system

Abstract

We provide the system. [Solution] A means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints, A means of presenting recommended cooking procedures to the user's device, A means of providing a timer for managing the progress of each cooking procedure and for time management, A means of identifying procedures for prioritizing the consumption of ingredients nearing their expiration date, 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 persona chatbot control method performed by at least one processor, the method including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern busy lifestyles, it is difficult to quickly select a suitable one from a variety of cooking procedures, especially efficient cooking within a limited time is required. However, it is difficult to manage time when multiple cooking procedures are carried out simultaneously, and waste is likely to occur if the ingredients available at home cannot be utilized well. These problems are particularly prominent for businessmen, dual-income families, and novice cooks, and are factors hindering efficient daily meal preparation.

Means for Solving the Problems

[0005] This invention provides a system that uses AI to recommend the optimal cooking procedure based on user-specified preferences, current inventory information, and time constraints. The system displays the recommended cooking procedure on the user's device, manages the progress of each step, and includes a timer function for efficient time management. Furthermore, it can reduce food waste by identifying procedures that prioritize the consumption of ingredients nearing their expiration date, improving the efficiency of inventory tracking and expiration-based ingredient usage.

[0006] "User preferences" refer to the conditions and characteristics that users favor based on their past usage history and personal preferences.

[0007] "Inventory information" refers to data such as the type, quantity, and expiration date of ingredients and materials currently in stock.

[0008] "Time constraints" refer to requirements that restrict the maximum amount of time or specific time slots that can be spent on cooking as specified by the user.

[0009] "Means for generating recommendations" refers to functions or methods for suggesting the optimal cooking procedure based on specified conditions.

[0010] "User's device" refers to electronic devices used by the user, such as computers, smartphones, and tablets.

[0011] "Cooking procedure" refers to the steps and processes necessary to prepare a dish.

[0012] A "timer for time management" is a function that measures the time required for each step of cooking and notifies you at the appropriate time.

[0013] "Food items nearing their expiration date" refers to food items that are nearing their best-before date and need to be consumed as a priority.

[0014] "Means for identifying procedures" refers to methods or functions for selecting appropriate cooking procedures or steps based on specified conditions.

Brief Description of the Drawings

[0015] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. <000007�>It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It 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 an 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 an emotion engine is combined.

Modes for Carrying Out the Invention

[0016] Next, 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0019] 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.

[0020] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0021] 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).

[0022] 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."

[0023] [First Embodiment]

[0024] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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".

[0036] This invention is configured as a system in which AI recommends the optimal cooking procedure based on user preferences, inventory information, and time constraints. The server analyzes this information and displays the appropriate cooking procedure on the user's device. It also features a smart timer function that manages progress and optimizes time to support the simultaneous execution of multiple cooking procedures. Furthermore, the inventory management system identifies ingredients nearing their expiration date in the refrigerator and provides cooking recommendations that include procedures for prioritizing the use of these ingredients.

[0037] Specifically, when a user inputs the conditions for the dish they want to cook, the system connects with the refrigerator to retrieve the status of the ingredients in stock. Based on this, the server refers to the user's preferences and past history to provide the optimal recipe. Based on the provided recipe, the terminal manages the time for each cooking step and sends notifications to the user at the appropriate time.

[0038] For example, if a user requests a chicken dish that can be prepared in under 30 minutes, the server will select a suitable recipe from among chicken dishes, taking into account the user's past preferences and current inventory. The terminal will then display a list of cooking steps and provide the user with voice and visual alerts as the cooking time changes. This allows the user to cook efficiently and reduces food waste.

[0039] The following describes the processing flow.

[0040] Step 1:

[0041] The user enters the cooking conditions (e.g., ingredients to be used, cooking time) into the app on their device.

[0042] Step 2:

[0043] The terminal sends the entered information, as well as inventory information obtained through its connection with the refrigerator, to the server.

[0044] Step 3:

[0045] The server uses an AI model to analyze user preferences and history based on the received data, and generates suitable recipe candidates.

[0046] Step 4:

[0047] The server sends a list of generated recipes to the terminal.

[0048] Step 5:

[0049] The device displays recommended cooking steps from the received recipes to the user.

[0050] Step 6:

[0051] The device is instructed to begin cooking based on the recipe selected by the user.

[0052] Step 7:

[0053] The terminal calculates the time required for each cooking step of the selected recipe and sends the information to the server.

[0054] Step 8:

[0055] The server optimizes cooking steps and creates a schedule to efficiently process multiple dishes.

[0056] Step 9:

[0057] The server sends an optimized cooking schedule to the terminal.

[0058] Step 10:

[0059] The device activates the smart cooking timer and notifies the user at the appropriate time for each step.

[0060] Step 11:

[0061] The refrigerator terminal periodically sends information about food inventory and expiration dates to the server.

[0062] Step 12:

[0063] The server identifies ingredients that are nearing their expiration date and generates recipes that prioritize their consumption.

[0064] Step 13:

[0065] The server sends the generated recipe to the terminal and suggests it to the user.

[0066] (Example 1)

[0067] 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."

[0068] Consumers face multiple challenges when preparing efficient and satisfying meals within limited timeframes, including managing ingredient inventory and optimizing cooking procedures. Furthermore, minimizing food waste while cooking according to users' personal preferences and time constraints is difficult.

[0069] 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.

[0070] In this invention, the server includes means for generating recommendations that optimize cooking procedures based on user preferences, inventory data, and time constraints; means for displaying the recommended cooking procedures on the user's terminal; and means for providing a timer function to monitor the progress of each cooking procedure and manage the time. This enables the user to cook according to their individual needs while efficiently using ingredients.

[0071] "User preferences" refer to information about the tastes, cooking styles, and ingredient choices that users prefer.

[0072] "Inventory data" refers to information about the food items currently stored in refrigerators and pantries, and their quantities.

[0073] "Time constraints" are conditions that indicate the range of time a user is allowed to spend on cooking.

[0074] "Means for generating recommendations" refers to technology that executes a process to derive the optimal cooking procedure based on the user's requests and circumstances.

[0075] "Means of displaying on a terminal" refers to technologies for displaying selected information on the screen of an electronic device used by the user.

[0076] The "timer function" is a feature that measures and manages the time for each step in cooking and notifies the user.

[0077] A "prompt message" is a text format in which the user enters specific cooking conditions they desire.

[0078] The "smart timer function" is a feature that efficiently manages the time for each cooking step and generates alerts according to the progress.

[0079] This invention is a system that provides optimal cooking procedures based on user preferences, inventory data, and time constraints. It is implemented using hardware such as a server and a refrigerator, and software such as a generative AI model.

[0080] The server receives prompt messages from the user and uses this information to generate cooking instructions using an AI model. The inventory management system works with the refrigerator and sends inventory data to the server. This data includes the type and quantity of ingredients, expiration dates, etc. Based on this, the server combines the user's past preference data and historical information to identify the optimal recipe.

[0081] The device receives information from the server and displays cooking instructions in a user-friendly format. A smart timer function manages the timing of each cooking step, and the device provides voice and visual notifications to the user. These notifications allow the user to proceed appropriately according to the cooking process.

[0082] As a concrete example, consider a scenario where a user gives the system instructions using the prompt, "A chicken dish that can be made in under 30 minutes." In this case, the server utilizes a generative AI model to recommend the optimal chicken dish and sends cooking instructions to the terminal, taking into account inventory status and the user's preferences. The terminal displays the instructions step by step, and a timer function notifies the user of appropriate alerts at each step.

[0083] This system allows users to cook efficiently, reduce food waste, and prepare satisfying meals within time constraints.

[0084] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0085] Step 1:

[0086] The user enters conditions for the dish they want to cook into the terminal. For example, it might provide a prompt message such as "a chicken dish that can be made in 30 minutes or less." This input specifies the cooking timeframe and becomes data sent to the system.

[0087] Step 2:

[0088] The terminal works in conjunction with the refrigerator to retrieve current inventory data from the inventory management system. This data includes the type, quantity, and expiration date of the ingredients. The terminal sends this inventory data to a server, and this information is used to optimize cooking procedures.

[0089] Step 3:

[0090] The server receives user prompts and inventory data. Using a generative AI model, it also references the user's past preferences and history to generate the optimal cooking procedure. In this process, a recipe that matches the input conditions provided by the user is selected, and that information is sent to the terminal.

[0091] Step 4:

[0092] The terminal displays cooking instructions received from the server on the screen in an easy-to-understand format. Furthermore, it uses a smart timer function to set time for each cooking step and prepares alerts tailored to each step. This output allows the user to proceed with cooking through visual and audible notifications.

[0093] Step 5:

[0094] Users begin cooking by following the displayed instructions and timer alerts. Based on the timer notifications provided by the device, they can understand the appropriate timing for each cooking step and proceed efficiently. This process makes it possible to complete a meal within a limited time while minimizing food waste.

[0095] (Application Example 1)

[0096] 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."

[0097] In modern households, the time available for cooking is limited due to busy daily schedules, and food waste is common. Therefore, users are required to complete cooking within a set timeframe while efficiently utilizing ingredients. However, traditional methods have struggled to automatically assemble the optimal cooking procedure while considering the expiration dates and inventory levels of individual ingredients. Furthermore, there remain challenges in providing appropriate instructions to automated machines when cooking without human intervention.

[0098] 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.

[0099] In this invention, the server includes means for selecting cooking procedures and generating recommendations based on user preferences, inventory data, and time constraints; means for presenting the recommended cooking procedures to the user's equipment; and means for providing a timer for managing the progress of each cooking procedure and for time management. This enables an automated humanoid machine to efficiently carry out the work according to the cooking procedures, minimizing food waste, and providing dishes that meet the user's preferences.

[0100] "User preferences" refer to the tendencies of individual users regarding foods and dishes they like, their past selection history, and their preference patterns.

[0101] "Inventory data" refers to data that includes information on the current quantity and expiration dates of food ingredients in refrigerators and food storage areas.

[0102] "Time constraints" refer to conditions that indicate the time limit a user has for cooking, or the target time by which a particular dish should be served.

[0103] "Means of generating recommendations" refers to processes or technologies for determining and suggesting the optimal cooking procedure based on user preferences, inventory data, and time constraints.

[0104] "User equipment" refers to electronic devices and other devices that the user owns and is expected to use, including smartphones and tablets.

[0105] "Managing the progress of the cooking process" refers to planning and monitoring each step of the cooking process to ensure it proceeds sequentially and efficiently.

[0106] "Means of providing a timing device" refers to functions or devices that provide notifications or alerts at the optimal timing for each step of a cooking procedure.

[0107] "Food ingredients" refers to all ingredients used for cooking, including meats, vegetables, and seasonings.

[0108] A "humanoid machine" refers to a robot or mechanical device designed to automatically perform cooking tasks by mimicking human manual labor.

[0109] This invention relates to a cooking support system for user use. The server receives user preferences, inventory data, and time constraints as input data and generates an optimal cooking procedure. This cooking procedure is suggested through the user's device and displayed on the device.

[0110] The server uses a Python®-based program and an AI model to generate optimal recipes. In this process, it utilizes TENSORFLOW® to analyze user preferences, ensuring that the suggested recipes are optimal based on the user's past history and preferences. Furthermore, the server integrates with inventory management sensors to monitor inventory data in the refrigerator and adjusts the system to prioritize food ingredients nearing their expiration dates.

[0111] The terminal uses a timer to count down the optimal cooking time and notifies the user via voice and visuals. The user can receive this information using a smartphone or tablet and proceed with cooking according to the instructions. When a humanoid robot is performing the cooking, it automatically proceeds with the cooking based on instructions from the server and notifies the user as needed.

[0112] For example, if a user enters a prompt such as "I want to make a delicious chicken recipe in a short amount of time," the system will consider current inventory and past preference data to suggest a chicken dish that can be completed in under 30 minutes. In this way, users can cook efficiently, and the efficient use of food ingredients is promoted.

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] The server receives a prompt from the user. The prompt may include a request such as, "I want to make a delicious chicken recipe in a short amount of time." The server then inputs the user's request as text data and prepares it for the next processing step.

[0116] Step 2:

[0117] The server communicates with inventory management sensors to obtain inventory data for food ingredients in the refrigerator. Here, the data from the sensors serves as input, determining the type, quantity, and expiration date of the food ingredients. The inventory data is then output as information necessary for the next processing step.

[0118] Step 3:

[0119] The server uses an AI model to generate the optimal cooking procedure based on the acquired inventory data and prompt content. Using TensorFlow, it creates a recipe that can be cooked within 30 minutes, comparing it with user preferences and past history. Here, preference data and inventory data are used as input, and appropriate recipe information is output.

