System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving from a user an ingredient to be used for cooking and a name of a dish to be prepared; means for obtaining related recipe information from a database based on the ingredient and the name of the dish; means for generating an optimum cooking procedure for efficiently preparing a plurality of dishes based on the obtained recipe information; and means for providing the user with the generated cooking procedure and a food waste.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In modern households, cooking typically requires a lot of time and effort. Furthermore, people often end up buying more ingredients than they need, resulting in food waste. This situation is problematic both economically and environmentally, creating a demand for efficient and waste-free cooking methods. Furthermore, when cooking multiple dishes at the same time, it can be difficult to coordinate the efficiency and timing of cooking procedures, increasing the amount of work required. To solve these issues, a system is needed that optimizes cooking procedures and provides efficient cooking methods. [Means for solving the problem]

[0005] The present invention is a system that includes a means for receiving ingredients to be used in a dish and the name of the dish desired from a user, a means for retrieving related recipe information from a database based on the received information, a means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, a means for providing the generated cooking procedures to the user, a means for receiving the amounts of ingredients actually used from the user, and a means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future dishes. This allows multiple dishes to be cooked efficiently simultaneously, contributing to reducing food waste. Furthermore, cooking efficiency can be further improved by optimizing the order in which cooking utensils are used and standby times when generating the cooking procedures based on the retrieved recipe information. Furthermore, user convenience is enhanced by providing procedures for simultaneously preparing multiple dishes based on cooking conditions entered by the user.

[0006] A "user" is an entity that operates the system and provides information such as ingredients to be used in cooking and the name of the dish they wish to make.

[0007] "Ingredients" refer to the food ingredients used in making a dish, including tomatoes, chicken, potatoes, etc.

[0008] The "dish name" is a name that indicates a specific dish and is used to specify the dish that the user wants to make.

[0009] A "database" is a collection of information for storing and managing related recipe information, cooking instructions, ingredient details, etc.

[0010] "Recipe information" is detailed data that includes a list of ingredients needed to prepare a particular dish, their quantities, cooking steps, cooking time, etc.

[0011] A "cooking procedure" refers to a series of steps or processes that are performed to complete a dish.

[0012] "Cookware" refers to various cooking utensils and equipment used in cooking, including, for example, pots, frying pans, ovens, etc.

[0013] "Waiting time" refers to the time spent waiting while other steps in the cooking process proceed.

[0014] "Food waste" refers to the situation where food is wasted and discarded without being used.

[0015] "Optimization" refers to the process of increasing overall efficiency to maximize achievement of goals under specific conditions and constraints. [Brief explanation of the drawings]

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

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

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

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0037] The system of the present invention processes the information entered by the user about ingredients to be used in the dish and the name of the dish they want to make, and generates and provides optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[0038] overview

[0039] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[0040] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user.

[0041] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0042] System Operation

[0043] Receiving and Sending Information

[0044] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make through the terminal interface. For example, they input "tomato," "chicken," and "potato" as the ingredients they want to use, and specify "dish A" and "dish B" as the names of the dishes they want to make.

[0045] The device sends the entered information to the server, including the ingredient list and the name of the dish, as well as any specific cooking conditions (such as time limits and available cooking equipment).

[0046] Get recipe information

[0047] Based on the received user information, the server retrieves related recipe information from its internal database, including detailed recipes for dishes A and B (ingredients, amounts, cooking steps, cooking time, etc.).

[0048] Generating optimal cooking procedures

[0049] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently creating multiple dishes. For example,

[0050] "Boil the potatoes while you chop the tomatoes."

[0051] This includes steps such as "mashing potatoes while frying chicken."

[0052] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[0053] Providing instructions

[0054] The server then sends the generated cooking instructions to the device. The instructions are structured in an easy-to-understand step-by-step format, and include diagrams and videos as needed.

[0055] The terminal displays these steps to the user, allowing them to follow them in real time.

[0056] Recording usage and suggesting next time

[0057] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[0058] The terminal transmits the input usage data to the server.

[0059] The server uses this data to manage food waste and generates suggestions on how to best use ingredients in the future.

[0060] Specific examples

[0061] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0062] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[0063] 2. The device sends this information to the server.

[0064] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0065] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0066] 5. The server sends the generated procedure to the terminal, which displays it to the user.

[0067] 6. The user follows the instructions to proceed with cooking, and after cooking is complete, enters the amount of ingredients used into the terminal.

[0068] 7. The device sends the usage data to the server, which then uses this data to suggest the optimal way to use ingredients for the next time onwards.

[0069] In this way, the system of the present invention supports the user's cooking process and enables efficient and waste-free cooking.

[0070] The processing flow will be explained below.

[0071] Step 1:

[0072] The user uses the terminal interface to input ingredients and the name of the dish they want to make, for example, "tomatoes," "chicken," and "potatoes," and names the dishes such as "Dish A" and "Dish B."

[0073] Step 2:

[0074] The device receives the information about ingredients and the name of the dish entered by the user and prepares to send it to the system. It also sends specific cooking conditions (e.g., cooking time limits and available cooking equipment) if necessary.

[0075] Step 3:

[0076] The terminal transmits the user-entered data to the server, including the list of ingredients, the name of the dish, and cooking conditions.

[0077] Step 4:

[0078] The server analyzes the received user data and accesses the database to retrieve related recipe information, such as the list of ingredients, quantities, cooking steps, and cooking time for the specified dish.

[0079] Step 5:

[0080] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0081] Step 6:

[0082] The server then sends the generated optimal cooking instructions to the device. These instructions are structured step by step and are organized in a way that makes them easy for the user to understand.

[0083] Step 7:

[0084] The terminal displays the cooking instructions sent from the server to the user, and the user can proceed with cooking by following these instructions. The instructions are presented in the form of text, images, and, if necessary, video.

[0085] Step 8:

[0086] The user records the amounts of ingredients actually used as they cook, and when cooking is complete, inputs the amounts into the terminal.

[0087] Step 9:

[0088] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[0089] Step 10:

[0090] The server manages food waste based on the collected usage data and suggests optimal ways to use ingredients from next time onwards. Specifically, it analyzes the user's past data and suggests combinations and amounts of ingredients that minimize waste.

[0091] In this way, specific actions at each step support efficient operation of the entire system, helping users to cook without waste.

[0092] Example 1

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

[0094] In modern life, it is extremely important for users to cook efficiently and reduce food waste. Conventional recipe provision systems do not optimize cooking procedures when making multiple dishes simultaneously, often resulting in wasted time and effort. Furthermore, they lack a mechanism for recording the amounts of ingredients actually used and using this information for future cooking. This leads to increased food waste. Furthermore, the cooking procedures are not visually easy to understand, which hinders users from cooking smoothly.

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

[0096] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for transmitting the generated cooking procedures to a terminal and displaying them to the user in real time, and means for displaying the retrieved recipe information and cooking procedures in visual or video format. This allows the user to efficiently cook multiple dishes simultaneously and follow the visual instructions while cooking, thereby saving time and effort and reducing food waste.

[0097] A "user" refers to a person who inputs ingredients and the name of the dish they want to make in order to create a dish.

[0098] "Terminal" refers to a device that receives information from a user, transmits it to a server, and displays the generated cooking instructions to the user.

[0099] The "server" refers to a device that references a database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0100] "Ingredients" refers to the substances, such as foods and seasonings, used to create a dish.

[0101] "Dish name" refers to the name of the dish the user wants to make.

[0102] "Recipe information" refers to information such as ingredients needed to prepare a dish, the required amounts, cooking steps, cooking time, etc.

[0103] A "database" refers to a collection of information that stores and manages recipe information, etc.

[0104] An "AI model" refers to an algorithm or program that uses artificial intelligence technology to analyze data and derive optimal solutions.

[0105] A "prompt sentence" refers to a sentence used to input specific instructions or questions to an AI model.

[0106] "Cooking procedure" refers to a series of steps for preparing a dish.

[0107] "Food waste" refers to the amount of food that is not consumed and is discarded.

[0108] "Visual display" refers to presenting information in an intuitive way using diagrams, videos, etc.

[0109] "Real-time display" refers to a display method that provides information immediately when a user performs an operation.

[0110] The system of the present invention processes the information entered by the user about the ingredients to be used in the dish and the name of the dish they want to make, and generates and provides the optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[0111] Hardware and software used

[0112] The system uses a "terminal" that receives user input, a "server" that accesses the database and performs calculations using AI models, and an internal database.

[0113] 1. Terminal: A device such as a smartphone, tablet, or PC. These devices receive user input through a user interface, send it to the server, and display the generated cooking instructions.

[0114] 2. Server: A computer with high-performance computing power and software for running AI models, specifically AI frameworks such as TensorFlow and PyTorch.

[0115] 3. Database: Stores and manages recipe information and user ingredient usage information. Typically, an SQL database or NoSQL database (e.g., MySQL, MongoDB) is used.

[0116] System Operation Overview

[0117] 1. The user inputs the ingredients to be used in the cooking and the name of the dish they wish to make through the terminal interface. For example, they can input "tomatoes, chicken, potatoes" as the ingredients they wish to use and specify "dish A" and "dish B" as the names of the dishes they wish to make. At this time, the user can also input specific cooking conditions (e.g., time limit, available cooking utensils).

[0118] 2. The device sends the information to the server as a data packet, including the ingredients list, the name of the dish, and the cooking instructions.

[0119] 3. The server references its internal database based on the received data and obtains the relevant recipe information (ingredients, required quantities, cooking steps, cooking time).

[0120] 4. The server uses the AI ​​model to generate efficient cooking instructions based on the acquired recipe information, using prompts such as "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?"

[0121] 5. The generated recipes are sent from the server to the device, which displays step-by-step instructions to the user in real time, including diagrams and videos as needed.

[0122] Specific examples

[0123] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0124] 1. The user enters "tomatoes, chicken, potatoes" as the ingredients to be used in the dish, and specifies "dish A, dish B" as the names of the dishes they want to make.

[0125] 2. The device sends this information to the server.

[0126] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0127] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0128] 5. The server sends the generated instructions to the terminal, which displays them to the user in real time.

