and sends it to the server. The server adds the received information to the user's profile and updates the database. It also analyzes the information to generate a list of available ingredients.

[0423] Step 3:

[0424] Based on the user's profile and the ingredients in the refrigerator, the server generates a weekly cooking plan, a set of recipes optimized for the user's dietary preferences, allergies, and lifestyle habits, including a list of the ingredients and cooking equipment needed.

[0425] Step 4:

[0426] The server then identifies any missing ingredients and cooking utensils based on the cooking plan and generates a shopping list. The shopping list is then sent to the user's terminal as a reminder message. The user terminal receives the reminder message and notifies the user.

[0427] Step 5:

[0428] The user selects a dish from the suggested recipes and transmits the selected recipe information to the server via the user terminal, which adds data related to the selected recipe to the user profile and updates the database.

[0429] Step 6:

[0430] While cooking, the user device monitors the user's actions (e.g., preparation of ingredients and cooking progress) in real time. As the user progresses through each step of the recipe, the progress information is sent to the server. The server analyzes the progress and generates a guide for the next step.

[0431] Step 7:

[0432] The emotion engine recognizes the user's emotional state and sends that data to the server. The server then adjusts the content and tone of the guide based on the emotional data. For example, if the user is feeling stressed, the tone of the guide will be set to a gentler tone.

[0433] Step 8:

[0434] The server uses a generative AI model to generate prompts based on the cooking progress and emotional state of the user. These prompts are sent to the user's device as audio or video and provided to the user at the appropriate time.

[0435] Step 9:

[0436] After the cooking is finished, the server generates a message to encourage sharing on SNS and sends it to the user's device. The user's device receives this message and notifies the user, encouraging them to post photos and information about the cooking on SNS.

[0437] This provides an efficient and personalized cooking experience, allowing users to enjoy cooking without stress, and also enables efficient purchasing of ingredients that may be in short supply.

[0438] 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.

[0439] 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.

[0440] 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.

[0441] [Second embodiment]

[0442] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0443] 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.

[0444] 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).

[0445] 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.

[0446] 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.

[0447] 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).

[0448] 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.

[0449] 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.

[0450] 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.

[0451] 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.

[0452] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0453] 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."

[0454] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[0455] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[0456] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[0457] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the cooking process of the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. After the dish is complete, the server sends a message to the device such as "Share this dish on social media" to encourage the user to share it.

[0458] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. It is expected that this invention will help solve many of the problems facing modern society.

[0459] The processing flow will be explained below.

[0460] Step 1:

[0461] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[0462] Step 2:

[0463] The terminal transmits the input information to the server.

[0464] Step 3:

[0465] The server creates a user profile based on the received information and stores it in a database.

[0466] Step 4:

[0467] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[0468] Step 5:

[0469] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[0470] Step 6:

[0471] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0472] Step 7:

[0473] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[0474] Step 8:

[0475] The server sends the shopping list as a reminder message to the user's terminal.

[0476] Step 9:

[0477] The user selects the recipe they like from the suggested recipes.

[0478] Step 10:

[0479] The terminal transmits the selected recipe information to the server.

[0480] Step 11:

[0481] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[0482] Step 12:

[0483] The server generates audio and video guides according to the progress and sends them to the device.

[0484] Step 13:

[0485] The device provides audio and video guidance to the user.

[0486] Step 14:

[0487] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[0488] Step 15:

[0489] The completed dish is shared on social media based on the message provided by the user.

[0490] This process allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[0491] Example 1

[0492] 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."

[0493] Conventional meal management systems struggle to provide personalized meal plans that comprehensively reflect a user's dietary preferences, allergies, and lifestyle habits. Furthermore, they lack systems that effectively utilize information about ingredients in the refrigerator, monitor the cooking progress in real time, and provide appropriate guidance. Furthermore, they lack functionality for continuously collecting and updating user behavior data and encouraging users to share their cooking on social media after cooking is complete.

[0494] 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.

[0495] In this invention, the server includes a means for monitoring the user's process of handling ingredients and cooking in real time and providing audio or video guidance as needed, a means for using an AI camera to recognize ingredient information in the refrigerator, and a means for automatically updating the shopping list based on information from the user's device, thereby enabling the creation of cooking plans based on the user's individual information, real-time cooking support, and efficient ingredient management.

[0496] "User" refers to a person who uses the system to provide personal information such as dietary preferences, allergy information, and lifestyle habits.

[0497] A "device" is an electronic device, such as a smartphone or tablet, that a user uses to enter information and receive reminders and guidance.

[0498] A "server" is a computer system that manages data sent by users and performs profile generation, cooking plan creation, real-time monitoring, etc.

[0499] A "user profile" is a data set constructed based on a user's dietary preferences, allergy information, lifestyle habits, etc.

[0500] A "database" is a data management system for storing user profile information, ingredient information, and the like.

[0501] "Information about ingredients in the refrigerator" is data about the types and quantities of ingredients stored in the refrigerator.

[0502] An "AI camera" is a camera system that uses image recognition technology to recognize information about ingredients in a refrigerator.

[0503] A "meal plan" is a weekly meal plan that is suggested based on the user's profile and the ingredients in their fridge.

[0504] A "shopping list" is a list of ingredients and equipment needed to execute a cooking plan, and is a list of items that the user must assemble.

[0505] A "reminding message" is a message that notifies the user of ingredients or equipment that need to be purchased.

[0506] "Recipe information" refers to detailed cooking instructions and ingredient information for the proposed recipe.

[0507] "Real-time monitoring" is the process of checking the user's cooking process in real time and understanding the status.

[0508] "Guides" are audio and video instructions provided to users as they progress through the cooking process.

[0509] "Sharing on social media" refers to the act of posting photos and information about the finished dish on a social networking service.

[0510] The following describes an embodiment of the present invention. The present invention is a system that provides personalized cooking plans based on a user's dietary preferences, allergy information, and lifestyle data, provides real-time assistance during cooking, and ultimately reduces food waste and improves the user's nutritional balance.

[0511] Hardware and software used

[0512] 1. Device: An electronic device such as a smartphone or tablet where users enter information and receive reminders and guidance.

[0513] 2. Server: A computer system that uses cloud services (e.g., AWS, Google Cloud) to manage the data sent by users and perform functions such as generating profiles, creating cooking plans, and real-time monitoring.

[0514] 3. AI Camera: This uses the device's built-in camera and image recognition software (e.g., TensorFlow, OpenCV) to recognize information about ingredients in the refrigerator.

[0515] 4. Database: A SQL or NoSQL database (e.g., MySQL, MongoDB) to store user profile information and ingredient information.

[0516] 5. Generative AI model: A language model (e.g., OpenAI GPT-4) to generate guides and messages based on prompts.

[0517] Example of a system

[0518] For example, the following shows a case where the AI ​​camera recognizes the chicken and vegetables in the user's refrigerator and sends the information to the server.

[0519] User information entry and submission

[0520] Using a smartphone app, users input data such as their dietary preferences, allergy information, and lifestyle habits. For example, they can enter information such as "I have a nut allergy" or "I like high-protein meals." The device then sends this information to a server, which then creates a user profile based on the information entered and stores it in a database.

[0521] Recognizing ingredients in the refrigerator

[0522] The user opens the refrigerator door and takes a picture of the inside with the AI ​​camera on their smartphone. The AI ​​camera recognizes ingredients such as chicken and cabbage and sends information such as "there is chicken and cabbage in the refrigerator" to the server.

[0523] Generate a meal plan

[0524] The server generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator, suggesting recipes such as "teriyaki chicken" and "stir-fried cabbage and chicken."

[0525] Missing item list and reminder messages

[0526] The server generates a list of missing ingredients and utensils needed to execute the cooking plan and sends a shopping list to the user's device as a reminder message, such as "You need to buy soy sauce and sugar."

[0527] Recipe selection and cooking assistance

[0528] The user selects "Teriyaki Chicken" from the suggested recipes and sends the information to the server. When the user starts cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the chicken over" and provides instructions to the user via voice.

[0529] Promoting social media sharing

[0530] After the dish is ready, the server generates a message such as "Share this dish on social media" and sends it to the user's device. The user taps the message to post it on social media.

[0531] Prompt Sentence Examples

[0532] 1. "Please suggest recipes based on the user's dietary preferences and allergy information."

[0533] 2. "Generate recipes using the chicken and vegetables in your fridge and guide you as you progress."

[0534] 3. "After cooking, please generate a message to share on social media."

[0535] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. This invention can help solve many of the problems facing modern society.

[0536] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0537] Step 1:

[0538] Users use a smartphone app to input their preferences, allergy information, and lifestyle data. The input information is personalized data about the user's preferences and allergies. Once the user has completed the input, the device sends it to the server. Specifically, the user enters information such as "I have a nut allergy" or "I like high-protein meals" into the input form and taps the "Submit" button.

[0539] Input: User-entered preferences, allergy information, and lifestyle data

[0540] Output: User data sent to the server

[0541] Step 2:

[0542] The server creates a user profile based on the received data and stores it in a database. This profile generation involves analyzing the user's input data and processing it to classify it into appropriate categories. Specifically, the server generates profile information such as "User A has a nut allergy and prefers a high-protein diet" and stores it in the database.

[0543] Input: User data sent to the server

[0544] Output: User profile stored in database

[0545] Step 3:

[0546] The user opens the refrigerator door and takes a picture of the inside of the refrigerator with the AI ​​camera on their smartphone. The AI ​​camera uses image recognition technology to automatically recognize the ingredients inside the refrigerator. The recognized ingredient information is sent from the device to the server. Specifically, the user takes a picture of chicken or cabbage with the camera, and the AI ​​camera recognizes them as "chicken" and "cabbage."

[0547] Input: Image data of the inside of the refrigerator

[0548] Output: Ingredient information sent to the server

[0549] Step 4:

[0550] The server generates a weekly cooking plan based on the received ingredient information and the user profile created earlier. This involves data calculations to select the optimal menu by comparing the ingredient information with the user's preferences. Specifically, the server suggests recipes such as "Teriyaki Chicken" and "Stir-fried Cabbage and Chicken."

[0551] Input: Ingredient information and user profile sent to the server

[0552] Output: Weekly meal plan

[0553] Step 5:

[0554] The server generates a list of ingredients and utensils needed to execute the cooking plan and sends it to the user's device as a reminder message. Specifically, the server creates a list such as "You need to buy soy sauce and sugar" and sends a message to the user's smartphone.

[0555] Enter: Weekly Meal Plan

[0556] Output: Shopping list sent as reminder messages

[0557] Step 6:

[0558] The user selects the desired dish from the suggested recipes, and the device sends that information to the server. Specifically, the user selects "Teriyaki Chicken" in the app and taps the "Select" button.

[0559] Input: Recipe information selected by the user

[0560] Output: Selected recipe information sent to the server

[0561] Step 7:

[0562] When the user starts cooking, the AI ​​camera monitors the cooking process in real time. The server provides appropriate guidance based on the recognized progress. Specifically, the AI ​​camera monitors the cooking of the chicken, and the server generates a voice prompt such as "Please turn the chicken over" and sends the instruction to the device.

[0563] Input: Real-time video of the cooking process

[0564] Output: Audio prompts provided to the user

[0565] Step 8:

[0566] Once the dish is ready, the server generates a message to share it on social media and sends it to the user's device. Specifically, the server generates a message such as "Share this dish on social media" and sends it to the user's smartphone.

[0567] Input: Notification of cooking completion

[0568] Output: Message encouraging social media sharing

[0569] The above are the specific processing steps of the program of this system.

[0570] (Application example 1)

[0571] 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."

[0572] In modern life, it is difficult to receive recipe suggestions that suit individual dietary preferences, allergies, and lifestyle habits. Furthermore, it is often inconvenient when certain ingredients or cooking equipment are lacking. Furthermore, without real-time monitoring of cooking progress or guidance, mistakes are likely to occur during the cooking process, making it difficult to have an efficient cooking experience. Furthermore, there are few systems that allow users to receive individually customized suggestions when selecting delivery menus. There is a need for an appropriate system to solve these issues.

[0573] 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.

[0574] In this invention, the server includes a means for generating an individually customized delivery menu based on a user profile and ingredient information, a means for providing the delivery menu to the user and receiving an order, and a means for transmitting recipe information selected by the user from the suggested recipes to the server. This allows users to receive customized cooking suggestions that suit their individual preferences, allergies, and lifestyles, and allows them to quickly identify missing ingredients and cooking utensils and receive reminders as a shopping list. Furthermore, the cooking progress is monitored in real time and audio or video guidance is provided as needed, providing an efficient and error-free cooking experience and allowing users to order a menu that meets their individual needs, even when ordering delivery.

[0575] A "user profile" is an individual data set created based on information such as a user's dietary preferences, allergy information, lifestyle habits, and behavioral data.

[0576] "Server" means a computing system that receives, processes, stores, and provides the necessary data to the User.

[0577] "Delivery Menu" means a meal or ingredient delivery option customized based on user profile and ingredient information.

[0578] "Cooking progress" is information that monitors the current stage of cooking in real time.

[0579] "Guide" means audio or video instructions provided to a user as they cook a dish.

[0580] "Ingredient information" is data relating to the types and quantities of ingredients present in the refrigerator.

[0581] A "reminder message" is a notification that prompts the user to purchase the necessary ingredients and cooking equipment.

[0582] A "suggested recipe" is a server-generated suggestion for how to cook a dish based on the user's profile and ingredient information.

[0583] "Ordering" means the act of a user purchasing a dish or ingredient selected from the delivery menu.

[0584] "SNS sharing message" is a notification that encourages the user to post the results of their cooking to a social networking service after they have finished cooking.

[0585] An "AI camera" is a camera that has the ability to recognize objects using artificial intelligence technology.

[0586] This invention is a system that provides individually customized meal suggestions and delivery menus based on a user's dietary preferences, allergy information, lifestyle habits, behavioral data, etc. Specifically, it is implemented in the following steps.

[0587] Program Generation

[0588] The server receives data on dietary preferences, allergies, and lifestyle habits entered from the user's device and creates a user profile based on this data. The created profile is stored in a database, and user behavior data is continuously collected and updated. Using this data, the server generates an individually customized delivery menu. In addition, information on ingredients in the refrigerator is recognized using an AI camera installed on the device and sent to the server.

[0589] Hardware and software used

[0590] 1. Server:

[0591] The server is built using Python and the Flask framework.

[0592] Machine learning libraries such as TensorFlow are used for data processing and AI models are executed.