[0120] Step 4:

[0121] The server sends the generated recipe information to the user's terminal. The terminal displays the received recipe information on its screen and provides the user with cooking instructions. The recipe information serves as input, and the user receives output that allows them to visually confirm the cooking instructions.

[0122] Step 5:

[0123] The device uses a timer to manage time at each cooking step and alerts the user at the appropriate times. The timer measures the cooking time as an input value, and outputs it to the user as audio or visual alerts.

[0124] Step 6:

[0125] The user follows the instructions on the terminal to proceed with cooking. The user's actions become input, and the progress of the cooking is displayed as output.

[0126] Step 7:

[0127] The server sends instructions to the humanoid robot as needed to proceed with the automated cooking process. Here, the instructions generated by the AI ​​become the input, and the humanoid robot automatically outputs actions to perform the cooking.

[0128] 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.

[0129] This invention is a cooking support system that integrates an emotion engine to identify the user's emotional state, in addition to user preferences, inventory information, and time constraints. Based on the cooking conditions entered by the user, the server uses the emotion engine to analyze the user's emotional state and flexibly adjusts the cooking procedure accordingly. It enables the provision of appropriate voice feedback, visual notifications, and suggestions of music and entertainment to alleviate user stress, depending on the user's emotions.

[0130] When a user enters cooking requirements via a terminal, the system retrieves inventory information by connecting with the refrigerator. The server then generates an optimal recipe based on this data, the user's existing preference data, and their current emotional state obtained from the emotion engine. The generated recipes are displayed on the terminal, and the user can select one from them.

[0131] For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting cooking methods and recipes with calming procedures. Furthermore, the device will play relaxing music during cooking to reduce the user's stress. In this way, the cooking procedure is dynamically adjusted to the user's emotions, improving the cooking experience, including emotional support.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The user enters the cooking conditions (ingredients used, cooking time, etc.) into the terminal.

[0135] Step 2:

[0136] The terminal sends the entered conditions and refrigerator inventory information to the server.

[0137] Step 3:

[0138] The server acquires voice and facial expression data from the terminal to analyze the user's emotional state using an emotion engine.

[0139] Step 4:

[0140] The server uses an AI model to generate optimal recipe candidates based on user preferences, inventory information, time constraints, and emotional state.

[0141] Step 5:

[0142] The server creates a list of generated recipes, along with additional suggestions tailored to the user's mood (e.g., relaxing music), and sends them to the terminal.

[0143] Step 6:

[0144] The device displays received recipes and suggestions to the user and provides visual and audio feedback.

[0145] Step 7:

[0146] The user selects a suggested recipe and additional features, and then gives the device instructions to begin cooking.

[0147] Step 8:

[0148] The device sends the time required for the cooking steps of the selected recipe to the server and prepares to start the timer.

[0149] Step 9:

[0150] The server optimizes the cooking steps, generates a time schedule that takes emotional states into account, and sends it to the terminal.

[0151] Step 10:

[0152] The device activates a smart cooking timer, provides voice notifications and plays music according to the time, and guides the user through the cooking process.

[0153] Step 11:

[0154] When cooking is complete, the device notifies the user and sends data to the server, based on feedback from the emotion engine, to be used for the next analysis.

[0155] (Example 2)

[0156] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0157] In modern life, users are busy and seek an efficient and enjoyable cooking experience. However, when cooking within limited time, it is difficult to consider the availability and expiration dates of ingredients, as well as the user's emotional state. This results in inefficient cooking, reduced food waste, and a lack of emotional support for the user. A system is needed to solve these problems and improve the cooking experience.

[0158] 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.

[0159] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on the user's preferences, inventory information, time constraints, and emotional state; means for presenting the recommended cooking procedures to the user's device and providing voice feedback and visual notifications based on the emotional state; and means for performing emotional analysis and suggesting music or entertainment according to the results. This makes it possible to suggest cooking procedures that take the user's emotional state into consideration, thereby realizing a comfortable and efficient cooking experience.

[0160] "User preferences" refer to information based on the tastes and preferences of individual users.

[0161] "Inventory information" refers to data about the types and quantities of food and ingredients stored in the kitchen or pantry.

[0162] "Time constraints" are conditions that indicate the limit of the time a user can spend cooking.

[0163] "Emotional state" refers to information that indicates the user's current psychological state, and includes elements such as stress, relaxation, and happiness.

[0164] "Cooking procedure" refers to the series of steps or processes necessary to complete a dish.

[0165] "Means of generating recommendations" refers to algorithms and system processes that provide users with the optimal cooking procedure.

[0166] "Voice feedback" is a function that provides information and guidance via voice in response to the user's actions and situation.

[0167] "Visual notifications" refer to visual information, including notifications and warnings, displayed on the device screen.

[0168] A "timekeeping device" is a device or function for measuring time that helps with the progress and time management of cooking.

[0169] "Emotional analysis" is a technology or process that analyzes a user's emotional state from data and identifies that state.

[0170] "Means of suggesting entertainment" refers to functions and technologies that suggest relaxation-oriented content such as music and video content that are tailored to the user's emotional state.

[0171] This invention is a system that proposes the optimal cooking procedure, taking into account the user's preferences, inventory information, time constraints, and emotional state. The user inputs cooking conditions using a dedicated terminal. Specifically, they can input the type of dish, desired cooking time, and ingredients to be used. Based on this input, the terminal transmits this data to a server.

[0172] The server executes specific procedures based on conditions entered by the user. It acquires inventory information by linking with external devices such as smart refrigerators and analyzes the user's current emotional state using an emotion engine. This analysis uses data analysis software to identify emotions from voice data and facial recognition data. By using libraries such as EmotionAI, emotions can be quantified.

[0173] After integrating this data, the server uses a generative AI model to generate the optimal recipe based on preference data, inventory data, and sentiment data. At this time, the AI ​​algorithm considers the user's past choices and emotional tendencies to make suggestions that match their current emotions.

[0174] Finally, the server sends the generated recipe to the device, which then visually presents it to the user. Based on the user's selected recipe, the device can then suggest and play audio feedback or relaxing music. The music selection utilizes APIs from common music streaming services.

[0175] For example, if a user inputs "I want to make a relaxing meal," the emotion engine will determine the user's stress level, and the server will suggest a recipe for a relaxing meal. Furthermore, the device will play ambient music that matches the user's emotions. An example of a prompt for the generative AI model would be, "Please tell me about a relaxing meal. My current emotional state is stressed. Please suggest the best recipe and music."

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The user enters the cooking conditions.

[0179] The user uses a terminal to enter conditions such as the type of dish, desired cooking time, and ingredients to be used into a text form. This input data forms the basis for processing in the next step.

[0180] Step 2:

[0181] The terminal sends the input data to the server.

[0182] The terminal converts the cooking conditions entered by the user into a digital format and securely transmits them to the server via the internet. A secure protocol is used for this transmission. The input data is used for analysis on the server.

[0183] Step 3:

[0184] The server retrieves inventory information.

[0185] The server communicates with external devices such as smart refrigerators to acquire food inventory data from within the refrigerator. This data is collected using sensors and image recognition technology within the refrigerator. This inventory data is then used in the next step to select recipes.

[0186] Step 4:

[0187] The server uses an emotion engine to analyze the user's emotions.

[0188] The server uses an emotion engine to quantify the user's emotional state based on the user's voice input and past usage information. The analysis results in levels of stress and relaxation, which are then reflected in recipe suggestions.

[0189] Step 5:

[0190] The server generates the optimal recipe using an AI model.

[0191] The server integrates the user preferences, inventory information, and emotional state mentioned above, and uses a generative AI model to generate the optimal recipe. The model operates using a prompt as input, and the output is cooking instructions. The string "Please suggest a relaxing recipe" is used as the prompt.

[0192] Step 6:

[0193] The server sends the generated recipe to the terminal.

[0194] The server transfers the generated recipe data to the terminal. This output data serves as the source of information for visual display on the terminal's screen.

[0195] Step 7:

[0196] The device displays the recipe to the user.

[0197] The device visually presents the received recipe to the user. Cooking instructions, ingredient list, and estimated preparation time are displayed on the screen. The interface is designed to be easy for the user to understand visually.

[0198] Step 8:

[0199] The device suggests and plays music and entertainment based on the user's emotional state.

[0200] The device suggests relaxing music and entertainment to the user based on emotion analysis results from the server. The selected music is automatically played using the streaming service's API, enhancing the user's cooking experience.

[0201] (Application Example 2)

[0202] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0203] Modern people face the challenge of effectively managing their emotions while cooking within their limited time and resources amidst their busy daily lives. Furthermore, there is a lack of cooking support systems that provide emotionally responsive assistance during and before cooking. Therefore, there is a need for technology that allows users to enjoy cooking more comfortably and efficiently.

[0204] 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.

[0205] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints; means for identifying the user's emotional state and dynamically adjusting the cooking procedures accordingly; and means for operating emotionally responsive audio feedback, visual notifications, or stress-relieving entertainment. This enables users to receive cooking assistance tailored to their emotions, thereby improving cooking efficiency and emotional satisfaction.

[0206] "User preferences" refer to the cooking styles, ingredient information, and flavor tendencies that users have previously preferred.

[0207] "Inventory information" refers to data regarding the quantity and expiration date of ingredients and materials available for cooking.

[0208] "Time constraints" refer to the time available to the user for cooking or the desired timeframe for completing the cooking process.

[0209] "Recommendations for selecting cooking procedures" is a function that suggests the optimal cooking method or recipe based on the user's conditions.

[0210] "Identifying emotional states" refers to the process of analyzing the user's facial expressions and vocal characteristics to identify their emotions in real time.

[0211] "Dynamic adjustment" means instantly changing cooking procedures and suggestions based on real-time data.

[0212] "Voice feedback" is a technology that provides users with information and advice in real time using voice.

[0213] "Visual notification" refers to a system that presents information visually through displays, lighting, and other means.

[0214] "Entertainment for stress relief" refers to content such as music and videos designed to reduce the user's mental burden and promote relaxation.

[0215] To implement this invention, a user-operated terminal is required. This terminal is equipped with a high-performance camera and microphone capable of identifying the user's emotional state, and collects the user's facial expressions and voice in real time. This makes it possible to analyze the user's emotional state with high accuracy.

[0216] The server uses cloud-based artificial intelligence services, such as Google Cloud Vision API and Amazon Rekognition, to analyze the collected emotional data. These services identify emotional states, and the server also uses Microsoft Azure Cognitive Services to detect emotions from speech. Based on these analysis results, the server suggests appropriate cooking procedures to the user.

[0217] The cooking instructions suggested by the server are generated based on user preferences, inventory information, and constraints. This includes a process of deriving the optimal recipe using generative AI models such as "IBM Watson®". The suggested recipes may include cooking methods and gentle procedures that help relieve stress, depending on the user's emotional state.

[0218] The device can notify the user of suggestions through voice feedback and visual information. Furthermore, it provides an interactive experience to alleviate stress while cooking through entertainment such as music and videos that respond to emotions.

[0219] For example, if a user enters "I'm especially tired today," the system will suggest a relaxing recipe such as "Creamy Chicken Stew" and play calming classical music while cooking.

[0220] Examples of prompt statements include the following:

[0221] "I'm feeling down today. Could you please suggest some easy and delicious recipes?"

[0222] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0223] Step 1:

[0224] Users input cooking conditions through their device. In particular, they input their emotional state and specific cooking preferences in voice or text format. Based on this input, the system works with an emotion engine to collect voice and text data.

[0225] Step 2:

[0226] The device sends the input voice and facial expression data to an artificial intelligence service in the cloud. The server uses "Google Cloud Vision API" or "Amazon Rekognition" to identify the user's emotional state from the collected data. The input here is the user's voice and facial expression data, and the output is the analyzed emotional state.

[0227] Step 3:

[0228] The server uses generative AI models such as IBM Watson based on the analysis of the user's emotional state to generate an optimal recipe set for the user. Furthermore, it combines this with user preference data, inventory information, and time constraints. The input to this process is the analyzed emotional state and user profile data, and the output is the proposed optimal recipe.

[0229] Step 4:

[0230] The server sends the generated recipe set to the terminal. The terminal notifies the user visually or audibly. The user selects their preferred recipe from the displayed list. At this point, the input is the generated recipe data, and the output is the user's selection.