[0129] 6. The user follows the instructions to proceed with cooking and inputs the amount of ingredients used after cooking is complete.

[0130] 7. The device sends the usage data to the server, and the server suggests the best way to use ingredients from next time onwards.

[0131] In this way, the system of the present invention supports the user's cooking process, enabling efficient and waste-free cooking, and can also provide specific suggestions for reducing food waste.

[0132] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0133] Step 1:

[0134] The user uses the terminal interface to input the ingredients to be used in cooking and the name of the dish they want to make. For example, if the user inputs "tomatoes, chicken, and potatoes" as the ingredients they want to use and specifies "dish A, dish B" as the names of the dishes they want to make, this information is treated as input data. Subsequent information processing is initiated based on this input.

[0135] Step 2:

[0136] The terminal sends the input data to the server as a data packet. The data sent includes a list of ingredients (e.g., "200g tomatoes, 300g chicken, 400g potatoes"), dish names (e.g., "Dish A, Dish B"), and cooking conditions (e.g., "Can be cooked within 30 minutes"). Based on this information, the server is ready to process and calculate the data.

[0137] Step 3:

[0138] The server references its internal database based on the received data and retrieves the relevant recipe information. For example, it executes a database query to retrieve recipe information (ingredients, quantities, cooking steps, and cooking time) related to "Dish A" and "Dish B." The retrieved recipe information is loaded from the database into computer memory and used in the next step.

[0139] Step 4:

[0140] The server uses an AI model to generate efficient cooking instructions based on the acquired recipe information. The AI ​​model (e.g., TensorFlow, PyTorch) performs processing based on the prompt, "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?" For example, an optimal cooking procedure is generated that includes parallel processing such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken." In this process, the AI ​​model performs data calculations and outputs the optimal procedure.

[0141] Step 5:

[0142] The server then sends the generated cooking instructions to the device. These instructions include step-by-step instructions, as well as diagrams and videos if necessary. For example, they may include specific instructions such as "Step 1: Finely chop the tomatoes (with diagram)" and "Step 2: Boil the potatoes while chopping the tomatoes (with video)."

[0143] Step 6:

[0144] The device displays the received cooking instructions to the user in real time, for example, by using a touchscreen or voice assistant to indicate the next step the user should take, allowing the user to smoothly proceed with cooking while looking at the screen.

[0145] Step 7:

[0146] After cooking is complete, the user inputs the amount of ingredients actually used into the terminal. For example, they might input "tomatoes: 180g, chicken: 250g, potatoes: 350g." This generates actual usage data.

[0147] Step 8:

[0148] The device sends the usage data entered by the user to the server. The server processes this data to manage food waste. For example, it analyzes the data and generates optimal instructions for using ingredients for the next time and beyond (e.g., "Next time, try a recipe that uses only 200g of potatoes").

[0149] Step 9:

[0150] The server sends the generated next cooking suggestion to the device, which displays the suggestion to the user so that the user can use it as a reference when planning their next cooking. This allows the user to use ingredients efficiently and reduce food waste.

[0151] In this way, the system of the present invention includes a series of processing steps that support the user's cooking process and enable efficient and waste-free cooking.

[0152] (Application example 1)

[0153] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0154] The present invention aims to reduce the effort and time users face during the cooking process and reduce food waste by providing an efficient cooking procedure. Another objective of the present invention is to provide a safe and efficient cooking environment in an autonomous vehicle, thereby providing a comfortable dining experience while driving.

[0155] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0156] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for allowing the user to input ingredients and the name of the dish by voice and receive cooking instructions visually or audibly, and means for linking with cooking utensils used in the autonomous vehicle and providing optimal cooking procedures according to the situation, thereby enabling users to cook efficiently and safely even while in an autonomous vehicle and reduce food waste.

[0157] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish they wish to make, and then cooks according to the system's instructions.

[0158] "Ingredients" are the ingredients and seasonings used to create a dish.

[0159] "Dish Name" is the name of the particular dish the user wants to make.

[0160] A "database" is an information storage device that stores related recipe information.

[0161] "Recipe information" refers to detailed information such as ingredients, amounts required, cooking steps, cooking time, etc., for making a particular dish.

[0162] An "optimal cooking procedure" is a series of cooking steps that optimizes the order in which cooking utensils are used and waiting time in order to efficiently prepare multiple dishes.

[0163] "Cooking instructions" are the specific steps and processes for creating a dish.

[0164] "Usage data" refers to data relating to the amount of material actually used by the user.

[0165] "Food waste" refers to the amount of food ingredients and dishes that are discarded unnecessarily.

[0166] "Voice input" is a method in which the user inputs information such as ingredients and the name of a dish using voice through a microphone.

[0167] "Visual instructions" are written or graphic instructions provided to the user through a display.

[0168] "Audio instructions" are audio instructions provided to the user through a speaker.

[0169] An "autonomous vehicle" is a vehicle that drives automatically and is equipped with simple cooking equipment inside.

[0170] "Cooking equipment" refers to equipment and tools used in cooking, including microwave ovens and hot plates.

[0171] A "situation-appropriate cooking procedure" is a cooking procedure that is optimized according to the condition of the cooking utensils and the user's state.

[0172] MODE FOR CARRYING OUT THE INVENTION

[0173] The present invention relates to a system for providing efficient cooking procedures in an autonomous vehicle, as described in detail below.

[0174] 1. System Overview

[0175] The system aims to help users prepare meals comfortably in their autonomous vehicles and is comprised of the following main components:

[0176] An interface that allows users to input ingredients and dish names by voice and receive cooking instructions visually or audibly

[0177] A server that obtains recipe information based on ingredients and dish names and generates optimal cooking instructions

[0178] A device that works with cooking appliances (e.g., microwave ovens, hot plates) installed in autonomous vehicles to provide cooking instructions according to the situation.

[0179] 2. Program Processing

[0180] The main processes in the system program are as follows:

[0181] Hardware and Software

[0182] Smart glasses: A display that shows visual cooking instructions and a microphone for receiving voice commands

[0183] Self-driving vehicles: equipped with cooking appliances (microwave oven, hot plate, etc.)

[0184] Server: Collects recipe information and generates optimal cooking instructions

[0185] Speech recognition engine: Software for processing user voice input

[0186] Network module: Software for data communication between the smart glasses and the server

[0187] Data processing and calculation

[0188] 1. Receiving and Sending User Input

[0189] The user inputs ingredients and the name of the dish by voice.

[0190] The smart glasses' voice recognition engine converts the voice into text data and sends it to the server.

[0191] 2. Obtaining recipe information and generating cooking instructions

[0192] The server retrieves the corresponding recipe information from the database.

[0193] Based on the acquired recipe information, a generative AI model is used to generate optimal cooking procedures.

[0194] If calibration is required, optimize the order in which cooking appliances are used and the waiting time.

[0195] 3. Providing cooking instructions

[0196] The server sends the generated cooking instructions to the smart glasses.

[0197] The smart glasses provide visual or audio instructions to the user.

[0198] 4. Recording usage data

[0199] After cooking, the user inputs the amount of ingredients actually used by voice.

[0200] The smart glasses convert the voice into text data and send this data to a server.

[0201] The server records the usage data received for food waste management and suggests the best way to use ingredients from next time onwards.

[0202] 3. Specific examples

[0203] If a user wants to cook "sauteed chicken" using "tomatoes" and "chicken" in an autonomous vehicle, the system operates as follows:

[0204] 1. The user speaks "tomato, chicken, chicken saute" into the smart glasses.

[0205] 2. The smart glasses convert the speech into text and send it to the server.

[0206] 3. The server retrieves the recipe information and generates efficient cooking instructions, such as "fry the chicken while chopping the tomatoes."

[0207] 4. The server sends the generated instructions to the smart glasses, which then display them to the user.

[0208] 5. After cooking is complete, the user can voice-input the amount of ingredients actually used, and the smart glasses will send that data to the server.

[0209] 6. The server records usage data to manage food waste and suggests optimal ways to use ingredients for future use.

[0210] 4. Examples of prompts

[0211] "Just tell me the ingredients you use in the dish. For example, 'tomatoes, chicken'."

[0212] "Just say the name of the dish you want to make. For example, 'Chicken Sauté'."

[0213] "Say 'Next' to move to the next step."

[0214] "Please tell me the quantities of the ingredients you used. For example, '2 tomatoes, 300g chicken'."

[0215] Thus, the system of the present invention provides a concrete means for efficient and comfortable cooking in an autonomous vehicle.

[0216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0217] Step 1:

[0218] Input: The user inputs ingredients and dish names by voice through the smart glasses.

[0219] How it works: The smart glasses' voice recognition engine converts the user's speech into text data.

[0220] Output: The converted text data, including ingredients and dish names such as "tomato," "chicken," and "sauteed chicken."

[0221] Step 2:

[0222] Input: Text data sent from the smart glasses to the server.

[0223] Operation: The server searches the database based on the received ingredients and dish name to retrieve related recipe information.

[0224] Output: Retrieved recipe information. For example, detailed information such as ingredients needed for "Sauteed Chicken", required quantities, cooking steps, cooking time, etc.

[0225] Step 3:

[0226] Input: Recipe information retrieved from the database.

[0227] How it works: The server uses generative AI models to generate optimal cooking instructions for efficiently creating multiple dishes.

[0228] Output: Optimal cooking steps. For example, an efficient process such as "fry chicken while chopping tomatoes."

[0229] Step 4:

[0230] Input: The optimal cooking instructions sent by the server.

[0231] How it works: The smart glasses receive the cooking instructions and present them to the user visually or audibly, along with diagrams and videos if needed.

[0232] Output: Cooking instructions that the user can follow in real time, for example, "Cut the tomatoes" on the display.

[0233] Step 5:

[0234] Input: The user inputs the actual amount of ingredients used by voice as the cooking progresses.

[0235] How it works: The smart glasses' voice recognition engine again converts the speech into text data and sends that data to the server.

[0236] Output: Converted text data. For example, usage data such as "2 tomatoes, 300g chicken."