[0593] 2. Terminal:

[0594] The user's smartphone or tablet.

[0595] An AI camera for recognizing food ingredient information.

[0596] Speakers and displays to provide audio and video guides.

[0597] Processing description

[0598] 1. Create a user profile:

[0599] The server receives the user's submitted data on preferences, allergies, and lifestyle habits and creates a user profile based on it, storing the information in a database for later use.

[0600] 2. Collecting ingredient information:

[0601] The AI ​​camera installed on the device recognizes the ingredients in the refrigerator and sends that information to a server, which uses it to generate recipes and menus.

[0602] 3. Generate delivery menu:

[0603] The server generates an individually customized delivery menu based on the user profile and ingredient information, using a generative AI model to suggest the optimal menu.

[0604] 4. Cooking Progression Guide:

[0605] Based on the recipe information selected by the user, the server monitors the cooking progress in real time and generates appropriate guidance (audio or video).

[0606] 5. Sharing to social media:

[0607] After cooking is complete, the server generates a message encouraging sharing on social media and sends it to the user's device.

[0608] Specific examples

[0609] To give a specific example, let's say a user uses the AI ​​camera on their smartphone to recognize the chicken and vegetables in their refrigerator. The server generates a cooking plan for "Teriyaki Chicken" based on the user profile, and sends a reminder message to purchase any necessary condiments if they are missing. While cooking, the device provides voice guidance such as "Please turn the meat over," and once the dish is finished, the server sends the user a message saying, "Share this dish on social media."

[0610] Prompt Sentence Examples

[0611] Here are some example prompts to input to the generative AI model based on the following information:

[0612] User Preferences: Japanese, Gluten-Free

[0613] Allergy Information: Dairy

[0614] Lifestyle: Health conscious

[0615] Ingredients in the refrigerator: chicken, carrots, cabbage, ginger

[0616] Generate a weekly cooking plan based on the information below.

[0617] This system allows users to receive optimal meal suggestions and delivery menus tailored to their individual preferences, allergies, and lifestyles, as well as receive support during the cooking process, helping to realize an efficient and healthy diet.

[0618] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0619] Step 1:

[0620] Creating and saving a user profile

[0621] Users use devices such as smartphones or tablets to input personal data such as preferences, allergy information, and lifestyle habits. This data is sent and received by a server, which creates a user profile. Specifically, an individual profile is stored in a database based on the user's preferences and allergy information. At this time, the database assigns each user a unique ID and centrally manages data related to that ID.

[0622] Input: User preferences, allergy information, lifestyle data

[0623] Data processing: Converting received data into a format and saving it to a database

[0624] Output: User profile creation and saving to database completed

[0625] Step 2:

[0626] Collecting information about ingredients in the refrigerator

[0627] The user takes a photo of the ingredients in the refrigerator using the AI ​​camera installed on the device. The device analyzes the image and recognizes the ingredient information. The recognized ingredient information is sent to the server and stored in an ingredient database. The AI ​​camera performs image analysis using machine learning models such as TensorFlow.

[0628] Input: Images of ingredients in the refrigerator

[0629] Data processing: Image analysis (machine learning model), food ingredient data extraction

[0630] Output: Recognized ingredients

[0631] Step 3:

[0632] Generate delivery menu

[0633] The server generates a personalized delivery menu based on the user profile and the ingredients in the refrigerator, using a generative AI model (e.g., GPT-3) to suggest menu items that suit the user's preferences and allergies.

[0634] Input: User profile, refrigerator ingredients information

[0635] Data processing: Menu generation using generative AI models

[0636] Output: Delivery menu suggestions

[0637] Step 4:

[0638] Generate shopping lists and send reminder messages

[0639] The server generates a shopping list of missing ingredients and cooking utensils based on the delivery menu and the information on ingredients in the refrigerator, and sends this shopping list to the user's device as a reminder message.

[0640] Input: Delivery menu, information on ingredients in the refrigerator

[0641] Data processing: Identifying necessary ingredients and equipment, and generating a shopping list

[0642] Output: Shopping list as reminder messages

[0643] Step 5:

[0644] Monitor cooking progress and provide guidance

[0645] Once the user selects a suggested recipe and begins cooking, the device monitors the cooking progress in real time. The server provides audio and video guidance to the user based on the progress. Instructions such as "Please turn the meat over" are sent to the device in real time, and the user follows them as they cook.

[0646] Input: User's cooking progress

[0647] Data processing: Real-time progress analysis, guide generation

[0648] Output: Audio and video guides

[0649] Step 6:

[0650] Encourage sharing on social media after cooking is complete

[0651] After the cooking is complete, the server generates a message prompting the user to share the cooking on social media and sends it to the user's device. The user receives this message and posts a photo of the cooking and a comment on the social media.

[0652] Input: Cooking completion information

[0653] Data processing: Generating SNS sharing messages

[0654] Output: SNS sharing message notification to user

[0655] 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.

[0656] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[0657] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[0658] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[0659] Furthermore, by combining it with an emotion engine, the system recognizes the user's emotional state and transmits that data to the server. The server then uses this emotional data to further personalize the user's cooking experience. Specifically, the system can adjust cooking suggestions and change the content and tone of guidance based on the user's progress based on the emotions recognized by the emotion engine.

[0660] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. Furthermore, if the user is feeling stressed, the guidance tone can be softened and instructions can be given in a gentler voice.

[0661] After the dish is complete, the server sends a message to the device, such as "Share this dish on social media," encouraging the user to share the joy of cooking. This system not only allows users to have an efficient and enjoyable cooking experience, but also reduces food waste and improves nutritional balance. This invention is expected to help solve many of the challenges facing modern society.

[0662] The processing flow will be explained below.

[0663] Step 1:

[0664] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[0665] Step 2:

[0666] The terminal transmits the input information to the server.

[0667] Step 3:

[0668] The server creates a user profile based on the received information and stores it in a database.

[0669] Step 4:

[0670] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[0671] Step 5:

[0672] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[0673] Step 6:

[0674] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0675] Step 7:

[0676] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[0677] Step 8:

[0678] The server sends the shopping list as a reminder message to the user's terminal.

[0679] Step 9:

[0680] The user selects the recipe they like from the suggested recipes.

[0681] Step 10:

[0682] The terminal transmits the selected recipe information to the server.

[0683] Step 11:

[0684] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, recognizing their emotional state.

[0685] Step 12:

[0686] The device transmits the recognized emotion data to the server.

[0687] Step 13:

[0688] The server uses the emotional data to personalize the user's cooking experience, adjusting the content and tone of the instructions depending on the cooking progress.

[0689] Step 14:

[0690] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[0691] Step 15:

[0692] The server generates audio and video guides according to the progress and sends them to the device.

[0693] Step 16:

[0694] The device provides users with audio and video guidance, and if the user is feeling stressed, the guidance tone will be softened and instructions will be given in a gentle voice.

[0695] Step 17:

[0696] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[0697] Step 18:

[0698] The finished dish is shared on social media based on a message provided by the user, which is also customized according to the user's emotional state.

[0699] This process allows users to have an efficient and enjoyable cooking experience, while receiving personalized support tailored to their individual emotional state.

[0700] Example 2

[0701] 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."

[0702] Currently, there are no systems that automatically generate personalized cooking plans based on dietary preferences, allergies, and lifestyle habits. There is also a lack of systems that can recognize ingredients in the refrigerator, list the necessary ingredients and cooking utensils, or provide guidance based on the cooking progress. Furthermore, technology that personalizes the cooking experience based on the user's emotional state is underdeveloped. Therefore, there is a need for systems that provide an efficient and enjoyable cooking experience, reduce food waste, and improve nutritional balance.

[0703] 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.

[0704] In this invention, the server includes: means for inputting data on a user's dietary preferences, allergy information, and lifestyle habits; means for transmitting the input information to the server; means for creating a user profile based on the received information and saving it to a database; means for collecting user behavior data and updating the profile; means for recognizing information about ingredients in the refrigerator and transmitting it to the server; means for generating a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator; means for generating a shopping list for missing ingredients and cooking utensils; means for transmitting the shopping list as a reminder message to the user's device; means for transmitting information about a recipe selected by the user from suggested recipes to the server; means for monitoring the cooking progress in real time and transmitting appropriate information to the server; means for generating and providing guidance based on the cooking progress; means for generating and providing a message encouraging sharing on social media after cooking is completed and transmitting it to the user's device; means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server; and means for adjusting the content and tone of the guidance provided based on the emotion data. This enables automatic generation of individual cooking plans, providing an efficient and enjoyable cooking experience, reducing food waste, and improving nutritional balance.

[0705] A "user" is a person who uses the system and provides data on dietary preferences, allergy information, and lifestyle habits.

[0706] A "server" is a computer system that receives, processes, stores, and performs various calculations on data.

[0707] "Terminal" means a device used by a user to enter data or receive notifications from the system, including a smartphone or tablet.

[0708] A "profile" is a data set that centralizes a user's unique information, including the user's dietary preferences, allergy information, lifestyle habits, and other behavioral data.

[0709] "Database" means the digital storage system in which the Server stores user profiles and other related information.

[0710] An "AI camera" is a camera that uses artificial intelligence to recognize ingredients in the refrigerator.

[0711] A "reminder message" is a notification message that prompts the user to take necessary action.

[0712] A "cooking plan" is a set of suggested cooking recipes and preparation plans based on a user profile and the ingredients in the refrigerator.

[0713] The "emotion engine" is a technology that analyzes a user's facial expressions and voice data to recognize their emotional state.

[0714] A "guide" is information containing instructions and advice that are generated as the cooking progresses and is provided in audio or video format.

[0715] The system collects data on a user's dietary preferences, allergies, and lifestyle habits, and provides personalized cooking plans based on that data. It also recognizes the ingredients in the refrigerator, provides a list of ingredients and cooking utensils needed, provides real-time cooking guidance, and personalizes the plan according to the user's emotional state.

[0716] Hardware and software used

[0717] Device: A smartphone or tablet where users enter information and receive instructions and guidance.

[0718] Server: A computer system that receives, processes, stores, and analyzes data.

[0719] AI camera: A camera used to recognize ingredients in the refrigerator.

[0720] Emotion engine: Technology for recognizing a user's emotional state by analyzing their facial expressions and voice data.

[0721] Specific details of data processing and calculation

[0722] 1. Data entry and submission

[0723] Device: Users enter their dietary preferences, allergy information, and lifestyle data through an app on their smartphone or tablet.

[0724] Server: Receives data sent from the device, creates a user profile, and stores it in a database.

[0725] 2. Recognition and transmission of food ingredient information

[0726] Terminal: An AI camera installed inside the refrigerator recognizes ingredients and sends that information to the server.

[0727] Server: Matches the received ingredient information with the user profile and generates an appropriate cooking plan.

[0728] 3. Generating a Cooking Plan

[0729] Server: Automatically generates a personalized weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0730] Server: Identifies missing ingredients and cooking equipment, creates a shopping list, and sends it to the user's device as a reminder message.

[0731] 4. Real-time cooking guide

[0732] User: Selects a suggested cooking recipe and sends the information to the server via the device.

[0733] Server: Monitors the cooking progress in real time and generates appropriate audio and video guides to send to the device.

[0734] 5. Recognizing and guiding emotional states

[0735] Emotion engine: Analyzes the user's facial expressions and voice data to recognize their emotional state.

[0736] Server: Based on emotional data, the content and tone of the guide can be adjusted to further personalize the user's cooking experience.

[0737] Specific operation example

[0738] The user enters their preferred ingredients (e.g., chicken, tomato), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) on their smartphone and presses the send button. This data is sent to the server, which creates a user profile and uses an AI camera to identify ingredients in the refrigerator (e.g., 200g of chicken, 1 cabbage). Based on this information, the server generates a cooking plan such as "Teriyaki Chicken" and sends the user a shopping list of missing seasonings and ingredients as a reminder message. When the user selects a recipe and begins cooking, the server provides audio guidance such as "Please turn the meat over," adjusting the guidance tone according to the user's stress level as recognized by the emotion engine. When the dish is complete, a notification is displayed urging the user to "Share this dish on social media."

[0739] Examples of prompt statements

[0740] "Generate the perfect weekly cooking plan based on your preferences and allergies."

[0741] "Recognize the ingredients in your refrigerator and suggest cooking recipes based on them."

[0742] "Consider the user's emotional state and adjust the content and tone of your cooking progression guide."

[0743] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0744] Step 1:

[0745] Data Entry and Submission

[0746] Users use the device to input their food preferences (e.g., favorite foods), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) through an app on their smartphone or tablet. This input data is stored on the device and prepared for transmission.

[0747] Input: User preferences, allergy information, and lifestyle data.

[0748] Data processing: Validation and formatting of input data.

[0749] Output: Data ready to be sent to the server.

[0750] Step 2:

[0751] Data transmission and storage

[0752] The server receives the data sent from the device. Based on this, the server generates a user profile and stores it in a database. For example, the server creates a new profile and stores each attribute (preferences, allergies, lifestyle habits) in the database.

[0753] Input: User data sent from the device.

[0754] Data processing: A profile is generated based on user data and stored in a database.

[0755] Output: The updated user profile in the database.

[0756] Step 3:

[0757] Recognizing and transmitting information about ingredients in the refrigerator

[0758] An AI camera connected to the device recognizes the ingredients in the refrigerator and sends that information to a server. For example, the AI ​​camera recognizes that the refrigerator contains 200g of chicken and one cabbage.

[0759] Input: Video of food in the refrigerator.

[0760] Data processing: Extraction of food ingredient information through video analysis.

[0761] Output: Ingredient information sent to the server.

[0762] Step 4:

[0763] Generate a recipe plan and list missing ingredients

[0764] The server generates a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator. It lists ingredients, seasonings, and cooking utensils that are in short supply and generates a shopping list. For example, it suggests "teriyaki chicken" and prompts the user to purchase necessary seasonings (e.g., soy sauce and sugar).

[0765] Input: User profile, refrigerator food information.

[0766] Data processing: Generate an appropriate cooking plan based on user profile and ingredient information. List ingredients that are in short supply.

[0767] Output: Meal plan and shopping list.

[0768] Step 5:

[0769] Sending shopping list reminder messages

[0770] The server then sends the generated shopping list to the device as a reminder message. For example, the user's smartphone might receive a notification saying, "Please buy soy sauce and sugar."

[0771] Enter: Shopping List.

[0772] Data processing: Convert shopping lists into reminder messages.

[0773] Output: The reminder message sent to the user's device.

