system

Abstract

We provide the system. [Solution] A means for entering user information and receiving dietary restriction information, including religious beliefs and allergy restrictions, A means for obtaining data on appropriate ingredients and cooking methods from a database based on the aforementioned dietary restriction information, A means for generating a recipe using an algorithm based on the acquired data, A means for transmitting and displaying the generated recipe data on a user terminal, The means of transmitting the aforementioned recipe data to a 3D food molding device and creating a dish, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a lack of a method that enables people with diverse religious beliefs and allergies to easily prepare safe and enjoyable meals that comply with their respective restrictions. In conventional meal provision systems, it has been difficult to make detailed accommodations according to specific beliefs and health restrictions, often imposing a burden on users. Also, existing technologies have required time and effort in the process from ingredient selection to meal preparation. The present invention aims to solve such problems and provide an individualized meal experience.

Means for Solving the Problems

[0005] This invention provides a means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions, from a terminal. Furthermore, it includes means for accessing a database to obtain appropriate ingredients and cooking methods based on the received information, and applies an algorithm to generate recipes based on the acquired data. The generated recipe data is transmitted to the user terminal and displayed to the user. Finally, the prepared recipe data is sent to a 3D food molding machine to create a dish according to the user's requests. It also includes means for receiving feedback from the user and incorporating it into future suggestions to provide a more refined and personalized service.

[0006] "User information" refers to data about individual users, including information related to diet, such as religious beliefs and allergy restrictions.

[0007] "Religious beliefs" refer to dietary norms and restrictions that stem from the beliefs or doctrines of an individual or group based on a particular religion.

[0008] "Allergy restrictions" refer to dietary restrictions established to avoid causing hypersensitivity reactions in the body to certain foods or ingredients.

[0009] "Ingredients" refer to raw materials used in cooking, and are foods that possess specific nutritional components and flavors.

[0010] "Cooking method" refers to the specific steps and techniques used to prepare a dish using ingredients, including the use of seasonings and temperature control.

[0011] A "database" refers to a collection of information that is organized to store data in a systematic way, making it easy to retrieve and manage.

[0012] A "recipe" refers to a set of instructions that lists the ingredients needed to prepare a particular dish, their quantities, and the steps and methods involved.

[0013] An "algorithm" refers to a system of procedures or calculation methods for solving a particular problem, and is expressed as a series of steps.

[0014] A "user terminal" refers to a computer or communication device that a user directly operates to input information and verify results.

[0015] A "3D food molding machine" refers to a machine that creates dishes with specified shapes and designs by layering ingredients in a three-dimensional manner. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of a plurality of arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of a plurality of types of arithmetic units. Examples of the arithmetic unit include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system for streamlining users' daily meal management and providing safe and appropriate meals. The system consists of a user terminal, a server, and a 3D food molding device. The user inputs necessary information, such as their religious beliefs, allergies, and dietary preferences, via the terminal. This information is sent to the server, which receives and authenticates it. Upon successful authentication, the server searches its database based on this information and retrieves data on suitable ingredients and cooking methods.

[0038] The server then generates a recipe tailored to the user's constraints and preferences based on the acquired data. The generated recipe is sent to the terminal, where the user can view and review it. At this point, the user can also customize the recipe. Finally, once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. Based on the transmitted data, the device creates the dish with the specified shape and cooking method.

[0039] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its database for plant-based, nut-free ingredients and generate a recipe based on them. The recipe will also detail the ingredients used and cooking procedures, allowing the user to enjoy their meal with peace of mind. This significantly simplifies daily dietary management and makes it possible to provide a personalized dining experience for each user.

[0040] The following describes the processing flow.

[0041] Step 1:

[0042] Users log in to the application using their device and enter personal information such as their religious beliefs, allergies, and dietary preferences.

[0043] Step 2:

[0044] The terminal sends the entered user information to the server and begins user account authentication. The server determines whether authentication was successful and returns an error message to the terminal if it fails.

[0045] Step 3:

[0046] The server searches the database based on authenticated user information to retrieve food data that matches the user's religious beliefs and allergies. This process creates a list of candidate foods that meet the user's restrictions.

[0047] Step 4:

[0048] The server uses the acquired ingredient data to generate the optimal recipe for the user through an algorithm. This recipe generation process also takes into account the balance of nutrients and flavor.

[0049] Step 5:

[0050] The server sends the generated recipe data to the terminal, allowing the user to review the recipe. The terminal then displays the recipe to the user and provides customization options as needed.

[0051] Step 6:

[0052] Once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. The device then begins cooking the food according to the specified shape and cooking method based on this data.

[0053] Step 7:

[0054] The terminal notifies the user when the meal is ready, and after the user receives the meal, they can enter feedback through the application. The server collects this feedback and uses it as data to improve future recipe suggestions.

[0055] (Example 1)

[0056] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0057] Providing safe and personalized meals to users with diverse religious beliefs and allergy restrictions is challenging. Traditional methods involve a significant amount of manual work to meet each user's individual needs, which is time-consuming and labor-intensive.

[0058] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0059] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for searching an information recording medium and obtaining data on appropriate ingredients and cooking methods; and means for generating cooking procedures using an artificial intelligence model based on the obtained data. This enables efficient individualized dietary management and the provision of appropriate meals to users.

[0060] "User information" refers to information that indicates the individual characteristics of a user, such as their religious beliefs, allergies, and dietary preferences.

[0061] "Dietary restriction information" refers to information indicating dietary restrictions based on the user's religious beliefs, allergies, etc.

[0062] An "information recording medium" refers to a database that stores data about ingredients and cooking methods, and allows for searching and retrieval of that data as needed.

[0063] An "artificial intelligence model" is a program that includes machine learning algorithms to generate cooking procedures that are optimal for the user's needs from input data.

[0064] "Cooking instructions" refer to information that shows the specific steps of cooking, generated based on acquired data and taking into account the user's dietary restrictions.

[0065] A "user device" is an electronic terminal used by the user to input information and receive, display, and customize the generated cooking instructions.

[0066] A "three-dimensional food processing device" is a device that processes food ingredients into specific shapes and cooking methods based on generated cooking procedure data to form a meal.

[0067] "Means of authentication" refers to a function that implements an authentication process to confirm that the information entered by the user is accurate and secure.

[0068] This invention provides a system for efficiently delivering personalized meals to users with diverse religious beliefs and allergy restrictions. The system includes a user terminal, a server, and a three-dimensional food processing device.

[0069] The user uses their terminal to input information such as their religious beliefs, allergies, and dietary preferences. The terminal encrypts and transmits this information to the server. Based on the received information, the server searches the information storage medium to obtain data on ingredients and cooking methods that meet the user's requirements.

[0070] The server uses a generative AI model to generate the optimal cooking procedure for the user from the acquired data. This generated cooking procedure is then sent back to the user's terminal for review. The user can review the new recipe and customize it as needed.

[0071] Finally, once the user approves the cooking procedure, the user terminal transmits the cooking procedure data to the 3D food processing device. The device processes the ingredients according to the specified shape and method to form the meal.

[0072] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its information storage medium for nut-free ingredients based on plant matter and generate a recipe and cooking instructions based on that. This process uses prompts to the generative AI model such as: "The user is vegetarian and has a nut allergy. Based on this information, the server should generate an appropriate recipe."

[0073] This system will enable users to efficiently obtain a safe and personalized dining experience that accommodates their individual dietary restrictions.

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

[0075] Step 1:

[0076] Users input information about their religious beliefs, allergies, and dietary preferences using their user terminal. This input can be efficiently processed using checkboxes and dropdown menus. The entered information is converted into a data structure such as JSON, encrypted, and sent to the server.

[0077] Step 2:

[0078] The server receives data sent from the terminal and performs authentication. The authentication process verifies the legitimacy of the data using authentication information such as a user ID and password. If authentication is successful, the server analyzes the received data, searches its information storage medium (database), and retrieves information on ingredients and cooking methods that meet the dietary restrictions. This search process uses SQL queries, among other methods.

[0079] Step 3:

[0080] The server generates cooking instructions using a generative AI model based on acquired ingredient and cooking method data. By providing specific cooking conditions to the AI ​​model via prompts, it outputs the optimal cooking instructions that suit the user's constraints and preferences. For example, a prompt such as "The user is a vegetarian and has a nut allergy. Generate appropriate cooking instructions based on this information" might be used. The generated cooking instructions are saved as data and used for subsequent processing.

[0081] Step 4:

[0082] The generated cooking procedure data is sent from the server to the user's terminal, which receives and displays it to the user. The user can check the recipe on the terminal and customize it as needed. For example, they can adjust the amount of seasonings or select different ingredients. User interaction is crucial in this step, and the interface is designed to be intuitive.

[0083] Step 5:

[0084] Once the user approves the recipe, the terminal transmits this finalized cooking procedure data to a three-dimensional food processing device. Based on the received data, the device processes and cooks the ingredients according to the specified shape and cooking method, forming the finished dish. Specifically, printing and heating technologies are used to provide a meal exactly as instructed by the user.

[0085] (Application Example 1)

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

[0087] In modern society, there is a need for a system that can rationally and flexibly provide meals tailored to individual needs, accommodating diverse dietary restrictions and preferences. Traditional food delivery services have problems such as limited options for users with specific religious beliefs or allergies, and the need for manual selection each time, which is time-consuming. Furthermore, it has been difficult to streamline daily meal management and provide a personalized dining experience that takes into account individual constraints.

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

[0089] In this invention, the server includes means for inputting user information and receiving constraint information, including religious beliefs and allergy restrictions; means for obtaining information on appropriate ingredients and cooking methods from a storage device based on the constraint information; and means for generating cooking procedures using a calculation means based on the obtained information. This makes it possible to automatically prepare safe and appropriate meals tailored to each user's constraints and preferences and deliver them to a specified location.

[0090] "User information" refers to individual data about users, including information such as their religious beliefs, allergy restrictions, and dietary preferences.

[0091] "Constraint information" refers to information that describes special conditions set by the user, such as religious beliefs, allergy restrictions, or food preferences.

[0092] "Ingredients" refer to raw materials used in cooking, selected according to the user's requirements.

[0093] A "cooking method" refers to the procedures and techniques used to prepare a dish by processing specific ingredients.

[0094] A "storage device" is equipment used to store information, and refers to computer databases, cloud storage, and other similar devices.

[0095] "Computational means" refers to methods and techniques for analyzing data and deriving specific results.

[0096] "Cooking procedure" refers to the specific steps and processes for cooking using ingredients.

[0097] A "generated dish" is a food product that has been completed by applying cooking methods based on the user's constraint information.

[0098] "Delivery method" refers to the means and methods for transporting cooked food to a location specified by the user.

[0099] The system for realizing this invention consists of a user terminal, a cloud server, a 3D food molding device, and a delivery method. The user uses a smartphone or other device to input user information, including their religious beliefs, allergy restrictions, and dietary preferences. The terminal transmits this information to the server.

[0100] The server operates in a cloud environment and searches its storage for data on appropriate ingredients and cooking methods based on constraint information received from the user. Using this data, the server generates cooking procedures that conform to the user's constraints through computational means. In this process, it is also possible to customize and suggest recipes using a generation AI model.

[0101] The cooking instructions are then displayed on the user's device for review and final customization. The confirmed cooking instructions are sent to a 3D food molding machine. This machine cooks the ingredients according to the instructions and produces the user-specified dish.

[0102] The prepared meals are delivered to the user's specified location via a delivery service. This system allows users to receive personalized meals tailored to their beliefs and preferences in a convenient and secure manner.

[0103] As a concrete example, let's consider a case where a user is vegetarian and has a nut allergy. This user inputs this information into a terminal, and the server generates a menu based on vegetables that does not contain nuts. This menu is then cooked using a 3D food molding machine and delivered to the user's home. At that time, the AI ​​model can be provided with a prompt message such as, "I am vegetarian and have a nut allergy, so please generate a safe and delicious meal recipe."