[0237] Step 6:

[0238] Input: Usage data sent from smart glasses.

[0239] How it works: The server manages food waste based on the usage data it receives, and suggests optimal ways to use ingredients from next time onwards.

[0240] Output: Food waste management data that will be useful for your next cooking and suggestions on how to best use ingredients. For example, "Since you used up all the tomatoes this time, use fresh tomatoes next time."

[0241] This will enable users to cook efficiently and safely inside self-driving vehicles and reduce food waste.

[0242] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0243] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[0244] overview

[0245] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[0246] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that recognizes the user's emotions.

[0247] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0248] System Operation

[0249] Receiving and Sending Information

[0250] The user uses the terminal to input ingredients to be used in cooking and the name of the dish they want to make. For example, they can specify ingredients such as "tomato," "chicken," and "potato," and also specify the name of the dish, such as "Dish A" or "Dish B."

[0251] The terminal acquires the information entered by the user and transmits it to the server along with specific cooking conditions (such as cooking time limits and available cooking utensils) as needed.

[0252] Get recipe information

[0253] The server accesses the database based on the received user data to retrieve relevant recipe information, including the list of ingredients, serving sizes, cooking steps, cooking time, etc., corresponding to the specified dish name.

[0254] Generating optimal cooking procedures

[0255] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" and "mash potatoes while frying chicken."

[0256] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[0257] Procedure adjustment by emotion engine

[0258] The device is equipped with an emotion engine that analyzes the user's voice input and facial expressions to identify emotions. For example, if the user is feeling stressed, the emotion engine will detect this and request the server to adjust the actual procedure.

[0259] The server generates cooking instructions based on the user's emotions based on the information from the emotion engine. For example, if the server determines that the user is under high stress, it suggests instructions that shorten cooking time or are simpler.

[0260] Providing instructions

[0261] The server then sends the generated optimal cooking instructions to the device. The instructions are structured step by step and are organized in a way that makes them easy for users to understand.

[0262] The device displays cooking instructions to the user, who can follow the instructions to proceed with the cooking. The instructions are presented in the form of text, images, and, if necessary, video.

[0263] Recording usage and suggesting next time

[0264] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[0265] The terminal transmits the input usage data to the server.

[0266] The server uses this data to manage food waste and generates suggestions on how to best use ingredients for future purchases.

[0267] Specific examples

[0268] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0269] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[0270] 2. The device sends this information to the server.

[0271] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0272] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0273] 5. The server sends the generated instructions back to the terminal, which displays them to the user.

[0274] 6. The user follows the cooking instructions. During the cooking process, the device analyzes the user's emotions and adjusts the cooking instructions as necessary.

[0275] 7. After the user has finished cooking, they input the amount of ingredients used into the terminal.

[0276] 8. The device sends the usage data to the server, which then uses this data to suggest the best way to use ingredients for the next time onwards.

[0277] In this way, the system of the present invention supports the cooking process of the user, realizing efficient and waste-free cooking that also takes emotions into consideration.

[0278] The processing flow will be explained below.

[0279] Step 1:

[0280] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make using the terminal interface. For example, they can specify ingredients such as "tomato," "chicken," and "potato" and dish names such as "Dish A" and "Dish B."

[0281] Step 2:

[0282] The device retrieves the ingredients and recipe name entered by the user and prepares all data to be sent to the server, which may also include specific cooking conditions (e.g., cooking time limits and available cooking equipment).

[0283] Step 3:

[0284] The device sends the input information to the server, which includes the ingredients list, the name of the dish, and cooking instructions.

[0285] Step 4:

[0286] The server analyzes the received information and accesses the database to retrieve related recipe information, such as the ingredient list, quantities, cooking steps, and cooking time for the specified dish.

[0287] Step 5:

[0288] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently preparing multiple dishes. For example, it optimizes the process by taking into account the order in which cooking utensils are used and waiting times, such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken."

[0289] Step 6:

[0290] The device analyzes the user's voice input and facial expressions in real time and uses an emotion engine to identify the user's emotions, for example, whether the user is feeling stressed or enjoying cooking.

[0291] Step 7:

[0292] The device uses the emotion engine's results to determine whether the cooking instructions need to be adjusted. For example, if the device determines that the user's stress level is high, it sends that information to the server.

[0293] Step 8:

[0294] The server receives data from the emotion engine and regenerates cooking instructions according to the user's emotions. For example, if the user is under high stress, the instructions are modified to shorten cooking time or provide simpler instructions.

[0295] Step 9:

[0296] The server then sends cooking instructions tailored to the user's emotions to the device, allowing the user to receive detailed support tailored to their emotions.

[0297] Step 10:

[0298] The device displays the adjusted steps to the user, allowing the user to follow the instructions to proceed with the cooking. For example, specific instructions such as "First, cut the tomatoes, then boil the potatoes" are displayed.

[0299] Step 11:

[0300] The user records the amounts of ingredients actually used while cooking, and inputs the amounts into the terminal when cooking is complete.

[0301] Step 12:

[0302] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[0303] Step 13:

[0304] The server manages food waste based on the collected usage data and generates suggestions on how to best use ingredients from next time onwards, allowing users to reduce waste the next time they cook.

[0305] This series of steps enables the system to provide efficient and waste-free cooking support while responding to the user's real-time emotional state.

[0306] Example 2

[0307] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0308] In today's world, efficiently preparing multiple dishes simultaneously and minimizing food waste are challenges facing many households and restaurants. Furthermore, the lack of adjustments to cooking procedures based on the user's emotions leaves the stress and difficulty experienced by users unresolved. Furthermore, conventional cooking assistance systems lack the functionality to reflect the amount of ingredients used by the user in the next cooking session, resulting in food waste.

[0309] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0310] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for analyzing the user's emotions, means for adjusting the cooking procedures based on the analysis results, means for receiving the amounts of ingredients actually used from the user, and means for managing food waste based on the received usage data and presenting optimal ways to use ingredients for future use. This enables efficient cooking support that takes the user's emotions into consideration, and can provide optimal cooking procedures while reducing food waste.

[0311] A "user" is an entity that uses the system to input ingredients to be used in cooking and the name of the dish they wish to make.

[0312] A "terminal" is a device that receives input from a user, sends it to the server, and displays the generated cooking instructions to the user. It may also include an emotion engine.

[0313] "Server" refers to a combination of hardware and software that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[0314] "Ingredients" refer to the foods or ingredients that a user specifies to make a dish.

[0315] "Dish name" refers to the name of the dish the user wants to make.

[0316] "Recipe information" refers to information such as ingredients, quantities, cooking steps, cooking time, etc.

[0317] A "database" is a digital system that manages and stores data such as recipe information.

[0318] An "AI model" is an algorithm that uses the latest artificial intelligence technology to analyze data and generate optimal cooking instructions.

[0319] An "emotion engine" is a system that analyzes a user's voice and facial expressions to identify their emotions.

[0320] A "cooking recipe" is a set of specific instructions for preparing a dish.

[0321] "Usage amount data" refers to information regarding the amount of ingredients actually used by the user in cooking.

[0322] "Food waste" refers to the waste that occurs when ingredients or food are discarded.

[0323] "Cooking conditions" refers to specific conditions that must be taken into consideration when cooking, such as cooking time and available cooking equipment.

[0324] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[0325] overview

[0326] User Roles

[0327] The user inputs the ingredients to be used and the name of the dish they want to make into the device. For example, they can specify ingredients such as "tomato," "chicken," or "potato," and names of dishes such as "Dish A" or "Dish B." The user simply needs to express naturally using voice and facial expressions any stress or joy they feel while cooking.

[0328] Device Role

[0329] The terminal is a device that receives input from the user, transmits it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that can analyze the user's voice and facial expressions. Examples of such devices include smartphones and tablets.

[0330] Server Roles

[0331] The server refers to the database based on the information sent by the user and uses an AI model (generative AI model) to generate and provide optimal cooking instructions. The server also processes data obtained from the emotion engine and can regenerate cooking instructions according to the user's emotions.

[0332] Hardware and software used

[0333] Both the server and the terminal use hardware with advanced processing capabilities. Specifically, MySQL or PostgreSQL is used as the database management system (DBMS), and machine learning frameworks such as TensorFlow and PyTorch can be used to generate AI models.

[0334] Data processing and calculation

[0335] 1. Receiving and Sending Data

[0336] The user uses the terminal to input ingredients and the name of the dish they want to make. For example, they input "tomatoes, chicken, and potatoes" and "dish A, dish B."

[0337] The device sends this information to the server. Specifically, text data is sent to the server in JSON or XML format.

[0338] 2. Get recipe information

[0339] The server accesses the database based on the information received from the user to retrieve relevant recipe information, including the list of ingredients, quantities, cooking steps, cooking time, etc., corresponding to the specified dish name.

[0340] 3. Generating optimal cooking procedures

[0341] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0342] 4. Procedure adjustment using emotion engine

[0343] The device is equipped with an emotion engine that analyzes the user's voice and facial expressions to identify their emotions, and if the user feels stressed, it requests the server to adjust the cooking instructions.

[0344] Based on this information, the server regenerates the cooking recipe and sends it to the terminal.

[0345] 5. Providing instructions and recording usage

[0346] The device displays the optimal cooking instructions sent from the server to the user, which are provided in the form of text, images, and videos.

[0347] The user follows the cooking procedure and, after cooking is complete, inputs the amounts of ingredients actually used into the terminal.

[0348] The device sends the inputted usage data to the server, which stores and analyzes it to suggest the best way to use ingredients for the next time.

[0349] Specific examples

[0350] For example, if a user wants to make "Dish A using tomatoes and chicken" and "Dish B using potatoes," the following operation will occur.

[0351] 1. The user enters "tomato," "chicken," and "potato" as ingredients and specifies "Dish A" and "Dish B" as dish names.

[0352] 2. The device sends this information to the server.

[0353] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0354] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0355] 5. The device analyzes the user's voice and facial expression data using an emotion engine and sends emotional information to the server as needed.

[0356] 6. The server generates the adjusted procedure again and sends the optimal procedure to the terminal.