[0774] Step 6:

[0775] Select and submit a recipe

[0776] The user selects their favorite recipe from the multiple recipe suggestions and sends the information to the server via their device. For example, they select "Teriyaki Chicken."

[0777] Input: A suggested recipe.

[0778] Data processing: The selected recipe information is sent to the server.

[0779] Output: The selected recipe information sent to the server.

[0780] Step 7:

[0781] Monitor cooking progress and provide guidance

[0782] The server monitors the cooking progress in real time and generates appropriate guidance (e.g., "Please turn the meat over") and sends it to the device.

[0783] Input: Select recipe information and real-time progress data.

[0784] Data processing: Proceeding and generating guides.

[0785] Output: The guide sent to your device.

[0786] Step 8:

[0787] Recognizing and guiding emotional states

[0788] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotional state. The server then adjusts the content and tone of the guide based on this data. For example, if the user is feeling stressed, the tone of the guide will be changed to a gentler tone.

[0789] Input: User's facial expressions and voice data.

[0790] Data processing: Data analysis for emotional state recognition and guided adjustment.

[0791] Output: Adjusted guide.

[0792] Step 9:

[0793] Encourage sharing on social media after cooking is complete

[0794] When the dish is complete, the server sends a message to the device saying, "Share this dish on social media," encouraging the user to share the results of their cooking with others.

[0795] Input: Notification that the food is ready.

[0796] Data processing: Generating messages encouraging sharing on social media.

[0797] Output: The sharing prompt sent to the device.

[0798] (Application example 2)

[0799] 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."

[0800] Conventional cooking assistance systems lack personalized recipe suggestions based on users' dietary preferences and allergy information, and have problems such as shortages of certain ingredients and tedious recipe planning. Furthermore, the content and tone of the cooking assistance could not be adjusted according to the user's emotional state, which often caused stress during the cooking process. Furthermore, purchasing missing ingredients was a manual process, preventing the establishment of an efficient supply chain.

[0801] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server, means for adjusting the content and tone of the guidance based on the emotion, means for ordering missing ingredients and cooking utensils, and means for generating prompt sentences with instruction content according to the emotion using a generative AI model. This enables personalized recipe suggestions for the user, enabling flexible cooking support according to emotions and efficient ingredient procurement.

[0802] "User dietary preferences" refer to the types of foods or cuisines that a particular user prefers to eat.

[0803] "Allergy information" refers to information that indicates a user's allergic reaction to a particular food or ingredient.

[0804] "Lifestyle habits" refers to the activities and behavioral patterns that a user engages in on a daily basis.

[0805] "Server" means a centralized computer system that receives and processes information from users and provides necessary data.

[0806] A "user profile" is an individual data set created based on information such as a user's food preferences, allergy information, and lifestyle habits.

[0807] A "database" is a system for systematically storing and managing information such as user profiles.

[0808] "Behavioral data" refers to data about a user's daily behavior, including information such as meal times and frequency, and the dishes they choose.

[0809] "Information about ingredients in the refrigerator" is information about the food and ingredients currently stored in the user's refrigerator.

[0810] A "cooking plan" is a cooking schedule for a specific period (for example, a week) that is created based on the user's profile and the ingredients in the refrigerator.

[0811] A "shopping list" is a list that is generated when specific ingredients or cooking equipment are in short supply based on a cooking plan.

[0812] A "remind message" is a message that notifies the user of important information or suggestions.

[0813] "Recipe information" refers to information about how to make the dish selected by the user and the ingredients needed.

[0814] "Cooking progress" refers to the current state of the user's cooking process.

[0815] "Guide" means instructions or advice provided to the user as they proceed with their cooking.

[0816] "Sharing on social media" refers to posting photos and information about the dishes created by users on social networking services.

[0817] The "emotion engine" is a system for recognizing a user's emotional state from their facial expressions and behavior.

[0818] A "generative AI model" is a machine learning algorithm that generates personalized content or instructions based on data.

[0819] A "prompt" is a document that provides specific instructions or guidelines generated by a generative AI model.

[0820] This invention is a system that provides personalized meal plans based on a user's dietary preferences, allergy information, lifestyle habits, and emotional state, and efficiently procures ingredients in cooperation with food delivery services. The system includes a user terminal, a server, an AI camera in the refrigerator, and an emotion engine.

[0821] First, the user enters data on their dietary preferences, allergies, and lifestyle habits through their device. This data is then sent to the server, which then creates a user profile based on that data and stores it in a database. The device also continuously collects user behavior data, which the server uses to update the profile.

[0822] Next, the refrigerator's AI camera recognizes the ingredients in the refrigerator and sends the information to a server. The server generates a weekly cooking plan based on this information and the user's profile. The cooking plan identifies any shortages of necessary ingredients or cooking equipment and generates a shopping list. This list is then sent to the user's device as a reminder message.

[0823] Once cooking begins, the user device sends the selected recipe information to the server, which monitors the cooking progress in real time. The server generates appropriate guidance based on the cooking progress and provides it to the user via audio and video. In addition, the emotion engine recognizes the user's emotional state and sends that data to the server to adjust the content and tone of the guidance. For example, if the user is feeling stressed, the server will provide instructions in a calmer tone.

[0824] After cooking is complete, the server sends a message to the user's device encouraging them to share the cooking experience on social media. This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[0825] The server generates a prompt like this:

[0826] Suggest recipes using the chicken and broccoli the user has in their fridge. If the user becomes stressed during the cooking process, calm the guide's tone and provide specific audio instructions.

[0827] This invention uses the Python Requests library to communicate with the server, and utilizes the server API to update profiles, update refrigerator contents, generate cooking plans, acquire emotions, and generate guides. This enables personalized recipe suggestions for users, enabling flexible cooking support based on emotions and efficient ingredient procurement.

[0828] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0829] Step 1:

[0830] Users input data such as dietary preferences, allergy information, and lifestyle habits into their device. The device then structures the data and sends it to the server, which then creates a user profile based on the data and stores it in a database.

[0831] Step 2:

[0832] The AI ​​camera recognizes the information about ingredients in the refrigerator and sends it to the server. The server adds the received information to the user's profile and updates the database. It also analyzes the information to generate a list of available ingredients.

[0833] Step 3:

[0834] Based on the user's profile and the ingredients in the refrigerator, the server generates a weekly cooking plan, a set of recipes optimized for the user's dietary preferences, allergies, and lifestyle habits, including a list of the ingredients and cooking equipment needed.

[0835] Step 4:

[0836] The server then identifies any missing ingredients and cooking utensils based on the cooking plan and generates a shopping list. The shopping list is then sent to the user's terminal as a reminder message. The user terminal receives the reminder message and notifies the user.

[0837] Step 5:

[0838] The user selects a dish from the suggested recipes and transmits the selected recipe information to the server via the user terminal, which adds data related to the selected recipe to the user profile and updates the database.

[0839] Step 6:

[0840] While cooking, the user device monitors the user's actions (e.g., preparation of ingredients and cooking progress) in real time. As the user progresses through each step of the recipe, the progress information is sent to the server. The server analyzes the progress and generates a guide for the next step.

[0841] Step 7:

[0842] The emotion engine recognizes the user's emotional state and sends that data to the server. The server then adjusts the content and tone of the guide based on the emotional data. For example, if the user is feeling stressed, the tone of the guide will be set to a gentler tone.

[0843] Step 8:

[0844] The server uses a generative AI model to generate prompts based on the cooking progress and emotional state of the user. These prompts are sent to the user's device as audio or video and provided to the user at the appropriate time.

[0845] Step 9:

[0846] After the cooking is finished, the server generates a message to encourage sharing on SNS and sends it to the user's device. The user's device receives this message and notifies the user, encouraging them to post photos and information about the cooking on SNS.

[0847] This provides an efficient and personalized cooking experience, allowing users to enjoy cooking without stress, and also enables efficient purchasing of ingredients that may be in short supply.

[0848] 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.

[0849] 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.

[0850] 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.

[0851] [Third embodiment]

[0852] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0853] 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.

[0854] 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).

[0855] 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.

[0856] 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.

[0857] 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).

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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."

[0864] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[0865] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[0866] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[0867] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the cooking process of the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. After the dish is complete, the server sends a message to the device such as "Share this dish on social media" to encourage the user to share it.

[0868] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. It is expected that this invention will help solve many of the problems facing modern society.

[0869] The processing flow will be explained below.

[0870] Step 1:

[0871] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[0872] Step 2:

[0873] The terminal transmits the input information to the server.

[0874] Step 3:

[0875] The server creates a user profile based on the received information and stores it in a database.

[0876] Step 4:

[0877] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[0878] Step 5:

[0879] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[0880] Step 6:

[0881] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[0882] Step 7:

[0883] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[0884] Step 8:

[0885] The server sends the shopping list as a reminder message to the user's terminal.

[0886] Step 9:

[0887] The user selects the recipe they like from the suggested recipes.

[0888] Step 10:

[0889] The terminal transmits the selected recipe information to the server.

[0890] Step 11:

[0891] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[0892] Step 12:

[0893] The server generates audio and video guides according to the progress and sends them to the device.

[0894] Step 13:

[0895] The device provides audio and video guidance to the user.

[0896] Step 14:

[0897] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[0898] Step 15:

[0899] The completed dish is shared on social media based on the message provided by the user.

[0900] This process allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[0901] Example 1

[0902] 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."

[0903] Conventional meal management systems struggle to provide personalized meal plans that comprehensively reflect a user's dietary preferences, allergies, and lifestyle habits. Furthermore, they lack systems that effectively utilize information about ingredients in the refrigerator, monitor the cooking progress in real time, and provide appropriate guidance. Furthermore, they lack functionality for continuously collecting and updating user behavior data and encouraging users to share their cooking on social media after cooking is complete.

[0904] 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.

[0905] In this invention, the server includes a means for monitoring the user's process of handling ingredients and cooking in real time and providing audio or video guidance as needed, a means for using an AI camera to recognize ingredient information in the refrigerator, and a means for automatically updating the shopping list based on information from the user's device, thereby enabling the creation of cooking plans based on the user's individual information, real-time cooking support, and efficient ingredient management.

[0906] "User" refers to a person who uses the system to provide personal information such as dietary preferences, allergy information, and lifestyle habits.

[0907] A "device" is an electronic device, such as a smartphone or tablet, that a user uses to enter information and receive reminders and guidance.

[0908] A "server" is a computer system that manages data sent by users and performs profile generation, cooking plan creation, real-time monitoring, etc.

[0909] A "user profile" is a data set constructed based on a user's dietary preferences, allergy information, lifestyle habits, etc.

[0910] A "database" is a data management system for storing user profile information, ingredient information, and the like.

[0911] "Information about ingredients in the refrigerator" is data about the types and quantities of ingredients stored in the refrigerator.

[0912] An "AI camera" is a camera system that uses image recognition technology to recognize information about ingredients in a refrigerator.

[0913] A "meal plan" is a weekly meal plan that is suggested based on the user's profile and the ingredients in their fridge.

[0914] A "shopping list" is a list of ingredients and equipment needed to execute a cooking plan, and is a list of items that the user must assemble.

[0915] A "reminding message" is a message that notifies the user of ingredients or equipment that need to be purchased.

[0916] "Recipe information" refers to detailed cooking instructions and ingredient information for the proposed recipe.

[0917] "Real-time monitoring" is the process of checking the user's cooking process in real time and understanding the status.

[0918] "Guides" are audio and video instructions provided to users as they progress through the cooking process.

[0919] "Sharing on social media" refers to the act of posting photos and information about the finished dish on a social networking service.

[0920] The following describes an embodiment of the present invention. The present invention is a system that provides personalized cooking plans based on a user's dietary preferences, allergy information, and lifestyle data, provides real-time assistance during cooking, and ultimately reduces food waste and improves the user's nutritional balance.

[0921] Hardware and software used

[0922] 1. Device: An electronic device such as a smartphone or tablet where users enter information and receive reminders and guidance.

[0923] 2. Server: A computer system that uses cloud services (e.g., AWS, Google Cloud) to manage the data sent by users and perform functions such as generating profiles, creating cooking plans, and real-time monitoring.

[0924] 3. AI Camera: This uses the device's built-in camera and image recognition software (e.g., TensorFlow, OpenCV) to recognize information about ingredients in the refrigerator.

[0925] 4. Database: A SQL or NoSQL database (e.g., MySQL, MongoDB) to store user profile information and ingredient information.

[0926] 5. Generative AI model: A language model (e.g., OpenAI GPT-4) to generate guides and messages based on prompts.

[0927] Example of a system

[0928] For example, the following shows a case where the AI ​​camera recognizes the chicken and vegetables in the user's refrigerator and sends the information to the server.

[0929] User information entry and submission

[0930] Using a smartphone app, users input data such as their dietary preferences, allergy information, and lifestyle habits. For example, they can enter information such as "I have a nut allergy" or "I like high-protein meals." The device then sends this information to a server, which then creates a user profile based on the information entered and stores it in a database.

[0931] Recognizing ingredients in the refrigerator

[0932] The user opens the refrigerator door and takes a picture of the inside with the AI ​​camera on their smartphone. The AI ​​camera recognizes ingredients such as chicken and cabbage and sends information such as "there is chicken and cabbage in the refrigerator" to the server.

[0933] Generate a meal plan

[0934] The server generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator, suggesting recipes such as "teriyaki chicken" and "stir-fried cabbage and chicken."

[0935] Missing item list and reminder messages

[0936] The server generates a list of missing ingredients and utensils needed to execute the cooking plan and sends a shopping list to the user's device as a reminder message, such as "You need to buy soy sauce and sugar."

[0937] Recipe selection and cooking assistance

[0938] The user selects "Teriyaki Chicken" from the suggested recipes and sends the information to the server. When the user starts cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the chicken over" and provides instructions to the user via voice.

[0939] Promoting social media sharing

[0940] After the dish is ready, the server generates a message such as "Share this dish on social media" and sends it to the user's device. The user taps the message to post it on social media.

[0941] Prompt Sentence Examples

[0942] 1. "Please suggest recipes based on the user's dietary preferences and allergy information."

[0943] 2. "Generate recipes using the chicken and vegetables in your fridge and guide you as you progress."

[0944] 3. "After cooking, please generate a message to share on social media."

[0945] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. This invention can help solve many of the problems facing modern society.