[0104] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0105] Step 1:

[0106] Users enter user information, including religious beliefs, allergy restrictions, and dietary preferences, using their smartphones or devices. This information is entered through the interface and received by the device system. This process formats the user's individual data, preparing it for transmission to the next step.

[0107] Step 2:

[0108] The terminal sends the received user information to the cloud server. The terminal sends that data to the server via a secure connection, and the server receives it. The information entered here specifically is restriction data regarding the user's dietary restrictions.

[0109] Step 3:

[0110] Based on the received constraint information, the server searches its storage for information on appropriate ingredients and cooking methods. The server queries the database and searches for items that match the user's constraints. The output is a list of ingredients and cooking methods that meet the conditions.

[0111] Step 4:

[0112] Based on the acquired information, the server uses computational means to generate cooking instructions that meet the user's requirements. This process utilizes a generative AI model, constructing a recipe using prompt messages as input. This step outputs customized cooking instruction data.

[0113] Step 5:

[0114] The server sends the generated cooking procedure data to the user's terminal and displays it on the terminal. This allows the user to review the generated cooking procedure and make final customizations as needed. If the user makes any changes, the procedure can be readjusted based on that information.

[0115] Step 6:

[0116] The confirmed cooking procedure is sent to the 3D food molding machine. Based on the procedure data, this machine cooks the ingredients as specified and produces the dish. The output here is the finished dish.

[0117] Step 7:

[0118] The prepared food is transported to the user's specified location via a delivery service. The food is delivered safely and quickly to its destination through the logistics system. In this step, the user can receive the food at home.

[0119] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0120] This invention relates to a system that provides personalized meal suggestions, taking into account the user's individual religious beliefs, allergy restrictions, and emotional state. The system comprises a user terminal, a server, an emotion engine, and further includes a 3D food molding device.

[0121] Users input information about their religious beliefs and allergies via the device. In addition, the device uses an emotion engine to recognize the user's current emotional state. This emotional information is used to consider the user's psychological impact on food. The recognized emotions and other user information are sent to the server.

[0122] Based on the information received, the server searches the database and extracts data on ingredients and cooking methods that suit the user's limitations and emotional state. Using this data, the server generates recipes using an algorithm. In this process, the user's emotional state is taken into consideration; for example, ingredients with relaxing effects may be suggested to a user who is highly stressed.

[0123] The generated recipe is sent to a terminal, where the user can review and customize it if necessary. Once the user approves the recipe, the terminal sends it to a 3D food molding device. This device then uses the data to mold the food into a specific shape and cooking method.

[0124] For example, if the use of a certain food is too sensitive, the information may be urgently needed, the system does not contain the recommended use, but the ingredients are effective. This is a recommended way to think about how to meet the demands of health and wellness, and to provide a more personalized and intentional drinking experience.

[0125] The following describes the processing flow.

[0126] Step 1:

[0127] Users log in to the application using their device and enter personal information such as religious beliefs, allergy information, and dietary preferences. The device collects this information.

[0128] Step 2:

[0129] The device uses a built-in emotion engine to recognize the user's current emotional state. This allows it to determine, for example, whether the user is stressed or relaxed.

[0130] Step 3:

[0131] The terminal sends the collected user information and recognized emotional state to the server. The server receives this information and begins user authentication and data processing.

[0132] Step 4:

[0133] The server searches the database based on the received information and selects ingredients and cooking methods. In doing so, it generates an ingredient list that takes into account religious restrictions, allergies, and emotional states.

[0134] Step 5:

[0135] The server uses a list of selected ingredients to generate recipes using an algorithm that meets the user's preferences and constraints. Depending on the user's emotional state, ingredients with refreshing effects, for example, may be selected.

[0136] Step 6:

[0137] The server sends the generated recipe data to the terminal, which then displays the contents to the user. The user can review the recipe and customize it as needed.

[0138] Step 7:

[0139] Once the user approves the recipe, the terminal sends the final recipe data to a 3D food molding device. Based on the received data, the device creates the dish with the specified shape and cooking method.

[0140] Step 8:

[0141] The terminal notifies the user when the meal is ready, and after receiving the meal, the user can provide feedback through the application. The server receives this feedback and uses it to make suggestions for the next time.

[0142] (Example 2)

[0143] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0144] Traditional meal suggestion systems could exclude certain ingredients based on users' religious beliefs or allergy restrictions, but they could not provide personalized suggestions that took into account the user's emotional state. Therefore, they failed to provide a dining experience that matched the user's emotions, resulting in lower satisfaction. Furthermore, the means of shaping meals to meet individual user needs were limited.

[0145] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0146] In this invention, the server includes means for inputting user information and receiving dietary restriction information including religious beliefs, allergy restrictions, and emotional state; means for obtaining data on appropriate ingredients and cooking methods from a data storage device based on the dietary restriction information and emotional state; and means for generating recipes using a generative model based on the obtained data. This makes it possible to provide personalized meal suggestions that meet the user's emotional state while accommodating their religious beliefs and allergy restrictions.

[0147] "User information" refers to individual data about a user, including religious beliefs, allergy restrictions, and emotional state.

[0148] "Religious beliefs" refer to a user's beliefs and values ​​related to ingredients or cooking methods that should be avoided based on a particular religion or faith.

[0149] "Allergy restrictions" refers to information about specific foods or ingredients that users should avoid consuming in order to protect their health.

[0150] "Emotional state" refers to the user's psychological and emotional state, including specific emotions such as stress and happiness.

[0151] "Dietary restriction information" refers to information about dietary restrictions based on religious beliefs, allergy restrictions, and emotional states.

[0152] A "data storage device" refers to a storage medium used to store data on ingredients and cooking methods, and to access it as needed.

[0153] A "generative model" is an algorithm and computational method for generating personalized recipes based on input data.

[0154] A "3D food molding machine" is a machine or device that molds food into a specific shape and cooking method based on electronic data.

[0155] This personalized meal suggestion system is implemented primarily using a user terminal, a server, an emotion analysis engine, and a 3D food molding device.

[0156] Users first input information about their religious beliefs and allergies into the device. This information includes data on specific foods and cooking methods to avoid. Furthermore, the device's built-in emotion analysis engine analyzes the user's emotional state from their voice and facial expressions. This emotional state is categorized into stress, happiness, etc., to improve the user experience.

[0157] The terminal sends this information to the server. Based on the received user information, the server accesses its data storage to obtain data on ingredients and cooking methods that suit the user's restrictions and emotional state. The obtained data is processed by a generative AI model to generate a recipe that matches the user's conditions. This generative AI model uses computational methods to suggest recipes adapted to various conditions.

[0158] The generated recipe is sent to the user's terminal and displayed visually to the user. The user can review the presented recipe and customize it as needed. Once the recipe is finalized, the terminal sends this information to a 3D food molding machine, which then creates the food in the specified shape and cooking method.

[0159] For example, if a user has a peanut allergy and is currently experiencing high levels of stress, the system can suggest a meal that excludes peanuts and uses herbs with relaxing properties. This allows the user to have a meal experience that addresses both their health and emotional needs.

[0160] An example of a prompt would be, "Please suggest a personalized meal recipe based on the user's allergy information and emotional state." The generative AI model would then generate a recipe based on this prompt. In this way, the entire system works together to provide the user with the optimal dining experience.

[0161] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0162] Step 1:

[0163] The user inputs information about their religious beliefs and allergies into the device. This input includes restrictions on specific foods and cooking methods. The device then uses built-in sensors and microphones to recognize the user's emotional state. Using voice tone analysis and facial recognition technology, the device classifies the user's emotions into categories such as "relaxed," "excited," and "stressed," and generates emotional information. The output at this point is a user profile that includes religious beliefs, allergy information, and emotional state.

[0164] Step 2:

[0165] The terminal sends the generated user profile to the server. The server receives this profile and accesses a database in its data storage. The server searches for ingredients and cooking methods that fit the user's restrictions and retrieves the corresponding dataset. This data processing outputs basic information about available ingredients and recipes that meet the user's constraints.

[0166] Step 3:

[0167] The server uses a generative AI model to generate personalized recipes based on the acquired dataset. The prompt is: "Create the optimal meal recipe considering the user's allergy information and emotional state." The generative AI model calculates a recipe optimized for the conditions and outputs it as recipe data. The generated recipe data includes specific ingredients, cooking methods, and combinations of emotional effects.

[0168] Step 4:

[0169] The server sends the generated recipe data to the user's terminal. The terminal visually displays the received data, allowing the user to review and customize it. At this stage, the user performs specific operations such as selecting and changing ingredients and cooking methods. The output is the customized recipe data that the user has finally approved.

[0170] Step 5:

[0171] The terminal transmits the final recipe data to a 3D food molding device. This device uses numerical control to form food according to the specified shape and cooking method. The food output by the operation is a meal that perfectly matches the user's needs. The device completes the food efficiently through an automated process.

[0172] (Application Example 2)

[0173] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0174] Conventional meal suggestion systems only consider the user's religious beliefs and allergy restrictions, lacking personalization based on emotional state. Furthermore, the process of actually preparing the suggested recipes is not sufficiently automated, leaving users with a burden.

[0175] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0176] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for obtaining data on appropriate ingredients and cooking methods from a database based on the dietary restriction information and the emotional state recognized by the emotion recognition module; and means for generating a recipe using an algorithm based on the obtained data and materializing the food using a robotic cooking device. This makes it possible to automatically suggest and cook a meal that is appropriate for the user's emotional state.

[0177] "Entering user information" refers to the process of providing the system with an individual user's religious beliefs, allergy information, and emotional state.

[0178] An "emotion recognition module" is a software or hardware component that analyzes and recognizes a user's current emotional state.

[0179] "Generating recipes using algorithms" refers to a computational method that determines appropriate ingredients and cooking methods based on data received from the user, and constructs cooking procedures tailored to individual requirements.

[0180] A "robot cooking device" is a mechanical device that automatically prepares and cooks a suggested dish based on a generated recipe.

[0181] "Dietary restriction information" refers to information about special requirements or restrictions regarding food that a user may have, such as religious beliefs or allergies.

[0182] To implement this invention, a specific hardware and software configuration is required. This system mainly consists of a user terminal, an emotion recognition module, a server, a database, an AI-based recipe generation algorithm, and a robotic cooking device.

[0183] The user terminal is responsible for receiving personal information from the user, such as religious beliefs, allergy information, and emotional state. This information is used to analyze the user's emotional state using an emotion recognition module. The acquired data is then sent to the server.

[0184] The server searches the database based on the received information to extract data on ingredients and cooking methods. A recipe generation algorithm based on a generative AI model is used to generate recipes tailored to each user's individual dietary restrictions and emotional state. This process requires, for example, database management software and the AI ​​algorithm integrated into it.

[0185] The generated recipe data is sent to the user's terminal for verification. It is also transferred to a robotic cooking device, where the food is cooked automatically. The robotic cooking device operates with mechanical hardware and embedded software, and performs cooking according to the generated instructions.

[0186] As a concrete example, when a user is feeling stressed, the system can suggest chamomile tea or a soothing soup, and a robotic cooking device can then prepare and serve the meal. An example of a prompt to give instructions to the system in this case would be: "Generate a recipe that is best suited to the user's emotional state and constraints. The user is currently vegetarian and wishes to relax."

[0187] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0188] Step 1:

[0189] The user terminal receives input from the user, including religious beliefs, allergy information, and emotional state. This input is processed, formatted, and then sent to the server.

[0190] Step 2:

[0191] The server uses an emotion recognition module to analyze the user's emotional state using the received user information as input. Based on this, it searches a database to obtain data on ingredients and cooking methods suitable for dietary restrictions and the user's emotional state as output. During this process, necessary data processing is performed to obtain the optimal results.

[0192] Step 3:

[0193] The server uses a generative AI model and a recipe generation algorithm to analyze acquired ingredient information and emotional states as input, and outputs an appropriate recipe. The generated recipe is then processed to provide cooking suggestions tailored to the user's individual requirements.