[0357] 7. The device displays the optimal cooking procedure to the user, who then follows it to proceed with the cooking.

[0358] 8. After the user has completed cooking, they input the amount of ingredients used into the terminal.

[0359] 9. The device sends the usage data to the server, which stores and analyzes the data to suggest optimal ingredient usage methods for the next time and beyond.

[0360] Prompt Sentence Examples

[0361] The following is an example of input to suggest the optimal procedure for the next time onwards.

[0362] User-entered ingredients: Tomato, Chicken, Potato

[0363] Name of the dish you want to make: Dish A, Dish B

[0364] Cookware restrictions: frying pans, pots

[0365] Cooking time limit: 30 minutes

[0366] User Emotion: Stress (Audio Analysis Results)

[0367] This allows the system to provide optimal cooking procedures according to the user's situation, enabling efficient and waste-free cooking.

[0368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0369] Step 1:

[0370] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. For example, they input "tomato," "chicken," "potato," and "dish A" and "dish B."

[0371] Input: ingredients and dish name

[0372] Output: Input information (ingredients and dish name)

[0373] Specific action: A user enters data into an input field on a smartphone or tablet and presses the submit button.

[0374] Step 2:

[0375] The device receives input from the user, formats it, and sends it to the server in JSON or XML format.

[0376] Input: Input information (ingredients and dish name)

[0377] Output: Formatted data (JSON or XML format)

[0378] What it does: The device formats the data internally and sends it to a server via the Internet.

[0379] Step 3:

[0380] The server accesses the database based on the data received from the user and obtains the corresponding recipe information.

[0381] Input: Formatted data (ingredients and dish name)

[0382] Output: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[0383] What happens: The server uses an SQL query to retrieve the required information from the database.

[0384] Step 4:

[0385] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information.

[0386] Input: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[0387] Output: Optimal cooking procedure

[0388] Specific operation: The server inputs a prompt sentence into the generative AI model, and the model generates optimal cooking instructions.

[0389] Step 5:

[0390] The terminal analyzes the user's voice and facial expressions and uses an emotion engine to identify the user's emotional state.

[0391] Input: User audio or video data

[0392] Output: User's emotional state (e.g., stressed, relaxed)

[0393] Specific operation: The device uses the camera and microphone to collect the user's voice and facial expression data, which is then analyzed by the emotion engine.

[0394] Step 6:

[0395] The server adjusts the cooking instructions as needed based on information from the emotion engine.

[0396] Input: optimal cooking procedure, user's emotional state

[0397] Output: Adjusted cooking instructions

[0398] What it does: The server re-runs the AI ​​model to generate cooking instructions based on the emotion.

[0399] Step 7:

[0400] The device displays the cooking instructions received from the server to the user. The instructions are provided in the form of text, images, or videos.

[0401] Input: Adjusted cooking instructions

[0402] Output: Cooking instructions displayed to the user

[0403] Specific operation: The device displays cooking instructions on the display.

[0404] Step 8:

[0405] The user proceeds with cooking by following the steps displayed on the terminal.

[0406] Input: User actions, adjusted cooking instructions

[0407] Output: Cooking progress

[0408] Specific Action: The user actually follows the steps using the ingredients and utensils.

[0409] Step 9:

[0410] After cooking is complete, the user inputs the amounts of ingredients actually used into the terminal.

[0411] Input: Amount of material used

[0412] Output: Actual usage data

[0413] Specific actions: The user enters the amount of ingredients used in the input field on the terminal and presses the send button.

[0414] Step 10:

[0415] The terminal transmits the input usage data to the server.

[0416] Input: Actual usage data

[0417] Output: Usage data (JSON or XML format)

[0418] What it does: The device formats the data and sends it to a server over the Internet.

[0419] Step 11:

[0420] The server stores and analyzes the received usage data to suggest optimal food usage methods for the next time and beyond.

[0421] Input: Usage data

[0422] Output: Proposal for optimal ingredient usage

[0423] What it does: The server stores usage data in a database and uses analytical algorithms to generate optimal recommendations.

[0424] (Application example 2)

[0425] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0426] Conventional food delivery services are unable to respond to users' emotions or current situations, resulting in a uniform experience for users, leading to low customer satisfaction. Furthermore, food delivery times and routes are set based on fixed standards, making it difficult to adapt to users' stress and urgent needs. This makes it difficult to provide the delivery experience users expect, resulting in a lack of emotional support in particular.

[0427] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredients to be used in a dish and the name of the dish to be made from the user; means for retrieving related recipe information from a database based on the ingredients and the name of the dish; means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information; means for providing the generated cooking procedures to the user; means for receiving the amounts of ingredients actually used from the user; means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future use; and an emotion engine that recognizes the user's emotions and means for adjusting the cooking procedures based on this emotion engine. This makes it possible to provide an optimal food delivery service that suits the user's emotions and current situation, thereby improving user satisfaction.

[0428] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish that the user wants to make.

[0429] A "terminal" is a device that receives input from a user, transmits it to the server, and displays the generated cooking instructions to the user.

[0430] The "server" is a system that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[0431] An "ingredient" is a food or ingredient used to make a dish.

[0432] "Dish name" is the name of the dish the user wants to make.

[0433] "Recipe information" refers to information stored in a database, such as ingredient lists, quantities, cooking instructions, and cooking times.

[0434] A "database" is a central location where recipe information is stored.

[0435] A "cooking procedure" is a series of tasks or steps to complete a dish.

[0436] The "emotion engine" is a system that identifies emotions by analyzing the user's voice input and facial expressions.

[0437] "Food waste" refers to food that is discarded without being used.

[0438] "Optimization" refers to adjusting processes to efficiently create multiple dishes.

[0439] "Delivery time" is the time it takes for food to be delivered to the user after it is ordered.

[0440] A "delivery route" is the route that food will take when delivered.

[0441] The food delivery system based on this invention consists of a user, a terminal, and a server. The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. The terminal acquires this information and sends it to the server. The server then references a database based on the received information and acquires related recipe information. The recipe information includes a list of ingredients, quantities, cooking steps, cooking time, etc.

[0442] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. This also optimizes the order in which cooking utensils are used and waiting times. The server then sends the generated cooking instructions to the device, which displays them to the user. The user can then proceed with the cooking process by following the displayed instructions.

[0443] Furthermore, the device is equipped with an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. Based on this emotion data, the server can adjust the cooking instructions. For example, if the user is feeling stressed, the server will suggest cooking instructions that shorten cooking time or simplify the process.

[0444] After the user has finished cooking, they input the amount of ingredients they actually used into the device. This data is sent to the server and used to generate recommendations for optimal use of ingredients for future meals, thereby helping to manage food waste.

[0445] The specific processing of this system is realized using programming languages ​​such as Python and AI frameworks (e.g., TensorFlow and PyTorch), and OpenCV and speech recognition APIs are used to recognize emotions.

[0446] Specific examples

[0447] Suppose a user opens a smartphone app and orders tomato pasta. The device's emotion engine determines from the user's tone of voice and facial expression that the user is feeling stressed. The server receives this information, calculates the optimal delivery route while shortening delivery time, and displays it to the user. This system allows the user to receive their food quickly and efficiently without feeling stressed.

[0448] Prompt Sentence Examples

[0449] "The user ordered tomato pasta. The user's voice tone indicates that they are stressed. Based on this emotion, please reduce the delivery time and generate the optimal delivery route. Please keep the estimated delivery time within XX minutes."

[0450] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0451] Step 1:

[0452] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the device. The input information is saved on the device as a list of ingredients (e.g., "tomatoes," "chicken") and the name of the dish (e.g., "tomato pasta").

[0453] Step 2:

[0454] The terminal sends the ingredient list and dish name obtained from the user to the server, where the terminal uses an HTTP request to send the ingredient and dish name data, and the server uses the received information as input for a database query.

[0455] Step 3:

[0456] The server retrieves related recipe information from the database based on the received ingredients and dish name. Specifically, it executes an SQL query on the database to find records with the corresponding dish name. The output is the recipe information (ingredients list, quantities, cooking steps, cooking time, etc.).

[0457] Step 4:

[0458] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. The AI ​​model optimizes the entire cooking process, taking into account the order in which cooking utensils are used and waiting times. At this stage, the generative AI model calculates the cutting order of ingredients, heating times, and processes that can be carried out simultaneously, and outputs efficient cooking instructions.

[0459] Step 5:

[0460] The server sends the generated optimal cooking instructions to the device, again using an HTTP request to return the cooking instruction data to the device, which receives and stores it.

[0461] Step 6:

[0462] The device displays cooking instructions to the user in the form of text, images, and videos, organized for easy understanding by the user. The user then proceeds with the cooking process based on this information.

[0463] Step 7:

[0464] The emotion engine installed on the device analyzes the user's voice and facial expressions to identify their current emotion. Emotion identification is performed in real time using a microphone and camera, OpenCV, and a speech recognition API. The output is the user's emotional state (e.g., "stress").

[0465] Step 8:

[0466] The device transmits the emotion data identified by the emotion engine to the server, which receives this data as input and adjusts the cooking instructions.

[0467] Step 9:

[0468] The server then adjusts the cooking instructions based on the user's emotional state. For example, if the user is feeling stressed, the AI ​​model can be used to generate instructions that shorten cooking time or simplify the process. In this process, the generative AI model receives specific emotional data as input and re-optimizes the instructions based on that data. The adjusted cooking instructions are then generated as output.

[0469] Step 10:

[0470] The server sends the adjusted cooking recipe to the terminal, which then displays the adjusted recipe to the user, allowing the user to proceed with cooking more comfortably.

[0471] Step 11:

[0472] After the user has finished cooking, they input the amount of ingredients they actually used into the device, which is important information for reducing food waste.

[0473] Step 12:

[0474] The device sends usage data to the server, which uses this data to manage food waste and propose optimal ingredient usage methods for future uses. At this stage, the server analyzes the previous usage data and outputs the next recipe proposal and adjusts the ingredient amounts.

[0475] The above steps realize a system that provides optimal food delivery services according to the user's emotions and current situation, thereby improving user satisfaction.