[0231] Step 5:

[0232] Based on the selected recipe, the device provides cooking instructions while utilizing music and visual content. If the user's emotional state changes during cooking, data is sent back to the server, and the cooking instructions are adjusted in real time. The input for this step is the user's choices and current emotional state, and the output is the adjusted cooking instructions and entertainment content.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] [Second Embodiment]

[0237] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0238] 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.

[0239] 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).

[0240] 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.

[0241] 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.

[0242] 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).

[0243] 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.

[0244] 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.

[0245] 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.

[0246] 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.

[0247] 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.

[0248] 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".

[0249] This invention is configured as a system in which AI recommends the optimal cooking procedure based on user preferences, inventory information, and time constraints. The server analyzes this information and displays the appropriate cooking procedure on the user's device. It also features a smart timer function that manages progress and optimizes time to support the simultaneous execution of multiple cooking procedures. Furthermore, the inventory management system identifies ingredients nearing their expiration date in the refrigerator and provides cooking recommendations that include procedures for prioritizing the use of these ingredients.

[0250] Specifically, when a user inputs the conditions for the dish they want to cook, the system connects with the refrigerator to retrieve the status of the ingredients in stock. Based on this, the server refers to the user's preferences and past history to provide the optimal recipe. Based on the provided recipe, the terminal manages the time for each cooking step and sends notifications to the user at the appropriate time.

[0251] For example, if a user requests a chicken dish that can be prepared in under 30 minutes, the server will select a suitable recipe from among chicken dishes, taking into account the user's past preferences and current inventory. The terminal will then display a list of cooking steps and provide the user with voice and visual alerts as the cooking time changes. This allows the user to cook efficiently and reduces food waste.

[0252] The following describes the processing flow.

[0253] Step 1:

[0254] The user enters the cooking conditions (e.g., ingredients to be used, cooking time) into the app on their device.

[0255] Step 2:

[0256] The terminal sends the entered information, as well as inventory information obtained through its connection with the refrigerator, to the server.

[0257] Step 3:

[0258] The server uses an AI model to analyze user preferences and history based on the received data, and generates suitable recipe candidates.

[0259] Step 4:

[0260] The server sends a list of generated recipes to the terminal.

[0261] Step 5:

[0262] The device displays recommended cooking steps from the received recipes to the user.

[0263] Step 6:

[0264] The device is instructed to begin cooking based on the recipe selected by the user.

[0265] Step 7:

[0266] The terminal calculates the time required for each cooking step of the selected recipe and sends the information to the server.

[0267] Step 8:

[0268] The server optimizes cooking steps and creates a schedule to efficiently process multiple dishes.

[0269] Step 9:

[0270] The server sends an optimized cooking schedule to the terminal.

[0271] Step 10:

[0272] The device activates the smart cooking timer and notifies the user at the appropriate time for each step.

[0273] Step 11:

[0274] The refrigerator terminal periodically sends information about food inventory and expiration dates to the server.

[0275] Step 12:

[0276] The server identifies ingredients that are nearing their expiration date and generates recipes that prioritize their consumption.

[0277] Step 13:

[0278] The server transmits the generated recipe to the terminal and proposes it to the user.

[0279] (Example 1)

[0280] Next, Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0281] When preparing an efficient and satisfactory meal within a limited time, consumers face multiple issues such as inventory management of ingredients and optimization of cooking procedures. Also, it is difficult to cook based on the user's personal preferences and time constraints while minimizing food waste.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0283] In this invention, the server includes means for generating a recommendation to optimize the cooking procedure based on the user's preferences, inventory data, and time constraints, means for displaying the recommended cooking procedure on the user's terminal, and means for providing a timer function to monitor the progress of each cooking procedure and manage time. Thereby, the user can cook according to individual needs while efficiently using the ingredients.

[0284] "User preferences" refers to information indicating the flavors, cooking styles, and ingredient options that the user likes.

[0285] "Inventory data" refers to information regarding the ingredients currently held in the refrigerator or pantry and their quantities.

[0286] "Time constraint" refers to a condition indicating the range of time that the user can tolerate for cooking.

[0287] "Means for generating a recommendation" is a technology that executes a process of deriving an optimal cooking procedure based on the user's desires and situation.

[0288] "Means of displaying on a terminal" refers to technologies for displaying selected information on the screen of an electronic device used by the user.

[0289] The "timer function" is a feature that measures and manages the time for each step in cooking and notifies the user.

[0290] A "prompt message" is a text format in which the user enters specific cooking conditions they desire.

[0291] The "smart timer function" is a feature that efficiently manages the time for each cooking step and generates alerts according to the progress.

[0292] This invention is a system that provides optimal cooking procedures based on user preferences, inventory data, and time constraints. It is implemented using hardware such as a server and a refrigerator, and software such as a generative AI model.

[0293] The server receives prompt messages from the user and uses this information to generate cooking instructions using an AI model. The inventory management system works with the refrigerator and sends inventory data to the server. This data includes the type and quantity of ingredients, expiration dates, etc. Based on this, the server combines the user's past preference data and historical information to identify the optimal recipe.

[0294] The device receives information from the server and displays cooking instructions in a user-friendly format. A smart timer function manages the timing of each cooking step, and the device provides voice and visual notifications to the user. These notifications allow the user to proceed appropriately according to the cooking process.

[0295] As a concrete example, consider a scenario where a user gives the system instructions using the prompt, "A chicken dish that can be made in under 30 minutes." In this case, the server utilizes a generative AI model to recommend the optimal chicken dish and sends cooking instructions to the terminal, taking into account inventory status and the user's preferences. The terminal displays the instructions step by step, and a timer function notifies the user of appropriate alerts at each step.

[0296] This system allows users to cook efficiently, reduce food waste, and prepare satisfying meals within time constraints.

[0297] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0298] Step 1:

[0299] The user enters conditions for the dish they want to cook into the terminal. For example, it might provide a prompt message such as "a chicken dish that can be made in 30 minutes or less." This input specifies the cooking timeframe and becomes data sent to the system.

[0300] Step 2:

[0301] The terminal works in conjunction with the refrigerator to retrieve current inventory data from the inventory management system. This data includes the type, quantity, and expiration date of the ingredients. The terminal sends this inventory data to a server, and this information is used to optimize cooking procedures.

[0302] Step 3:

[0303] The server receives user prompts and inventory data. Using a generative AI model, it also references the user's past preferences and history to generate the optimal cooking procedure. In this process, a recipe that matches the input conditions provided by the user is selected, and that information is sent to the terminal.

[0304] Step 4:

[0305] The terminal displays the cooking procedure received from the server on the screen in an easy-to-understand format for the user. Furthermore, it sets the time for each cooking step using the smart timer function and prepares an alert for each procedure. With this output, the user can proceed with cooking through visual and audio notifications.

[0306] Step 5:

[0307] The user starts the actual cooking according to the displayed procedures and timer alerts. Based on the timer notifications provided by the terminal, the user can grasp the appropriate timing for each cooking step and proceed with cooking efficiently. Through this process, it is possible to complete cooking within a limited time while minimizing waste of ingredients.

[0308] (Application Example 1)

[0309] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0310] In modern households, the time available for cooking is limited due to daily busyness, and there is also a high likelihood of a lot of food waste. Therefore, users are required to complete cooking within the time while using ingredients efficiently. However, with conventional methods, it was difficult to automatically assemble the optimal cooking procedure considering the expiration dates and inventory status of individual ingredients. Also, there are still issues regarding appropriate instruction giving when an automated machine proceeds with cooking without human intervention.

[0311] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following respective means.

[0312] In this invention, the server includes means for selecting cooking procedures and generating recommendations based on user preferences, inventory data, and time constraints; means for presenting the recommended cooking procedures to the user's equipment; and means for providing a timer for managing the progress of each cooking procedure and for time management. This enables an automated humanoid machine to efficiently carry out the work according to the cooking procedures, minimizing food waste, and providing dishes that meet the user's preferences.

[0313] "User preferences" refer to the tendencies of individual users regarding foods and dishes they like, their past selection history, and their preference patterns.

[0314] "Inventory data" refers to data that includes information on the current quantity and expiration dates of food ingredients in refrigerators and food storage areas.

[0315] "Time constraints" refer to conditions that indicate the time limit a user has for cooking, or the target time by which a particular dish should be served.

[0316] "Means of generating recommendations" refers to processes or technologies for determining and suggesting the optimal cooking procedure based on user preferences, inventory data, and time constraints.

[0317] "User equipment" refers to electronic devices and other devices that the user owns and is expected to use, including smartphones and tablets.

[0318] "Managing the progress of the cooking process" refers to planning and monitoring each step of the cooking process to ensure it proceeds sequentially and efficiently.

[0319] "Means of providing a timing device" refers to functions or devices that provide notifications or alerts at the optimal timing for each step of a cooking procedure.

[0320] "Food ingredients" refers to all ingredients used for cooking, including meats, vegetables, and seasonings.

[0321] A "humanoid machine" refers to a robot or mechanical device designed to automatically perform cooking tasks by mimicking human manual labor.

[0322] This invention relates to a cooking support system for user use. The server receives user preferences, inventory data, and time constraints as input data and generates an optimal cooking procedure. This cooking procedure is suggested through the user's device and displayed on the device.

[0323] The server uses a Python-based program and an AI model to generate optimal recipes. TensorFlow is used to analyze user preferences, ensuring that the suggested recipes are optimal based on the user's past history and preferences. Furthermore, the server integrates with inventory sensors to monitor inventory data in the refrigerator and adjusts the system to prioritize food ingredients nearing their expiration dates.

[0324] The terminal uses a timer to count down the optimal cooking time and notifies the user via voice and visuals. The user can receive this information using a smartphone or tablet and proceed with cooking according to the instructions. When a humanoid robot is performing the cooking, it automatically proceeds with the cooking based on instructions from the server and notifies the user as needed.

[0325] For example, if a user enters a prompt such as "I want to make a delicious chicken recipe in a short amount of time," the system will consider current inventory and past preference data to suggest a chicken dish that can be completed in under 30 minutes. In this way, users can cook efficiently, and the efficient use of food ingredients is promoted.

[0326] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0327] Step 1:

[0328] The server receives a prompt from the user. The prompt may include a request such as, "I want to make a delicious chicken recipe in a short amount of time." The server then inputs the user's request as text data and prepares it for the next processing step.

[0329] Step 2:

[0330] The server communicates with inventory management sensors to obtain inventory data for food ingredients in the refrigerator. Here, the data from the sensors serves as input, determining the type, quantity, and expiration date of the food ingredients. The inventory data is then output as information necessary for the next processing step.

[0331] Step 3:

[0332] The server uses an AI model to generate the optimal cooking procedure based on the acquired inventory data and prompt content. Using TensorFlow, it creates a recipe that can be cooked within 30 minutes, comparing it with user preferences and past history. Here, preference data and inventory data are used as input, and appropriate recipe information is output.

[0333] Step 4:

[0334] The server sends the generated recipe information to the user's terminal. The terminal displays the received recipe information on its screen and provides the user with cooking instructions. The recipe information serves as input, and the user receives output that allows them to visually confirm the cooking instructions.

[0335] Step 5:

[0336] The device uses a timer to manage time at each cooking step and alerts the user at the appropriate times. The timer measures the cooking time as an input value, and outputs it to the user as audio or visual alerts.

[0337] Step 6:

[0338] The user follows the instructions on the terminal to proceed with cooking. The user's actions become input, and the progress of the cooking is displayed as output.

[0339] Step 7:

[0340] The server sends instructions to the humanoid robot as needed to proceed with the automated cooking process. Here, the instructions generated by the AI ​​become the input, and the humanoid robot automatically outputs actions to perform the cooking.

[0341] 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.

[0342] This invention is a cooking support system that integrates an emotion engine to identify the user's emotional state, in addition to user preferences, inventory information, and time constraints. Based on the cooking conditions entered by the user, the server uses the emotion engine to analyze the user's emotional state and flexibly adjusts the cooking procedure accordingly. It enables the provision of appropriate voice feedback, visual notifications, and suggestions of music and entertainment to alleviate user stress, depending on the user's emotions.

[0343] When a user enters cooking requirements via a terminal, the system retrieves inventory information by connecting with the refrigerator. The server then generates an optimal recipe based on this data, the user's existing preference data, and their current emotional state obtained from the emotion engine. The generated recipes are displayed on the terminal, and the user can select one from them.

[0344] For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting cooking methods and recipes with calming procedures. Furthermore, the device will play relaxing music during cooking to reduce the user's stress. In this way, the cooking procedure is dynamically adjusted to the user's emotions, improving the cooking experience, including emotional support.

[0345] The following describes the processing flow.