[0194] Step 4:

[0195] The server sends the generated recipe data as output to the user's terminal. This allows the user to review the suggested recipe and provide customization inputs as needed.

[0196] Step 5:

[0197] The server sends the finally approved recipe data as input to the robotic cooking device. The robotic cooking device uses this data to perform the specific cooking process and produces the finished dish as output.

[0198] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0199] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0200] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0201] [Second Embodiment]

[0202] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0203] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0204] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0205] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0206] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0207] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0208] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0209] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0210] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0211] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0212] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0213] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0214] This invention is a system for streamlining users' daily meal management and providing safe and appropriate meals. The system consists of a user terminal, a server, and a 3D food molding device. The user inputs necessary information, such as their religious beliefs, allergies, and dietary preferences, via the terminal. This information is sent to the server, which receives and authenticates it. Upon successful authentication, the server searches its database based on this information and retrieves data on suitable ingredients and cooking methods.

[0215] The server then generates a recipe tailored to the user's constraints and preferences based on the acquired data. The generated recipe is sent to the terminal, where the user can view and review it. At this point, the user can also customize the recipe. Finally, once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. Based on the transmitted data, the device creates the dish with the specified shape and cooking method.

[0216] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its database for plant-based, nut-free ingredients and generate a recipe based on them. The recipe will also detail the ingredients used and cooking procedures, allowing the user to enjoy their meal with peace of mind. This significantly simplifies daily dietary management and makes it possible to provide a personalized dining experience for each user.

[0217] The following describes the processing flow.

[0218] Step 1:

[0219] Users log in to the application using their device and enter personal information such as their religious beliefs, allergies, and dietary preferences.

[0220] Step 2:

[0221] The terminal sends the entered user information to the server and begins user account authentication. The server determines whether authentication was successful and returns an error message to the terminal if it fails.

[0222] Step 3:

[0223] The server searches the database based on authenticated user information to retrieve food data that matches the user's religious beliefs and allergies. This process creates a list of candidate foods that meet the user's restrictions.

[0224] Step 4:

[0225] The server uses the acquired ingredient data to generate the optimal recipe for the user through an algorithm. This recipe generation process also takes into account the balance of nutrients and flavor.

[0226] Step 5:

[0227] The server sends the generated recipe data to the terminal, allowing the user to review the recipe. The terminal then displays the recipe to the user and provides customization options as needed.

[0228] Step 6:

[0229] Once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. The device then begins cooking the food according to the specified shape and cooking method based on this data.

[0230] Step 7:

[0231] The terminal notifies the user when the meal is ready, and after the user receives the meal, they can enter feedback through the application. The server collects this feedback and uses it as data to improve future recipe suggestions.

[0232] (Example 1)

[0233] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0234] Providing safe and personalized meals to users with diverse religious beliefs and allergy restrictions is challenging. Traditional methods involve a significant amount of manual work to meet each user's individual needs, which is time-consuming and labor-intensive.

[0235] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0236] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for searching an information recording medium and obtaining data on appropriate ingredients and cooking methods; and means for generating cooking procedures using an artificial intelligence model based on the obtained data. This enables efficient individualized dietary management and the provision of appropriate meals to users.

[0237] "User information" refers to information that indicates the individual characteristics of a user, such as their religious beliefs, allergies, and dietary preferences.

[0238] "Dietary restriction information" refers to information indicating dietary restrictions based on the user's religious beliefs, allergies, etc.

[0239] An "information recording medium" refers to a database that stores data about ingredients and cooking methods, and allows for searching and retrieval of that data as needed.

[0240] An "artificial intelligence model" is a program that includes machine learning algorithms to generate cooking procedures that are optimal for the user's needs from input data.

[0241] "Cooking instructions" refer to information that shows the specific steps of cooking, generated based on acquired data and taking into account the user's dietary restrictions.

[0242] A "user device" is an electronic terminal used by the user to input information and receive, display, and customize the generated cooking instructions.

[0243] A "three-dimensional food processing device" is a device that processes food ingredients into specific shapes and cooking methods based on generated cooking procedure data to form a meal.

[0244] "Means of authentication" refers to a function that implements an authentication process to confirm that the information entered by the user is accurate and secure.

[0245] This invention provides a system for efficiently delivering personalized meals to users with diverse religious beliefs and allergy restrictions. The system includes a user terminal, a server, and a three-dimensional food processing device.

[0246] The user uses their terminal to input information such as their religious beliefs, allergies, and dietary preferences. The terminal encrypts and transmits this information to the server. Based on the received information, the server searches the information storage medium to obtain data on ingredients and cooking methods that meet the user's requirements.

[0247] The server uses a generative AI model to generate the optimal cooking procedure for the user from the acquired data. This generated cooking procedure is then sent back to the user's terminal for review. The user can review the new recipe and customize it as needed.

[0248] Finally, once the user approves the cooking procedure, the user terminal transmits the cooking procedure data to the 3D food processing device. The device processes the ingredients according to the specified shape and method to form the meal.

[0249] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its information storage medium for nut-free ingredients based on plant matter and generate a recipe and cooking instructions based on that. This process uses prompts to the generative AI model such as: "The user is vegetarian and has a nut allergy. Based on this information, the server should generate an appropriate recipe."

[0250] This system will enable users to efficiently obtain a safe and personalized dining experience that accommodates their individual dietary restrictions.

[0251] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0252] Step 1:

[0253] Users input information about their religious beliefs, allergies, and dietary preferences using their user terminal. This input can be efficiently processed using checkboxes and dropdown menus. The entered information is converted into a data structure such as JSON, encrypted, and sent to the server.

[0254] Step 2:

[0255] The server receives data sent from the terminal and performs authentication. The authentication process verifies the legitimacy of the data using authentication information such as a user ID and password. If authentication is successful, the server analyzes the received data, searches its information storage medium (database), and retrieves information on ingredients and cooking methods that meet the dietary restrictions. This search process uses SQL queries, among other methods.

[0256] Step 3:

[0257] The server generates cooking instructions using a generative AI model based on acquired ingredient and cooking method data. By providing specific cooking conditions to the AI ​​model via prompts, it outputs the optimal cooking instructions that suit the user's constraints and preferences. For example, a prompt such as "The user is a vegetarian and has a nut allergy. Generate appropriate cooking instructions based on this information" might be used. The generated cooking instructions are saved as data and used for subsequent processing.

[0258] Step 4:

[0259] The generated cooking procedure data is sent from the server to the user's terminal, which receives and displays it to the user. The user can check the recipe on the terminal and customize it as needed. For example, they can adjust the amount of seasonings or select different ingredients. User interaction is crucial in this step, and the interface is designed to be intuitive.

[0260] Step 5:

[0261] Once the user approves the recipe, the terminal transmits this finalized cooking procedure data to a three-dimensional food processing device. Based on the received data, the device processes and cooks the ingredients according to the specified shape and cooking method, forming the finished dish. Specifically, printing and heating technologies are used to provide a meal exactly as instructed by the user.

[0262] (Application Example 1)

[0263] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0264] In modern society, there is a need for a system that can rationally and flexibly provide meals tailored to individual needs, accommodating diverse dietary restrictions and preferences. Traditional food delivery services have problems such as limited options for users with specific religious beliefs or allergies, and the need for manual selection each time, which is time-consuming. Furthermore, it has been difficult to streamline daily meal management and provide a personalized dining experience that takes into account individual constraints.

[0265] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0266] In this invention, the server includes means for inputting user information and receiving constraint information, including religious beliefs and allergy restrictions; means for obtaining information on appropriate ingredients and cooking methods from a storage device based on the constraint information; and means for generating cooking procedures using a calculation means based on the obtained information. This makes it possible to automatically prepare safe and appropriate meals tailored to each user's constraints and preferences and deliver them to a specified location.

[0267] "User information" refers to individual data about users, including information such as their religious beliefs, allergy restrictions, and dietary preferences.

[0268] "Constraint information" refers to information that describes special conditions set by the user, such as religious beliefs, allergy restrictions, or food preferences.

[0269] "Ingredients" refer to raw materials used in cooking, selected according to the user's requirements.

[0270] A "cooking method" refers to the procedures and techniques used to prepare a dish by processing specific ingredients.

[0271] A "storage device" is equipment used to store information, and refers to computer databases, cloud storage, and other similar devices.

[0272] "Computational means" refers to methods and techniques for analyzing data and deriving specific results.

[0273] "Cooking procedure" refers to the specific steps and processes for cooking using ingredients.

[0274] A "generated dish" is a food product that has been completed by applying cooking methods based on the user's constraint information.

[0275] "Delivery method" refers to the means and methods for transporting cooked food to a location specified by the user.

[0276] The system for realizing this invention consists of a user terminal, a cloud server, a 3D food molding device, and a delivery method. The user uses a smartphone or other device to input user information, including their religious beliefs, allergy restrictions, and dietary preferences. The terminal transmits this information to the server.

[0277] The server operates in a cloud environment and searches its storage for data on appropriate ingredients and cooking methods based on constraint information received from the user. Using this data, the server generates cooking procedures that conform to the user's constraints through computational means. In this process, it is also possible to customize and suggest recipes using a generation AI model.

[0278] The cooking instructions are then displayed on the user's device for review and final customization. The confirmed cooking instructions are sent to a 3D food molding machine. This machine cooks the ingredients according to the instructions and produces the user-specified dish.

[0279] The prepared meals are delivered to the user's specified location via a delivery service. This system allows users to receive personalized meals tailored to their beliefs and preferences in a convenient and secure manner.

[0280] As a concrete example, let's consider a case where a user is vegetarian and has a nut allergy. This user inputs this information into a terminal, and the server generates a menu based on vegetables that does not contain nuts. This menu is then cooked using a 3D food molding machine and delivered to the user's home. At that time, the AI ​​model can be provided with a prompt message such as, "I am vegetarian and have a nut allergy, so please generate a safe and delicious meal recipe."

[0281] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0282] Step 1:

[0283] The user uses a smartphone or a terminal to input user information including religious beliefs, allergy restrictions, and dietary preferences. This information is input through an interface and received by the terminal system. Through this process, the user's individual data is formatted and arranged in a form that can be transmitted to the next step.

[0284] Step 2:

[0285] The terminal transmits the received user information to the cloud server. The terminal transmits the data to the server via a secure connection, and the server receives it. The information input here is specifically the constraint data regarding the user's dietary restrictions.

[0286] Step 3:

[0287] Based on the received constraint information, the server searches the storage device for information on appropriate food ingredients and cooking methods. The server queries the database and performs a process of searching for those that match the user's constraints. The output is a list of food ingredients and cooking methods that meet the conditions.

[0288] Step 4:

[0289] Based on the acquired information, the server uses computational means to generate cooking procedures that meet the user's conditions. In this procedure, a generation AI model is utilized, and a recipe for cooking is constructed with the prompt text as input. Through this step, customized cooking procedure data is output.

[0290] Step 5:

[0291] The server transmits the generated cooking procedure data to the user terminal and displays it on the terminal. As a result, the user can check the generated cooking procedure and make final customization if necessary. If there are any changes by the user, the procedure can be adjusted again based on that information.

[0292] Step 6:

[0293] The confirmed cooking procedure is sent to the 3D food molding machine. Based on the procedure data, this machine cooks the ingredients as specified and produces the dish. The output here is the finished dish.

[0294] Step 7:

[0295] The prepared food is transported to the user's specified location via a delivery service. The food is delivered safely and quickly to its destination through the logistics system. In this step, the user can receive the food at home.

[0296] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0297] This invention relates to a system that provides personalized meal suggestions, taking into account the user's individual religious beliefs, allergy restrictions, and emotional state. The system comprises a user terminal, a server, an emotion engine, and further includes a 3D food molding device.

[0298] Users input information about their religious beliefs and allergies via the device. In addition, the device uses an emotion engine to recognize the user's current emotional state. This emotional information is used to consider the user's psychological impact on food. The recognized emotions and other user information are sent to the server.