[0476] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0477] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0478] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0479] [Second embodiment]

[0480] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0481] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0482] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0483] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0484] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0485] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0486] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0487] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0488] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0489] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0490] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0491] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0492] The system of the present invention processes the information entered by the user about ingredients to be used in the dish and the name of the dish they want to make, and generates and provides optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[0493] overview

[0494] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[0495] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user.

[0496] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0497] System Operation

[0498] Receiving and Sending Information

[0499] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make through the terminal interface. For example, they input "tomato," "chicken," and "potato" as the ingredients they want to use, and specify "dish A" and "dish B" as the names of the dishes they want to make.

[0500] The device sends the entered information to the server, including the ingredient list and the name of the dish, as well as any specific cooking conditions (such as time limits and available cooking equipment).

[0501] Get recipe information

[0502] Based on the received user information, the server retrieves related recipe information from its internal database, including detailed recipes for dishes A and B (ingredients, amounts, cooking steps, cooking time, etc.).

[0503] Generating optimal cooking procedures

[0504] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently creating multiple dishes. For example,

[0505] "Boil the potatoes while you chop the tomatoes."

[0506] This includes steps such as "mashing potatoes while frying chicken."

[0507] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[0508] Providing instructions

[0509] The server then sends the generated cooking instructions to the device. The instructions are structured in an easy-to-understand step-by-step format, and include diagrams and videos as needed.

[0510] The terminal displays these steps to the user, allowing them to follow them in real time.

[0511] Recording usage and suggesting next time

[0512] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[0513] The terminal transmits the input usage data to the server.

[0514] The server uses this data to manage food waste and generates suggestions on how to best use ingredients in the future.

[0515] Specific examples

[0516] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0517] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[0518] 2. The device sends this information to the server.

[0519] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0520] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0521] 5. The server sends the generated procedure to the terminal, which displays it to the user.

[0522] 6. The user follows the instructions to proceed with cooking, and after cooking is complete, enters the amount of ingredients used into the terminal.

[0523] 7. The device sends the usage data to the server, which then uses this data to suggest the optimal way to use ingredients for the next time onwards.

[0524] In this way, the system of the present invention supports the user's cooking process and enables efficient and waste-free cooking.

[0525] The processing flow will be explained below.

[0526] Step 1:

[0527] The user uses the terminal interface to input ingredients and the name of the dish they want to make, for example, "tomatoes," "chicken," and "potatoes," and names the dishes such as "Dish A" and "Dish B."

[0528] Step 2:

[0529] The device receives the information about ingredients and the name of the dish entered by the user and prepares to send it to the system. It also sends specific cooking conditions (e.g., cooking time limits and available cooking equipment) if necessary.

[0530] Step 3:

[0531] The terminal transmits the user-entered data to the server, including the list of ingredients, the name of the dish, and cooking conditions.

[0532] Step 4:

[0533] The server analyzes the received user data and accesses the database to retrieve related recipe information, such as the list of ingredients, quantities, cooking steps, and cooking time for the specified dish.

[0534] Step 5:

[0535] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0536] Step 6:

[0537] The server then sends the generated optimal cooking instructions to the device. These instructions are structured step by step and are organized in a way that makes them easy for the user to understand.

[0538] Step 7:

[0539] The terminal displays the cooking instructions sent from the server to the user, and the user can proceed with cooking by following these instructions. The instructions are presented in the form of text, images, and, if necessary, video.

[0540] Step 8:

[0541] The user records the amounts of ingredients actually used as they cook, and when cooking is complete, inputs the amounts into the terminal.

[0542] Step 9:

[0543] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[0544] Step 10:

[0545] The server manages food waste based on the collected usage data and suggests optimal ways to use ingredients from next time onwards. Specifically, it analyzes the user's past data and suggests combinations and amounts of ingredients that minimize waste.

[0546] In this way, specific actions at each step support efficient operation of the entire system, helping users to cook without waste.

[0547] Example 1

[0548] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0549] In modern life, it is extremely important for users to cook efficiently and reduce food waste. Conventional recipe provision systems do not optimize cooking procedures when making multiple dishes simultaneously, often resulting in wasted time and effort. Furthermore, they lack a mechanism for recording the amounts of ingredients actually used and using this information for future cooking. This leads to increased food waste. Furthermore, the cooking procedures are not visually easy to understand, which hinders users from cooking smoothly.

[0550] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0551] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for transmitting the generated cooking procedures to a terminal and displaying them to the user in real time, and means for displaying the retrieved recipe information and cooking procedures in visual or video format. This allows the user to efficiently cook multiple dishes simultaneously and follow the visual instructions while cooking, thereby saving time and effort and reducing food waste.

[0552] A "user" refers to a person who inputs ingredients and the name of the dish they want to make in order to create a dish.

[0553] "Terminal" refers to a device that receives information from a user, transmits it to a server, and displays the generated cooking instructions to the user.

[0554] The "server" refers to a device that references a database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0555] "Ingredients" refers to the substances, such as foods and seasonings, used to create a dish.

[0556] "Dish name" refers to the name of the dish the user wants to make.

[0557] "Recipe information" refers to information such as ingredients needed to prepare a dish, the required amounts, cooking steps, cooking time, etc.

[0558] A "database" refers to a collection of information that stores and manages recipe information, etc.

[0559] An "AI model" refers to an algorithm or program that uses artificial intelligence technology to analyze data and derive optimal solutions.

[0560] A "prompt sentence" refers to a sentence used to input specific instructions or questions to an AI model.

[0561] "Cooking procedure" refers to a series of steps for preparing a dish.

[0562] "Food waste" refers to the amount of food that is not consumed and is discarded.

[0563] "Visual display" refers to presenting information in an intuitive way using diagrams, videos, etc.

[0564] "Real-time display" refers to a display method that provides information immediately when a user performs an operation.

[0565] The system of the present invention processes the information entered by the user about the ingredients to be used in the dish and the name of the dish they want to make, and generates and provides the optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[0566] Hardware and software used

[0567] The system uses a "terminal" that receives user input, a "server" that accesses the database and performs calculations using AI models, and an internal database.

[0568] 1. Terminal: A device such as a smartphone, tablet, or PC. These devices receive user input through a user interface, send it to the server, and display the generated cooking instructions.

[0569] 2. Server: A computer with high-performance computing power and software for running AI models, specifically AI frameworks such as TensorFlow and PyTorch.

[0570] 3. Database: Stores and manages recipe information and user ingredient usage information. Typically, an SQL database or NoSQL database (e.g., MySQL, MongoDB) is used.

[0571] System Operation Overview

[0572] 1. The user inputs the ingredients to be used in the cooking and the name of the dish they wish to make through the terminal interface. For example, they can input "tomatoes, chicken, potatoes" as the ingredients they wish to use and specify "dish A" and "dish B" as the names of the dishes they wish to make. At this time, the user can also input specific cooking conditions (e.g., time limit, available cooking utensils).

[0573] 2. The device sends the information to the server as a data packet, including the ingredients list, the name of the dish, and the cooking instructions.

[0574] 3. The server references its internal database based on the received data and obtains the relevant recipe information (ingredients, required quantities, cooking steps, cooking time).

[0575] 4. The server uses the AI ​​model to generate efficient cooking instructions based on the acquired recipe information, using prompts such as "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?"

[0576] 5. The generated recipes are sent from the server to the device, which displays step-by-step instructions to the user in real time, including diagrams and videos as needed.

[0577] Specific examples

[0578] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0579] 1. The user enters "tomatoes, chicken, potatoes" as the ingredients to be used in the dish, and specifies "dish A, dish B" as the names of the dishes they want to make.

[0580] 2. The device sends this information to the server.

[0581] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0582] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0583] 5. The server sends the generated instructions to the terminal, which displays them to the user in real time.

[0584] 6. The user follows the instructions to proceed with cooking and inputs the amount of ingredients used after cooking is complete.

[0585] 7. The device sends the usage data to the server, and the server suggests the best way to use ingredients from next time onwards.

[0586] In this way, the system of the present invention supports the user's cooking process, enabling efficient and waste-free cooking, and can also provide specific suggestions for reducing food waste.

[0587] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0588] Step 1:

[0589] The user uses the terminal interface to input the ingredients to be used in cooking and the name of the dish they want to make. For example, if the user inputs "tomatoes, chicken, and potatoes" as the ingredients they want to use and specifies "dish A, dish B" as the names of the dishes they want to make, this information is treated as input data. Subsequent information processing is initiated based on this input.

[0590] Step 2:

[0591] The terminal sends the input data to the server as a data packet. The data sent includes a list of ingredients (e.g., "200g tomatoes, 300g chicken, 400g potatoes"), dish names (e.g., "Dish A, Dish B"), and cooking conditions (e.g., "Can be cooked within 30 minutes"). Based on this information, the server is ready to process and calculate the data.

[0592] Step 3:

[0593] The server references its internal database based on the received data and retrieves the relevant recipe information. For example, it executes a database query to retrieve recipe information (ingredients, quantities, cooking steps, and cooking time) related to "Dish A" and "Dish B." The retrieved recipe information is loaded from the database into computer memory and used in the next step.

[0594] Step 4:

[0595] The server uses an AI model to generate efficient cooking instructions based on the acquired recipe information. The AI ​​model (e.g., TensorFlow, PyTorch) performs processing based on the prompt, "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?" For example, an optimal cooking procedure is generated that includes parallel processing such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken." In this process, the AI ​​model performs data calculations and outputs the optimal procedure.

[0596] Step 5:

[0597] The server then sends the generated cooking instructions to the device. These instructions include step-by-step instructions, as well as diagrams and videos if necessary. For example, they may include specific instructions such as "Step 1: Finely chop the tomatoes (with diagram)" and "Step 2: Boil the potatoes while chopping the tomatoes (with video)."

[0598] Step 6:

[0599] The device displays the received cooking instructions to the user in real time, for example, by using a touchscreen or voice assistant to indicate the next step the user should take, allowing the user to smoothly proceed with cooking while looking at the screen.