[0346] Step 1:

[0347] The user enters the cooking conditions (ingredients used, cooking time, etc.) into the terminal.

[0348] Step 2:

[0349] The terminal sends the entered conditions and refrigerator inventory information to the server.

[0350] Step 3:

[0351] The server acquires voice and facial expression data from the terminal to analyze the user's emotional state using an emotion engine.

[0352] Step 4:

[0353] The server uses an AI model to generate optimal recipe candidates based on user preferences, inventory information, time constraints, and emotional state.

[0354] Step 5:

[0355] The server creates a list of generated recipes, along with additional suggestions tailored to the user's mood (e.g., relaxing music), and sends them to the terminal.

[0356] Step 6:

[0357] The device displays received recipes and suggestions to the user and provides visual and audio feedback.

[0358] Step 7:

[0359] The user selects a suggested recipe and additional features, and then gives the device instructions to begin cooking.

[0360] Step 8:

[0361] The device sends the time required for the cooking steps of the selected recipe to the server and prepares to start the timer.

[0362] Step 9:

[0363] The server optimizes the cooking steps, generates a time schedule that takes emotional states into account, and sends it to the terminal.

[0364] Step 10:

[0365] The device activates a smart cooking timer, provides voice notifications and plays music according to the time, and guides the user through the cooking process.

[0366] Step 11:

[0367] When cooking is complete, the device notifies the user and sends data to the server, based on feedback from the emotion engine, to be used for the next analysis.

[0368] (Example 2)

[0369] 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".

[0370] In modern life, users are busy and seek an efficient and enjoyable cooking experience. However, when cooking within limited time, it is difficult to consider the availability and expiration dates of ingredients, as well as the user's emotional state. This results in inefficient cooking, reduced food waste, and a lack of emotional support for the user. A system is needed to solve these problems and improve the cooking experience.

[0371] 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.

[0372] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on the user's preferences, inventory information, time constraints, and emotional state; means for presenting the recommended cooking procedures to the user's device and providing voice feedback and visual notifications based on the emotional state; and means for performing emotional analysis and suggesting music or entertainment according to the results. This makes it possible to suggest cooking procedures that take the user's emotional state into consideration, thereby realizing a comfortable and efficient cooking experience.

[0373] "User preferences" refer to information based on the tastes and preferences of individual users.

[0374] "Inventory information" refers to data about the types and quantities of food and ingredients stored in the kitchen or pantry.

[0375] "Time constraints" are conditions that indicate the limit of the time a user can spend cooking.

[0376] "Emotional state" refers to information that indicates the user's current psychological state, and includes elements such as stress, relaxation, and happiness.

[0377] "Cooking procedure" refers to the series of steps or processes necessary to complete a dish.

[0378] "Means of generating recommendations" refers to algorithms and system processes that provide users with the optimal cooking procedure.

[0379] "Voice feedback" is a function that provides information and guidance via voice in response to the user's actions and situation.

[0380] "Visual notifications" refer to visual information, including notifications and warnings, displayed on the device screen.

[0381] A "timekeeping device" is a device or function for measuring time that helps with the progress and time management of cooking.

[0382] "Emotional analysis" is a technology or process that analyzes a user's emotional state from data and identifies that state.

[0383] "Means of suggesting entertainment" refers to functions and technologies that suggest relaxation-oriented content such as music and video content that are tailored to the user's emotional state.

[0384] This invention is a system that proposes the optimal cooking procedure, taking into account the user's preferences, inventory information, time constraints, and emotional state. The user inputs cooking conditions using a dedicated terminal. Specifically, they can input the type of dish, desired cooking time, and ingredients to be used. Based on this input, the terminal transmits this data to a server.

[0385] The server executes specific procedures based on conditions entered by the user. It acquires inventory information by linking with external devices such as smart refrigerators and analyzes the user's current emotional state using an emotion engine. This analysis uses data analysis software to identify emotions from voice data and facial recognition data. By using libraries such as EmotionAI, emotions can be quantified.

[0386] After integrating this data, the server uses a generative AI model to generate the optimal recipe based on preference data, inventory data, and sentiment data. At this time, the AI ​​algorithm considers the user's past choices and emotional tendencies to make suggestions that match their current emotions.

[0387] Finally, the server sends the generated recipe to the device, which then visually presents it to the user. Based on the user's selected recipe, the device can then suggest and play audio feedback or relaxing music. The music selection utilizes APIs from common music streaming services.

[0388] For example, if a user inputs "I want to make a relaxing meal," the emotion engine will determine the user's stress level, and the server will suggest a recipe for a relaxing meal. Furthermore, the device will play ambient music that matches the user's emotions. An example of a prompt for the generative AI model would be, "Please tell me about a relaxing meal. My current emotional state is stressed. Please suggest the best recipe and music."

[0389] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0390] Step 1:

[0391] The user enters the cooking conditions.

[0392] The user uses a terminal to enter conditions such as the type of dish, desired cooking time, and ingredients to be used into a text form. This input data forms the basis for processing in the next step.

[0393] Step 2:

[0394] The terminal sends the input data to the server.

[0395] The terminal converts the cooking conditions entered by the user into a digital format and securely transmits them to the server via the internet. A secure protocol is used for this transmission. The input data is used for analysis on the server.

[0396] Step 3:

[0397] The server retrieves inventory information.

[0398] The server communicates with external devices such as smart refrigerators to acquire food inventory data from within the refrigerator. This data is collected using sensors and image recognition technology within the refrigerator. This inventory data is then used in the next step to select recipes.

[0399] Step 4:

[0400] The server uses an emotion engine to analyze the user's emotions.

[0401] The server uses an emotion engine to quantify the user's emotional state based on the user's voice input and past usage information. The analysis results in levels of stress and relaxation, which are then reflected in recipe suggestions.

[0402] Step 5:

[0403] The server generates the optimal recipe using an AI model.

[0404] The server integrates the user preferences, inventory information, and emotional state mentioned above, and uses a generative AI model to generate the optimal recipe. The model operates using a prompt as input, and the output is cooking instructions. The string "Please suggest a relaxing recipe" is used as the prompt.

[0405] Step 6:

[0406] The server sends the generated recipe to the terminal.

[0407] The server transfers the generated recipe data to the terminal. This output data serves as the source of information for visual display on the terminal's screen.

[0408] Step 7:

[0409] The device displays the recipe to the user.

[0410] The device visually presents the received recipe to the user. Cooking instructions, ingredient list, and estimated preparation time are displayed on the screen. The interface is designed to be easy for the user to understand visually.

[0411] Step 8:

[0412] The device suggests and plays music and entertainment based on the user's emotional state.

[0413] The device suggests relaxing music and entertainment to the user based on emotion analysis results from the server. The selected music is automatically played using the streaming service's API, enhancing the user's cooking experience.

[0414] (Application Example 2)

[0415] 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."

[0416] Modern people face the challenge of effectively managing their emotions while cooking within their limited time and resources amidst their busy daily lives. Furthermore, there is a lack of cooking support systems that provide emotionally responsive assistance during and before cooking. Therefore, there is a need for technology that allows users to enjoy cooking more comfortably and efficiently.

[0417] 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.

[0418] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints; means for identifying the user's emotional state and dynamically adjusting the cooking procedures accordingly; and means for operating emotionally responsive audio feedback, visual notifications, or stress-relieving entertainment. This enables users to receive cooking assistance tailored to their emotions, thereby improving cooking efficiency and emotional satisfaction.

[0419] "User preferences" refer to the cooking styles, ingredient information, and flavor tendencies that users have previously preferred.

[0420] "Inventory information" refers to data regarding the quantity and expiration date of ingredients and materials available for cooking.

[0421] "Time constraints" refer to the time available to the user for cooking or the desired timeframe for completing the cooking process.

[0422] "Recommendations for selecting cooking procedures" is a function that suggests the optimal cooking method or recipe based on the user's conditions.

[0423] "Identifying emotional states" refers to the process of analyzing the user's facial expressions and vocal characteristics to identify their emotions in real time.

[0424] "Dynamic adjustment" means instantly changing cooking procedures and suggestions based on real-time data.

[0425] "Voice feedback" is a technology that provides users with information and advice in real time using voice.

[0426] "Visual notification" refers to a system that presents information visually through displays, lighting, and other means.

[0427] "Entertainment for stress relief" refers to content such as music and videos designed to reduce the user's mental burden and promote relaxation.

[0428] To implement this invention, a user-operated terminal is required. This terminal is equipped with a high-performance camera and microphone capable of identifying the user's emotional state, and collects the user's facial expressions and voice in real time. This makes it possible to analyze the user's emotional state with high accuracy.

[0429] The server uses cloud-based artificial intelligence services, such as "Google Cloud Vision API" and "Amazon Rekognition," to analyze the collected emotional data. These services identify emotional states, and "Microsoft Azure Cognitive Services" is used to detect emotions from voice as well. Based on these analysis results, the server suggests appropriate cooking procedures to the user.

[0430] The cooking instructions suggested by the server are generated based on user preferences, inventory information, and constraints. This includes a process of deriving the optimal recipe using generative AI models such as IBM Watson. The suggested recipes may include cooking methods and gentle procedures that help relieve stress, depending on the user's emotional state.

[0431] The device can notify the user of suggestions through voice feedback and visual information. Furthermore, it provides an interactive experience to alleviate stress while cooking through entertainment such as music and videos that respond to emotions.

[0432] For example, if a user enters "I'm especially tired today," the system will suggest a relaxing recipe such as "Creamy Chicken Stew" and play calming classical music while cooking.

[0433] Examples of prompt statements include the following:

[0434] "I'm feeling down today. Could you please suggest some easy and delicious recipes?"

[0435] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0436] Step 1:

[0437] Users input cooking conditions through their device. In particular, they input their emotional state and specific cooking preferences in voice or text format. Based on this input, the system works with an emotion engine to collect voice and text data.

[0438] Step 2:

[0439] The device sends the input voice and facial expression data to an artificial intelligence service in the cloud. The server uses "Google Cloud Vision API" or "Amazon Rekognition" to identify the user's emotional state from the collected data. The input here is the user's voice and facial expression data, and the output is the analyzed emotional state.

[0440] Step 3:

[0441] The server uses generative AI models such as IBM Watson based on the analysis of the user's emotional state to generate an optimal recipe set for the user. Furthermore, it combines this with user preference data, inventory information, and time constraints. The input to this process is the analyzed emotional state and user profile data, and the output is the proposed optimal recipe.

[0442] Step 4:

[0443] The server sends the generated recipe set to the terminal. The terminal notifies the user visually or audibly. The user selects their preferred recipe from the displayed list. At this point, the input is the generated recipe data, and the output is the user's selection.

[0444] Step 5:

[0445] Based on the selected recipe, the device provides cooking instructions while utilizing music and visual content. If the user's emotional state changes during cooking, data is sent back to the server, and the cooking instructions are adjusted in real time. The input for this step is the user's choices and current emotional state, and the output is the adjusted cooking instructions and entertainment content.

[0446] 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.

[0447] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0448] 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.

[0449] [Third Embodiment]

[0450] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0451] 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.

[0452] 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).

[0453] 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.

[0454] 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.

[0455] 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).

[0456] 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.

[0457] 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.

[0458] 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.

[0459] 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.

[0460] 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.

[0461] 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".

[0462] This invention is configured as a system in which AI recommends the optimal cooking procedure based on user preferences, inventory information, and time constraints. The server analyzes this information and displays the appropriate cooking procedure on the user's device. It also features a smart timer function that manages progress and optimizes time to support the simultaneous execution of multiple cooking procedures. Furthermore, the inventory management system identifies ingredients nearing their expiration date in the refrigerator and provides cooking recommendations that include procedures for prioritizing the use of these ingredients.

[0463] Specifically, when a user inputs the conditions for the dish they want to cook, the system connects with the refrigerator to retrieve the status of the ingredients in stock. Based on this, the server refers to the user's preferences and past history to provide the optimal recipe. Based on the provided recipe, the terminal manages the time for each cooking step and sends notifications to the user at the appropriate time.

[0464] For example, if a user requests a chicken dish that can be prepared in under 30 minutes, the server will select a suitable recipe from among chicken dishes, taking into account the user's past preferences and current inventory. The terminal will then display a list of cooking steps and provide the user with voice and visual alerts as the cooking time changes. This allows the user to cook efficiently and reduces food waste.

[0465] The following describes the processing flow.

[0466] Step 1:

[0467] The user enters the cooking conditions (e.g., ingredients to be used, cooking time) into the app on their device.