[0299] Based on the information received, the server searches the database and extracts data on ingredients and cooking methods that suit the user's limitations and emotional state. Using this data, the server generates recipes using an algorithm. In this process, the user's emotional state is taken into consideration; for example, ingredients with relaxing effects may be suggested to a user who is highly stressed.

[0300] The generated recipe is sent to the terminal, where the user can view it and customize it if necessary. Once the user approves the recipe, the terminal sends it to the 3D food shaping device. Based on the data, this device shapes the food into a specific form and cooking method.

[0301] For example, if the user has allergies to certain foods and is in urgent need of emotional relief, the system will recommend ingredients that are allergen-free and have a soothing effect. This recommendation takes into account the user's health and emotional needs, aiming to provide a more personalized and satisfactory dining experience.

[0302] The following describes the processing flow.

[0303] Step 1:

[0304] The user logs in to the application using the terminal and enters personal information such as religious beliefs, allergy information, and dietary preferences. The terminal collects this information.

[0305] Step 2:

[0306] The terminal uses the built-in emotion engine to recognize the user's current emotional state. This determines, for example, whether the user is feeling stressed or relaxed.

[0307] Step 3:

[0308] The terminal sends the collected user information and recognized emotional state to the server. The server receives this and starts the user authentication and data processing.

[0309] Step 4:

[0310] The server searches the database based on the received information and selects ingredients and cooking methods. At this time, a list of ingredients considering religious restrictions, allergies, and emotional state is generated.

[0311] Step 5:

[0312] The server uses a list of selected ingredients to generate recipes using an algorithm that meets the user's preferences and constraints. Depending on the user's emotional state, ingredients with refreshing effects, for example, may be selected.

[0313] Step 6:

[0314] The server sends the generated recipe data to the terminal, which then displays the contents to the user. The user can review the recipe and customize it as needed.

[0315] Step 7:

[0316] Once the user approves the recipe, the terminal sends the final recipe data to a 3D food molding device. Based on the received data, the device creates the dish with the specified shape and cooking method.

[0317] Step 8:

[0318] The terminal notifies the user when the meal is ready, and after receiving the meal, the user can provide feedback through the application. The server receives this feedback and uses it to make suggestions for the next time.

[0319] (Example 2)

[0320] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0321] Traditional meal suggestion systems could exclude certain ingredients based on users' religious beliefs or allergy restrictions, but they could not provide personalized suggestions that took into account the user's emotional state. Therefore, they failed to provide a dining experience that matched the user's emotions, resulting in lower satisfaction. Furthermore, the means of shaping meals to meet individual user needs were limited.

[0322] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0323] In this invention, the server includes means for inputting user information and receiving dietary restriction information including religious beliefs, allergy restrictions, and emotional state; means for obtaining data on appropriate ingredients and cooking methods from a data storage device based on the dietary restriction information and emotional state; and means for generating recipes using a generative model based on the obtained data. This makes it possible to provide personalized meal suggestions that meet the user's emotional state while accommodating their religious beliefs and allergy restrictions.

[0324] "User information" refers to individual data about a user, including religious beliefs, allergy restrictions, and emotional state.

[0325] "Religious beliefs" refer to a user's beliefs and values ​​related to ingredients or cooking methods that should be avoided based on a particular religion or faith.

[0326] "Allergy restrictions" refers to information about specific foods or ingredients that users should avoid consuming in order to protect their health.

[0327] "Emotional state" refers to the user's psychological and emotional state, including specific emotions such as stress and happiness.

[0328] "Dietary restriction information" refers to information about dietary restrictions based on religious beliefs, allergy restrictions, and emotional states.

[0329] A "data storage device" refers to a storage medium used to store data on ingredients and cooking methods, and to access it as needed.

[0330] A "generative model" is an algorithm and computational method for generating personalized recipes based on input data.

[0331] A "3D food molding machine" is a machine or device that molds food into a specific shape and cooking method based on electronic data.

[0332] This personalized meal suggestion system is implemented primarily using a user terminal, a server, an emotion analysis engine, and a 3D food molding device.

[0333] Users first input information about their religious beliefs and allergies into the device. This information includes data on specific foods and cooking methods to avoid. Furthermore, the device's built-in emotion analysis engine analyzes the user's emotional state from their voice and facial expressions. This emotional state is categorized into stress, happiness, etc., to improve the user experience.

[0334] The terminal sends this information to the server. Based on the received user information, the server accesses its data storage to obtain data on ingredients and cooking methods that suit the user's restrictions and emotional state. The obtained data is processed by a generative AI model to generate a recipe that matches the user's conditions. This generative AI model uses computational methods to suggest recipes adapted to various conditions.

[0335] The generated recipe is sent to the user's terminal and displayed visually to the user. The user can review the presented recipe and customize it as needed. Once the recipe is finalized, the terminal sends this information to a 3D food molding machine, which then creates the food in the specified shape and cooking method.

[0336] For example, if a user has a peanut allergy and is currently experiencing high levels of stress, the system can suggest a meal that excludes peanuts and uses herbs with relaxing properties. This allows the user to have a meal experience that addresses both their health and emotional needs.

[0337] An example of a prompt would be, "Please suggest a personalized meal recipe based on the user's allergy information and emotional state." The generative AI model would then generate a recipe based on this prompt. In this way, the entire system works together to provide the user with the optimal dining experience.

[0338] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0339] Step 1:

[0340] The user inputs information about their religious beliefs and allergies into the device. This input includes restrictions on specific foods and cooking methods. The device then uses built-in sensors and microphones to recognize the user's emotional state. Using voice tone analysis and facial recognition technology, the device classifies the user's emotions into categories such as "relaxed," "excited," and "stressed," and generates emotional information. The output at this point is a user profile that includes religious beliefs, allergy information, and emotional state.

[0341] Step 2:

[0342] The terminal sends the generated user profile to the server. The server receives this profile and accesses a database in its data storage. The server searches for ingredients and cooking methods that fit the user's restrictions and retrieves the corresponding dataset. This data processing outputs basic information about available ingredients and recipes that meet the user's constraints.

[0343] Step 3:

[0344] The server uses a generative AI model to generate personalized recipes based on the acquired dataset. The prompt is: "Create the optimal meal recipe considering the user's allergy information and emotional state." The generative AI model calculates a recipe optimized for the conditions and outputs it as recipe data. The generated recipe data includes specific ingredients, cooking methods, and combinations of emotional effects.

[0345] Step 4:

[0346] The server sends the generated recipe data to the user's terminal. The terminal visually displays the received data, allowing the user to review and customize it. At this stage, the user performs specific operations such as selecting and changing ingredients and cooking methods. The output is the customized recipe data that the user has finally approved.

[0347] Step 5:

[0348] The terminal transmits the final recipe data to a 3D food molding device. This device uses numerical control to form food according to the specified shape and cooking method. The food output by the operation is a meal that perfectly matches the user's needs. The device completes the food efficiently through an automated process.

[0349] (Application Example 2)

[0350] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0351] Conventional meal suggestion systems only consider the user's religious beliefs and allergy restrictions, lacking personalization based on emotional state. Furthermore, the process of actually preparing the suggested recipes is not sufficiently automated, leaving users with a burden.

[0352] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0353] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for obtaining data on appropriate ingredients and cooking methods from a database based on the dietary restriction information and the emotional state recognized by the emotion recognition module; and means for generating a recipe using an algorithm based on the obtained data and materializing the food using a robotic cooking device. This makes it possible to automatically suggest and cook a meal that is appropriate for the user's emotional state.

[0354] "Entering user information" refers to the process of providing the system with an individual user's religious beliefs, allergy information, and emotional state.

[0355] An "emotion recognition module" is a software or hardware component that analyzes and recognizes a user's current emotional state.

[0356] "Generating recipes using algorithms" refers to a computational method that determines appropriate ingredients and cooking methods based on data received from the user, and constructs cooking procedures tailored to individual requirements.

[0357] A "robot cooking device" is a mechanical device that automatically prepares and cooks a suggested dish based on a generated recipe.

[0358] "Dietary restriction information" refers to information about special requirements or restrictions regarding food that a user may have, such as religious beliefs or allergies.

[0359] To implement this invention, a specific hardware and software configuration is required. This system mainly consists of a user terminal, an emotion recognition module, a server, a database, an AI-based recipe generation algorithm, and a robotic cooking device.

[0360] The user terminal is responsible for receiving personal information from the user, such as religious beliefs, allergy information, and emotional state. This information is used to analyze the user's emotional state using an emotion recognition module. The acquired data is then sent to the server.

[0361] The server searches the database based on the received information to extract data on ingredients and cooking methods. A recipe generation algorithm based on a generative AI model is used to generate recipes tailored to each user's individual dietary restrictions and emotional state. This process requires, for example, database management software and the AI ​​algorithm integrated into it.

[0362] The generated recipe data is sent to the user's terminal for verification. It is also transferred to a robotic cooking device, where the food is cooked automatically. The robotic cooking device operates with mechanical hardware and embedded software, and performs cooking according to the generated instructions.

[0363] As a concrete example, when a user is feeling stressed, the system can suggest chamomile tea or a soothing soup, and a robotic cooking device can then prepare and serve the meal. An example of a prompt to give instructions to the system in this case would be: "Generate a recipe that is best suited to the user's emotional state and constraints. The user is currently vegetarian and wishes to relax."

[0364] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0365] Step 1:

[0366] The user terminal receives input from the user, including religious beliefs, allergy information, and emotional state. This input is processed, formatted, and then sent to the server.

[0367] Step 2:

[0368] The server uses an emotion recognition module to analyze the user's emotional state using the received user information as input. Based on this, it searches a database to obtain data on ingredients and cooking methods suitable for dietary restrictions and the user's emotional state as output. During this process, necessary data processing is performed to obtain the optimal results.

[0369] Step 3:

[0370] The server uses a generative AI model and a recipe generation algorithm to analyze acquired ingredient information and emotional states as input, and outputs an appropriate recipe. The generated recipe is then processed to provide cooking suggestions tailored to the user's individual requirements.

[0371] Step 4:

[0372] The server sends the generated recipe data as output to the user's terminal. This allows the user to review the suggested recipe and provide customization inputs as needed.

[0373] Step 5:

[0374] The server sends the finally approved recipe data as input to the robotic cooking device. The robotic cooking device uses this data to perform the specific cooking process and produces the finished dish as output.

[0375] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0376] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0377] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0378] [Third Embodiment]

[0379] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0380] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0381] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0382] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0383] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0384] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0385] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0386] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0387] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0388] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0389] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0390] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0391] This invention is a system for streamlining users' daily meal management and providing safe and appropriate meals. The system consists of a user terminal, a server, and a 3D food molding device. The user inputs necessary information, such as their religious beliefs, allergies, and dietary preferences, via the terminal. This information is sent to the server, which receives and authenticates it. Upon successful authentication, the server searches its database based on this information and retrieves data on suitable ingredients and cooking methods.

[0392] The server then generates a recipe tailored to the user's constraints and preferences based on the acquired data. The generated recipe is sent to the terminal, where the user can view and review it. At this point, the user can also customize the recipe. Finally, once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. Based on the transmitted data, the device creates the dish with the specified shape and cooking method.

[0393] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its database for plant-based, nut-free ingredients and generate a recipe based on them. The recipe will also detail the ingredients used and cooking procedures, allowing the user to enjoy their meal with peace of mind. This significantly simplifies daily dietary management and makes it possible to provide a personalized dining experience for each user.

[0394] The following describes the processing flow.

[0395] Step 1:

[0396] Users log in to the application using their device and enter personal information such as their religious beliefs, allergies, and dietary preferences.

[0397] Step 2:

[0398] The terminal sends the entered user information to the server and begins user account authentication. The server determines whether authentication was successful and returns an error message to the terminal if it fails.

[0399] Step 3:

[0400] The server searches the database based on authenticated user information to retrieve food data that matches the user's religious beliefs and allergies. This process creates a list of candidate foods that meet the user's restrictions.