[0600] Step 7:

[0601] After cooking is complete, the user inputs the amount of ingredients actually used into the terminal. For example, they might input "tomatoes: 180g, chicken: 250g, potatoes: 350g." This generates actual usage data.

[0602] Step 8:

[0603] The device sends the usage data entered by the user to the server. The server processes this data to manage food waste. For example, it analyzes the data and generates optimal instructions for using ingredients for the next time and beyond (e.g., "Next time, try a recipe that uses only 200g of potatoes").

[0604] Step 9:

[0605] The server sends the generated next cooking suggestion to the device, which displays the suggestion to the user so that the user can use it as a reference when planning their next cooking. This allows the user to use ingredients efficiently and reduce food waste.

[0606] In this way, the system of the present invention includes a series of processing steps that support the user's cooking process and enable efficient and waste-free cooking.

[0607] (Application example 1)

[0608] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0609] The present invention aims to reduce the effort and time users face during the cooking process and reduce food waste by providing an efficient cooking procedure. Another objective of the present invention is to provide a safe and efficient cooking environment in an autonomous vehicle, thereby providing a comfortable dining experience while driving.

[0610] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0611] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for allowing the user to input ingredients and the name of the dish by voice and receive cooking instructions visually or audibly, and means for linking with cooking utensils used in the autonomous vehicle and providing optimal cooking procedures according to the situation, thereby enabling users to cook efficiently and safely even while in an autonomous vehicle and reduce food waste.

[0612] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish they wish to make, and then cooks according to the system's instructions.

[0613] "Ingredients" are the ingredients and seasonings used to create a dish.

[0614] "Dish Name" is the name of the particular dish the user wants to make.

[0615] A "database" is an information storage device that stores related recipe information.

[0616] "Recipe information" refers to detailed information such as ingredients, amounts required, cooking steps, cooking time, etc., for making a particular dish.

[0617] An "optimal cooking procedure" is a series of cooking steps that optimizes the order in which cooking utensils are used and waiting time in order to efficiently prepare multiple dishes.

[0618] "Cooking instructions" are the specific steps and processes for creating a dish.

[0619] "Usage data" refers to data relating to the amount of material actually used by the user.

[0620] "Food waste" refers to the amount of food ingredients and dishes that are discarded unnecessarily.

[0621] "Voice input" is a method in which the user inputs information such as ingredients and the name of a dish using voice through a microphone.

[0622] "Visual instructions" are written or graphic instructions provided to the user through a display.

[0623] "Audio instructions" are audio instructions provided to the user through a speaker.

[0624] An "autonomous vehicle" is a vehicle that drives automatically and is equipped with simple cooking equipment inside.

[0625] "Cooking equipment" refers to equipment and tools used in cooking, including microwave ovens and hot plates.

[0626] A "situation-appropriate cooking procedure" is a cooking procedure that is optimized according to the condition of the cooking utensils and the user's state.

[0627] MODE FOR CARRYING OUT THE INVENTION

[0628] The present invention relates to a system for providing efficient cooking procedures in an autonomous vehicle, as described in detail below.

[0629] 1. System Overview

[0630] The system aims to help users prepare meals comfortably in their autonomous vehicles and is comprised of the following main components:

[0631] An interface that allows users to input ingredients and dish names by voice and receive cooking instructions visually or audibly

[0632] A server that obtains recipe information based on ingredients and dish names and generates optimal cooking instructions

[0633] A device that works with cooking appliances (e.g., microwave ovens, hot plates) installed in autonomous vehicles to provide cooking instructions according to the situation.

[0634] 2. Program Processing

[0635] The main processes in the system program are as follows:

[0636] Hardware and Software

[0637] Smart glasses: A display that shows visual cooking instructions and a microphone for receiving voice commands

[0638] Self-driving vehicles: equipped with cooking appliances (microwave oven, hot plate, etc.)

[0639] Server: Collects recipe information and generates optimal cooking instructions

[0640] Speech recognition engine: Software for processing user voice input

[0641] Network module: Software for data communication between the smart glasses and the server

[0642] Data processing and calculation

[0643] 1. Receiving and Sending User Input

[0644] The user inputs ingredients and the name of the dish by voice.

[0645] The smart glasses' voice recognition engine converts the voice into text data and sends it to the server.

[0646] 2. Obtaining recipe information and generating cooking instructions

[0647] The server retrieves the corresponding recipe information from the database.

[0648] Based on the acquired recipe information, a generative AI model is used to generate optimal cooking procedures.

[0649] If calibration is required, optimize the order in which cooking appliances are used and the waiting time.

[0650] 3. Providing cooking instructions

[0651] The server sends the generated cooking instructions to the smart glasses.

[0652] The smart glasses provide visual or audio instructions to the user.

[0653] 4. Recording usage data

[0654] After cooking, the user inputs the amount of ingredients actually used by voice.

[0655] The smart glasses convert the voice into text data and send this data to a server.

[0656] The server records the usage data received for food waste management and suggests the best way to use ingredients from next time onwards.

[0657] 3. Specific examples

[0658] If a user wants to cook "sauteed chicken" using "tomatoes" and "chicken" in an autonomous vehicle, the system operates as follows:

[0659] 1. The user speaks "tomato, chicken, chicken saute" into the smart glasses.

[0660] 2. The smart glasses convert the speech into text and send it to the server.

[0661] 3. The server retrieves the recipe information and generates efficient cooking instructions, such as "fry the chicken while chopping the tomatoes."

[0662] 4. The server sends the generated instructions to the smart glasses, which then display them to the user.

[0663] 5. After cooking is complete, the user can voice-input the amount of ingredients actually used, and the smart glasses will send that data to the server.

[0664] 6. The server records usage data to manage food waste and suggests optimal ways to use ingredients for future use.

[0665] 4. Examples of prompts

[0666] "Just tell me the ingredients you use in the dish. For example, 'tomatoes, chicken'."

[0667] "Just say the name of the dish you want to make. For example, 'Chicken Sauté'."

[0668] "Say 'Next' to move to the next step."

[0669] "Please tell me the quantities of the ingredients you used. For example, '2 tomatoes, 300g chicken'."

[0670] Thus, the system of the present invention provides a concrete means for efficient and comfortable cooking in an autonomous vehicle.

[0671] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0672] Step 1:

[0673] Input: The user inputs ingredients and dish names by voice through the smart glasses.

[0674] How it works: The smart glasses' voice recognition engine converts the user's speech into text data.

[0675] Output: The converted text data, including ingredients and dish names such as "tomato," "chicken," and "sauteed chicken."

[0676] Step 2:

[0677] Input: Text data sent from the smart glasses to the server.

[0678] Operation: The server searches the database based on the received ingredients and dish name to retrieve related recipe information.

[0679] Output: Retrieved recipe information. For example, detailed information such as ingredients needed for "Sauteed Chicken", required quantities, cooking steps, cooking time, etc.

[0680] Step 3:

[0681] Input: Recipe information retrieved from the database.

[0682] How it works: The server uses generative AI models to generate optimal cooking instructions for efficiently creating multiple dishes.

[0683] Output: Optimal cooking steps. For example, an efficient process such as "fry chicken while chopping tomatoes."

[0684] Step 4:

[0685] Input: The optimal cooking instructions sent by the server.

[0686] How it works: The smart glasses receive the cooking instructions and present them to the user visually or audibly, along with diagrams and videos if needed.

[0687] Output: Cooking instructions that the user can follow in real time, for example, "Cut the tomatoes" on the display.

[0688] Step 5:

[0689] Input: The user inputs the actual amount of ingredients used by voice as the cooking progresses.

[0690] How it works: The smart glasses' voice recognition engine again converts the speech into text data and sends that data to the server.

[0691] Output: Converted text data. For example, usage data such as "2 tomatoes, 300g chicken."

[0692] Step 6:

[0693] Input: Usage data sent from smart glasses.

[0694] How it works: The server manages food waste based on the usage data it receives, and suggests optimal ways to use ingredients from next time onwards.

[0695] Output: Food waste management data that will be useful for your next cooking and suggestions on how to best use ingredients. For example, "Since you used up all the tomatoes this time, use fresh tomatoes next time."

[0696] This will enable users to cook efficiently and safely inside self-driving vehicles and reduce food waste.

[0697] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0698] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[0699] overview

[0700] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[0701] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that recognizes the user's emotions.

[0702] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0703] System Operation

[0704] Receiving and Sending Information

[0705] The user uses the terminal to input ingredients to be used in cooking and the name of the dish they want to make. For example, they can specify ingredients such as "tomato," "chicken," and "potato," and also specify the name of the dish, such as "Dish A" or "Dish B."

[0706] The terminal acquires the information entered by the user and transmits it to the server along with specific cooking conditions (such as cooking time limits and available cooking utensils) as needed.

[0707] Get recipe information

[0708] The server accesses the database based on the received user data to retrieve relevant recipe information, including the list of ingredients, serving sizes, cooking steps, cooking time, etc., corresponding to the specified dish name.

[0709] Generating optimal cooking procedures

[0710] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" and "mash potatoes while frying chicken."

[0711] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[0712] Procedure adjustment by emotion engine

[0713] The device is equipped with an emotion engine that analyzes the user's voice input and facial expressions to identify emotions. For example, if the user is feeling stressed, the emotion engine will detect this and request the server to adjust the actual procedure.

[0714] The server generates cooking instructions based on the user's emotions based on the information from the emotion engine. For example, if the server determines that the user is under high stress, it suggests instructions that shorten cooking time or are simpler.

[0715] Providing instructions

[0716] The server then sends the generated optimal cooking instructions to the device. The instructions are structured step by step and are organized in a way that makes them easy for users to understand.

[0717] The device displays cooking instructions to the user, who can follow the instructions to proceed with the cooking. The instructions are presented in the form of text, images, and, if necessary, video.

[0718] Recording usage and suggesting next time

[0719] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[0720] The terminal transmits the input usage data to the server.

[0721] The server uses this data to manage food waste and generates suggestions on how to best use ingredients for future purchases.

[0722] Specific examples

[0723] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0724] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[0725] 2. The device sends this information to the server.