[0468] Step 2:

[0469] The terminal sends the entered information, as well as inventory information obtained through its connection with the refrigerator, to the server.

[0470] Step 3:

[0471] The server uses an AI model to analyze user preferences and history based on the received data, and generates suitable recipe candidates.

[0472] Step 4:

[0473] The server sends a list of generated recipes to the terminal.

[0474] Step 5:

[0475] The device displays recommended cooking steps from the received recipes to the user.

[0476] Step 6:

[0477] The device is instructed to begin cooking based on the recipe selected by the user.

[0478] Step 7:

[0479] The terminal calculates the time required for each cooking step of the selected recipe and sends the information to the server.

[0480] Step 8:

[0481] The server optimizes cooking steps and creates a schedule to efficiently process multiple dishes.

[0482] Step 9:

[0483] The server sends an optimized cooking schedule to the terminal.

[0484] Step 10:

[0485] The device activates the smart cooking timer and notifies the user at the appropriate time for each step.

[0486] Step 11:

[0487] The refrigerator terminal periodically sends information about food inventory and expiration dates to the server.

[0488] Step 12:

[0489] The server identifies ingredients that are nearing their expiration date and generates recipes that prioritize their consumption.

[0490] Step 13:

[0491] The server sends the generated recipe to the terminal and suggests it to the user.

[0492] (Example 1)

[0493] 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."

[0494] Consumers face multiple challenges when preparing efficient and satisfying meals within limited timeframes, including managing ingredient inventory and optimizing cooking procedures. Furthermore, minimizing food waste while cooking according to users' personal preferences and time constraints is difficult.

[0495] 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.

[0496] In this invention, the server includes means for generating recommendations that optimize cooking procedures based on user preferences, inventory data, and time constraints; means for displaying the recommended cooking procedures on the user's terminal; and means for providing a timer function to monitor the progress of each cooking procedure and manage the time. This enables the user to cook according to their individual needs while efficiently using ingredients.

[0497] "User preferences" refer to information about the tastes, cooking styles, and ingredient choices that users prefer.

[0498] "Inventory data" refers to information about the food items currently stored in refrigerators and pantries, and their quantities.

[0499] "Time constraints" are conditions that indicate the range of time a user is allowed to spend on cooking.

[0500] "Means for generating recommendations" refers to technology that executes a process to derive the optimal cooking procedure based on the user's requests and circumstances.

[0501] "Means of displaying on a terminal" refers to technologies for displaying selected information on the screen of an electronic device used by the user.

[0502] The "timer function" is a feature that measures and manages the time for each step in cooking and notifies the user.

[0503] A "prompt message" is a text format in which the user enters specific cooking conditions they desire.

[0504] The "smart timer function" is a feature that efficiently manages the time for each cooking step and generates alerts according to the progress.

[0505] This invention is a system that provides optimal cooking procedures based on user preferences, inventory data, and time constraints. It is implemented using hardware such as a server and a refrigerator, and software such as a generative AI model.

[0506] The server receives prompt messages from the user and uses this information to generate cooking instructions using an AI model. The inventory management system works with the refrigerator and sends inventory data to the server. This data includes the type and quantity of ingredients, expiration dates, etc. Based on this, the server combines the user's past preference data and historical information to identify the optimal recipe.

[0507] The device receives information from the server and displays cooking instructions in a user-friendly format. A smart timer function manages the timing of each cooking step, and the device provides voice and visual notifications to the user. These notifications allow the user to proceed appropriately according to the cooking process.

[0508] As a concrete example, consider a scenario where a user gives the system instructions using the prompt, "A chicken dish that can be made in under 30 minutes." In this case, the server utilizes a generative AI model to recommend the optimal chicken dish and sends cooking instructions to the terminal, taking into account inventory status and the user's preferences. The terminal displays the instructions step by step, and a timer function notifies the user of appropriate alerts at each step.

[0509] This system allows users to cook efficiently, reduce food waste, and prepare satisfying meals within time constraints.

[0510] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0511] Step 1:

[0512] The user enters conditions for the dish they want to cook into the terminal. For example, it might provide a prompt message such as "a chicken dish that can be made in 30 minutes or less." This input specifies the cooking timeframe and becomes data sent to the system.

[0513] Step 2:

[0514] The terminal works in conjunction with the refrigerator to retrieve current inventory data from the inventory management system. This data includes the type, quantity, and expiration date of the ingredients. The terminal sends this inventory data to a server, and this information is used to optimize cooking procedures.

[0515] Step 3:

[0516] The server receives user prompts and inventory data. Using a generative AI model, it also references the user's past preferences and history to generate the optimal cooking procedure. In this process, a recipe that matches the input conditions provided by the user is selected, and that information is sent to the terminal.

[0517] Step 4:

[0518] The terminal displays cooking instructions received from the server on the screen in an easy-to-understand format. Furthermore, it uses a smart timer function to set time for each cooking step and prepares alerts tailored to each step. This output allows the user to proceed with cooking through visual and audible notifications.

[0519] Step 5:

[0520] Users begin cooking by following the displayed instructions and timer alerts. Based on the timer notifications provided by the device, they can understand the appropriate timing for each cooking step and proceed efficiently. This process makes it possible to complete a meal within a limited time while minimizing food waste.

[0521] (Application Example 1)

[0522] 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."

[0523] In modern households, the time available for cooking is limited due to busy daily schedules, and food waste is common. Therefore, users are required to complete cooking within a set timeframe while efficiently utilizing ingredients. However, traditional methods have struggled to automatically assemble the optimal cooking procedure while considering the expiration dates and inventory levels of individual ingredients. Furthermore, there remain challenges in providing appropriate instructions to automated machines when cooking without human intervention.

[0524] 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.

[0525] In this invention, the server includes means for selecting cooking procedures and generating recommendations based on user preferences, inventory data, and time constraints; means for presenting the recommended cooking procedures to the user's equipment; and means for providing a timer for managing the progress of each cooking procedure and for time management. This enables an automated humanoid machine to efficiently carry out the work according to the cooking procedures, minimizing food waste, and providing dishes that meet the user's preferences.

[0526] "User preferences" refer to the tendencies of individual users regarding foods and dishes they like, their past selection history, and their preference patterns.

[0527] "Inventory data" refers to data that includes information on the current quantity and expiration dates of food ingredients in refrigerators and food storage areas.

[0528] "Time constraints" refer to conditions that indicate the time limit a user has for cooking, or the target time by which a particular dish should be served.

[0529] "Means of generating recommendations" refers to processes or technologies for determining and suggesting the optimal cooking procedure based on user preferences, inventory data, and time constraints.

[0530] "User equipment" refers to electronic devices and other devices that the user owns and is expected to use, including smartphones and tablets.

[0531] "Managing the progress of the cooking process" refers to planning and monitoring each step of the cooking process to ensure it proceeds sequentially and efficiently.

[0532] "Means of providing a timing device" refers to functions or devices that provide notifications or alerts at the optimal timing for each step of a cooking procedure.

[0533] "Food ingredients" refers to all ingredients used for cooking, including meats, vegetables, and seasonings.

[0534] A "humanoid machine" refers to a robot or mechanical device designed to automatically perform cooking tasks by mimicking human manual labor.

[0535] This invention relates to a cooking support system for user use. The server receives user preferences, inventory data, and time constraints as input data and generates an optimal cooking procedure. This cooking procedure is suggested through the user's device and displayed on the device.

[0536] The server uses a Python-based program and an AI model to generate optimal recipes. TensorFlow is used to analyze user preferences, ensuring that the suggested recipes are optimal based on the user's past history and preferences. Furthermore, the server integrates with inventory sensors to monitor inventory data in the refrigerator and adjusts the system to prioritize food ingredients nearing their expiration dates.

[0537] The terminal uses a timer to count down the optimal cooking time and notifies the user via voice and visuals. The user can receive this information using a smartphone or tablet and proceed with cooking according to the instructions. When a humanoid robot is performing the cooking, it automatically proceeds with the cooking based on instructions from the server and notifies the user as needed.

[0538] For example, if a user enters a prompt such as "I want to make a delicious chicken recipe in a short amount of time," the system will consider current inventory and past preference data to suggest a chicken dish that can be completed in under 30 minutes. In this way, users can cook efficiently, and the efficient use of food ingredients is promoted.

[0539] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0540] Step 1:

[0541] The server receives a prompt from the user. The prompt may include a request such as, "I want to make a delicious chicken recipe in a short amount of time." The server then inputs the user's request as text data and prepares it for the next processing step.

[0542] Step 2:

[0543] The server communicates with inventory management sensors to obtain inventory data for food ingredients in the refrigerator. Here, the data from the sensors serves as input, determining the type, quantity, and expiration date of the food ingredients. The inventory data is then output as information necessary for the next processing step.

[0544] Step 3:

[0545] The server uses an AI model to generate the optimal cooking procedure based on the acquired inventory data and prompt content. Using TensorFlow, it creates a recipe that can be cooked within 30 minutes, comparing it with user preferences and past history. Here, preference data and inventory data are used as input, and appropriate recipe information is output.

[0546] Step 4:

[0547] The server sends the generated recipe information to the user's terminal. The terminal displays the received recipe information on its screen and provides the user with cooking instructions. The recipe information serves as input, and the user receives output that allows them to visually confirm the cooking instructions.

[0548] Step 5:

[0549] The device uses a timer to manage time at each cooking step and alerts the user at the appropriate times. The timer measures the cooking time as an input value, and outputs it to the user as audio or visual alerts.

[0550] Step 6:

[0551] The user follows the instructions on the terminal to proceed with cooking. The user's actions become input, and the progress of the cooking is displayed as output.

[0552] Step 7:

[0553] The server sends instructions to the humanoid robot as needed to proceed with the automated cooking process. Here, the instructions generated by the AI ​​become the input, and the humanoid robot automatically outputs actions to perform the cooking.

[0554] 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.

[0555] This invention is a cooking support system that integrates an emotion engine to identify the user's emotional state, in addition to user preferences, inventory information, and time constraints. Based on the cooking conditions entered by the user, the server uses the emotion engine to analyze the user's emotional state and flexibly adjusts the cooking procedure accordingly. It enables the provision of appropriate voice feedback, visual notifications, and suggestions of music and entertainment to alleviate user stress, depending on the user's emotions.

[0556] When a user enters cooking requirements via a terminal, the system retrieves inventory information by connecting with the refrigerator. The server then generates an optimal recipe based on this data, the user's existing preference data, and their current emotional state obtained from the emotion engine. The generated recipes are displayed on the terminal, and the user can select one from them.

[0557] For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting cooking methods and recipes with calming procedures. Furthermore, the device will play relaxing music during cooking to reduce the user's stress. In this way, the cooking procedure is dynamically adjusted to the user's emotions, improving the cooking experience, including emotional support.

[0558] The following describes the processing flow.

[0559] Step 1:

[0560] The user enters the cooking conditions (ingredients used, cooking time, etc.) into the terminal.

[0561] Step 2:

[0562] The terminal sends the entered conditions and refrigerator inventory information to the server.

[0563] Step 3:

[0564] The server acquires voice and facial expression data from the terminal to analyze the user's emotional state using an emotion engine.

[0565] Step 4:

[0566] The server uses an AI model to generate optimal recipe candidates based on user preferences, inventory information, time constraints, and emotional state.

[0567] Step 5:

[0568] The server creates a list of generated recipes, along with additional suggestions tailored to the user's mood (e.g., relaxing music), and sends them to the terminal.

[0569] Step 6:

[0570] The device displays received recipes and suggestions to the user and provides visual and audio feedback.

[0571] Step 7:

[0572] The user selects a suggested recipe and additional features, and then gives the device instructions to begin cooking.

[0573] Step 8:

[0574] The device sends the time required for the cooking steps of the selected recipe to the server and prepares to start the timer.

[0575] Step 9:

[0576] The server optimizes the cooking steps, generates a time schedule that takes emotional states into account, and sends it to the terminal.

[0577] Step 10:

[0578] The device activates a smart cooking timer, provides voice notifications and plays music according to the time, and guides the user through the cooking process.

[0579] Step 11:

[0580] When cooking is complete, the device notifies the user and sends data to the server, based on feedback from the emotion engine, to be used for the next analysis.

[0581] (Example 2)

[0582] 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."

[0583] In modern life, users are busy and seek an efficient and enjoyable cooking experience. However, when cooking within limited time, it is difficult to consider the availability and expiration dates of ingredients, as well as the user's emotional state. This results in inefficient cooking, reduced food waste, and a lack of emotional support for the user. A system is needed to solve these problems and improve the cooking experience.