[0946] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0947] Step 1:

[0948] Users use a smartphone app to input their preferences, allergy information, and lifestyle data. The input information is personalized data about the user's preferences and allergies. Once the user has completed the input, the device sends it to the server. Specifically, the user enters information such as "I have a nut allergy" or "I like high-protein meals" into the input form and taps the "Submit" button.

[0949] Input: User-entered preferences, allergy information, and lifestyle data

[0950] Output: User data sent to the server

[0951] Step 2:

[0952] The server creates a user profile based on the received data and stores it in a database. This profile generation involves analyzing the user's input data and processing it to classify it into appropriate categories. Specifically, the server generates profile information such as "User A has a nut allergy and prefers a high-protein diet" and stores it in the database.

[0953] Input: User data sent to the server

[0954] Output: User profile stored in database

[0955] Step 3:

[0956] The user opens the refrigerator door and takes a picture of the inside of the refrigerator with the AI ​​camera on their smartphone. The AI ​​camera uses image recognition technology to automatically recognize the ingredients inside the refrigerator. The recognized ingredient information is sent from the device to the server. Specifically, the user takes a picture of chicken or cabbage with the camera, and the AI ​​camera recognizes them as "chicken" and "cabbage."

[0957] Input: Image data of the inside of the refrigerator

[0958] Output: Ingredient information sent to the server

[0959] Step 4:

[0960] The server generates a weekly cooking plan based on the received ingredient information and the user profile created earlier. This involves data calculations to select the optimal menu by comparing the ingredient information with the user's preferences. Specifically, the server suggests recipes such as "Teriyaki Chicken" and "Stir-fried Cabbage and Chicken."

[0961] Input: Ingredient information and user profile sent to the server

[0962] Output: Weekly meal plan

[0963] Step 5:

[0964] The server generates a list of ingredients and utensils needed to execute the cooking plan and sends it to the user's device as a reminder message. Specifically, the server creates a list such as "You need to buy soy sauce and sugar" and sends a message to the user's smartphone.

[0965] Enter: Weekly Meal Plan

[0966] Output: Shopping list sent as reminder messages

[0967] Step 6:

[0968] The user selects the desired dish from the suggested recipes, and the device sends that information to the server. Specifically, the user selects "Teriyaki Chicken" in the app and taps the "Select" button.

[0969] Input: Recipe information selected by the user

[0970] Output: Selected recipe information sent to the server

[0971] Step 7:

[0972] When the user starts cooking, the AI ​​camera monitors the cooking process in real time. The server provides appropriate guidance based on the recognized progress. Specifically, the AI ​​camera monitors the cooking of the chicken, and the server generates a voice prompt such as "Please turn the chicken over" and sends the instruction to the device.

[0973] Input: Real-time video of the cooking process

[0974] Output: Audio prompts provided to the user

[0975] Step 8:

[0976] Once the dish is ready, the server generates a message to share it on social media and sends it to the user's device. Specifically, the server generates a message such as "Share this dish on social media" and sends it to the user's smartphone.

[0977] Input: Notification of cooking completion

[0978] Output: Message encouraging social media sharing

[0979] The above are the specific processing steps of the program of this system.

[0980] (Application example 1)

[0981] 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."

[0982] In modern life, it is difficult to receive recipe suggestions that suit individual dietary preferences, allergies, and lifestyle habits. Furthermore, it is often inconvenient when certain ingredients or cooking equipment are lacking. Furthermore, without real-time monitoring of cooking progress or guidance, mistakes are likely to occur during the cooking process, making it difficult to have an efficient cooking experience. Furthermore, there are few systems that allow users to receive individually customized suggestions when selecting delivery menus. There is a need for an appropriate system to solve these issues.

[0983] 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.

[0984] In this invention, the server includes a means for generating an individually customized delivery menu based on a user profile and ingredient information, a means for providing the delivery menu to the user and receiving an order, and a means for transmitting recipe information selected by the user from the suggested recipes to the server. This allows users to receive customized cooking suggestions that suit their individual preferences, allergies, and lifestyles, and allows them to quickly identify missing ingredients and cooking utensils and receive reminders as a shopping list. Furthermore, the cooking progress is monitored in real time and audio or video guidance is provided as needed, providing an efficient and error-free cooking experience and allowing users to order a menu that meets their individual needs, even when ordering delivery.

[0985] A "user profile" is an individual data set created based on information such as a user's dietary preferences, allergy information, lifestyle habits, and behavioral data.

[0986] "Server" means a computing system that receives, processes, stores, and provides the necessary data to the User.

[0987] "Delivery Menu" means a meal or ingredient delivery option customized based on user profile and ingredient information.

[0988] "Cooking progress" is information that monitors the current stage of cooking in real time.

[0989] "Guide" means audio or video instructions provided to a user as they cook a dish.

[0990] "Ingredient information" is data relating to the types and quantities of ingredients present in the refrigerator.

[0991] A "reminder message" is a notification that prompts the user to purchase the necessary ingredients and cooking equipment.

[0992] A "suggested recipe" is a server-generated suggestion for how to cook a dish based on the user's profile and ingredient information.

[0993] "Ordering" means the act of a user purchasing a dish or ingredient selected from the delivery menu.

[0994] "SNS sharing message" is a notification that encourages the user to post the results of their cooking to a social networking service after they have finished cooking.

[0995] An "AI camera" is a camera that has the ability to recognize objects using artificial intelligence technology.

[0996] This invention is a system that provides individually customized meal suggestions and delivery menus based on a user's dietary preferences, allergy information, lifestyle habits, behavioral data, etc. Specifically, it is implemented in the following steps.

[0997] Program Generation

[0998] The server receives data on dietary preferences, allergies, and lifestyle habits entered from the user's device and creates a user profile based on this data. The created profile is stored in a database, and user behavior data is continuously collected and updated. Using this data, the server generates an individually customized delivery menu. In addition, information on ingredients in the refrigerator is recognized using an AI camera installed on the device and sent to the server.

[0999] Hardware and software used

[1000] 1. Server:

[1001] The server is built using Python and the Flask framework.

[1002] Machine learning libraries such as TensorFlow are used for data processing and AI models are executed.

[1003] 2. Terminal:

[1004] The user's smartphone or tablet.

[1005] An AI camera for recognizing food ingredient information.

[1006] Speakers and displays to provide audio and video guides.

[1007] Processing description

[1008] 1. Create a user profile:

[1009] The server receives the user's submitted data on preferences, allergies, and lifestyle habits and creates a user profile based on it, storing the information in a database for later use.

[1010] 2. Collecting ingredient information:

[1011] The AI ​​camera installed on the device recognizes the ingredients in the refrigerator and sends that information to a server, which uses it to generate recipes and menus.

[1012] 3. Generate delivery menu:

[1013] The server generates an individually customized delivery menu based on the user profile and ingredient information, using a generative AI model to suggest the optimal menu.

[1014] 4. Cooking Progression Guide:

[1015] Based on the recipe information selected by the user, the server monitors the cooking progress in real time and generates appropriate guidance (audio or video).

[1016] 5. Sharing to social media:

[1017] After cooking is complete, the server generates a message encouraging sharing on social media and sends it to the user's device.

[1018] Specific examples

[1019] To give a specific example, let's say a user uses the AI ​​camera on their smartphone to recognize the chicken and vegetables in their refrigerator. The server generates a cooking plan for "Teriyaki Chicken" based on the user profile, and sends a reminder message to purchase any necessary condiments if they are missing. While cooking, the device provides voice guidance such as "Please turn the meat over," and once the dish is finished, the server sends the user a message saying, "Share this dish on social media."

[1020] Prompt Sentence Examples

[1021] Here are some example prompts to input to the generative AI model based on the following information:

[1022] User Preferences: Japanese, Gluten-Free

[1023] Allergy Information: Dairy

[1024] Lifestyle: Health conscious

[1025] Ingredients in the refrigerator: chicken, carrots, cabbage, ginger

[1026] Generate a weekly cooking plan based on the information below.

[1027] This system allows users to receive optimal meal suggestions and delivery menus tailored to their individual preferences, allergies, and lifestyles, as well as receive support during the cooking process, helping to realize an efficient and healthy diet.

[1028] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1029] Step 1:

[1030] Creating and saving a user profile

[1031] Users use devices such as smartphones or tablets to input personal data such as preferences, allergy information, and lifestyle habits. This data is sent and received by a server, which creates a user profile. Specifically, an individual profile is stored in a database based on the user's preferences and allergy information. At this time, the database assigns each user a unique ID and centrally manages data related to that ID.

[1032] Input: User preferences, allergy information, lifestyle data

[1033] Data processing: Converting received data into a format and saving it to a database

[1034] Output: User profile creation and saving to database completed

[1035] Step 2:

[1036] Collecting information about ingredients in the refrigerator

[1037] The user takes a photo of the ingredients in the refrigerator using the AI ​​camera installed on the device. The device analyzes the image and recognizes the ingredient information. The recognized ingredient information is sent to the server and stored in an ingredient database. The AI ​​camera performs image analysis using machine learning models such as TensorFlow.

[1038] Input: Images of ingredients in the refrigerator

[1039] Data processing: Image analysis (machine learning model), food ingredient data extraction

[1040] Output: Recognized ingredients

[1041] Step 3:

[1042] Generate delivery menu

[1043] The server generates a personalized delivery menu based on the user profile and the ingredients in the refrigerator, using a generative AI model (e.g., GPT-3) to suggest menu items that suit the user's preferences and allergies.

[1044] Input: User profile, refrigerator ingredients information

[1045] Data processing: Menu generation using generative AI models

[1046] Output: Delivery menu suggestions

[1047] Step 4:

[1048] Generate shopping lists and send reminder messages

[1049] The server generates a shopping list of missing ingredients and cooking utensils based on the delivery menu and the information on ingredients in the refrigerator, and sends this shopping list to the user's device as a reminder message.

[1050] Input: Delivery menu, information on ingredients in the refrigerator

[1051] Data processing: Identifying necessary ingredients and equipment, and generating a shopping list

[1052] Output: Shopping list as reminder messages

[1053] Step 5:

[1054] Monitor cooking progress and provide guidance

[1055] Once the user selects a suggested recipe and begins cooking, the device monitors the cooking progress in real time. The server provides audio and video guidance to the user based on the progress. Instructions such as "Please turn the meat over" are sent to the device in real time, and the user follows them as they cook.

[1056] Input: User's cooking progress

[1057] Data processing: Real-time progress analysis, guide generation

[1058] Output: Audio and video guides

[1059] Step 6:

[1060] Encourage sharing on social media after cooking is complete

[1061] After the cooking is complete, the server generates a message prompting the user to share the cooking on social media and sends it to the user's device. The user receives this message and posts a photo of the cooking and a comment on the social media.

[1062] Input: Cooking completion information

[1063] Data processing: Generating SNS sharing messages

[1064] Output: SNS sharing message notification to user

[1065] 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.

[1066] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[1067] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[1068] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[1069] Furthermore, by combining it with an emotion engine, the system recognizes the user's emotional state and transmits that data to the server. The server then uses this emotional data to further personalize the user's cooking experience. Specifically, the system can adjust cooking suggestions and change the content and tone of guidance based on the user's progress based on the emotions recognized by the emotion engine.

[1070] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. Furthermore, if the user is feeling stressed, the guidance tone can be softened and instructions can be given in a gentler voice.

[1071] After the dish is complete, the server sends a message to the device, such as "Share this dish on social media," encouraging the user to share the joy of cooking. This system not only allows users to have an efficient and enjoyable cooking experience, but also reduces food waste and improves nutritional balance. This invention is expected to help solve many of the challenges facing modern society.

[1072] The processing flow will be explained below.

[1073] Step 1:

[1074] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[1075] Step 2:

[1076] The terminal transmits the input information to the server.

[1077] Step 3:

[1078] The server creates a user profile based on the received information and stores it in a database.

[1079] Step 4:

[1080] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[1081] Step 5:

[1082] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[1083] Step 6:

[1084] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[1085] Step 7:

[1086] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[1087] Step 8:

[1088] The server sends the shopping list as a reminder message to the user's terminal.

[1089] Step 9:

[1090] The user selects the recipe they like from the suggested recipes.

[1091] Step 10:

[1092] The terminal transmits the selected recipe information to the server.

[1093] Step 11:

[1094] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, recognizing their emotional state.

[1095] Step 12:

[1096] The device transmits the recognized emotion data to the server.

[1097] Step 13:

[1098] The server uses the emotional data to personalize the user's cooking experience, adjusting the content and tone of the instructions depending on the cooking progress.

[1099] Step 14:

[1100] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[1101] Step 15:

[1102] The server generates audio and video guides according to the progress and sends them to the device.

[1103] Step 16:

[1104] The device provides users with audio and video guidance, and if the user is feeling stressed, the guidance tone will be softened and instructions will be given in a gentle voice.

[1105] Step 17:

[1106] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[1107] Step 18:

[1108] The finished dish is shared on social media based on a message provided by the user, which is also customized according to the user's emotional state.

[1109] This process allows users to have an efficient and enjoyable cooking experience, while receiving personalized support tailored to their individual emotional state.

[1110] Example 2

[1111] 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."

[1112] Currently, there are no systems that automatically generate personalized cooking plans based on dietary preferences, allergies, and lifestyle habits. There is also a lack of systems that can recognize ingredients in the refrigerator, list the necessary ingredients and cooking utensils, or provide guidance based on the cooking progress. Furthermore, technology that personalizes the cooking experience based on the user's emotional state is underdeveloped. Therefore, there is a need for systems that provide an efficient and enjoyable cooking experience, reduce food waste, and improve nutritional balance.

[1113] 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.

[1114] In this invention, the server includes: means for inputting data on a user's dietary preferences, allergy information, and lifestyle habits; means for transmitting the input information to the server; means for creating a user profile based on the received information and saving it to a database; means for collecting user behavior data and updating the profile; means for recognizing information about ingredients in the refrigerator and transmitting it to the server; means for generating a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator; means for generating a shopping list for missing ingredients and cooking utensils; means for transmitting the shopping list as a reminder message to the user's device; means for transmitting information about a recipe selected by the user from suggested recipes to the server; means for monitoring the cooking progress in real time and transmitting appropriate information to the server; means for generating and providing guidance based on the cooking progress; means for generating and providing a message encouraging sharing on social media after cooking is completed and transmitting it to the user's device; means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server; and means for adjusting the content and tone of the guidance provided based on the emotion data. This enables automatic generation of individual cooking plans, providing an efficient and enjoyable cooking experience, reducing food waste, and improving nutritional balance.