[0726] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0727] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0728] 5. The server sends the generated instructions back to the terminal, which displays them to the user.

[0729] 6. The user follows the cooking instructions. During the cooking process, the device analyzes the user's emotions and adjusts the cooking instructions as necessary.

[0730] 7. After the user has finished cooking, they input the amount of ingredients used into the terminal.

[0731] 8. The device sends the usage data to the server, which then uses this data to suggest the best way to use ingredients for the next time onwards.

[0732] In this way, the system of the present invention supports the cooking process of the user, realizing efficient and waste-free cooking that also takes emotions into consideration.

[0733] The processing flow will be explained below.

[0734] Step 1:

[0735] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make using the terminal interface. For example, they can specify ingredients such as "tomato," "chicken," and "potato" and dish names such as "Dish A" and "Dish B."

[0736] Step 2:

[0737] The device retrieves the ingredients and recipe name entered by the user and prepares all data to be sent to the server, which may also include specific cooking conditions (e.g., cooking time limits and available cooking equipment).

[0738] Step 3:

[0739] The device sends the input information to the server, which includes the ingredients list, the name of the dish, and cooking instructions.

[0740] Step 4:

[0741] The server analyzes the received information and accesses the database to retrieve related recipe information, such as the ingredient list, quantities, cooking steps, and cooking time for the specified dish.

[0742] Step 5:

[0743] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently preparing multiple dishes. For example, it optimizes the process by taking into account the order in which cooking utensils are used and waiting times, such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken."

[0744] Step 6:

[0745] The device analyzes the user's voice input and facial expressions in real time and uses an emotion engine to identify the user's emotions, for example, whether the user is feeling stressed or enjoying cooking.

[0746] Step 7:

[0747] The device uses the emotion engine's results to determine whether the cooking instructions need to be adjusted. For example, if the device determines that the user's stress level is high, it sends that information to the server.

[0748] Step 8:

[0749] The server receives data from the emotion engine and regenerates cooking instructions according to the user's emotions. For example, if the user is under high stress, the instructions are modified to shorten cooking time or provide simpler instructions.

[0750] Step 9:

[0751] The server then sends cooking instructions tailored to the user's emotions to the device, allowing the user to receive detailed support tailored to their emotions.

[0752] Step 10:

[0753] The device displays the adjusted steps to the user, allowing the user to follow the instructions to proceed with the cooking. For example, specific instructions such as "First, cut the tomatoes, then boil the potatoes" are displayed.

[0754] Step 11:

[0755] The user records the amounts of ingredients actually used while cooking, and inputs the amounts into the terminal when cooking is complete.

[0756] Step 12:

[0757] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[0758] Step 13:

[0759] The server manages food waste based on the collected usage data and generates suggestions on how to best use ingredients from next time onwards, allowing users to reduce waste the next time they cook.

[0760] This series of steps enables the system to provide efficient and waste-free cooking support while responding to the user's real-time emotional state.

[0761] Example 2

[0762] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0763] In today's world, efficiently preparing multiple dishes simultaneously and minimizing food waste are challenges facing many households and restaurants. Furthermore, the lack of adjustments to cooking procedures based on the user's emotions leaves the stress and difficulty experienced by users unresolved. Furthermore, conventional cooking assistance systems lack the functionality to reflect the amount of ingredients used by the user in the next cooking session, resulting in food waste.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0765] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for analyzing the user's emotions, means for adjusting the cooking procedures based on the analysis results, means for receiving the amounts of ingredients actually used from the user, and means for managing food waste based on the received usage data and presenting optimal ways to use ingredients for future use. This enables efficient cooking support that takes the user's emotions into consideration, and can provide optimal cooking procedures while reducing food waste.

[0766] A "user" is an entity that uses the system to input ingredients to be used in cooking and the name of the dish they wish to make.

[0767] A "terminal" is a device that receives input from a user, sends it to the server, and displays the generated cooking instructions to the user. It may also include an emotion engine.

[0768] "Server" refers to a combination of hardware and software that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[0769] "Ingredients" refer to the foods or ingredients that a user specifies to make a dish.

[0770] "Dish name" refers to the name of the dish the user wants to make.

[0771] "Recipe information" refers to information such as ingredients, quantities, cooking steps, cooking time, etc.

[0772] A "database" is a digital system that manages and stores data such as recipe information.

[0773] An "AI model" is an algorithm that uses the latest artificial intelligence technology to analyze data and generate optimal cooking instructions.

[0774] An "emotion engine" is a system that analyzes a user's voice and facial expressions to identify their emotions.

[0775] A "cooking recipe" is a set of specific instructions for preparing a dish.

[0776] "Usage amount data" refers to information regarding the amount of ingredients actually used by the user in cooking.

[0777] "Food waste" refers to the waste that occurs when ingredients or food are discarded.

[0778] "Cooking conditions" refers to specific conditions that must be taken into consideration when cooking, such as cooking time and available cooking equipment.

[0779] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[0780] overview

[0781] User Roles

[0782] The user inputs the ingredients to be used and the name of the dish they want to make into the device. For example, they can specify ingredients such as "tomato," "chicken," or "potato," and names of dishes such as "Dish A" or "Dish B." The user simply needs to express naturally using voice and facial expressions any stress or joy they feel while cooking.

[0783] Device Role

[0784] The terminal is a device that receives input from the user, transmits it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that can analyze the user's voice and facial expressions. Examples of such devices include smartphones and tablets.

[0785] Server Roles

[0786] The server refers to the database based on the information sent by the user and uses an AI model (generative AI model) to generate and provide optimal cooking instructions. The server also processes data obtained from the emotion engine and can regenerate cooking instructions according to the user's emotions.

[0787] Hardware and software used

[0788] Both the server and the terminal use hardware with advanced processing capabilities. Specifically, MySQL or PostgreSQL is used as the database management system (DBMS), and machine learning frameworks such as TensorFlow and PyTorch can be used to generate AI models.

[0789] Data processing and calculation

[0790] 1. Receiving and Sending Data

[0791] The user uses the terminal to input ingredients and the name of the dish they want to make. For example, they input "tomatoes, chicken, and potatoes" and "dish A, dish B."

[0792] The device sends this information to the server. Specifically, text data is sent to the server in JSON or XML format.

[0793] 2. Get recipe information

[0794] The server accesses the database based on the information received from the user to retrieve relevant recipe information, including the list of ingredients, quantities, cooking steps, cooking time, etc., corresponding to the specified dish name.

[0795] 3. Generating optimal cooking procedures

[0796] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0797] 4. Procedure adjustment using emotion engine

[0798] The device is equipped with an emotion engine that analyzes the user's voice and facial expressions to identify their emotions, and if the user feels stressed, it requests the server to adjust the cooking instructions.

[0799] Based on this information, the server regenerates the cooking recipe and sends it to the terminal.

[0800] 5. Providing instructions and recording usage

[0801] The device displays the optimal cooking instructions sent from the server to the user, which are provided in the form of text, images, and videos.

[0802] The user follows the cooking procedure and, after cooking is complete, inputs the amounts of ingredients actually used into the terminal.

[0803] The device sends the inputted usage data to the server, which stores and analyzes it to suggest the best way to use ingredients for the next time.

[0804] Specific examples

[0805] For example, if a user wants to make "Dish A using tomatoes and chicken" and "Dish B using potatoes," the following operation will occur.

[0806] 1. The user enters "tomato," "chicken," and "potato" as ingredients and specifies "Dish A" and "Dish B" as dish names.

[0807] 2. The device sends this information to the server.

[0808] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0809] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0810] 5. The device analyzes the user's voice and facial expression data using an emotion engine and sends emotional information to the server as needed.

[0811] 6. The server generates the adjusted procedure again and sends the optimal procedure to the terminal.

[0812] 7. The device displays the optimal cooking procedure to the user, who then follows it to proceed with the cooking.

[0813] 8. After the user has completed cooking, they input the amount of ingredients used into the terminal.

[0814] 9. The device sends the usage data to the server, which stores and analyzes the data to suggest optimal ingredient usage methods for the next time and beyond.

[0815] Prompt Sentence Examples

[0816] The following is an example of input to suggest the optimal procedure for the next time onwards.

[0817] User-entered ingredients: Tomato, Chicken, Potato

[0818] Name of the dish you want to make: Dish A, Dish B

[0819] Cookware restrictions: frying pans, pots

[0820] Cooking time limit: 30 minutes

[0821] User Emotion: Stress (Audio Analysis Results)

[0822] This allows the system to provide optimal cooking procedures according to the user's situation, enabling efficient and waste-free cooking.

[0823] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0824] Step 1:

[0825] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. For example, they input "tomato," "chicken," "potato," and "dish A" and "dish B."

[0826] Input: ingredients and dish name

[0827] Output: Input information (ingredients and dish name)

[0828] Specific action: A user enters data into an input field on a smartphone or tablet and presses the submit button.

[0829] Step 2:

[0830] The device receives input from the user, formats it, and sends it to the server in JSON or XML format.

[0831] Input: Input information (ingredients and dish name)

[0832] Output: Formatted data (JSON or XML format)

[0833] What it does: The device formats the data internally and sends it to a server via the Internet.

[0834] Step 3:

[0835] The server accesses the database based on the data received from the user and obtains the corresponding recipe information.

[0836] Input: Formatted data (ingredients and dish name)

[0837] Output: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[0838] What happens: The server uses an SQL query to retrieve the required information from the database.

[0839] Step 4:

[0840] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information.

[0841] Input: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[0842] Output: Optimal cooking procedure

[0843] Specific operation: The server inputs a prompt sentence into the generative AI model, and the model generates optimal cooking instructions.

[0844] Step 5:

[0845] The terminal analyzes the user's voice and facial expressions and uses an emotion engine to identify the user's emotional state.

[0846] Input: User audio or video data

[0847] Output: User's emotional state (e.g., stressed, relaxed)

[0848] Specific operation: The device uses the camera and microphone to collect the user's voice and facial expression data, which is then analyzed by the emotion engine.