[0584] 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.

[0585] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on the user's preferences, inventory information, time constraints, and emotional state; means for presenting the recommended cooking procedures to the user's device and providing voice feedback and visual notifications based on the emotional state; and means for performing emotional analysis and suggesting music or entertainment according to the results. This makes it possible to suggest cooking procedures that take the user's emotional state into consideration, thereby realizing a comfortable and efficient cooking experience.

[0586] "User preferences" refer to information based on the tastes and preferences of individual users.

[0587] "Inventory information" refers to data about the types and quantities of food and ingredients stored in the kitchen or pantry.

[0588] "Time constraints" are conditions that indicate the limit of the time a user can spend cooking.

[0589] "Emotional state" refers to information that indicates the user's current psychological state, and includes elements such as stress, relaxation, and happiness.

[0590] "Cooking procedure" refers to the series of steps or processes necessary to complete a dish.

[0591] "Means of generating recommendations" refers to algorithms and system processes that provide users with the optimal cooking procedure.

[0592] "Voice feedback" is a function that provides information and guidance via voice in response to the user's actions and situation.

[0593] "Visual notifications" refer to visual information, including notifications and warnings, displayed on the device screen.

[0594] A "timekeeping device" is a device or function for measuring time that helps with the progress and time management of cooking.

[0595] "Emotional analysis" is a technology or process that analyzes a user's emotional state from data and identifies that state.

[0596] "Means of suggesting entertainment" refers to functions and technologies that suggest relaxation-oriented content such as music and video content that are tailored to the user's emotional state.

[0597] This invention is a system that proposes the optimal cooking procedure, taking into account the user's preferences, inventory information, time constraints, and emotional state. The user inputs cooking conditions using a dedicated terminal. Specifically, they can input the type of dish, desired cooking time, and ingredients to be used. Based on this input, the terminal transmits this data to a server.

[0598] The server executes specific procedures based on conditions entered by the user. It acquires inventory information by linking with external devices such as smart refrigerators and analyzes the user's current emotional state using an emotion engine. This analysis uses data analysis software to identify emotions from voice data and facial recognition data. By using libraries such as EmotionAI, emotions can be quantified.

[0599] After integrating this data, the server uses a generative AI model to generate the optimal recipe based on preference data, inventory data, and sentiment data. At this time, the AI ​​algorithm considers the user's past choices and emotional tendencies to make suggestions that match their current emotions.

[0600] Finally, the server sends the generated recipe to the device, which then visually presents it to the user. Based on the user's selected recipe, the device can then suggest and play audio feedback or relaxing music. The music selection utilizes APIs from common music streaming services.

[0601] For example, if a user inputs "I want to make a relaxing meal," the emotion engine will determine the user's stress level, and the server will suggest a recipe for a relaxing meal. Furthermore, the device will play ambient music that matches the user's emotions. An example of a prompt for the generative AI model would be, "Please tell me about a relaxing meal. My current emotional state is stressed. Please suggest the best recipe and music."

[0602] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0603] Step 1:

[0604] The user enters the cooking conditions.

[0605] The user uses a terminal to enter conditions such as the type of dish, desired cooking time, and ingredients to be used into a text form. This input data forms the basis for processing in the next step.

[0606] Step 2:

[0607] The terminal sends the input data to the server.

[0608] The terminal converts the cooking conditions entered by the user into a digital format and securely transmits them to the server via the internet. A secure protocol is used for this transmission. The input data is used for analysis on the server.

[0609] Step 3:

[0610] The server retrieves inventory information.

[0611] The server communicates with external devices such as smart refrigerators to acquire food inventory data from within the refrigerator. This data is collected using sensors and image recognition technology within the refrigerator. This inventory data is then used in the next step to select recipes.

[0612] Step 4:

[0613] The server uses an emotion engine to analyze the user's emotions.

[0614] The server uses an emotion engine to quantify the user's emotional state based on the user's voice input and past usage information. The analysis results in levels of stress and relaxation, which are then reflected in recipe suggestions.

[0615] Step 5:

[0616] The server generates the optimal recipe using an AI model.

[0617] The server integrates the user preferences, inventory information, and emotional state mentioned above, and uses a generative AI model to generate the optimal recipe. The model operates using a prompt as input, and the output is cooking instructions. The string "Please suggest a relaxing recipe" is used as the prompt.

[0618] Step 6:

[0619] The server sends the generated recipe to the terminal.

[0620] The server transfers the generated recipe data to the terminal. This output data serves as the source of information for visual display on the terminal's screen.

[0621] Step 7:

[0622] The device displays the recipe to the user.

[0623] The device visually presents the received recipe to the user. Cooking instructions, ingredient list, and estimated preparation time are displayed on the screen. The interface is designed to be easy for the user to understand visually.

[0624] Step 8:

[0625] The device suggests and plays music and entertainment based on the user's emotional state.

[0626] The device suggests relaxing music and entertainment to the user based on emotion analysis results from the server. The selected music is automatically played using the streaming service's API, enhancing the user's cooking experience.

[0627] (Application Example 2)

[0628] 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."

[0629] Modern people face the challenge of effectively managing their emotions while cooking within their limited time and resources amidst their busy daily lives. Furthermore, there is a lack of cooking support systems that provide emotionally responsive assistance during and before cooking. Therefore, there is a need for technology that allows users to enjoy cooking more comfortably and efficiently.

[0630] 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.

[0631] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints; means for identifying the user's emotional state and dynamically adjusting the cooking procedures accordingly; and means for operating emotionally responsive audio feedback, visual notifications, or stress-relieving entertainment. This enables users to receive cooking assistance tailored to their emotions, thereby improving cooking efficiency and emotional satisfaction.

[0632] "User preferences" refer to the cooking styles, ingredient information, and flavor tendencies that users have previously preferred.

[0633] "Inventory information" refers to data regarding the quantity and expiration date of ingredients and materials available for cooking.

[0634] "Time constraints" refer to the time available to the user for cooking or the desired timeframe for completing the cooking process.

[0635] "Recommendations for selecting cooking procedures" is a function that suggests the optimal cooking method or recipe based on the user's conditions.

[0636] "Identifying emotional states" refers to the process of analyzing the user's facial expressions and vocal characteristics to identify their emotions in real time.

[0637] "Dynamic adjustment" means instantly changing cooking procedures and suggestions based on real-time data.

[0638] "Voice feedback" is a technology that provides users with information and advice in real time using voice.

[0639] "Visual notification" refers to a system that presents information visually through displays, lighting, and other means.

[0640] "Entertainment for stress relief" refers to content such as music and videos designed to reduce the user's mental burden and promote relaxation.

[0641] To implement this invention, a user-operated terminal is required. This terminal is equipped with a high-performance camera and microphone capable of identifying the user's emotional state, and collects the user's facial expressions and voice in real time. This makes it possible to analyze the user's emotional state with high accuracy.

[0642] The server uses cloud-based artificial intelligence services, such as "Google Cloud Vision API" and "Amazon Rekognition," to analyze the collected emotional data. These services identify emotional states, and "Microsoft Azure Cognitive Services" is used to detect emotions from voice as well. Based on these analysis results, the server suggests appropriate cooking procedures to the user.

[0643] The cooking instructions suggested by the server are generated based on user preferences, inventory information, and constraints. This includes a process of deriving the optimal recipe using generative AI models such as IBM Watson. The suggested recipes may include cooking methods and gentle procedures that help relieve stress, depending on the user's emotional state.

[0644] The device can notify the user of suggestions through voice feedback and visual information. Furthermore, it provides an interactive experience to alleviate stress while cooking through entertainment such as music and videos that respond to emotions.

[0645] For example, if a user enters "I'm especially tired today," the system will suggest a relaxing recipe such as "Creamy Chicken Stew" and play calming classical music while cooking.

[0646] Examples of prompt statements include the following:

[0647] "I'm feeling down today. Could you please suggest some easy and delicious recipes?"

[0648] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0649] Step 1:

[0650] Users input cooking conditions through their device. In particular, they input their emotional state and specific cooking preferences in voice or text format. Based on this input, the system works with an emotion engine to collect voice and text data.

[0651] Step 2:

[0652] The device sends the input voice and facial expression data to an artificial intelligence service in the cloud. The server uses "Google Cloud Vision API" or "Amazon Rekognition" to identify the user's emotional state from the collected data. The input here is the user's voice and facial expression data, and the output is the analyzed emotional state.

[0653] Step 3:

[0654] The server uses generative AI models such as IBM Watson based on the analysis of the user's emotional state to generate an optimal recipe set for the user. Furthermore, it combines this with user preference data, inventory information, and time constraints. The input to this process is the analyzed emotional state and user profile data, and the output is the proposed optimal recipe.

[0655] Step 4:

[0656] The server sends the generated recipe set to the terminal. The terminal notifies the user visually or audibly. The user selects their preferred recipe from the displayed list. At this point, the input is the generated recipe data, and the output is the user's selection.

[0657] Step 5:

[0658] Based on the selected recipe, the device provides cooking instructions while utilizing music and visual content. If the user's emotional state changes during cooking, data is sent back to the server, and the cooking instructions are adjusted in real time. The input for this step is the user's choices and current emotional state, and the output is the adjusted cooking instructions and entertainment content.

[0659] 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.

[0660] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0661] 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.

[0662] [Fourth Embodiment]

[0663] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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).

[0669] 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.

[0670] 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.

[0671] 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.

[0672] 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.

[0673] 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.

[0674] 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.

[0675] 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".

[0676] This invention is configured as a system in which AI recommends the optimal cooking procedure based on user preferences, inventory information, and time constraints. The server analyzes this information and displays the appropriate cooking procedure on the user's device. It also features a smart timer function that manages progress and optimizes time to support the simultaneous execution of multiple cooking procedures. Furthermore, the inventory management system identifies ingredients nearing their expiration date in the refrigerator and provides cooking recommendations that include procedures for prioritizing the use of these ingredients.

[0677] Specifically, when a user inputs the conditions for the dish they want to cook, the system connects with the refrigerator to retrieve the status of the ingredients in stock. Based on this, the server refers to the user's preferences and past history to provide the optimal recipe. Based on the provided recipe, the terminal manages the time for each cooking step and sends notifications to the user at the appropriate time.

[0678] For example, if a user requests a chicken dish that can be prepared in under 30 minutes, the server will select a suitable recipe from among chicken dishes, taking into account the user's past preferences and current inventory. The terminal will then display a list of cooking steps and provide the user with voice and visual alerts as the cooking time changes. This allows the user to cook efficiently and reduces food waste.

[0679] The following describes the processing flow.

[0680] Step 1:

[0681] The user enters the cooking conditions (e.g., ingredients to be used, cooking time) into the app on their device.

[0682] Step 2:

[0683] The terminal sends the entered information, as well as inventory information obtained through its connection with the refrigerator, to the server.

[0684] Step 3:

[0685] The server uses an AI model to analyze user preferences and history based on the received data, and generates suitable recipe candidates.

[0686] Step 4:

[0687] The server sends a list of generated recipes to the terminal.

[0688] Step 5:

[0689] The device displays recommended cooking steps from the received recipes to the user.

[0690] Step 6:

[0691] The device is instructed to begin cooking based on the recipe selected by the user.

[0692] Step 7:

[0693] The terminal calculates the time required for each cooking step of the selected recipe and sends the information to the server.

[0694] Step 8:

[0695] The server optimizes cooking steps and creates a schedule to efficiently process multiple dishes.

[0696] Step 9:

[0697] The server sends an optimized cooking schedule to the terminal.

[0698] Step 10:

[0699] The device activates the smart cooking timer and notifies the user at the appropriate time for each step.

[0700] Step 11:

[0701] The refrigerator terminal periodically sends information about food inventory and expiration dates to the server.

[0702] Step 12:

[0703] The server identifies ingredients that are nearing their expiration date and generates recipes that prioritize their consumption.

[0704] Step 13:

[0705] The server sends the generated recipe to the terminal and suggests it to the user.

[0706] (Example 1)

[0707] 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".

[0708] Consumers face multiple challenges when preparing efficient and satisfying meals within limited timeframes, including managing ingredient inventory and optimizing cooking procedures. Furthermore, minimizing food waste while cooking according to users' personal preferences and time constraints is difficult.

[0709] 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.

[0710] In this invention, the server includes means for generating recommendations that optimize cooking procedures based on user preferences, inventory data, and time constraints; means for displaying the recommended cooking procedures on the user's terminal; and means for providing a timer function to monitor the progress of each cooking procedure and manage the time. This enables the user to cook according to their individual needs while efficiently using ingredients.