[1115] A "user" is a person who uses the system and provides data on dietary preferences, allergy information, and lifestyle habits.

[1116] A "server" is a computer system that receives, processes, stores, and performs various calculations on data.

[1117] "Terminal" means a device used by a user to enter data or receive notifications from the system, including a smartphone or tablet.

[1118] A "profile" is a data set that centralizes a user's unique information, including the user's dietary preferences, allergy information, lifestyle habits, and other behavioral data.

[1119] "Database" means the digital storage system in which the Server stores user profiles and other related information.

[1120] An "AI camera" is a camera that uses artificial intelligence to recognize ingredients in the refrigerator.

[1121] A "reminder message" is a notification message that prompts the user to take necessary action.

[1122] A "cooking plan" is a set of suggested cooking recipes and preparation plans based on a user profile and the ingredients in the refrigerator.

[1123] The "emotion engine" is a technology that analyzes a user's facial expressions and voice data to recognize their emotional state.

[1124] A "guide" is information containing instructions and advice that are generated as the cooking progresses and is provided in audio or video format.

[1125] The system collects data on a user's dietary preferences, allergies, and lifestyle habits, and provides personalized cooking plans based on that data. It also recognizes the ingredients in the refrigerator, provides a list of ingredients and cooking utensils needed, provides real-time cooking guidance, and personalizes the plan according to the user's emotional state.

[1126] Hardware and software used

[1127] Device: A smartphone or tablet where users enter information and receive instructions and guidance.

[1128] Server: A computer system that receives, processes, stores, and analyzes data.

[1129] AI camera: A camera used to recognize ingredients in the refrigerator.

[1130] Emotion engine: Technology for recognizing a user's emotional state by analyzing their facial expressions and voice data.

[1131] Specific details of data processing and calculation

[1132] 1. Data entry and submission

[1133] Device: Users enter their dietary preferences, allergy information, and lifestyle data through an app on their smartphone or tablet.

[1134] Server: Receives data sent from the device, creates a user profile, and stores it in a database.

[1135] 2. Recognition and transmission of food ingredient information

[1136] Terminal: An AI camera installed inside the refrigerator recognizes ingredients and sends that information to the server.

[1137] Server: Matches the received ingredient information with the user profile and generates an appropriate cooking plan.

[1138] 3. Generating a Cooking Plan

[1139] Server: Automatically generates a personalized weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[1140] Server: Identifies missing ingredients and cooking equipment, creates a shopping list, and sends it to the user's device as a reminder message.

[1141] 4. Real-time cooking guide

[1142] User: Selects a suggested cooking recipe and sends the information to the server via the device.

[1143] Server: Monitors the cooking progress in real time and generates appropriate audio and video guides to send to the device.

[1144] 5. Recognizing and guiding emotional states

[1145] Emotion engine: Analyzes the user's facial expressions and voice data to recognize their emotional state.

[1146] Server: Based on emotional data, the content and tone of the guide can be adjusted to further personalize the user's cooking experience.

[1147] Specific operation example

[1148] The user enters their preferred ingredients (e.g., chicken, tomato), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) on their smartphone and presses the send button. This data is sent to the server, which creates a user profile and uses an AI camera to identify ingredients in the refrigerator (e.g., 200g of chicken, 1 cabbage). Based on this information, the server generates a cooking plan such as "Teriyaki Chicken" and sends the user a shopping list of missing seasonings and ingredients as a reminder message. When the user selects a recipe and begins cooking, the server provides audio guidance such as "Please turn the meat over," adjusting the guidance tone according to the user's stress level as recognized by the emotion engine. When the dish is complete, a notification is displayed urging the user to "Share this dish on social media."

[1149] Examples of prompt statements

[1150] "Generate the perfect weekly cooking plan based on your preferences and allergies."

[1151] "Recognize the ingredients in your refrigerator and suggest cooking recipes based on them."

[1152] "Consider the user's emotional state and adjust the content and tone of your cooking progression guide."

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

[1154] Step 1:

[1155] Data Entry and Submission

[1156] Users use the device to input their food preferences (e.g., favorite foods), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) through an app on their smartphone or tablet. This input data is stored on the device and prepared for transmission.

[1157] Input: User preferences, allergy information, and lifestyle data.

[1158] Data processing: Validation and formatting of input data.

[1159] Output: Data ready to be sent to the server.

[1160] Step 2:

[1161] Data transmission and storage

[1162] The server receives the data sent from the device. Based on this, the server generates a user profile and stores it in a database. For example, the server creates a new profile and stores each attribute (preferences, allergies, lifestyle habits) in the database.

[1163] Input: User data sent from the device.

[1164] Data processing: A profile is generated based on user data and stored in a database.

[1165] Output: The updated user profile in the database.

[1166] Step 3:

[1167] Recognizing and transmitting information about ingredients in the refrigerator

[1168] An AI camera connected to the device recognizes the ingredients in the refrigerator and sends that information to a server. For example, the AI ​​camera recognizes that the refrigerator contains 200g of chicken and one cabbage.

[1169] Input: Video of food in the refrigerator.

[1170] Data processing: Extraction of food ingredient information through video analysis.

[1171] Output: Ingredient information sent to the server.

[1172] Step 4:

[1173] Generate a recipe plan and list missing ingredients

[1174] The server generates a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator. It lists ingredients, seasonings, and cooking utensils that are in short supply and generates a shopping list. For example, it suggests "teriyaki chicken" and prompts the user to purchase necessary seasonings (e.g., soy sauce and sugar).

[1175] Input: User profile, refrigerator food information.

[1176] Data processing: Generate an appropriate cooking plan based on user profile and ingredient information. List ingredients that are in short supply.

[1177] Output: Meal plan and shopping list.

[1178] Step 5:

[1179] Sending shopping list reminder messages

[1180] The server then sends the generated shopping list to the device as a reminder message. For example, the user's smartphone might receive a notification saying, "Please buy soy sauce and sugar."

[1181] Enter: Shopping List.

[1182] Data processing: Convert shopping lists into reminder messages.

[1183] Output: The reminder message sent to the user's device.

[1184] Step 6:

[1185] Select and submit a recipe

[1186] The user selects their favorite recipe from the multiple recipe suggestions and sends the information to the server via their device. For example, they select "Teriyaki Chicken."

[1187] Input: A suggested recipe.

[1188] Data processing: The selected recipe information is sent to the server.

[1189] Output: The selected recipe information sent to the server.

[1190] Step 7:

[1191] Monitor cooking progress and provide guidance

[1192] The server monitors the cooking progress in real time and generates appropriate guidance (e.g., "Please turn the meat over") and sends it to the device.

[1193] Input: Select recipe information and real-time progress data.

[1194] Data processing: Proceeding and generating guides.

[1195] Output: The guide sent to your device.

[1196] Step 8:

[1197] Recognizing and guiding emotional states

[1198] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotional state. The server then adjusts the content and tone of the guide based on this data. For example, if the user is feeling stressed, the tone of the guide will be changed to a gentler tone.

[1199] Input: User's facial expressions and voice data.

[1200] Data processing: Data analysis for emotional state recognition and guided adjustment.

[1201] Output: Adjusted guide.

[1202] Step 9:

[1203] Encourage sharing on social media after cooking is complete

[1204] When the dish is complete, the server sends a message to the device saying, "Share this dish on social media," encouraging the user to share the results of their cooking with others.

[1205] Input: Notification that the food is ready.

[1206] Data processing: Generating messages encouraging sharing on social media.

[1207] Output: The sharing prompt sent to the device.

[1208] (Application example 2)

[1209] 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."

[1210] Conventional cooking assistance systems lack personalized recipe suggestions based on users' dietary preferences and allergy information, and have problems such as shortages of certain ingredients and tedious recipe planning. Furthermore, the content and tone of the cooking assistance could not be adjusted according to the user's emotional state, which often caused stress during the cooking process. Furthermore, purchasing missing ingredients was a manual process, preventing the establishment of an efficient supply chain.

[1211] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server, means for adjusting the content and tone of the guidance based on the emotion, means for ordering missing ingredients and cooking utensils, and means for generating prompt sentences with instruction content according to the emotion using a generative AI model. This enables personalized recipe suggestions for the user, enabling flexible cooking support according to emotions and efficient ingredient procurement.

[1212] "User dietary preferences" refer to the types of foods or cuisines that a particular user prefers to eat.

[1213] "Allergy information" refers to information that indicates a user's allergic reaction to a particular food or ingredient.

[1214] "Lifestyle habits" refers to the activities and behavioral patterns that a user engages in on a daily basis.

[1215] "Server" means a centralized computer system that receives and processes information from users and provides necessary data.

[1216] A "user profile" is an individual data set created based on information such as a user's food preferences, allergy information, and lifestyle habits.

[1217] A "database" is a system for systematically storing and managing information such as user profiles.

[1218] "Behavioral data" refers to data about a user's daily behavior, including information such as meal times and frequency, and the dishes they choose.

[1219] "Information about ingredients in the refrigerator" is information about the food and ingredients currently stored in the user's refrigerator.

[1220] A "cooking plan" is a cooking schedule for a specific period (for example, a week) that is created based on the user's profile and the ingredients in the refrigerator.

[1221] A "shopping list" is a list that is generated when specific ingredients or cooking equipment are in short supply based on a cooking plan.

[1222] A "remind message" is a message that notifies the user of important information or suggestions.

[1223] "Recipe information" refers to information about how to make the dish selected by the user and the ingredients needed.

[1224] "Cooking progress" refers to the current state of the user's cooking process.

[1225] "Guide" means instructions or advice provided to the user as they proceed with their cooking.

[1226] "Sharing on social media" refers to posting photos and information about the dishes created by users on social networking services.

[1227] The "emotion engine" is a system for recognizing a user's emotional state from their facial expressions and behavior.

[1228] A "generative AI model" is a machine learning algorithm that generates personalized content or instructions based on data.

[1229] A "prompt" is a document that provides specific instructions or guidelines generated by a generative AI model.

[1230] This invention is a system that provides personalized meal plans based on a user's dietary preferences, allergy information, lifestyle habits, and emotional state, and efficiently procures ingredients in cooperation with food delivery services. The system includes a user terminal, a server, an AI camera in the refrigerator, and an emotion engine.

[1231] First, the user enters data on their dietary preferences, allergies, and lifestyle habits through their device. This data is then sent to the server, which then creates a user profile based on that data and stores it in a database. The device also continuously collects user behavior data, which the server uses to update the profile.

[1232] Next, the refrigerator's AI camera recognizes the ingredients in the refrigerator and sends the information to a server. The server generates a weekly cooking plan based on this information and the user's profile. The cooking plan identifies any shortages of necessary ingredients or cooking equipment and generates a shopping list. This list is then sent to the user's device as a reminder message.

[1233] Once cooking begins, the user device sends the selected recipe information to the server, which monitors the cooking progress in real time. The server generates appropriate guidance based on the cooking progress and provides it to the user via audio and video. In addition, the emotion engine recognizes the user's emotional state and sends that data to the server to adjust the content and tone of the guidance. For example, if the user is feeling stressed, the server will provide instructions in a calmer tone.

[1234] After cooking is complete, the server sends a message to the user's device encouraging them to share the cooking experience on social media. This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[1235] The server generates a prompt like this:

[1236] Suggest recipes using the chicken and broccoli the user has in their fridge. If the user becomes stressed during the cooking process, calm the guide's tone and provide specific audio instructions.

[1237] This invention uses the Python Requests library to communicate with the server, and utilizes the server API to update profiles, update refrigerator contents, generate cooking plans, acquire emotions, and generate guides. This enables personalized recipe suggestions for users, enabling flexible cooking support based on emotions and efficient ingredient procurement.

[1238] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1239] Step 1:

[1240] Users input data such as dietary preferences, allergy information, and lifestyle habits into their device. The device then structures the data and sends it to the server, which then creates a user profile based on the data and stores it in a database.

[1241] Step 2:

[1242] The AI ​​camera recognizes the information about ingredients in the refrigerator and sends it to the server. The server adds the received information to the user's profile and updates the database. It also analyzes the information to generate a list of available ingredients.

[1243] Step 3:

[1244] Based on the user's profile and the ingredients in the refrigerator, the server generates a weekly cooking plan, a set of recipes optimized for the user's dietary preferences, allergies, and lifestyle habits, including a list of the ingredients and cooking equipment needed.

[1245] Step 4:

[1246] The server then identifies any missing ingredients and cooking utensils based on the cooking plan and generates a shopping list. The shopping list is then sent to the user's terminal as a reminder message. The user terminal receives the reminder message and notifies the user.

[1247] Step 5:

[1248] The user selects a dish from the suggested recipes and transmits the selected recipe information to the server via the user terminal, which adds data related to the selected recipe to the user profile and updates the database.

[1249] Step 6:

[1250] While cooking, the user device monitors the user's actions (e.g., preparation of ingredients and cooking progress) in real time. As the user progresses through each step of the recipe, the progress information is sent to the server. The server analyzes the progress and generates a guide for the next step.

[1251] Step 7:

[1252] The emotion engine recognizes the user's emotional state and sends that data to the server. The server then adjusts the content and tone of the guide based on the emotional data. For example, if the user is feeling stressed, the tone of the guide will be set to a gentler tone.

[1253] Step 8:

[1254] The server uses a generative AI model to generate prompts based on the cooking progress and emotional state of the user. These prompts are sent to the user's device as audio or video and provided to the user at the appropriate time.

[1255] Step 9:

[1256] After the cooking is finished, the server generates a message to encourage sharing on SNS and sends it to the user's device. The user's device receives this message and notifies the user, encouraging them to post photos and information about the cooking on SNS.

[1257] This provides an efficient and personalized cooking experience, allowing users to enjoy cooking without stress, and also enables efficient purchasing of ingredients that may be in short supply.

[1258] 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.

[1259] 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.

[1260] 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.

[1261] [Fourth embodiment]

[1262] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1263] 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.

[1264] 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).

[1265] 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.

[1266] 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.

[1267] 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).

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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.

[1272] 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.

[1273] 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.

[1274] 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."

[1275] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[1276] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[1277] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[1278] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the cooking process of the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. After the dish is complete, the server sends a message to the device such as "Share this dish on social media" to encourage the user to share it.

[1279] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. It is expected that this invention will help solve many of the problems facing modern society.

[1280] The processing flow will be explained below.

[1281] Step 1:

[1282] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[1283] Step 2:

[1284] The terminal transmits the input information to the server.

[1285] Step 3:

[1286] The server creates a user profile based on the received information and stores it in a database.