[0401] Step 4:

[0402] The server uses the acquired ingredient data to generate the optimal recipe for the user through an algorithm. This recipe generation process also takes into account the balance of nutrients and flavor.

[0403] Step 5:

[0404] The server sends the generated recipe data to the terminal, allowing the user to review the recipe. The terminal then displays the recipe to the user and provides customization options as needed.

[0405] Step 6:

[0406] Once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. The device then begins cooking the food according to the specified shape and cooking method based on this data.

[0407] Step 7:

[0408] The terminal notifies the user when the meal is ready, and after the user receives the meal, they can enter feedback through the application. The server collects this feedback and uses it as data to improve future recipe suggestions.

[0409] (Example 1)

[0410] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0411] Providing safe and personalized meals to users with diverse religious beliefs and allergy restrictions is challenging. Traditional methods involve a significant amount of manual work to meet each user's individual needs, which is time-consuming and labor-intensive.

[0412] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0413] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for searching an information recording medium and obtaining data on appropriate ingredients and cooking methods; and means for generating cooking procedures using an artificial intelligence model based on the obtained data. This enables efficient individualized dietary management and the provision of appropriate meals to users.

[0414] "User information" refers to information that indicates the individual characteristics of a user, such as their religious beliefs, allergies, and dietary preferences.

[0415] "Dietary restriction information" refers to information indicating dietary restrictions based on the user's religious beliefs, allergies, etc.

[0416] An "information recording medium" refers to a database that stores data about ingredients and cooking methods, and allows for searching and retrieval of that data as needed.

[0417] An "artificial intelligence model" is a program that includes machine learning algorithms to generate cooking procedures that are optimal for the user's needs from input data.

[0418] "Cooking instructions" refer to information that shows the specific steps of cooking, generated based on acquired data and taking into account the user's dietary restrictions.

[0419] A "user device" is an electronic terminal used by the user to input information and receive, display, and customize the generated cooking instructions.

[0420] A "three-dimensional food processing device" is a device that processes food ingredients into specific shapes and cooking methods based on generated cooking procedure data to form a meal.

[0421] "Means of authentication" refers to a function that implements an authentication process to confirm that the information entered by the user is accurate and secure.

[0422] This invention provides a system for efficiently delivering personalized meals to users with diverse religious beliefs and allergy restrictions. The system includes a user terminal, a server, and a three-dimensional food processing device.

[0423] The user uses their terminal to input information such as their religious beliefs, allergies, and dietary preferences. The terminal encrypts and transmits this information to the server. Based on the received information, the server searches the information storage medium to obtain data on ingredients and cooking methods that meet the user's requirements.

[0424] The server uses a generative AI model to generate the optimal cooking procedure for the user from the acquired data. This generated cooking procedure is then sent back to the user's terminal for review. The user can review the new recipe and customize it as needed.

[0425] Finally, once the user approves the cooking procedure, the user terminal transmits the cooking procedure data to the 3D food processing device. The device processes the ingredients according to the specified shape and method to form the meal.

[0426] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its information storage medium for nut-free ingredients based on plant matter and generate a recipe and cooking instructions based on that. This process uses prompts to the generative AI model such as: "The user is vegetarian and has a nut allergy. Based on this information, the server should generate an appropriate recipe."

[0427] This system will enable users to efficiently obtain a safe and personalized dining experience that accommodates their individual dietary restrictions.

[0428] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0429] Step 1:

[0430] Users input information about their religious beliefs, allergies, and dietary preferences using their user terminal. This input can be efficiently processed using checkboxes and dropdown menus. The entered information is converted into a data structure such as JSON, encrypted, and sent to the server.

[0431] Step 2:

[0432] The server receives data sent from the terminal and performs authentication. The authentication process verifies the legitimacy of the data using authentication information such as a user ID and password. If authentication is successful, the server analyzes the received data, searches its information storage medium (database), and retrieves information on ingredients and cooking methods that meet the dietary restrictions. This search process uses SQL queries, among other methods.

[0433] Step 3:

[0434] The server generates cooking instructions using a generative AI model based on acquired ingredient and cooking method data. By providing specific cooking conditions to the AI ​​model via prompts, it outputs the optimal cooking instructions that suit the user's constraints and preferences. For example, a prompt such as "The user is a vegetarian and has a nut allergy. Generate appropriate cooking instructions based on this information" might be used. The generated cooking instructions are saved as data and used for subsequent processing.

[0435] Step 4:

[0436] The generated cooking procedure data is sent from the server to the user's terminal, which receives and displays it to the user. The user can check the recipe on the terminal and customize it as needed. For example, they can adjust the amount of seasonings or select different ingredients. User interaction is crucial in this step, and the interface is designed to be intuitive.

[0437] Step 5:

[0438] Once the user approves the recipe, the terminal transmits this finalized cooking procedure data to a three-dimensional food processing device. Based on the received data, the device processes and cooks the ingredients according to the specified shape and cooking method, forming the finished dish. Specifically, printing and heating technologies are used to provide a meal exactly as instructed by the user.

[0439] (Application Example 1)

[0440] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0441] In modern society, there is a need for a system that can rationally and flexibly provide meals tailored to individual needs, accommodating diverse dietary restrictions and preferences. Traditional food delivery services have problems such as limited options for users with specific religious beliefs or allergies, and the need for manual selection each time, which is time-consuming. Furthermore, it has been difficult to streamline daily meal management and provide a personalized dining experience that takes into account individual constraints.

[0442] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0443] In this invention, the server includes means for inputting user information and receiving constraint information, including religious beliefs and allergy restrictions; means for obtaining information on appropriate ingredients and cooking methods from a storage device based on the constraint information; and means for generating cooking procedures using a calculation means based on the obtained information. This makes it possible to automatically prepare safe and appropriate meals tailored to each user's constraints and preferences and deliver them to a specified location.

[0444] "User information" refers to individual data about users, including information such as their religious beliefs, allergy restrictions, and dietary preferences.

[0445] "Constraint information" refers to information that describes special conditions set by the user, such as religious beliefs, allergy restrictions, or food preferences.

[0446] "Ingredients" refer to raw materials used in cooking, selected according to the user's requirements.

[0447] A "cooking method" refers to the procedures and techniques used to prepare a dish by processing specific ingredients.

[0448] A "storage device" is equipment used to store information, and refers to computer databases, cloud storage, and other similar devices.

[0449] "Computational means" refers to methods and techniques for analyzing data and deriving specific results.

[0450] "Cooking procedure" refers to the specific steps and processes for cooking using ingredients.

[0451] A "generated dish" is a food product that has been completed by applying cooking methods based on the user's constraint information.

[0452] "Delivery method" refers to the means and methods for transporting cooked food to a location specified by the user.

[0453] The system for realizing this invention consists of a user terminal, a cloud server, a 3D food molding device, and a delivery method. The user uses a smartphone or other device to input user information, including their religious beliefs, allergy restrictions, and dietary preferences. The terminal transmits this information to the server.

[0454] The server operates in a cloud environment and searches its storage for data on appropriate ingredients and cooking methods based on constraint information received from the user. Using this data, the server generates cooking procedures that conform to the user's constraints through computational means. In this process, it is also possible to customize and suggest recipes using a generation AI model.

[0455] The cooking instructions are then displayed on the user's device for review and final customization. The confirmed cooking instructions are sent to a 3D food molding machine. This machine cooks the ingredients according to the instructions and produces the user-specified dish.

[0456] The prepared meals are delivered to the user's specified location via a delivery service. This system allows users to receive personalized meals tailored to their beliefs and preferences in a convenient and secure manner.

[0457] As a concrete example, let's consider a case where a user is vegetarian and has a nut allergy. This user inputs this information into a terminal, and the server generates a menu based on vegetables that does not contain nuts. This menu is then cooked using a 3D food molding machine and delivered to the user's home. At that time, the AI ​​model can be provided with a prompt message such as, "I am vegetarian and have a nut allergy, so please generate a safe and delicious meal recipe."

[0458] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0459] Step 1:

[0460] Users enter user information, including religious beliefs, allergy restrictions, and dietary preferences, using their smartphones or devices. This information is entered through the interface and received by the device system. This process formats the user's individual data, preparing it for transmission to the next step.

[0461] Step 2:

[0462] The terminal sends the received user information to the cloud server. The terminal sends that data to the server via a secure connection, and the server receives it. The information entered here specifically is restriction data regarding the user's dietary restrictions.

[0463] Step 3:

[0464] Based on the received constraint information, the server searches its storage for information on appropriate ingredients and cooking methods. The server queries the database and searches for items that match the user's constraints. The output is a list of ingredients and cooking methods that meet the conditions.

[0465] Step 4:

[0466] Based on the acquired information, the server uses computational means to generate cooking instructions that meet the user's requirements. This process utilizes a generative AI model, constructing a recipe using prompt messages as input. This step outputs customized cooking instruction data.

[0467] Step 5:

[0468] The server sends the generated cooking procedure data to the user's terminal and displays it on the terminal. This allows the user to review the generated cooking procedure and make final customizations as needed. If the user makes any changes, the procedure can be readjusted based on that information.

[0469] Step 6:

[0470] The confirmed cooking procedure is sent to the 3D food molding machine. Based on the procedure data, this machine cooks the ingredients as specified and produces the dish. The output here is the finished dish.

[0471] Step 7:

[0472] The prepared food is transported to the user's specified location via a delivery service. The food is delivered safely and quickly to its destination through the logistics system. In this step, the user can receive the food at home.

[0473] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0474] This invention relates to a system that provides personalized meal suggestions, taking into account the user's individual religious beliefs, allergy restrictions, and emotional state. The system comprises a user terminal, a server, an emotion engine, and further includes a 3D food molding device.

[0475] Users input information about their religious beliefs and allergies via the device. In addition, the device uses an emotion engine to recognize the user's current emotional state. This emotional information is used to consider the user's psychological impact on food. The recognized emotions and other user information are sent to the server.

[0476] Based on the information received, the server searches the database and extracts data on ingredients and cooking methods that suit the user's limitations and emotional state. Using this data, the server generates recipes using an algorithm. In this process, the user's emotional state is taken into consideration; for example, ingredients with relaxing effects may be suggested to a user who is highly stressed.

[0477] The generated recipe is sent to a terminal, where the user can review and customize it if necessary. Once the user approves the recipe, the terminal sends it to a 3D food molding device. This device then uses the data to mold the food into a specific shape and cooking method.

[0478] For example, if the use of a certain food is too sensitive, the information may be urgently needed, the system does not contain the recommended use, but the ingredients are effective. This is a recommended way to think about how to meet the demands of health and wellness, and to provide a more personalized and intentional drinking experience.

[0479] The following describes the processing flow.

[0480] Step 1:

[0481] Users log in to the application using their device and enter personal information such as religious beliefs, allergy information, and dietary preferences. The device collects this information.

[0482] Step 2:

[0483] The device uses a built-in emotion engine to recognize the user's current emotional state. This allows it to determine, for example, whether the user is stressed or relaxed.

[0484] Step 3:

[0485] The terminal sends the collected user information and recognized emotional state to the server. The server receives this information and begins user authentication and data processing.

[0486] Step 4:

[0487] The server searches the database based on the received information and selects ingredients and cooking methods. In doing so, it generates an ingredient list that takes into account religious restrictions, allergies, and emotional states.

[0488] Step 5:

[0489] The server uses a list of selected ingredients to generate recipes using an algorithm that meets the user's preferences and constraints. Depending on the user's emotional state, ingredients with refreshing effects, for example, may be selected.

[0490] Step 6:

[0491] The server sends the generated recipe data to the terminal, which then displays the contents to the user. The user can review the recipe and customize it as needed.

[0492] Step 7:

[0493] Once the user approves the recipe, the terminal sends the final recipe data to a 3D food molding device. Based on the received data, the device creates the dish with the specified shape and cooking method.