[0711] "User preferences" refer to information about the tastes, cooking styles, and ingredient choices that users prefer.

[0712] "Inventory data" refers to information about the food items currently stored in refrigerators and pantries, and their quantities.

[0713] "Time constraints" are conditions that indicate the range of time a user is allowed to spend on cooking.

[0714] "Means for generating recommendations" refers to technology that executes a process to derive the optimal cooking procedure based on the user's requests and circumstances.

[0715] "Means of displaying on a terminal" refers to technologies for displaying selected information on the screen of an electronic device used by the user.

[0716] The "timer function" is a feature that measures and manages the time for each step in cooking and notifies the user.

[0717] A "prompt message" is a text format in which the user enters specific cooking conditions they desire.

[0718] The "smart timer function" is a feature that efficiently manages the time for each cooking step and generates alerts according to the progress.

[0719] This invention is a system that provides optimal cooking procedures based on user preferences, inventory data, and time constraints. It is implemented using hardware such as a server and a refrigerator, and software such as a generative AI model.

[0720] The server receives prompt messages from the user and uses this information to generate cooking instructions using an AI model. The inventory management system works with the refrigerator and sends inventory data to the server. This data includes the type and quantity of ingredients, expiration dates, etc. Based on this, the server combines the user's past preference data and historical information to identify the optimal recipe.

[0721] The device receives information from the server and displays cooking instructions in a user-friendly format. A smart timer function manages the timing of each cooking step, and the device provides voice and visual notifications to the user. These notifications allow the user to proceed appropriately according to the cooking process.

[0722] As a concrete example, consider a scenario where a user gives the system instructions using the prompt, "A chicken dish that can be made in under 30 minutes." In this case, the server utilizes a generative AI model to recommend the optimal chicken dish and sends cooking instructions to the terminal, taking into account inventory status and the user's preferences. The terminal displays the instructions step by step, and a timer function notifies the user of appropriate alerts at each step.

[0723] This system allows users to cook efficiently, reduce food waste, and prepare satisfying meals within time constraints.

[0724] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0725] Step 1:

[0726] The user enters conditions for the dish they want to cook into the terminal. For example, it might provide a prompt message such as "a chicken dish that can be made in 30 minutes or less." This input specifies the cooking timeframe and becomes data sent to the system.

[0727] Step 2:

[0728] The terminal works in conjunction with the refrigerator to retrieve current inventory data from the inventory management system. This data includes the type, quantity, and expiration date of the ingredients. The terminal sends this inventory data to a server, and this information is used to optimize cooking procedures.

[0729] Step 3:

[0730] The server receives user prompts and inventory data. Using a generative AI model, it also references the user's past preferences and history to generate the optimal cooking procedure. In this process, a recipe that matches the input conditions provided by the user is selected, and that information is sent to the terminal.

[0731] Step 4:

[0732] The terminal displays cooking instructions received from the server on the screen in an easy-to-understand format. Furthermore, it uses a smart timer function to set time for each cooking step and prepares alerts tailored to each step. This output allows the user to proceed with cooking through visual and audible notifications.

[0733] Step 5:

[0734] Users begin cooking by following the displayed instructions and timer alerts. Based on the timer notifications provided by the device, they can understand the appropriate timing for each cooking step and proceed efficiently. This process makes it possible to complete a meal within a limited time while minimizing food waste.

[0735] (Application Example 1)

[0736] 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".

[0737] In modern households, the time available for cooking is limited due to busy daily schedules, and food waste is common. Therefore, users are required to complete cooking within a set timeframe while efficiently utilizing ingredients. However, traditional methods have struggled to automatically assemble the optimal cooking procedure while considering the expiration dates and inventory levels of individual ingredients. Furthermore, there remain challenges in providing appropriate instructions to automated machines when cooking without human intervention.

[0738] 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.

[0739] In this invention, the server includes means for selecting cooking procedures and generating recommendations based on user preferences, inventory data, and time constraints; means for presenting the recommended cooking procedures to the user's equipment; and means for providing a timer for managing the progress of each cooking procedure and for time management. This enables an automated humanoid machine to efficiently carry out the work according to the cooking procedures, minimizing food waste, and providing dishes that meet the user's preferences.

[0740] "User preferences" refer to the tendencies of individual users regarding foods and dishes they like, their past selection history, and their preference patterns.

[0741] "Inventory data" refers to data that includes information on the current quantity and expiration dates of food ingredients in refrigerators and food storage areas.

[0742] "Time constraints" refer to conditions that indicate the time limit a user has for cooking, or the target time by which a particular dish should be served.

[0743] "Means of generating recommendations" refers to processes or technologies for determining and suggesting the optimal cooking procedure based on user preferences, inventory data, and time constraints.

[0744] "User equipment" refers to electronic devices and other devices that the user owns and is expected to use, including smartphones and tablets.

[0745] "Managing the progress of the cooking process" refers to planning and monitoring each step of the cooking process to ensure it proceeds sequentially and efficiently.

[0746] "Means of providing a timing device" refers to functions or devices that provide notifications or alerts at the optimal timing for each step of a cooking procedure.

[0747] "Food ingredients" refers to all ingredients used for cooking, including meats, vegetables, and seasonings.

[0748] A "humanoid machine" refers to a robot or mechanical device designed to automatically perform cooking tasks by mimicking human manual labor.

[0749] This invention relates to a cooking support system for user use. The server receives user preferences, inventory data, and time constraints as input data and generates an optimal cooking procedure. This cooking procedure is suggested through the user's device and displayed on the device.

[0750] The server uses a Python-based program and an AI model to generate optimal recipes. TensorFlow is used to analyze user preferences, ensuring that the suggested recipes are optimal based on the user's past history and preferences. Furthermore, the server integrates with inventory sensors to monitor inventory data in the refrigerator and adjusts the system to prioritize food ingredients nearing their expiration dates.

[0751] The terminal uses a timer to count down the optimal cooking time and notifies the user via voice and visuals. The user can receive this information using a smartphone or tablet and proceed with cooking according to the instructions. When a humanoid robot is performing the cooking, it automatically proceeds with the cooking based on instructions from the server and notifies the user as needed.

[0752] For example, if a user enters a prompt such as "I want to make a delicious chicken recipe in a short amount of time," the system will consider current inventory and past preference data to suggest a chicken dish that can be completed in under 30 minutes. In this way, users can cook efficiently, and the efficient use of food ingredients is promoted.

[0753] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0754] Step 1:

[0755] The server receives a prompt from the user. The prompt may include a request such as, "I want to make a delicious chicken recipe in a short amount of time." The server then inputs the user's request as text data and prepares it for the next processing step.

[0756] Step 2:

[0757] The server communicates with inventory management sensors to obtain inventory data for food ingredients in the refrigerator. Here, the data from the sensors serves as input, determining the type, quantity, and expiration date of the food ingredients. The inventory data is then output as information necessary for the next processing step.

[0758] Step 3:

[0759] The server uses an AI model to generate the optimal cooking procedure based on the acquired inventory data and prompt content. Using TensorFlow, it creates a recipe that can be cooked within 30 minutes, comparing it with user preferences and past history. Here, preference data and inventory data are used as input, and appropriate recipe information is output.

[0760] Step 4:

[0761] The server sends the generated recipe information to the user's terminal. The terminal displays the received recipe information on its screen and provides the user with cooking instructions. The recipe information serves as input, and the user receives output that allows them to visually confirm the cooking instructions.

[0762] Step 5:

[0763] The device uses a timer to manage time at each cooking step and alerts the user at the appropriate times. The timer measures the cooking time as an input value, and outputs it to the user as audio or visual alerts.

[0764] Step 6:

[0765] The user follows the instructions on the terminal to proceed with cooking. The user's actions become input, and the progress of the cooking is displayed as output.

[0766] Step 7:

[0767] The server sends instructions to the humanoid robot as needed to proceed with the automated cooking process. Here, the instructions generated by the AI ​​become the input, and the humanoid robot automatically outputs actions to perform the cooking.

[0768] 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.

[0769] This invention is a cooking support system that integrates an emotion engine to identify the user's emotional state, in addition to user preferences, inventory information, and time constraints. Based on the cooking conditions entered by the user, the server uses the emotion engine to analyze the user's emotional state and flexibly adjusts the cooking procedure accordingly. It enables the provision of appropriate voice feedback, visual notifications, and suggestions of music and entertainment to alleviate user stress, depending on the user's emotions.

[0770] When a user enters cooking requirements via a terminal, the system retrieves inventory information by connecting with the refrigerator. The server then generates an optimal recipe based on this data, the user's existing preference data, and their current emotional state obtained from the emotion engine. The generated recipes are displayed on the terminal, and the user can select one from them.

[0771] For example, if the emotion engine detects that the user is feeling stressed, the server will prioritize suggesting cooking methods and recipes with calming procedures. Furthermore, the device will play relaxing music during cooking to reduce the user's stress. In this way, the cooking procedure is dynamically adjusted to the user's emotions, improving the cooking experience, including emotional support.

[0772] The following describes the processing flow.

[0773] Step 1:

[0774] The user enters the cooking conditions (ingredients used, cooking time, etc.) into the terminal.

[0775] Step 2:

[0776] The terminal sends the entered conditions and refrigerator inventory information to the server.

[0777] Step 3:

[0778] The server acquires voice and facial expression data from the terminal to analyze the user's emotional state using an emotion engine.

[0779] Step 4:

[0780] The server uses an AI model to generate optimal recipe candidates based on user preferences, inventory information, time constraints, and emotional state.

[0781] Step 5:

[0782] The server creates a list of generated recipes, along with additional suggestions tailored to the user's mood (e.g., relaxing music), and sends them to the terminal.

[0783] Step 6:

[0784] The device displays received recipes and suggestions to the user and provides visual and audio feedback.

[0785] Step 7:

[0786] The user selects a suggested recipe and additional features, and then gives the device instructions to begin cooking.

[0787] Step 8:

[0788] The device sends the time required for the cooking steps of the selected recipe to the server and prepares to start the timer.

[0789] Step 9:

[0790] The server optimizes the cooking steps, generates a time schedule that takes emotional states into account, and sends it to the terminal.

[0791] Step 10:

[0792] The device activates a smart cooking timer, provides voice notifications and plays music according to the time, and guides the user through the cooking process.

[0793] Step 11:

[0794] When cooking is complete, the device notifies the user and sends data to the server, based on feedback from the emotion engine, to be used for the next analysis.

[0795] (Example 2)

[0796] 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".

[0797] In modern life, users are busy and seek an efficient and enjoyable cooking experience. However, when cooking within limited time, it is difficult to consider the availability and expiration dates of ingredients, as well as the user's emotional state. This results in inefficient cooking, reduced food waste, and a lack of emotional support for the user. A system is needed to solve these problems and improve the cooking experience.

[0798] 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.

[0799] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on the user's preferences, inventory information, time constraints, and emotional state; means for presenting the recommended cooking procedures to the user's device and providing voice feedback and visual notifications based on the emotional state; and means for performing emotional analysis and suggesting music or entertainment according to the results. This makes it possible to suggest cooking procedures that take the user's emotional state into consideration, thereby realizing a comfortable and efficient cooking experience.

[0800] "User preferences" refer to information based on the tastes and preferences of individual users.

[0801] "Inventory information" refers to data about the types and quantities of food and ingredients stored in the kitchen or pantry.

[0802] "Time constraints" are conditions that indicate the limit of the time a user can spend cooking.

[0803] "Emotional state" refers to information that indicates the user's current psychological state, and includes elements such as stress, relaxation, and happiness.

[0804] "Cooking procedure" refers to the series of steps or processes necessary to complete a dish.

[0805] "Means of generating recommendations" refers to algorithms and system processes that provide users with the optimal cooking procedure.

[0806] "Voice feedback" is a function that provides information and guidance via voice in response to the user's actions and situation.

[0807] "Visual notifications" refer to visual information, including notifications and warnings, displayed on the device screen.

[0808] A "timekeeping device" is a device or function for measuring time that helps with the progress and time management of cooking.

[0809] "Emotional analysis" is a technology or process that analyzes a user's emotional state from data and identifies that state.

[0810] "Means of suggesting entertainment" refers to functions and technologies that suggest relaxation-oriented content such as music and video content that are tailored to the user's emotional state.

[0811] This invention is a system that proposes the optimal cooking procedure, taking into account the user's preferences, inventory information, time constraints, and emotional state. The user inputs cooking conditions using a dedicated terminal. Specifically, they can input the type of dish, desired cooking time, and ingredients to be used. Based on this input, the terminal transmits this data to a server.