[1287] Step 4:

[1288] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[1289] Step 5:

[1290] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[1291] Step 6:

[1292] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[1293] Step 7:

[1294] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[1295] Step 8:

[1296] The server sends the shopping list as a reminder message to the user's terminal.

[1297] Step 9:

[1298] The user selects the recipe they like from the suggested recipes.

[1299] Step 10:

[1300] The terminal transmits the selected recipe information to the server.

[1301] Step 11:

[1302] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[1303] Step 12:

[1304] The server generates audio and video guides according to the progress and sends them to the device.

[1305] Step 13:

[1306] The device provides audio and video guidance to the user.

[1307] Step 14:

[1308] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[1309] Step 15:

[1310] The completed dish is shared on social media based on the message provided by the user.

[1311] This process allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[1312] Example 1

[1313] 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."

[1314] Conventional meal management systems struggle to provide personalized meal plans that comprehensively reflect a user's dietary preferences, allergies, and lifestyle habits. Furthermore, they lack systems that effectively utilize information about ingredients in the refrigerator, monitor the cooking progress in real time, and provide appropriate guidance. Furthermore, they lack functionality for continuously collecting and updating user behavior data and encouraging users to share their cooking on social media after cooking is complete.

[1315] 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.

[1316] In this invention, the server includes a means for monitoring the user's process of handling ingredients and cooking in real time and providing audio or video guidance as needed, a means for using an AI camera to recognize ingredient information in the refrigerator, and a means for automatically updating the shopping list based on information from the user's device, thereby enabling the creation of cooking plans based on the user's individual information, real-time cooking support, and efficient ingredient management.

[1317] "User" refers to a person who uses the system to provide personal information such as dietary preferences, allergy information, and lifestyle habits.

[1318] A "device" is an electronic device, such as a smartphone or tablet, that a user uses to enter information and receive reminders and guidance.

[1319] A "server" is a computer system that manages data sent by users and performs profile generation, cooking plan creation, real-time monitoring, etc.

[1320] A "user profile" is a data set constructed based on a user's dietary preferences, allergy information, lifestyle habits, etc.

[1321] A "database" is a data management system for storing user profile information, ingredient information, and the like.

[1322] "Information about ingredients in the refrigerator" is data about the types and quantities of ingredients stored in the refrigerator.

[1323] An "AI camera" is a camera system that uses image recognition technology to recognize information about ingredients in a refrigerator.

[1324] A "meal plan" is a weekly meal plan that is suggested based on the user's profile and the ingredients in their fridge.

[1325] A "shopping list" is a list of ingredients and equipment needed to execute a cooking plan, and is a list of items that the user must assemble.

[1326] A "reminding message" is a message that notifies the user of ingredients or equipment that need to be purchased.

[1327] "Recipe information" refers to detailed cooking instructions and ingredient information for the proposed recipe.

[1328] "Real-time monitoring" is the process of checking the user's cooking process in real time and understanding the status.

[1329] "Guides" are audio and video instructions provided to users as they progress through the cooking process.

[1330] "Sharing on social media" refers to the act of posting photos and information about the finished dish on a social networking service.

[1331] The following describes an embodiment of the present invention. The present invention is a system that provides personalized cooking plans based on a user's dietary preferences, allergy information, and lifestyle data, provides real-time assistance during cooking, and ultimately reduces food waste and improves the user's nutritional balance.

[1332] Hardware and software used

[1333] 1. Device: An electronic device such as a smartphone or tablet where users enter information and receive reminders and guidance.

[1334] 2. Server: A computer system that uses cloud services (e.g., AWS, Google Cloud) to manage the data sent by users and perform functions such as generating profiles, creating cooking plans, and real-time monitoring.

[1335] 3. AI Camera: This uses the device's built-in camera and image recognition software (e.g., TensorFlow, OpenCV) to recognize information about ingredients in the refrigerator.

[1336] 4. Database: A SQL or NoSQL database (e.g., MySQL, MongoDB) to store user profile information and ingredient information.

[1337] 5. Generative AI model: A language model (e.g., OpenAI GPT-4) to generate guides and messages based on prompts.

[1338] Example of a system

[1339] For example, the following shows a case where the AI ​​camera recognizes the chicken and vegetables in the user's refrigerator and sends the information to the server.

[1340] User information entry and submission

[1341] Using a smartphone app, users input data such as their dietary preferences, allergy information, and lifestyle habits. For example, they can enter information such as "I have a nut allergy" or "I like high-protein meals." The device then sends this information to a server, which then creates a user profile based on the information entered and stores it in a database.

[1342] Recognizing ingredients in the refrigerator

[1343] The user opens the refrigerator door and takes a picture of the inside with the AI ​​camera on their smartphone. The AI ​​camera recognizes ingredients such as chicken and cabbage and sends information such as "there is chicken and cabbage in the refrigerator" to the server.

[1344] Generate a meal plan

[1345] The server generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator, suggesting recipes such as "teriyaki chicken" and "stir-fried cabbage and chicken."

[1346] Missing item list and reminder messages

[1347] The server generates a list of missing ingredients and utensils needed to execute the cooking plan and sends a shopping list to the user's device as a reminder message, such as "You need to buy soy sauce and sugar."

[1348] Recipe selection and cooking assistance

[1349] The user selects "Teriyaki Chicken" from the suggested recipes and sends the information to the server. When the user starts cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the chicken over" and provides instructions to the user via voice.

[1350] Promoting social media sharing

[1351] After the dish is ready, the server generates a message such as "Share this dish on social media" and sends it to the user's device. The user taps the message to post it on social media.

[1352] Prompt Sentence Examples

[1353] 1. "Please suggest recipes based on the user's dietary preferences and allergy information."

[1354] 2. "Generate recipes using the chicken and vegetables in your fridge and guide you as you progress."

[1355] 3. "After cooking, please generate a message to share on social media."

[1356] This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance. This invention can help solve many of the problems facing modern society.

[1357] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1358] Step 1:

[1359] Users use a smartphone app to input their preferences, allergy information, and lifestyle data. The input information is personalized data about the user's preferences and allergies. Once the user has completed the input, the device sends it to the server. Specifically, the user enters information such as "I have a nut allergy" or "I like high-protein meals" into the input form and taps the "Submit" button.

[1360] Input: User-entered preferences, allergy information, and lifestyle data

[1361] Output: User data sent to the server

[1362] Step 2:

[1363] The server creates a user profile based on the received data and stores it in a database. This profile generation involves analyzing the user's input data and processing it to classify it into appropriate categories. Specifically, the server generates profile information such as "User A has a nut allergy and prefers a high-protein diet" and stores it in the database.

[1364] Input: User data sent to the server

[1365] Output: User profile stored in database

[1366] Step 3:

[1367] The user opens the refrigerator door and takes a picture of the inside of the refrigerator with the AI ​​camera on their smartphone. The AI ​​camera uses image recognition technology to automatically recognize the ingredients inside the refrigerator. The recognized ingredient information is sent from the device to the server. Specifically, the user takes a picture of chicken or cabbage with the camera, and the AI ​​camera recognizes them as "chicken" and "cabbage."

[1368] Input: Image data of the inside of the refrigerator

[1369] Output: Ingredient information sent to the server

[1370] Step 4:

[1371] The server generates a weekly cooking plan based on the received ingredient information and the user profile created earlier. This involves data calculations to select the optimal menu by comparing the ingredient information with the user's preferences. Specifically, the server suggests recipes such as "Teriyaki Chicken" and "Stir-fried Cabbage and Chicken."

[1372] Input: Ingredient information and user profile sent to the server

[1373] Output: Weekly meal plan

[1374] Step 5:

[1375] The server generates a list of ingredients and utensils needed to execute the cooking plan and sends it to the user's device as a reminder message. Specifically, the server creates a list such as "You need to buy soy sauce and sugar" and sends a message to the user's smartphone.

[1376] Enter: Weekly Meal Plan

[1377] Output: Shopping list sent as reminder messages

[1378] Step 6:

[1379] The user selects the desired dish from the suggested recipes, and the device sends that information to the server. Specifically, the user selects "Teriyaki Chicken" in the app and taps the "Select" button.

[1380] Input: Recipe information selected by the user

[1381] Output: Selected recipe information sent to the server

[1382] Step 7:

[1383] When the user starts cooking, the AI ​​camera monitors the cooking process in real time. The server provides appropriate guidance based on the recognized progress. Specifically, the AI ​​camera monitors the cooking of the chicken, and the server generates a voice prompt such as "Please turn the chicken over" and sends the instruction to the device.

[1384] Input: Real-time video of the cooking process

[1385] Output: Audio prompts provided to the user

[1386] Step 8:

[1387] Once the dish is ready, the server generates a message to share it on social media and sends it to the user's device. Specifically, the server generates a message such as "Share this dish on social media" and sends it to the user's smartphone.

[1388] Input: Notification of cooking completion

[1389] Output: Message encouraging social media sharing

[1390] The above are the specific processing steps of the program of this system.

[1391] (Application example 1)

[1392] 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."

[1393] In modern life, it is difficult to receive recipe suggestions that suit individual dietary preferences, allergies, and lifestyle habits. Furthermore, it is often inconvenient when certain ingredients or cooking equipment are lacking. Furthermore, without real-time monitoring of cooking progress or guidance, mistakes are likely to occur during the cooking process, making it difficult to have an efficient cooking experience. Furthermore, there are few systems that allow users to receive individually customized suggestions when selecting delivery menus. There is a need for an appropriate system to solve these issues.

[1394] 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.

[1395] In this invention, the server includes a means for generating an individually customized delivery menu based on a user profile and ingredient information, a means for providing the delivery menu to the user and receiving an order, and a means for transmitting recipe information selected by the user from the suggested recipes to the server. This allows users to receive customized cooking suggestions that suit their individual preferences, allergies, and lifestyles, and allows them to quickly identify missing ingredients and cooking utensils and receive reminders as a shopping list. Furthermore, the cooking progress is monitored in real time and audio or video guidance is provided as needed, providing an efficient and error-free cooking experience and allowing users to order a menu that meets their individual needs, even when ordering delivery.

[1396] A "user profile" is an individual data set created based on information such as a user's dietary preferences, allergy information, lifestyle habits, and behavioral data.

[1397] "Server" means a computing system that receives, processes, stores, and provides the necessary data to the User.

[1398] "Delivery Menu" means a meal or ingredient delivery option customized based on user profile and ingredient information.

[1399] "Cooking progress" is information that monitors the current stage of cooking in real time.

[1400] "Guide" means audio or video instructions provided to a user as they cook a dish.

[1401] "Ingredient information" is data relating to the types and quantities of ingredients present in the refrigerator.

[1402] A "reminder message" is a notification that prompts the user to purchase the necessary ingredients and cooking equipment.

[1403] A "suggested recipe" is a server-generated suggestion for how to cook a dish based on the user's profile and ingredient information.

[1404] "Ordering" means the act of a user purchasing a dish or ingredient selected from the delivery menu.

[1405] "SNS sharing message" is a notification that encourages the user to post the results of their cooking to a social networking service after they have finished cooking.

[1406] An "AI camera" is a camera that has the ability to recognize objects using artificial intelligence technology.

[1407] This invention is a system that provides individually customized meal suggestions and delivery menus based on a user's dietary preferences, allergy information, lifestyle habits, behavioral data, etc. Specifically, it is implemented in the following steps.

[1408] Program Generation

[1409] The server receives data on dietary preferences, allergies, and lifestyle habits entered from the user's device and creates a user profile based on this data. The created profile is stored in a database, and user behavior data is continuously collected and updated. Using this data, the server generates an individually customized delivery menu. In addition, information on ingredients in the refrigerator is recognized using an AI camera installed on the device and sent to the server.

[1410] Hardware and software used

[1411] 1. Server:

[1412] The server is built using Python and the Flask framework.

[1413] Machine learning libraries such as TensorFlow are used for data processing and AI models are executed.

[1414] 2. Terminal:

[1415] The user's smartphone or tablet.

[1416] An AI camera for recognizing food ingredient information.

[1417] Speakers and displays to provide audio and video guides.

[1418] Processing description

[1419] 1. Create a user profile:

[1420] The server receives the user's submitted data on preferences, allergies, and lifestyle habits and creates a user profile based on it, storing the information in a database for later use.

[1421] 2. Collecting ingredient information:

[1422] The AI ​​camera installed on the device recognizes the ingredients in the refrigerator and sends that information to a server, which uses it to generate recipes and menus.

[1423] 3. Generate delivery menu:

[1424] The server generates an individually customized delivery menu based on the user profile and ingredient information, using a generative AI model to suggest the optimal menu.

[1425] 4. Cooking Progression Guide:

[1426] Based on the recipe information selected by the user, the server monitors the cooking progress in real time and generates appropriate guidance (audio or video).

[1427] 5. Sharing to social media:

[1428] After cooking is complete, the server generates a message encouraging sharing on social media and sends it to the user's device.

[1429] Specific examples

[1430] To give a specific example, let's say a user uses the AI ​​camera on their smartphone to recognize the chicken and vegetables in their refrigerator. The server generates a cooking plan for "Teriyaki Chicken" based on the user profile, and sends a reminder message to purchase any necessary condiments if they are missing. While cooking, the device provides voice guidance such as "Please turn the meat over," and once the dish is finished, the server sends the user a message saying, "Share this dish on social media."

[1431] Prompt Sentence Examples

[1432] Here are some example prompts to input to the generative AI model based on the following information:

[1433] User Preferences: Japanese, Gluten-Free

[1434] Allergy Information: Dairy

[1435] Lifestyle: Health conscious

[1436] Ingredients in the refrigerator: chicken, carrots, cabbage, ginger

[1437] Generate a weekly cooking plan based on the information below.

[1438] This system allows users to receive optimal meal suggestions and delivery menus tailored to their individual preferences, allergies, and lifestyles, as well as receive support during the cooking process, helping to realize an efficient and healthy diet.

[1439] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1440] Step 1:

[1441] Creating and saving a user profile

[1442] Users use devices such as smartphones or tablets to input personal data such as preferences, allergy information, and lifestyle habits. This data is sent and received by a server, which creates a user profile. Specifically, an individual profile is stored in a database based on the user's preferences and allergy information. At this time, the database assigns each user a unique ID and centrally manages data related to that ID.