[0494] Step 8:

[0495] The terminal notifies the user when the meal is ready, and after receiving the meal, the user can provide feedback through the application. The server receives this feedback and uses it to make suggestions for the next time.

[0496] (Example 2)

[0497] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0498] Traditional meal suggestion systems could exclude certain ingredients based on users' religious beliefs or allergy restrictions, but they could not provide personalized suggestions that took into account the user's emotional state. Therefore, they failed to provide a dining experience that matched the user's emotions, resulting in lower satisfaction. Furthermore, the means of shaping meals to meet individual user needs were limited.

[0499] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0500] In this invention, the server includes means for inputting user information and receiving dietary restriction information including religious beliefs, allergy restrictions, and emotional state; means for obtaining data on appropriate ingredients and cooking methods from a data storage device based on the dietary restriction information and emotional state; and means for generating recipes using a generative model based on the obtained data. This makes it possible to provide personalized meal suggestions that meet the user's emotional state while accommodating their religious beliefs and allergy restrictions.

[0501] "User information" refers to individual data about a user, including religious beliefs, allergy restrictions, and emotional state.

[0502] "Religious beliefs" refer to a user's beliefs and values ​​related to ingredients or cooking methods that should be avoided based on a particular religion or faith.

[0503] "Allergy restrictions" refers to information about specific foods or ingredients that users should avoid consuming in order to protect their health.

[0504] "Emotional state" refers to the user's psychological and emotional state, including specific emotions such as stress and happiness.

[0505] "Dietary restriction information" refers to information about dietary restrictions based on religious beliefs, allergy restrictions, and emotional states.

[0506] A "data storage device" refers to a storage medium used to store data on ingredients and cooking methods, and to access it as needed.

[0507] A "generative model" is an algorithm and computational method for generating personalized recipes based on input data.

[0508] A "3D food molding machine" is a machine or device that molds food into a specific shape and cooking method based on electronic data.

[0509] This personalized meal suggestion system is implemented primarily using a user terminal, a server, an emotion analysis engine, and a 3D food molding device.

[0510] Users first input information about their religious beliefs and allergies into the device. This information includes data on specific foods and cooking methods to avoid. Furthermore, the device's built-in emotion analysis engine analyzes the user's emotional state from their voice and facial expressions. This emotional state is categorized into stress, happiness, etc., to improve the user experience.

[0511] The terminal sends this information to the server. Based on the received user information, the server accesses its data storage to obtain data on ingredients and cooking methods that suit the user's restrictions and emotional state. The obtained data is processed by a generative AI model to generate a recipe that matches the user's conditions. This generative AI model uses computational methods to suggest recipes adapted to various conditions.

[0512] The generated recipe is sent to the user's terminal and displayed visually to the user. The user can review the presented recipe and customize it as needed. Once the recipe is finalized, the terminal sends this information to a 3D food molding machine, which then creates the food in the specified shape and cooking method.

[0513] For example, if a user has a peanut allergy and is currently experiencing high levels of stress, the system can suggest a meal that excludes peanuts and uses herbs with relaxing properties. This allows the user to have a meal experience that addresses both their health and emotional needs.

[0514] An example of a prompt would be, "Please suggest a personalized meal recipe based on the user's allergy information and emotional state." The generative AI model would then generate a recipe based on this prompt. In this way, the entire system works together to provide the user with the optimal dining experience.

[0515] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0516] Step 1:

[0517] The user inputs information about their religious beliefs and allergies into the device. This input includes restrictions on specific foods and cooking methods. The device then uses built-in sensors and microphones to recognize the user's emotional state. Using voice tone analysis and facial recognition technology, the device classifies the user's emotions into categories such as "relaxed," "excited," and "stressed," and generates emotional information. The output at this point is a user profile that includes religious beliefs, allergy information, and emotional state.

[0518] Step 2:

[0519] The terminal sends the generated user profile to the server. The server receives this profile and accesses a database in its data storage. The server searches for ingredients and cooking methods that fit the user's restrictions and retrieves the corresponding dataset. This data processing outputs basic information about available ingredients and recipes that meet the user's constraints.

[0520] Step 3:

[0521] The server uses a generative AI model to generate personalized recipes based on the acquired dataset. The prompt is: "Create the optimal meal recipe considering the user's allergy information and emotional state." The generative AI model calculates a recipe optimized for the conditions and outputs it as recipe data. The generated recipe data includes specific ingredients, cooking methods, and combinations of emotional effects.

[0522] Step 4:

[0523] The server sends the generated recipe data to the user's terminal. The terminal visually displays the received data, allowing the user to review and customize it. At this stage, the user performs specific operations such as selecting and changing ingredients and cooking methods. The output is the customized recipe data that the user has finally approved.

[0524] Step 5:

[0525] The terminal transmits the final recipe data to a 3D food molding device. This device uses numerical control to form food according to the specified shape and cooking method. The food output by the operation is a meal that perfectly matches the user's needs. The device completes the food efficiently through an automated process.

[0526] (Application Example 2)

[0527] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0528] Conventional meal suggestion systems only consider the user's religious beliefs and allergy restrictions, lacking personalization based on emotional state. Furthermore, the process of actually preparing the suggested recipes is not sufficiently automated, leaving users with a burden.

[0529] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0530] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for obtaining data on appropriate ingredients and cooking methods from a database based on the dietary restriction information and the emotional state recognized by the emotion recognition module; and means for generating a recipe using an algorithm based on the obtained data and materializing the food using a robotic cooking device. This makes it possible to automatically suggest and cook a meal that is appropriate for the user's emotional state.

[0531] "Entering user information" refers to the process of providing the system with an individual user's religious beliefs, allergy information, and emotional state.

[0532] An "emotion recognition module" is a software or hardware component that analyzes and recognizes a user's current emotional state.

[0533] "Generating recipes using algorithms" refers to a computational method that determines appropriate ingredients and cooking methods based on data received from the user, and constructs cooking procedures tailored to individual requirements.

[0534] A "robot cooking device" is a mechanical device that automatically prepares and cooks a suggested dish based on a generated recipe.

[0535] "Dietary restriction information" refers to information about special requirements or restrictions regarding food that a user may have, such as religious beliefs or allergies.

[0536] To implement this invention, a specific hardware and software configuration is required. This system mainly consists of a user terminal, an emotion recognition module, a server, a database, an AI-based recipe generation algorithm, and a robotic cooking device.

[0537] The user terminal is responsible for receiving personal information from the user, such as religious beliefs, allergy information, and emotional state. This information is used to analyze the user's emotional state using an emotion recognition module. The acquired data is then sent to the server.

[0538] The server searches the database based on the received information to extract data on ingredients and cooking methods. A recipe generation algorithm based on a generative AI model is used to generate recipes tailored to each user's individual dietary restrictions and emotional state. This process requires, for example, database management software and the AI ​​algorithm integrated into it.

[0539] The generated recipe data is sent to the user's terminal for verification. It is also transferred to a robotic cooking device, where the food is cooked automatically. The robotic cooking device operates with mechanical hardware and embedded software, and performs cooking according to the generated instructions.

[0540] As a concrete example, when a user is feeling stressed, the system can suggest chamomile tea or a soothing soup, and a robotic cooking device can then prepare and serve the meal. An example of a prompt to give instructions to the system in this case would be: "Generate a recipe that is best suited to the user's emotional state and constraints. The user is currently vegetarian and wishes to relax."

[0541] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0542] Step 1:

[0543] The user terminal receives input from the user, including religious beliefs, allergy information, and emotional state. This input is processed, formatted, and then sent to the server.

[0544] Step 2:

[0545] The server uses an emotion recognition module to analyze the user's emotional state using the received user information as input. Based on this, it searches a database to obtain data on ingredients and cooking methods suitable for dietary restrictions and the user's emotional state as output. During this process, necessary data processing is performed to obtain the optimal results.

[0546] Step 3:

[0547] The server uses a generative AI model and a recipe generation algorithm to analyze acquired ingredient information and emotional states as input, and outputs an appropriate recipe. The generated recipe is then processed to provide cooking suggestions tailored to the user's individual requirements.

[0548] Step 4:

[0549] The server sends the generated recipe data as output to the user's terminal. This allows the user to review the suggested recipe and provide customization inputs as needed.

[0550] Step 5:

[0551] The server sends the finally approved recipe data as input to the robotic cooking device. The robotic cooking device uses this data to perform the specific cooking process and produces the finished dish as output.

[0552] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0553] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0554] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0555] [Fourth Embodiment]

[0556] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0557] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0558] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0559] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0560] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0561] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0562] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0563] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0564] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0565] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0566] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0567] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0568] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0569] This invention is a system for streamlining users' daily meal management and providing safe and appropriate meals. The system consists of a user terminal, a server, and a 3D food molding device. The user inputs necessary information, such as their religious beliefs, allergies, and dietary preferences, via the terminal. This information is sent to the server, which receives and authenticates it. Upon successful authentication, the server searches its database based on this information and retrieves data on suitable ingredients and cooking methods.

[0570] The server then generates a recipe tailored to the user's constraints and preferences based on the acquired data. The generated recipe is sent to the terminal, where the user can view and review it. At this point, the user can also customize the recipe. Finally, once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. Based on the transmitted data, the device creates the dish with the specified shape and cooking method.

[0571] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its database for plant-based, nut-free ingredients and generate a recipe based on them. The recipe will also detail the ingredients used and cooking procedures, allowing the user to enjoy their meal with peace of mind. This significantly simplifies daily dietary management and makes it possible to provide a personalized dining experience for each user.

[0572] The following describes the processing flow.

[0573] Step 1:

[0574] Users log in to the application using their device and enter personal information such as their religious beliefs, allergies, and dietary preferences.

[0575] Step 2:

[0576] The terminal sends the entered user information to the server and begins user account authentication. The server determines whether authentication was successful and returns an error message to the terminal if it fails.

[0577] Step 3:

[0578] The server searches the database based on authenticated user information to retrieve food data that matches the user's religious beliefs and allergies. This process creates a list of candidate foods that meet the user's restrictions.

[0579] Step 4:

[0580] The server uses the acquired ingredient data to generate the optimal recipe for the user through an algorithm. This recipe generation process also takes into account the balance of nutrients and flavor.

[0581] Step 5:

[0582] The server sends the generated recipe data to the terminal, allowing the user to review the recipe. The terminal then displays the recipe to the user and provides customization options as needed.

[0583] Step 6:

[0584] Once the user approves the recipe, the terminal sends the recipe data to a 3D food molding device. The device then begins cooking the food according to the specified shape and cooking method based on this data.

[0585] Step 7:

[0586] The terminal notifies the user when the meal is ready, and after the user receives the meal, they can enter feedback through the application. The server collects this feedback and uses it as data to improve future recipe suggestions.

[0587] (Example 1)

[0588] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0589] Providing safe and personalized meals to users with diverse religious beliefs and allergy restrictions is challenging. Traditional methods involve a significant amount of manual work to meet each user's individual needs, which is time-consuming and labor-intensive.

[0590] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0591] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for searching an information recording medium and obtaining data on appropriate ingredients and cooking methods; and means for generating cooking procedures using an artificial intelligence model based on the obtained data. This enables efficient individualized dietary management and the provision of appropriate meals to users.

[0592] "User information" refers to information that indicates the individual characteristics of a user, such as their religious beliefs, allergies, and dietary preferences.

[0593] "Dietary restriction information" refers to information indicating dietary restrictions based on the user's religious beliefs, allergies, etc.

[0594] An "information recording medium" refers to a database that stores data about ingredients and cooking methods, and allows for searching and retrieval of that data as needed.

[0595] An "artificial intelligence model" is a program that includes machine learning algorithms to generate cooking procedures that are optimal for the user's needs from input data.

[0596] "Cooking instructions" refer to information that shows the specific steps of cooking, generated based on acquired data and taking into account the user's dietary restrictions.

[0597] A "user device" is an electronic terminal used by the user to input information and receive, display, and customize the generated cooking instructions.