[0812] The server executes specific procedures based on conditions entered by the user. It acquires inventory information by linking with external devices such as smart refrigerators and analyzes the user's current emotional state using an emotion engine. This analysis uses data analysis software to identify emotions from voice data and facial recognition data. By using libraries such as EmotionAI, emotions can be quantified.

[0813] After integrating this data, the server uses a generative AI model to generate the optimal recipe based on preference data, inventory data, and sentiment data. At this time, the AI ​​algorithm considers the user's past choices and emotional tendencies to make suggestions that match their current emotions.

[0814] Finally, the server sends the generated recipe to the device, which then visually presents it to the user. Based on the user's selected recipe, the device can then suggest and play audio feedback or relaxing music. The music selection utilizes APIs from common music streaming services.

[0815] For example, if a user inputs "I want to make a relaxing meal," the emotion engine will determine the user's stress level, and the server will suggest a recipe for a relaxing meal. Furthermore, the device will play ambient music that matches the user's emotions. An example of a prompt for the generative AI model would be, "Please tell me about a relaxing meal. My current emotional state is stressed. Please suggest the best recipe and music."

[0816] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0817] Step 1:

[0818] The user enters the cooking conditions.

[0819] The user uses a terminal to enter conditions such as the type of dish, desired cooking time, and ingredients to be used into a text form. This input data forms the basis for processing in the next step.

[0820] Step 2:

[0821] The terminal sends the input data to the server.

[0822] The terminal converts the cooking conditions entered by the user into a digital format and securely transmits them to the server via the internet. A secure protocol is used for this transmission. The input data is used for analysis on the server.

[0823] Step 3:

[0824] The server retrieves inventory information.

[0825] The server communicates with external devices such as smart refrigerators to acquire food inventory data from within the refrigerator. This data is collected using sensors and image recognition technology within the refrigerator. This inventory data is then used in the next step to select recipes.

[0826] Step 4:

[0827] The server uses an emotion engine to analyze the user's emotions.

[0828] The server uses an emotion engine to quantify the user's emotional state based on the user's voice input and past usage information. The analysis results in levels of stress and relaxation, which are then reflected in recipe suggestions.

[0829] Step 5:

[0830] The server generates the optimal recipe using an AI model.

[0831] The server integrates the user preferences, inventory information, and emotional state mentioned above, and uses a generative AI model to generate the optimal recipe. The model operates using a prompt as input, and the output is cooking instructions. The string "Please suggest a relaxing recipe" is used as the prompt.

[0832] Step 6:

[0833] The server sends the generated recipe to the terminal.

[0834] The server transfers the generated recipe data to the terminal. This output data serves as the source of information for visual display on the terminal's screen.

[0835] Step 7:

[0836] The device displays the recipe to the user.

[0837] The device visually presents the received recipe to the user. Cooking instructions, ingredient list, and estimated preparation time are displayed on the screen. The interface is designed to be easy for the user to understand visually.

[0838] Step 8:

[0839] The device suggests and plays music and entertainment based on the user's emotional state.

[0840] The device suggests relaxing music and entertainment to the user based on emotion analysis results from the server. The selected music is automatically played using the streaming service's API, enhancing the user's cooking experience.

[0841] (Application Example 2)

[0842] 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".

[0843] Modern people face the challenge of effectively managing their emotions while cooking within their limited time and resources amidst their busy daily lives. Furthermore, there is a lack of cooking support systems that provide emotionally responsive assistance during and before cooking. Therefore, there is a need for technology that allows users to enjoy cooking more comfortably and efficiently.

[0844] 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.

[0845] In this invention, the server includes means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints; means for identifying the user's emotional state and dynamically adjusting the cooking procedures accordingly; and means for operating emotionally responsive audio feedback, visual notifications, or stress-relieving entertainment. This enables users to receive cooking assistance tailored to their emotions, thereby improving cooking efficiency and emotional satisfaction.

[0846] "User preferences" refer to the cooking styles, ingredient information, and flavor tendencies that users have previously preferred.

[0847] "Inventory information" refers to data regarding the quantity and expiration date of ingredients and materials available for cooking.

[0848] "Time constraints" refer to the time available to the user for cooking or the desired timeframe for completing the cooking process.

[0849] "Recommendations for selecting cooking procedures" is a function that suggests the optimal cooking method or recipe based on the user's conditions.

[0850] "Identifying emotional states" refers to the process of analyzing the user's facial expressions and vocal characteristics to identify their emotions in real time.

[0851] "Dynamic adjustment" means instantly changing cooking procedures and suggestions based on real-time data.

[0852] "Voice feedback" is a technology that provides users with information and advice in real time using voice.

[0853] "Visual notification" refers to a system that presents information visually through displays, lighting, and other means.

[0854] "Entertainment for stress relief" refers to content such as music and videos designed to reduce the user's mental burden and promote relaxation.

[0855] To implement this invention, a user-operated terminal is required. This terminal is equipped with a high-performance camera and microphone capable of identifying the user's emotional state, and collects the user's facial expressions and voice in real time. This makes it possible to analyze the user's emotional state with high accuracy.

[0856] The server uses cloud-based artificial intelligence services, such as "Google Cloud Vision API" and "Amazon Rekognition," to analyze the collected emotional data. These services identify emotional states, and "Microsoft Azure Cognitive Services" is used to detect emotions from voice as well. Based on these analysis results, the server suggests appropriate cooking procedures to the user.

[0857] The cooking instructions suggested by the server are generated based on user preferences, inventory information, and constraints. This includes a process of deriving the optimal recipe using generative AI models such as IBM Watson. The suggested recipes may include cooking methods and gentle procedures that help relieve stress, depending on the user's emotional state.

[0858] The device can notify the user of suggestions through voice feedback and visual information. Furthermore, it provides an interactive experience to alleviate stress while cooking through entertainment such as music and videos that respond to emotions.

[0859] For example, if a user enters "I'm especially tired today," the system will suggest a relaxing recipe such as "Creamy Chicken Stew" and play calming classical music while cooking.

[0860] Examples of prompt statements include the following:

[0861] "I'm feeling down today. Could you please suggest some easy and delicious recipes?"

[0862] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0863] Step 1:

[0864] Users input cooking conditions through their device. In particular, they input their emotional state and specific cooking preferences in voice or text format. Based on this input, the system works with an emotion engine to collect voice and text data.

[0865] Step 2:

[0866] The device sends the input voice and facial expression data to an artificial intelligence service in the cloud. The server uses "Google Cloud Vision API" or "Amazon Rekognition" to identify the user's emotional state from the collected data. The input here is the user's voice and facial expression data, and the output is the analyzed emotional state.

[0867] Step 3:

[0868] The server uses generative AI models such as IBM Watson based on the analysis of the user's emotional state to generate an optimal recipe set for the user. Furthermore, it combines this with user preference data, inventory information, and time constraints. The input to this process is the analyzed emotional state and user profile data, and the output is the proposed optimal recipe.

[0869] Step 4:

[0870] The server sends the generated recipe set to the terminal. The terminal notifies the user visually or audibly. The user selects their preferred recipe from the displayed list. At this point, the input is the generated recipe data, and the output is the user's selection.

[0871] Step 5:

[0872] Based on the selected recipe, the device provides cooking instructions while utilizing music and visual content. If the user's emotional state changes during cooking, data is sent back to the server, and the cooking instructions are adjusted in real time. The input for this step is the user's choices and current emotional state, and the output is the adjusted cooking instructions and entertainment content.

[0873] 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.

[0874] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] 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."

[0882] 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.

[0883] 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.

[0884] 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.

[0885] 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.

[0886] 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.

[0887] 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.

[0888] 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.

[0889] 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.

[0890] 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.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] The following is further disclosed regarding the embodiments described above.

[0895] (Claim 1)

[0896] A means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints,

[0897] A means of presenting recommended cooking procedures to the user's device,

[0898] A means of providing a timer for managing the progress of each cooking procedure and for time management,

[0899] A means of identifying procedures for prioritizing the consumption of ingredients nearing their expiration date,

[0900] A system that includes this.

[0901] (Claim 2)

[0902] The system according to claim 1, further comprising means for optimizing the progress of multiple cooking procedures based on the cooking time and ingredients selected by the user.

[0903] (Claim 3)

[0904] The system according to claim 1, further comprising means for tracking inventory and improving the efficiency of ingredient use based on expiration dates.

[0905] "Example 1"

[0906] (Claim 1)

[0907] A means for generating recommendations that optimize cooking procedures based on user preferences, inventory data, and time constraints,

[0908] A means of displaying recommended cooking procedures on the user's device,

[0909] A means of monitoring the progress of each cooking procedure and providing a timer function for managing the time,

[0910] A means of determining procedures for prioritizing the use of materials nearing their expiration date,

[0911] A method for generating the optimal recipe using a generative AI model based on a prompt message,

[0912] A means that has a function to clearly notify the user of each step in the cooking process,

[0913] A system that includes this.

[0914] (Claim 2)

[0915] The system according to claim 1, further comprising means for efficiently optimizing the progress of multiple cooking steps based on the cooking time and ingredients selected by the user.

[0916] (Claim 3)

[0917] The system according to claim 1, further comprising means for improving the efficiency of material use based on inventory management and expiration dates.

[0918] "Application Example 1"

[0919] (Claim 1)

[0920] A means for selecting cooking procedures and generating recommendations based on user preferences, inventory data, and time constraints,

[0921] A means of presenting recommended cooking procedures for the user's equipment,

[0922] A means of providing a timekeeping device for managing the progress of each cooking procedure and for time management,

[0923] A means of identifying procedures for prioritizing the use of food ingredients nearing their expiration date,

[0924] A means for sequentially transmitting instructions to a humanoid machine used for automated cooking,

[0925] A system that includes this.

[0926] (Claim 2)

[0927] The system according to claim 1, further comprising means for optimizing the progress of multiple cooking steps based on the cooking time and food ingredients selected by the user.

[0928] (Claim 3)

[0929] The system according to claim 1, further comprising means for tracking inventory and improving the efficiency of food ingredient use based on expiration dates, and having means for displaying the progress of cooking by a humanoid machine.

[0930] "Example 2 of combining an emotion engine"

[0931] (Claim 1)

[0932] A means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, time constraints, and emotional state,

[0933] A means for presenting recommended cooking procedures to the user's device and providing voice feedback and visual notifications based on emotional state,

[0934] A means for providing a timing device for managing the progress of each cooking procedure and for managing the time,

[0935] A means of identifying procedures for prioritizing the consumption of ingredients nearing their expiration date,

[0936] A means of performing emotional analysis and suggesting music and entertainment based on the results,

[0937] A system that includes this.

[0938] (Claim 2)

[0939] The system according to claim 1, further comprising means for optimizing the progress of multiple cooking procedures based on the cooking time and ingredients selected by the user, and for making adjustments according to the user's emotional state.

[0940] (Claim 3)

[0941] The system according to claim 1, further comprising means for tracking inventory and improving the efficiency of food use based on expiration dates, while taking into account the results of sentiment analysis.

[0942] "Application example 2 when combining with an emotional engine"

[0943] (Claim 1)

[0944] A means for generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints,

[0945] A means of presenting recommended cooking procedures to the user's device,

[0946] A means for providing a timing device for managing the progress of each cooking procedure and for managing the time,

[0947] A means of identifying procedures for prioritizing the consumption of ingredients nearing their expiration date,

[0948] A means for identifying the user's emotional state and dynamically adjusting the cooking procedure based on it,

[0949] Means of controlling emotion-responsive audio feedback, visual notifications, or entertainment for stress relief,

[0950] A system that includes this.

[0951] (Claim 2)

[0952] The system according to claim 1, further comprising means for optimizing the progress of multiple cooking procedures based on the cooking time and ingredients selected by the user.

[0953] (Claim 3)

[0954] The system according to claim 1, further comprising means for tracking inventory and improving the efficiency of ingredient use based on expiration dates. [Explanation of Symbols]

[0955] 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 generating recommendations for selecting cooking procedures based on user preferences, inventory information, and time constraints, A means of presenting recommended cooking procedures to the user's device, A means of providing a timer for managing the progress of each cooking procedure and for time management, A means of identifying procedures for prioritizing the consumption of ingredients nearing their expiration date, A system that includes this.

2. The system according to claim 1, further comprising means for optimizing the progress of multiple cooking procedures based on the cooking time and ingredients selected by the user.

3. The system according to claim 1, further comprising means for tracking inventory and improving the efficiency of ingredient use based on expiration dates.

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