[1443] Input: User preferences, allergy information, lifestyle data

[1444] Data processing: Converting received data into a format and saving it to a database

[1445] Output: User profile creation and saving to database completed

[1446] Step 2:

[1447] Collecting information about ingredients in the refrigerator

[1448] The user takes a photo of the ingredients in the refrigerator using the AI ​​camera installed on the device. The device analyzes the image and recognizes the ingredient information. The recognized ingredient information is sent to the server and stored in an ingredient database. The AI ​​camera performs image analysis using machine learning models such as TensorFlow.

[1449] Input: Images of ingredients in the refrigerator

[1450] Data processing: Image analysis (machine learning model), food ingredient data extraction

[1451] Output: Recognized ingredients

[1452] Step 3:

[1453] Generate delivery menu

[1454] The server generates a personalized delivery menu based on the user profile and the ingredients in the refrigerator, using a generative AI model (e.g., GPT-3) to suggest menu items that suit the user's preferences and allergies.

[1455] Input: User profile, refrigerator ingredients information

[1456] Data processing: Menu generation using generative AI models

[1457] Output: Delivery menu suggestions

[1458] Step 4:

[1459] Generate shopping lists and send reminder messages

[1460] The server generates a shopping list of missing ingredients and cooking utensils based on the delivery menu and the information on ingredients in the refrigerator, and sends this shopping list to the user's device as a reminder message.

[1461] Input: Delivery menu, information on ingredients in the refrigerator

[1462] Data processing: Identifying necessary ingredients and equipment, and generating a shopping list

[1463] Output: Shopping list as reminder messages

[1464] Step 5:

[1465] Monitor cooking progress and provide guidance

[1466] Once the user selects a suggested recipe and begins cooking, the device monitors the cooking progress in real time. The server provides audio and video guidance to the user based on the progress. Instructions such as "Please turn the meat over" are sent to the device in real time, and the user follows them as they cook.

[1467] Input: User's cooking progress

[1468] Data processing: Real-time progress analysis, guide generation

[1469] Output: Audio and video guides

[1470] Step 6:

[1471] Encourage sharing on social media after cooking is complete

[1472] After the cooking is complete, the server generates a message prompting the user to share the cooking on social media and sends it to the user's device. The user receives this message and posts a photo of the cooking and a comment on the social media.

[1473] Input: Cooking completion information

[1474] Data processing: Generating SNS sharing messages

[1475] Output: SNS sharing message notification to user

[1476] 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.

[1477] To implement this invention, we begin by building a system that allows users to input data on their dietary preferences, allergies, and lifestyle habits. This data is sent to a server via the user's terminal, and the server creates a user profile based on this information and stores it in a database. It is also possible to continuously collect user behavior data and update the profile.

[1478] The device uses an AI camera to recognize the ingredients in the refrigerator and sends that information to the server. The server then generates a weekly cooking plan based on the user's profile and the ingredients in the refrigerator. Based on this cooking plan, it generates a shopping list for any ingredients or cooking utensils that are running low and sends it to the user's device as a reminder message.

[1479] The recipe information selected by the user from the suggested recipes is sent to the server via the device. The server monitors the cooking progress in real time and sends appropriate information to the device. Specifically, it generates audio and video guides according to the cooking progress and provides them to the user. After cooking is completed, it also generates a message encouraging sharing on social media and sends it to the user's device.

[1480] Furthermore, by combining it with an emotion engine, the system recognizes the user's emotional state and transmits that data to the server. The server then uses this emotional data to further personalize the user's cooking experience. Specifically, the system can adjust cooking suggestions and change the content and tone of guidance based on the user's progress based on the emotions recognized by the emotion engine.

[1481] As a concrete example, consider a case where an AI camera recognizes the chicken and vegetables in a user's refrigerator and sends the information to a server. The server generates a cooking plan for "Teriyaki Chicken" based on the user's profile and sends a reminder message to encourage the user to purchase the necessary condiments. When the user selects "Teriyaki Chicken" and begins cooking, the AI ​​camera monitors the process of grilling the chicken and sends progress information to the server. The server generates guidance such as "Please turn the meat over" and provides voice instructions through the device. Furthermore, if the user is feeling stressed, the guidance tone can be softened and instructions can be given in a gentler voice.

[1482] After the dish is complete, the server sends a message to the device, such as "Share this dish on social media," encouraging the user to share the joy of cooking. This system not only allows users to have an efficient and enjoyable cooking experience, but also reduces food waste and improves nutritional balance. This invention is expected to help solve many of the challenges facing modern society.

[1483] The processing flow will be explained below.

[1484] Step 1:

[1485] The user inputs data on their dietary preferences, allergy information, and lifestyle habits into the terminal.

[1486] Step 2:

[1487] The terminal transmits the input information to the server.

[1488] Step 3:

[1489] The server creates a user profile based on the received information and stores it in a database.

[1490] Step 4:

[1491] The server continuously collects user behavioral data (actual dishes cooked and ingredients purchased) and updates the profile.

[1492] Step 5:

[1493] The terminal (AI camera) recognizes the information about ingredients in the refrigerator and sends that information to the server.

[1494] Step 6:

[1495] The server generates a weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[1496] Step 7:

[1497] The server generates a purchase list for missing ingredients and cooking equipment based on the cooking plan.

[1498] Step 8:

[1499] The server sends the shopping list as a reminder message to the user's terminal.

[1500] Step 9:

[1501] The user selects the recipe they like from the suggested recipes.

[1502] Step 10:

[1503] The terminal transmits the selected recipe information to the server.

[1504] Step 11:

[1505] The device uses an emotion engine to analyze the user's facial expressions and tone of voice, recognizing their emotional state.

[1506] Step 12:

[1507] The device transmits the recognized emotion data to the server.

[1508] Step 13:

[1509] The server uses the emotional data to personalize the user's cooking experience, adjusting the content and tone of the instructions depending on the cooking progress.

[1510] Step 14:

[1511] The terminal (AI camera) monitors the progress of cooking in real time and sends appropriate information to the server.

[1512] Step 15:

[1513] The server generates audio and video guides according to the progress and sends them to the device.

[1514] Step 16:

[1515] The device provides users with audio and video guidance, and if the user is feeling stressed, the guidance tone will be softened and instructions will be given in a gentle voice.

[1516] Step 17:

[1517] After the cooking is complete, the server generates a message encouraging the user to share the food on social media and sends it to the user's device.

[1518] Step 18:

[1519] The finished dish is shared on social media based on a message provided by the user, which is also customized according to the user's emotional state.

[1520] This process allows users to have an efficient and enjoyable cooking experience, while receiving personalized support tailored to their individual emotional state.

[1521] Example 2

[1522] 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."

[1523] Currently, there are no systems that automatically generate personalized cooking plans based on dietary preferences, allergies, and lifestyle habits. There is also a lack of systems that can recognize ingredients in the refrigerator, list the necessary ingredients and cooking utensils, or provide guidance based on the cooking progress. Furthermore, technology that personalizes the cooking experience based on the user's emotional state is underdeveloped. Therefore, there is a need for systems that provide an efficient and enjoyable cooking experience, reduce food waste, and improve nutritional balance.

[1524] 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.

[1525] In this invention, the server includes: means for inputting data on a user's dietary preferences, allergy information, and lifestyle habits; means for transmitting the input information to the server; means for creating a user profile based on the received information and saving it to a database; means for collecting user behavior data and updating the profile; means for recognizing information about ingredients in the refrigerator and transmitting it to the server; means for generating a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator; means for generating a shopping list for missing ingredients and cooking utensils; means for transmitting the shopping list as a reminder message to the user's device; means for transmitting information about a recipe selected by the user from suggested recipes to the server; means for monitoring the cooking progress in real time and transmitting appropriate information to the server; means for generating and providing guidance based on the cooking progress; means for generating and providing a message encouraging sharing on social media after cooking is completed and transmitting it to the user's device; means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server; and means for adjusting the content and tone of the guidance provided based on the emotion data. This enables automatic generation of individual cooking plans, providing an efficient and enjoyable cooking experience, reducing food waste, and improving nutritional balance.

[1526] A "user" is a person who uses the system and provides data on dietary preferences, allergy information, and lifestyle habits.

[1527] A "server" is a computer system that receives, processes, stores, and performs various calculations on data.

[1528] "Terminal" means a device used by a user to enter data or receive notifications from the system, including a smartphone or tablet.

[1529] A "profile" is a data set that centralizes a user's unique information, including the user's dietary preferences, allergy information, lifestyle habits, and other behavioral data.

[1530] "Database" means the digital storage system in which the Server stores user profiles and other related information.

[1531] An "AI camera" is a camera that uses artificial intelligence to recognize ingredients in the refrigerator.

[1532] A "reminder message" is a notification message that prompts the user to take necessary action.

[1533] A "cooking plan" is a set of suggested cooking recipes and preparation plans based on a user profile and the ingredients in the refrigerator.

[1534] The "emotion engine" is a technology that analyzes a user's facial expressions and voice data to recognize their emotional state.

[1535] A "guide" is information containing instructions and advice that are generated as the cooking progresses and is provided in audio or video format.

[1536] The system collects data on a user's dietary preferences, allergies, and lifestyle habits, and provides personalized cooking plans based on that data. It also recognizes the ingredients in the refrigerator, provides a list of ingredients and cooking utensils needed, provides real-time cooking guidance, and personalizes the plan according to the user's emotional state.

[1537] Hardware and software used

[1538] Device: A smartphone or tablet where users enter information and receive instructions and guidance.

[1539] Server: A computer system that receives, processes, stores, and analyzes data.

[1540] AI camera: A camera used to recognize ingredients in the refrigerator.

[1541] Emotion engine: Technology for recognizing a user's emotional state by analyzing their facial expressions and voice data.

[1542] Specific details of data processing and calculation

[1543] 1. Data entry and submission

[1544] Device: Users enter their dietary preferences, allergy information, and lifestyle data through an app on their smartphone or tablet.

[1545] Server: Receives data sent from the device, creates a user profile, and stores it in a database.

[1546] 2. Recognition and transmission of food ingredient information

[1547] Terminal: An AI camera installed inside the refrigerator recognizes ingredients and sends that information to the server.

[1548] Server: Matches the received ingredient information with the user profile and generates an appropriate cooking plan.

[1549] 3. Generating a Cooking Plan

[1550] Server: Automatically generates a personalized weekly cooking plan based on the user profile and the ingredients in the refrigerator.

[1551] Server: Identifies missing ingredients and cooking equipment, creates a shopping list, and sends it to the user's device as a reminder message.

[1552] 4. Real-time cooking guide

[1553] User: Selects a suggested cooking recipe and sends the information to the server via the device.

[1554] Server: Monitors the cooking progress in real time and generates appropriate audio and video guides to send to the device.

[1555] 5. Recognizing and guiding emotional states

[1556] Emotion engine: Analyzes the user's facial expressions and voice data to recognize their emotional state.

[1557] Server: Based on emotional data, the content and tone of the guide can be adjusted to further personalize the user's cooking experience.

[1558] Specific operation example

[1559] The user enters their preferred ingredients (e.g., chicken, tomato), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) on their smartphone and presses the send button. This data is sent to the server, which creates a user profile and uses an AI camera to identify ingredients in the refrigerator (e.g., 200g of chicken, 1 cabbage). Based on this information, the server generates a cooking plan such as "Teriyaki Chicken" and sends the user a shopping list of missing seasonings and ingredients as a reminder message. When the user selects a recipe and begins cooking, the server provides audio guidance such as "Please turn the meat over," adjusting the guidance tone according to the user's stress level as recognized by the emotion engine. When the dish is complete, a notification is displayed urging the user to "Share this dish on social media."

[1560] Examples of prompt statements

[1561] "Generate the perfect weekly cooking plan based on your preferences and allergies."

[1562] "Recognize the ingredients in your refrigerator and suggest cooking recipes based on them."

[1563] "Consider the user's emotional state and adjust the content and tone of your cooking progression guide."

[1564] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1565] Step 1:

[1566] Data Entry and Submission

[1567] Users use the device to input their food preferences (e.g., favorite foods), allergy information (e.g., nut allergy), and lifestyle habits (e.g., late bedtime, early rise) through an app on their smartphone or tablet. This input data is stored on the device and prepared for transmission.

[1568] Input: User preferences, allergy information, and lifestyle data.

[1569] Data processing: Validation and formatting of input data.

[1570] Output: Data ready to be sent to the server.

[1571] Step 2:

[1572] Data transmission and storage

[1573] The server receives the data sent from the device. Based on this, the server generates a user profile and stores it in a database. For example, the server creates a new profile and stores each attribute (preferences, allergies, lifestyle habits) in the database.

[1574] Input: User data sent from the device.

[1575] Data processing: A profile is generated based on user data and stored in a database.

[1576] Output: The updated user profile in the database.

[1577] Step 3:

[1578] Recognizing and transmitting information about ingredients in the refrigerator

[1579] An AI camera connected to the device recognizes the ingredients in the refrigerator and sends that information to a server. For example, the AI ​​camera recognizes that the refrigerator contains 200g of chicken and one cabbage.

[1580] Input: Video of food in the refrigerator.

[1581] Data processing: Extraction of food ingredient information through video analysis.

[1582] Output: Ingredient information sent to the server.

[1583] Step 4:

[1584] Generate a recipe plan and list missing ingredients

[1585] The server generates a weekly cooking plan based on the user profile and the information about ingredients in the refrigerator. It lists ingredients, seasonings, and cooking utensils that are in short supply and generates a shopping list. For example, it suggests "teriyaki chicken" and prompts the user to purchase necessary seasonings (e.g., soy sauce and sugar).

[1586] Input: User profile, refrigerator food information.

[1587] Data processing: Generate an appropriate cooking plan based on user profile and ingredient information. List ingredients that are in short supply.

[1588] Output: Meal plan and shopping list.

[1589] Step 5:

[1590] Sending shopping list reminder messages

[1591] The server then sends the generated shopping list to the device as a reminder message. For example, the user's smartphone might receive a notification saying, "Please buy soy sauce and sugar."

[1592] Enter: Shopping List.

[1593] Data processing: Convert shopping lists into reminder messages.

[1594] Output: The reminder message sent to the user's device.

[1595] Step 6:

[1596] Select and submit a recipe

[1597] The user selects their favorite recipe from the multiple recipe suggestions and sends the information to the server via their device. For example, they select "Teriyaki Chicken."

[1598] Input: A suggested recipe.

[1599] Data processing: The selected recipe information is sent to the server.

[1600] Output: The selected recipe information sent to the server.