[0598] A "three-dimensional food processing device" is a device that processes food ingredients into specific shapes and cooking methods based on generated cooking procedure data to form a meal.

[0599] "Means of authentication" refers to a function that implements an authentication process to confirm that the information entered by the user is accurate and secure.

[0600] This invention provides a system for efficiently delivering personalized meals to users with diverse religious beliefs and allergy restrictions. The system includes a user terminal, a server, and a three-dimensional food processing device.

[0601] The user uses their terminal to input information such as their religious beliefs, allergies, and dietary preferences. The terminal encrypts and transmits this information to the server. Based on the received information, the server searches the information storage medium to obtain data on ingredients and cooking methods that meet the user's requirements.

[0602] The server uses a generative AI model to generate the optimal cooking procedure for the user from the acquired data. This generated cooking procedure is then sent back to the user's terminal for review. The user can review the new recipe and customize it as needed.

[0603] Finally, once the user approves the cooking procedure, the user terminal transmits the cooking procedure data to the 3D food processing device. The device processes the ingredients according to the specified shape and method to form the meal.

[0604] For example, if a user has dietary restrictions such as being vegetarian and having a nut allergy, the server will search its information storage medium for nut-free ingredients based on plant matter and generate a recipe and cooking instructions based on that. This process uses prompts to the generative AI model such as: "The user is vegetarian and has a nut allergy. Based on this information, the server should generate an appropriate recipe."

[0605] This system will enable users to efficiently obtain a safe and personalized dining experience that accommodates their individual dietary restrictions.

[0606] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0607] Step 1:

[0608] Users input information about their religious beliefs, allergies, and dietary preferences using their user terminal. This input can be efficiently processed using checkboxes and dropdown menus. The entered information is converted into a data structure such as JSON, encrypted, and sent to the server.

[0609] Step 2:

[0610] The server receives data sent from the terminal and performs authentication. The authentication process verifies the legitimacy of the data using authentication information such as a user ID and password. If authentication is successful, the server analyzes the received data, searches its information storage medium (database), and retrieves information on ingredients and cooking methods that meet the dietary restrictions. This search process uses SQL queries, among other methods.

[0611] Step 3:

[0612] The server generates cooking instructions using a generative AI model based on acquired ingredient and cooking method data. By providing specific cooking conditions to the AI ​​model via prompts, it outputs the optimal cooking instructions that suit the user's constraints and preferences. For example, a prompt such as "The user is a vegetarian and has a nut allergy. Generate appropriate cooking instructions based on this information" might be used. The generated cooking instructions are saved as data and used for subsequent processing.

[0613] Step 4:

[0614] The generated cooking procedure data is sent from the server to the user's terminal, which receives and displays it to the user. The user can check the recipe on the terminal and customize it as needed. For example, they can adjust the amount of seasonings or select different ingredients. User interaction is crucial in this step, and the interface is designed to be intuitive.

[0615] Step 5:

[0616] Once the user approves the recipe, the terminal transmits this finalized cooking procedure data to a three-dimensional food processing device. Based on the received data, the device processes and cooks the ingredients according to the specified shape and cooking method, forming the finished dish. Specifically, printing and heating technologies are used to provide a meal exactly as instructed by the user.

[0617] (Application Example 1)

[0618] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0619] In modern society, there is a need for a system that can rationally and flexibly provide meals tailored to individual needs, accommodating diverse dietary restrictions and preferences. Traditional food delivery services have problems such as limited options for users with specific religious beliefs or allergies, and the need for manual selection each time, which is time-consuming. Furthermore, it has been difficult to streamline daily meal management and provide a personalized dining experience that takes into account individual constraints.

[0620] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0621] In this invention, the server includes means for inputting user information and receiving constraint information, including religious beliefs and allergy restrictions; means for obtaining information on appropriate ingredients and cooking methods from a storage device based on the constraint information; and means for generating cooking procedures using a calculation means based on the obtained information. This makes it possible to automatically prepare safe and appropriate meals tailored to each user's constraints and preferences and deliver them to a specified location.

[0622] "User information" refers to individual data about users, including information such as their religious beliefs, allergy restrictions, and dietary preferences.

[0623] "Constraint information" refers to information that describes special conditions set by the user, such as religious beliefs, allergy restrictions, or food preferences.

[0624] "Ingredients" refer to raw materials used in cooking, selected according to the user's requirements.

[0625] A "cooking method" refers to the procedures and techniques used to prepare a dish by processing specific ingredients.

[0626] A "storage device" is equipment used to store information, and refers to computer databases, cloud storage, and other similar devices.

[0627] "Computational means" refers to methods and techniques for analyzing data and deriving specific results.

[0628] "Cooking procedure" refers to the specific steps and processes for cooking using ingredients.

[0629] A "generated dish" is a food product that has been completed by applying cooking methods based on the user's constraint information.

[0630] "Delivery method" refers to the means and methods for transporting cooked food to a location specified by the user.

[0631] The system for realizing this invention consists of a user terminal, a cloud server, a 3D food molding device, and a delivery method. The user uses a smartphone or other device to input user information, including their religious beliefs, allergy restrictions, and dietary preferences. The terminal transmits this information to the server.

[0632] The server operates in a cloud environment and searches its storage for data on appropriate ingredients and cooking methods based on constraint information received from the user. Using this data, the server generates cooking procedures that conform to the user's constraints through computational means. In this process, it is also possible to customize and suggest recipes using a generation AI model.

[0633] The cooking instructions are then displayed on the user's device for review and final customization. The confirmed cooking instructions are sent to a 3D food molding machine. This machine cooks the ingredients according to the instructions and produces the user-specified dish.

[0634] The prepared meals are delivered to the user's specified location via a delivery service. This system allows users to receive personalized meals tailored to their beliefs and preferences in a convenient and secure manner.

[0635] As a concrete example, let's consider a case where a user is vegetarian and has a nut allergy. This user inputs this information into a terminal, and the server generates a menu based on vegetables that does not contain nuts. This menu is then cooked using a 3D food molding machine and delivered to the user's home. At that time, the AI ​​model can be provided with a prompt message such as, "I am vegetarian and have a nut allergy, so please generate a safe and delicious meal recipe."

[0636] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0637] Step 1:

[0638] Users enter user information, including religious beliefs, allergy restrictions, and dietary preferences, using their smartphones or devices. This information is entered through the interface and received by the device system. This process formats the user's individual data, preparing it for transmission to the next step.

[0639] Step 2:

[0640] The terminal sends the received user information to the cloud server. The terminal sends that data to the server via a secure connection, and the server receives it. The information entered here specifically is restriction data regarding the user's dietary restrictions.

[0641] Step 3:

[0642] Based on the received constraint information, the server searches its storage for information on appropriate ingredients and cooking methods. The server queries the database and searches for items that match the user's constraints. The output is a list of ingredients and cooking methods that meet the conditions.

[0643] Step 4:

[0644] Based on the acquired information, the server uses computational means to generate cooking instructions that meet the user's requirements. This process utilizes a generative AI model, constructing a recipe using prompt messages as input. This step outputs customized cooking instruction data.

[0645] Step 5:

[0646] The server sends the generated cooking procedure data to the user's terminal and displays it on the terminal. This allows the user to review the generated cooking procedure and make final customizations as needed. If the user makes any changes, the procedure can be readjusted based on that information.

[0647] Step 6:

[0648] The confirmed cooking procedure is sent to the 3D food molding machine. Based on the procedure data, this machine cooks the ingredients as specified and produces the dish. The output here is the finished dish.

[0649] Step 7:

[0650] The prepared food is transported to the user's specified location via a delivery service. The food is delivered safely and quickly to its destination through the logistics system. In this step, the user can receive the food at home.

[0651] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0652] This invention relates to a system that provides personalized meal suggestions, taking into account the user's individual religious beliefs, allergy restrictions, and emotional state. The system comprises a user terminal, a server, an emotion engine, and further includes a 3D food molding device.

[0653] Users input information about their religious beliefs and allergies via the device. In addition, the device uses an emotion engine to recognize the user's current emotional state. This emotional information is used to consider the user's psychological impact on food. The recognized emotions and other user information are sent to the server.

[0654] Based on the information received, the server searches the database and extracts data on ingredients and cooking methods that suit the user's limitations and emotional state. Using this data, the server generates recipes using an algorithm. In this process, the user's emotional state is taken into consideration; for example, ingredients with relaxing effects may be suggested to a user who is highly stressed.

[0655] The generated recipe is sent to a terminal, where the user can review and customize it if necessary. Once the user approves the recipe, the terminal sends it to a 3D food molding device. This device then uses the data to mold the food into a specific shape and cooking method.

[0656] For example, if the use of a certain food is too sensitive, the information may be urgently needed, the system does not contain the recommended use, but the ingredients are effective. This is a recommended way to think about how to meet the demands of health and wellness, and to provide a more personalized and intentional drinking experience.

[0657] The following describes the processing flow.

[0658] Step 1:

[0659] Users log in to the application using their device and enter personal information such as religious beliefs, allergy information, and dietary preferences. The device collects this information.

[0660] Step 2:

[0661] The device uses a built-in emotion engine to recognize the user's current emotional state. This allows it to determine, for example, whether the user is stressed or relaxed.

[0662] Step 3:

[0663] The terminal sends the collected user information and recognized emotional state to the server. The server receives this information and begins user authentication and data processing.

[0664] Step 4:

[0665] The server searches the database based on the received information and selects ingredients and cooking methods. In doing so, it generates an ingredient list that takes into account religious restrictions, allergies, and emotional states.

[0666] Step 5:

[0667] The server uses a list of selected ingredients to generate recipes using an algorithm that meets the user's preferences and constraints. Depending on the user's emotional state, ingredients with refreshing effects, for example, may be selected.

[0668] Step 6:

[0669] The server sends the generated recipe data to the terminal, which then displays the contents to the user. The user can review the recipe and customize it as needed.

[0670] Step 7:

[0671] Once the user approves the recipe, the terminal sends the final recipe data to a 3D food molding device. Based on the received data, the device creates the dish with the specified shape and cooking method.

[0672] Step 8:

[0673] The terminal notifies the user when the meal is ready, and after receiving the meal, the user can provide feedback through the application. The server receives this feedback and uses it to make suggestions for the next time.

[0674] (Example 2)

[0675] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0676] Traditional meal suggestion systems could exclude certain ingredients based on users' religious beliefs or allergy restrictions, but they could not provide personalized suggestions that took into account the user's emotional state. Therefore, they failed to provide a dining experience that matched the user's emotions, resulting in lower satisfaction. Furthermore, the means of shaping meals to meet individual user needs were limited.

[0677] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0678] In this invention, the server includes means for inputting user information and receiving dietary restriction information including religious beliefs, allergy restrictions, and emotional state; means for obtaining data on appropriate ingredients and cooking methods from a data storage device based on the dietary restriction information and emotional state; and means for generating recipes using a generative model based on the obtained data. This makes it possible to provide personalized meal suggestions that meet the user's emotional state while accommodating their religious beliefs and allergy restrictions.

[0679] "User information" refers to individual data about a user, including religious beliefs, allergy restrictions, and emotional state.

[0680] "Religious beliefs" refer to a user's beliefs and values ​​related to ingredients or cooking methods that should be avoided based on a particular religion or faith.

[0681] "Allergy restrictions" refers to information about specific foods or ingredients that users should avoid consuming in order to protect their health.

[0682] "Emotional state" refers to the user's psychological and emotional state, including specific emotions such as stress and happiness.

[0683] "Dietary restriction information" refers to information about dietary restrictions based on religious beliefs, allergy restrictions, and emotional states.

[0684] A "data storage device" refers to a storage medium used to store data on ingredients and cooking methods, and to access it as needed.

[0685] A "generative model" is an algorithm and computational method for generating personalized recipes based on input data.

[0686] A "3D food molding machine" is a machine or device that molds food into a specific shape and cooking method based on electronic data.

[0687] This personalized meal suggestion system is implemented primarily using a user terminal, a server, an emotion analysis engine, and a 3D food molding device.

[0688] Users first input information about their religious beliefs and allergies into the device. This information includes data on specific foods and cooking methods to avoid. Furthermore, the device's built-in emotion analysis engine analyzes the user's emotional state from their voice and facial expressions. This emotional state is categorized into stress, happiness, etc., to improve the user experience.

[0689] The terminal sends this information to the server. Based on the received user information, the server accesses its data storage to obtain data on ingredients and cooking methods that suit the user's restrictions and emotional state. The obtained data is processed by a generative AI model to generate a recipe that matches the user's conditions. This generative AI model uses computational methods to suggest recipes adapted to various conditions.

[0690] The generated recipe is sent to the user's terminal and displayed visually to the user. The user can review the presented recipe and customize it as needed. Once the recipe is finalized, the terminal sends this information to a 3D food molding machine, which then creates the food in the specified shape and cooking method.

[0691] For example, if a user has a peanut allergy and is currently experiencing high levels of stress, the system can suggest a meal that excludes peanuts and uses herbs with relaxing properties. This allows the user to have a meal experience that addresses both their health and emotional needs.

[0692] An example of a prompt would be, "Please suggest a personalized meal recipe based on the user's allergy information and emotional state." The generative AI model would then generate a recipe based on this prompt. In this way, the entire system works together to provide the user with the optimal dining experience.

[0693] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0694] Step 1:

[0695] The user inputs information about their religious beliefs and allergies into the device. This input includes restrictions on specific foods and cooking methods. The device then uses built-in sensors and microphones to recognize the user's emotional state. Using voice tone analysis and facial recognition technology, the device classifies the user's emotions into categories such as "relaxed," "excited," and "stressed," and generates emotional information. The output at this point is a user profile that includes religious beliefs, allergy information, and emotional state.

[0696] Step 2:

[0697] The terminal sends the generated user profile to the server. The server receives this profile and accesses a database in its data storage. The server searches for ingredients and cooking methods that fit the user's restrictions and retrieves the corresponding dataset. This data processing outputs basic information about available ingredients and recipes that meet the user's constraints.

[0698] Step 3:

[0699] The server uses a generative AI model to generate personalized recipes based on the acquired dataset. The prompt is: "Create the optimal meal recipe considering the user's allergy information and emotional state." The generative AI model calculates a recipe optimized for the conditions and outputs it as recipe data. The generated recipe data includes specific ingredients, cooking methods, and combinations of emotional effects.

[0700] Step 4:

[0701] The server sends the generated recipe data to the user's terminal. The terminal visually displays the received data, allowing the user to review and customize it. At this stage, the user performs specific operations such as selecting and changing ingredients and cooking methods. The output is the customized recipe data that the user has finally approved.

[0702] Step 5:

[0703] The terminal transmits the final recipe data to a 3D food molding device. This device uses numerical control to form food according to the specified shape and cooking method. The food output by the operation is a meal that perfectly matches the user's needs. The device completes the food efficiently through an automated process.

[0704] (Application Example 2)

[0705] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0706] Conventional meal suggestion systems only consider the user's religious beliefs and allergy restrictions, lacking personalization based on emotional state. Furthermore, the process of actually preparing the suggested recipes is not sufficiently automated, leaving users with a burden.

[0707] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0708] In this invention, the server includes means for inputting user information and receiving dietary restriction information, including religious beliefs and allergy restrictions; means for obtaining data on appropriate ingredients and cooking methods from a database based on the dietary restriction information and the emotional state recognized by the emotion recognition module; and means for generating a recipe using an algorithm based on the obtained data and materializing the food using a robotic cooking device. This makes it possible to automatically suggest and cook a meal that is appropriate for the user's emotional state.

[0709] "Entering user information" refers to the process of providing the system with an individual user's religious beliefs, allergy information, and emotional state.

[0710] An "emotion recognition module" is a software or hardware component that analyzes and recognizes a user's current emotional state.

[0711] "Generating recipes using algorithms" refers to a computational method that determines appropriate ingredients and cooking methods based on data received from the user, and constructs cooking procedures tailored to individual requirements.

[0712] A "robot cooking device" is a mechanical device that automatically prepares and cooks a suggested dish based on a generated recipe.

[0713] "Dietary restriction information" refers to information about special requirements or restrictions regarding food that a user may have, such as religious beliefs or allergies.

[0714] To implement this invention, a specific hardware and software configuration is required. This system mainly consists of a user terminal, an emotion recognition module, a server, a database, an AI-based recipe generation algorithm, and a robotic cooking device.

[0715] The user terminal is responsible for receiving personal information from the user, such as religious beliefs, allergy information, and emotional state. This information is used to analyze the user's emotional state using an emotion recognition module. The acquired data is then sent to the server.

[0716] The server searches the database based on the received information to extract data on ingredients and cooking methods. A recipe generation algorithm based on a generative AI model is used to generate recipes tailored to each user's individual dietary restrictions and emotional state. This process requires, for example, database management software and the AI ​​algorithm integrated into it.

[0717] The generated recipe data is sent to the user's terminal for verification. It is also transferred to a robotic cooking device, where the food is cooked automatically. The robotic cooking device operates with mechanical hardware and embedded software, and performs cooking according to the generated instructions.

[0718] As a concrete example, when a user is feeling stressed, the system can suggest chamomile tea or a soothing soup, and a robotic cooking device can then prepare and serve the meal. An example of a prompt to give instructions to the system in this case would be: "Generate a recipe that is best suited to the user's emotional state and constraints. The user is currently vegetarian and wishes to relax."

[0719] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0720] Step 1:

[0721] The user terminal receives input from the user, including religious beliefs, allergy information, and emotional state. This input is processed, formatted, and then sent to the server.

[0722] Step 2:

[0723] The server uses an emotion recognition module to analyze the user's emotional state using the received user information as input. Based on this, it searches a database to obtain data on ingredients and cooking methods suitable for dietary restrictions and the user's emotional state as output. During this process, necessary data processing is performed to obtain the optimal results.

[0724] Step 3:

[0725] The server uses a generative AI model and a recipe generation algorithm to analyze acquired ingredient information and emotional states as input, and outputs an appropriate recipe. The generated recipe is then processed to provide cooking suggestions tailored to the user's individual requirements.

[0726] Step 4:

[0727] The server sends the generated recipe data as output to the user's terminal. This allows the user to review the suggested recipe and provide customization inputs as needed.

[0728] Step 5:

[0729] The server sends the finally approved recipe data as input to the robotic cooking device. The robotic cooking device uses this data to perform the specific cooking process and produces the finished dish as output.

[0730] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0731] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0732] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0733] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0734] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0735] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0736] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0737] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0738] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0739] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0740] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0741] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0742] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0743] 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.

[0744] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0745] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0746] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0747] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0748] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0749] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0750] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0751] The following is further disclosed regarding the embodiments described above.

[0752] (Claim 1)

[0753] A means for entering user information and receiving dietary restriction information, including religious beliefs and allergy restrictions,

[0754] A means for obtaining data on appropriate ingredients and cooking methods from a database based on the aforementioned dietary restriction information,

[0755] A means for generating a recipe using an algorithm based on the acquired data,

[0756] A means for transmitting and displaying the generated recipe data on a user terminal,

[0757] The means of transmitting the aforementioned recipe data to a 3D food molding device and creating a dish,

[0758] A system that includes this.

[0759] (Claim 2)

[0760] The system according to claim 1, which provides a customized list of ingredients based on the religious beliefs and allergy restriction information entered by the user.

[0761] (Claim 3)

[0762] The system according to claim 1, which receives user feedback and incorporates it into future recipe suggestions.

[0763] "Example 1"

[0764] (Claim 1)

[0765] A means for entering user information and receiving dietary restriction information, including religious beliefs and allergy restrictions,

[0766] A means for obtaining data on appropriate ingredients and cooking methods from an information recording medium based on the aforementioned dietary restriction information,

[0767] A means for generating cooking procedures using an artificial intelligence model based on the acquired data,

[0768] The means for transmitting and displaying the generated cooking procedure data on a user device,

[0769] The means of transmitting the aforementioned cooking procedure data to a three-dimensional food processing device and forming a meal,

[0770] A means for verifying and authenticating information recording media based on the entered user information,

[0771] A system that includes this.

[0772] (Claim 2)

[0773] The system according to claim 1, which provides an individualized list of ingredients based on religious beliefs and allergy restriction information entered by the user.

[0774] (Claim 3)

[0775] The system according to claim 1, which receives user feedback and applies it to suggestions for the next cooking procedure.

[0776] "Application Example 1"

[0777] (Claim 1)

[0778] A means for entering user information and receiving restriction information, including religious beliefs and allergy restrictions,

[0779] A means for obtaining information on appropriate ingredients and cooking methods from a storage device based on the aforementioned constraint information,

[0780] A means for generating cooking procedures using a calculation means based on acquired information,

[0781] A means for transmitting and displaying the generated cooking procedure data on the user's terminal,

[0782] The means for transmitting the aforementioned cooking procedure data to a three-dimensional food molding device and cooking the ingredients,

[0783] A means of transporting the prepared food to the user's designated location using a delivery method,

[0784] A system that includes this.

[0785] (Claim 2)

[0786] The system according to claim 1, which provides a customized list of ingredients based on the religious beliefs and allergy restriction information entered by the user.

[0787] (Claim 3)

[0788] The system according to claim 1, which receives feedback from users and incorporates it into the next cooking procedure suggestion.

[0789] "Example 2 of combining an emotion engine"

[0790] (Claim 1)

[0791] A means for inputting user information and receiving dietary restriction information including religious beliefs, allergy restrictions, and emotional state,

[0792] Means for obtaining data on appropriate ingredients and cooking methods from a data storage device based on the aforementioned dietary restriction information and emotional state,

[0793] A means for generating a recipe using a generative model based on the acquired data,

[0794] The generated recipe data is transmitted to the user terminal and displayed visually;

[0795] The means for transmitting the aforementioned recipe data to a 3D food molding machine and forming food,

[0796] A system that includes this.

[0797] (Claim 2)

[0798] The system according to claim 1, which provides a customized list of ingredients based on the religious beliefs, allergy restrictions, and emotional state entered by the user.

[0799] (Claim 3)

[0800] The system according to claim 1, which receives user feedback and incorporates it into future recipe suggestions.

[0801] "Application example 2 when combining with an emotional engine"

[0802] (Claim 1)

[0803] A means for entering user information and receiving dietary restriction information, including religious beliefs and allergy restrictions,

[0804] A means for obtaining data on appropriate ingredients and cooking methods from a database based on the aforementioned dietary restriction information,

[0805] A means for generating a recipe using an algorithm based on the acquired data and the emotional state recognized by the emotion recognition module,

[0806] The generated recipe data is transmitted to a user terminal, and the food is materialized by a robotic cooking device.

[0807] A means for transmitting and displaying the aforementioned recipe data on a user terminal,

[0808] A system that includes this.

[0809] (Claim 2)

[0810] The system according to claim 1, which provides a customized list of ingredients based on the user's religious beliefs and allergy restriction information, as well as their emotional state.

[0811] (Claim 3)

[0812] The system according to claim 1, which receives user feedback and incorporates it into future recipe suggestions. [Explanation of symbols]

[0813] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for entering user information and receiving dietary restriction information, including religious beliefs and allergy restrictions, A means for obtaining data on appropriate ingredients and cooking methods from a database based on the aforementioned dietary restriction information, A means for generating a recipe using an algorithm based on the acquired data, A means for transmitting and displaying the generated recipe data on a user terminal, The means of transmitting the aforementioned recipe data to a three-dimensional food molding device and creating a dish, A system that includes this.

2. The system according to claim 1, which provides a customized list of ingredients based on religious beliefs and allergy restriction information entered by the user.

3. The system according to claim 1, which receives feedback from users and incorporates it into future recipe suggestions.

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