[1601] Step 7:

[1602] Monitor cooking progress and provide guidance

[1603] The server monitors the cooking progress in real time and generates appropriate guidance (e.g., "Please turn the meat over") and sends it to the device.

[1604] Input: Select recipe information and real-time progress data.

[1605] Data processing: Proceeding and generating guides.

[1606] Output: The guide sent to your device.

[1607] Step 8:

[1608] Recognizing and guiding emotional states

[1609] The emotion engine analyzes the user's facial expressions and voice data to recognize their emotional state. The server then adjusts the content and tone of the guide based on this data. For example, if the user is feeling stressed, the tone of the guide will be changed to a gentler tone.

[1610] Input: User's facial expressions and voice data.

[1611] Data processing: Data analysis for emotional state recognition and guided adjustment.

[1612] Output: Adjusted guide.

[1613] Step 9:

[1614] Encourage sharing on social media after cooking is complete

[1615] When the dish is complete, the server sends a message to the device saying, "Share this dish on social media," encouraging the user to share the results of their cooking with others.

[1616] Input: Notification that the food is ready.

[1617] Data processing: Generating messages encouraging sharing on social media.

[1618] Output: The sharing prompt sent to the device.

[1619] (Application example 2)

[1620] 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."

[1621] Conventional cooking assistance systems lack personalized recipe suggestions based on users' dietary preferences and allergy information, and have problems such as shortages of certain ingredients and tedious recipe planning. Furthermore, the content and tone of the cooking assistance could not be adjusted according to the user's emotional state, which often caused stress during the cooking process. Furthermore, purchasing missing ingredients was a manual process, preventing the establishment of an efficient supply chain.

[1622] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recognizing the user's emotional state using an emotion engine and transmitting that data to the server, means for adjusting the content and tone of the guidance based on the emotion, means for ordering missing ingredients and cooking utensils, and means for generating prompt sentences with instruction content according to the emotion using a generative AI model. This enables personalized recipe suggestions for the user, enabling flexible cooking support according to emotions and efficient ingredient procurement.

[1623] "User dietary preferences" refer to the types of foods or cuisines that a particular user prefers to eat.

[1624] "Allergy information" refers to information that indicates a user's allergic reaction to a particular food or ingredient.

[1625] "Lifestyle habits" refers to the activities and behavioral patterns that a user engages in on a daily basis.

[1626] "Server" means a centralized computer system that receives and processes information from users and provides necessary data.

[1627] A "user profile" is an individual data set created based on information such as a user's food preferences, allergy information, and lifestyle habits.

[1628] A "database" is a system for systematically storing and managing information such as user profiles.

[1629] "Behavioral data" refers to data about a user's daily behavior, including information such as meal times and frequency, and the dishes they choose.

[1630] "Information about ingredients in the refrigerator" is information about the food and ingredients currently stored in the user's refrigerator.

[1631] A "cooking plan" is a cooking schedule for a specific period (for example, a week) that is created based on the user's profile and the ingredients in the refrigerator.

[1632] A "shopping list" is a list that is generated when specific ingredients or cooking equipment are in short supply based on a cooking plan.

[1633] A "remind message" is a message that notifies the user of important information or suggestions.

[1634] "Recipe information" refers to information about how to make the dish selected by the user and the ingredients needed.

[1635] "Cooking progress" refers to the current state of the user's cooking process.

[1636] "Guide" means instructions or advice provided to the user as they proceed with their cooking.

[1637] "Sharing on social media" refers to posting photos and information about the dishes created by users on social networking services.

[1638] The "emotion engine" is a system for recognizing a user's emotional state from their facial expressions and behavior.

[1639] A "generative AI model" is a machine learning algorithm that generates personalized content or instructions based on data.

[1640] A "prompt" is a document that provides specific instructions or guidelines generated by a generative AI model.

[1641] This invention is a system that provides personalized meal plans based on a user's dietary preferences, allergy information, lifestyle habits, and emotional state, and efficiently procures ingredients in cooperation with food delivery services. The system includes a user terminal, a server, an AI camera in the refrigerator, and an emotion engine.

[1642] First, the user enters data on their dietary preferences, allergies, and lifestyle habits through their device. This data is then sent to the server, which then creates a user profile based on that data and stores it in a database. The device also continuously collects user behavior data, which the server uses to update the profile.

[1643] Next, the refrigerator's AI camera recognizes the ingredients in the refrigerator and sends the information to a server. The server generates a weekly cooking plan based on this information and the user's profile. The cooking plan identifies any shortages of necessary ingredients or cooking equipment and generates a shopping list. This list is then sent to the user's device as a reminder message.

[1644] Once cooking begins, the user device sends the selected recipe information to the server, which monitors the cooking progress in real time. The server generates appropriate guidance based on the cooking progress and provides it to the user via audio and video. In addition, the emotion engine recognizes the user's emotional state and sends that data to the server to adjust the content and tone of the guidance. For example, if the user is feeling stressed, the server will provide instructions in a calmer tone.

[1645] After cooking is complete, the server sends a message to the user's device encouraging them to share the cooking experience on social media. This system allows users to have an efficient and enjoyable cooking experience, while also reducing food waste and improving nutritional balance.

[1646] The server generates a prompt like this:

[1647] Suggest recipes using the chicken and broccoli the user has in their fridge. If the user becomes stressed during the cooking process, calm the guide's tone and provide specific audio instructions.

[1648] This invention uses the Python Requests library to communicate with the server, and utilizes the server API to update profiles, update refrigerator contents, generate cooking plans, acquire emotions, and generate guides. This enables personalized recipe suggestions for users, enabling flexible cooking support based on emotions and efficient ingredient procurement.

[1649] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1650] Step 1:

[1651] Users input data such as dietary preferences, allergy information, and lifestyle habits into their device. The device then structures the data and sends it to the server, which then creates a user profile based on the data and stores it in a database.

[1652] Step 2:

[1653] The AI ​​camera recognizes the information about ingredients in the refrigerator and sends it to the server. The server adds the received information to the user's profile and updates the database. It also analyzes the information to generate a list of available ingredients.

[1654] Step 3:

[1655] Based on the user's profile and the ingredients in the refrigerator, the server generates a weekly cooking plan, a set of recipes optimized for the user's dietary preferences, allergies, and lifestyle habits, including a list of the ingredients and cooking equipment needed.

[1656] Step 4:

[1657] The server then identifies any missing ingredients and cooking utensils based on the cooking plan and generates a shopping list. The shopping list is then sent to the user's terminal as a reminder message. The user terminal receives the reminder message and notifies the user.

[1658] Step 5:

[1659] The user selects a dish from the suggested recipes and transmits the selected recipe information to the server via the user terminal, which adds data related to the selected recipe to the user profile and updates the database.

[1660] Step 6:

[1661] While cooking, the user device monitors the user's actions (e.g., preparation of ingredients and cooking progress) in real time. As the user progresses through each step of the recipe, the progress information is sent to the server. The server analyzes the progress and generates a guide for the next step.

[1662] Step 7:

[1663] The emotion engine recognizes the user's emotional state and sends that data to the server. The server then adjusts the content and tone of the guide based on the emotional data. For example, if the user is feeling stressed, the tone of the guide will be set to a gentler tone.

[1664] Step 8:

[1665] The server uses a generative AI model to generate prompts based on the cooking progress and emotional state of the user. These prompts are sent to the user's device as audio or video and provided to the user at the appropriate time.

[1666] Step 9:

[1667] After the cooking is finished, the server generates a message to encourage sharing on SNS and sends it to the user's device. The user's device receives this message and notifies the user, encouraging them to post photos and information about the cooking on SNS.

[1668] This provides an efficient and personalized cooking experience, allowing users to enjoy cooking without stress, and also enables efficient purchasing of ingredients that may be in short supply.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] 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.

[1674] 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.

[1675] 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).

[1676] 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.

[1677] 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."

[1678] 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.

[1679] 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).

[1680] 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.

[1681] 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.

[1682] 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.

[1683] 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.

[1684] 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.

[1685] 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.

[1686] 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.

[1687] 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.

[1688] 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.

[1689] 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.

[1690] The following is further disclosed regarding the above embodiment.

[1691] (Claim 1)

[1692] A means for inputting the user's dietary preferences, allergy information, and lifestyle data;

[1693] means for transmitting the input information to a server;

[1694] means for creating a user profile based on the received information and storing it in a database;

[1695] A means of collecting user behavior data and updating profiles;

[1696] A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server;

[1697] means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information;

[1698] A means to generate a shopping list for missing ingredients and cooking equipment;

[1699] a means for sending the shopping list as a reminder message to the user's device;

[1700] means for transmitting recipe information selected by the user from the suggested recipes to a server;

[1701] a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server;

[1702] A means for generating and providing progress-based guidance to the user;

[1703] A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device.

[1704] A system including:

[1705] (Claim 2)

[1706] The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance in a timely manner.

[1707] (Claim 3)

[1708] The system of claim 1 uses an AI camera to recognize food information in the refrigerator.

[1709] (Claim 4)

[1710] 2. The system according to claim 1, further comprising means for transmitting a shopping list of ingredients and cooking equipment at an optimal timing based on the user's lifestyle.

[1711] "Example 1"

[1712] (Claim 1)

[1713] A means for inputting the user's dietary preferences, allergy information, and lifestyle data;

[1714] means for transmitting the input information to a server;

[1715] means for creating a user profile based on the received information and storing it in a database;

[1716] A means of collecting user behavior data and updating profiles;

[1717] A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server;

[1718] means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information;

[1719] A means to generate a shopping list for missing ingredients and cooking equipment;

[1720] a means for sending the shopping list as a reminder message to the user's device;

[1721] means for transmitting recipe information selected by the user from the suggested recipes to a server;

[1722] a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server;

[1723] A means for generating and providing progress-based guidance to the user;

[1724] A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device.

[1725] A means to automatically update the shopping list based on information from the user's device,

[1726] A means of real-time monitoring using AI cameras based on information about ingredients in the refrigerator, and

[1727] A system including:

[1728] (Claim 2)

[1729] The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance in a timely manner.

[1730] (Claim 3)

[1731] The system of claim 1 uses an AI camera to recognize food information in the refrigerator.

[1732] "Application Example 1"

[1733] (Claim 1)

[1734] A means for inputting the user's dietary preferences, allergy information, and lifestyle data;

[1735] means for transmitting the input information to a server;

[1736] means for creating a user profile based on the received information and storing it in a database;

[1737] A means of collecting user behavior data and updating profiles;

[1738] A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server;

[1739] means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information;

[1740] A means to generate a shopping list for missing ingredients and cooking equipment;

[1741] a means for sending the shopping list as a reminder message to the user's device;

[1742] means for transmitting recipe information selected by the user from the suggested recipes to a server;

[1743] a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server;

[1744] A means for generating and providing progress-based guidance to the user;

[1745] A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device.

[1746] A means for generating a personalized delivery menu based on a user profile and ingredient information;

[1747] A means of providing users with a delivery menu and taking orders;

[1748] A system including:

[1749] (Claim 2)

[1750] The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance in a timely manner.

[1751] (Claim 3)

[1752] The system of claim 1 uses an AI camera to recognize food information in the refrigerator.

[1753] "Example 2: Combining Emotion Engines"

[1754] (Claim 1)

[1755] A means for inputting the user's dietary preferences, allergy information, and lifestyle data;

[1756] means for transmitting the input information to a server;

[1757] means for creating a user profile based on the received information and storing it in a database;

[1758] A means of collecting user behavior data and updating profiles;

[1759] A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server;

[1760] means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information;

[1761] A means to generate a shopping list for missing ingredients and cooking equipment;

[1762] a means for sending the shopping list as a reminder message to the user's device;

[1763] means for transmitting recipe information selected by the user from the suggested recipes to a server;

[1764] a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server;

[1765] A means for generating and providing progress-based guidance to the user;

[1766] A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device.

[1767] means for utilizing an emotion engine to recognize the user's emotional state and transmitting that data to a server;

[1768] A means to tailor the content and tone of the guidance provided based on emotional data; and

[1769] A system including:

[1770] (Claim 2)

[1771] The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance in a timely manner.

[1772] (Claim 3)

[1773] The system of claim 1 uses an AI camera to recognize food information in the refrigerator.

[1774] "Application example 2 when combining emotion engines"

[1775] (Claim 1)

[1776] A means for inputting the user's dietary preferences, allergy information, and lifestyle data;

[1777] means for transmitting the input information to a server;

[1778] means for creating a user profile based on the received information and storing it in a database;

[1779] A means of collecting user behavior data and updating profiles;

[1780] A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server;

[1781] means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information;

[1782] A means to generate a shopping list for missing ingredients and cooking equipment;

[1783] a means for sending the shopping list as a reminder message to the user's device;

[1784] means for transmitting recipe information selected by the user from the suggested recipes to a server;

[1785] a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server;

[1786] A means for generating and providing progress-based guidance to the user;

[1787] A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device.

[1788] means for recognizing the user's emotional state by an emotion engine and transmitting the data to a server;

[1789] A way to adjust the content and tone of your guide based on your emotions;

[1790] A way to order ingredients and cooking equipment that are in short supply,

[1791] A means for generating a prompt sentence with instruction content according to emotion using a generative AI model;

[1792] A system including:

[1793] (Claim 2)

[1794] The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance in a timely manner.

[1795] (Claim 3)

[1796] The system of claim 1 uses an AI camera to recognize food information in the refrigerator. [Explanation of symbols]

[1797] 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 the user's dietary preferences, allergy information, and lifestyle data; means for transmitting the input information to a server; means for creating a user profile based on the received information and storing it in a database; A means of collecting user behavior data and updating profiles; A means for recognizing information about ingredients in a refrigerator and transmitting the information to a server; means for generating a weekly cooking plan based on a user profile and refrigerator ingredient information; A means to generate a shopping list for missing ingredients and cooking equipment; a means for sending the shopping list as a reminder message to the user's device; means for transmitting recipe information selected by the user from the suggested recipes to a server; a means for monitoring the progress of cooking in real time and transmitting appropriate information to the server; A means for generating and providing progress-based guidance to the user; A method to generate a message prompting users to share the cooking on social media after cooking is completed and send it to their device. A system including:

2. The system according to claim 1, wherein the system monitors the process of the user manipulating ingredients and cooking in real time and provides audio or video guidance at appropriate times.

3. The system of claim 1 uses an AI camera to recognize food information in the refrigerator.

4. 2. The system according to claim 1, further comprising means for transmitting a shopping list of ingredients and cooking equipment at an optimal timing based on the user's lifestyle.

Images