[0849] Step 6:

[0850] The server adjusts the cooking instructions as needed based on information from the emotion engine.

[0851] Input: optimal cooking procedure, user's emotional state

[0852] Output: Adjusted cooking instructions

[0853] What it does: The server re-runs the AI ​​model to generate cooking instructions based on the emotion.

[0854] Step 7:

[0855] The device displays the cooking instructions received from the server to the user. The instructions are provided in the form of text, images, or videos.

[0856] Input: Adjusted cooking instructions

[0857] Output: Cooking instructions displayed to the user

[0858] Specific operation: The device displays cooking instructions on the display.

[0859] Step 8:

[0860] The user proceeds with cooking by following the steps displayed on the terminal.

[0861] Input: User actions, adjusted cooking instructions

[0862] Output: Cooking progress

[0863] Specific Action: The user actually follows the steps using the ingredients and utensils.

[0864] Step 9:

[0865] After cooking is complete, the user inputs the amounts of ingredients actually used into the terminal.

[0866] Input: Amount of material used

[0867] Output: Actual usage data

[0868] Specific actions: The user enters the amount of ingredients used in the input field on the terminal and presses the send button.

[0869] Step 10:

[0870] The terminal transmits the input usage data to the server.

[0871] Input: Actual usage data

[0872] Output: Usage data (JSON or XML format)

[0873] What it does: The device formats the data and sends it to a server over the Internet.

[0874] Step 11:

[0875] The server stores and analyzes the received usage data to suggest optimal food usage methods for the next time and beyond.

[0876] Input: Usage data

[0877] Output: Proposal for optimal ingredient usage

[0878] What it does: The server stores usage data in a database and uses analytical algorithms to generate optimal recommendations.

[0879] (Application example 2)

[0880] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0881] Conventional food delivery services are unable to respond to users' emotions or current situations, resulting in a uniform experience for users, leading to low customer satisfaction. Furthermore, food delivery times and routes are set based on fixed standards, making it difficult to adapt to users' stress and urgent needs. This makes it difficult to provide the delivery experience users expect, resulting in a lack of emotional support in particular.

[0882] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredients to be used in a dish and the name of the dish to be made from the user; means for retrieving related recipe information from a database based on the ingredients and the name of the dish; means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information; means for providing the generated cooking procedures to the user; means for receiving the amounts of ingredients actually used from the user; means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future use; and an emotion engine that recognizes the user's emotions and means for adjusting the cooking procedures based on this emotion engine. This makes it possible to provide an optimal food delivery service that suits the user's emotions and current situation, thereby improving user satisfaction.

[0883] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish that the user wants to make.

[0884] A "terminal" is a device that receives input from a user, transmits it to the server, and displays the generated cooking instructions to the user.

[0885] The "server" is a system that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[0886] An "ingredient" is a food or ingredient used to make a dish.

[0887] "Dish name" is the name of the dish the user wants to make.

[0888] "Recipe information" refers to information stored in a database, such as ingredient lists, quantities, cooking instructions, and cooking times.

[0889] A "database" is a central location where recipe information is stored.

[0890] A "cooking procedure" is a series of tasks or steps to complete a dish.

[0891] The "emotion engine" is a system that identifies emotions by analyzing the user's voice input and facial expressions.

[0892] "Food waste" refers to food that is discarded without being used.

[0893] "Optimization" refers to adjusting processes to efficiently create multiple dishes.

[0894] "Delivery time" is the time it takes for food to be delivered to the user after it is ordered.

[0895] A "delivery route" is the route that food will take when delivered.

[0896] The food delivery system based on this invention consists of a user, a terminal, and a server. The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. The terminal acquires this information and sends it to the server. The server then references a database based on the received information and acquires related recipe information. The recipe information includes a list of ingredients, quantities, cooking steps, cooking time, etc.

[0897] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. This also optimizes the order in which cooking utensils are used and waiting times. The server then sends the generated cooking instructions to the device, which displays them to the user. The user can then proceed with the cooking process by following the displayed instructions.

[0898] Furthermore, the device is equipped with an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. Based on this emotion data, the server can adjust the cooking instructions. For example, if the user is feeling stressed, the server will suggest cooking instructions that shorten cooking time or simplify the process.

[0899] After the user has finished cooking, they input the amount of ingredients they actually used into the device. This data is sent to the server and used to generate recommendations for optimal use of ingredients for future meals, thereby helping to manage food waste.

[0900] The specific processing of this system is realized using programming languages ​​such as Python and AI frameworks (e.g., TensorFlow and PyTorch), and OpenCV and speech recognition APIs are used to recognize emotions.

[0901] Specific examples

[0902] Suppose a user opens a smartphone app and orders tomato pasta. The device's emotion engine determines from the user's tone of voice and facial expression that the user is feeling stressed. The server receives this information, calculates the optimal delivery route while shortening delivery time, and displays it to the user. This system allows the user to receive their food quickly and efficiently without feeling stressed.

[0903] Prompt Sentence Examples

[0904] "The user ordered tomato pasta. The user's voice tone indicates that they are stressed. Based on this emotion, please reduce the delivery time and generate the optimal delivery route. Please keep the estimated delivery time within XX minutes."

[0905] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0906] Step 1:

[0907] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the device. The input information is saved on the device as a list of ingredients (e.g., "tomatoes," "chicken") and the name of the dish (e.g., "tomato pasta").

[0908] Step 2:

[0909] The terminal sends the ingredient list and dish name obtained from the user to the server, where the terminal uses an HTTP request to send the ingredient and dish name data, and the server uses the received information as input for a database query.

[0910] Step 3:

[0911] The server retrieves related recipe information from the database based on the received ingredients and dish name. Specifically, it executes an SQL query on the database to find records with the corresponding dish name. The output is the recipe information (ingredients list, quantities, cooking steps, cooking time, etc.).

[0912] Step 4:

[0913] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. The AI ​​model optimizes the entire cooking process, taking into account the order in which cooking utensils are used and waiting times. At this stage, the generative AI model calculates the cutting order of ingredients, heating times, and processes that can be carried out simultaneously, and outputs efficient cooking instructions.

[0914] Step 5:

[0915] The server sends the generated optimal cooking instructions to the device, again using an HTTP request to return the cooking instruction data to the device, which receives and stores it.

[0916] Step 6:

[0917] The device displays cooking instructions to the user in the form of text, images, and videos, organized for easy understanding by the user. The user then proceeds with the cooking process based on this information.

[0918] Step 7:

[0919] The emotion engine installed on the device analyzes the user's voice and facial expressions to identify their current emotion. Emotion identification is performed in real time using a microphone and camera, OpenCV, and a speech recognition API. The output is the user's emotional state (e.g., "stress").

[0920] Step 8:

[0921] The device transmits the emotion data identified by the emotion engine to the server, which receives this data as input and adjusts the cooking instructions.

[0922] Step 9:

[0923] The server then adjusts the cooking instructions based on the user's emotional state. For example, if the user is feeling stressed, the AI ​​model can be used to generate instructions that shorten cooking time or simplify the process. In this process, the generative AI model receives specific emotional data as input and re-optimizes the instructions based on that data. The adjusted cooking instructions are then generated as output.

[0924] Step 10:

[0925] The server sends the adjusted cooking recipe to the terminal, which then displays the adjusted recipe to the user, allowing the user to proceed with cooking more comfortably.

[0926] Step 11:

[0927] After the user has finished cooking, they input the amount of ingredients they actually used into the device, which is important information for reducing food waste.

[0928] Step 12:

[0929] The device sends usage data to the server, which uses this data to manage food waste and propose optimal ingredient usage methods for future uses. At this stage, the server analyzes the previous usage data and outputs the next recipe proposal and adjusts the ingredient amounts.

[0930] The above steps realize a system that provides optimal food delivery services according to the user's emotions and current situation, thereby improving user satisfaction.

[0931] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0932] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0933] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0934] [Third embodiment]

[0935] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0936] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0937] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0938] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0939] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0940] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0941] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0942] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0943] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0944] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0945] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0946] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0947] The system of the present invention processes the information entered by the user about ingredients to be used in the dish and the name of the dish they want to make, and generates and provides optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[0948] overview

[0949] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[0950] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user.

[0951] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[0952] System Operation

[0953] Receiving and Sending Information

[0954] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make through the terminal interface. For example, they input "tomato," "chicken," and "potato" as the ingredients they want to use, and specify "dish A" and "dish B" as the names of the dishes they want to make.

[0955] The device sends the entered information to the server, including the ingredient list and the name of the dish, as well as any specific cooking conditions (such as time limits and available cooking equipment).

[0956] Get recipe information

[0957] Based on the received user information, the server retrieves related recipe information from its internal database, including detailed recipes for dishes A and B (ingredients, amounts, cooking steps, cooking time, etc.).

[0958] Generating optimal cooking procedures

[0959] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently creating multiple dishes. For example,

[0960] "Boil the potatoes while you chop the tomatoes."

[0961] This includes steps such as "mashing potatoes while frying chicken."

[0962] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[0963] Providing instructions

[0964] The server then sends the generated cooking instructions to the device. The instructions are structured in an easy-to-understand step-by-step format, and include diagrams and videos as needed.

[0965] The terminal displays these steps to the user, allowing them to follow them in real time.

[0966] Recording usage and suggesting next time

[0967] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[0968] The terminal transmits the input usage data to the server.

[0969] The server uses this data to manage food waste and generates suggestions on how to best use ingredients in the future.

[0970] Specific examples

[0971] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[0972] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[0973] 2. The device sends this information to the server.

[0974] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[0975] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0976] 5. The server sends the generated procedure to the terminal, which displays it to the user.

[0977] 6. The user follows the instructions to proceed with cooking, and after cooking is complete, enters the amount of ingredients used into the terminal.

[0978] 7. The device sends the usage data to the server, which then uses this data to suggest the optimal way to use ingredients for the next time onwards.

[0979] In this way, the system of the present invention supports the user's cooking process and enables efficient and waste-free cooking.

[0980] The processing flow will be explained below.

[0981] Step 1:

[0982] The user uses the terminal interface to input ingredients and the name of the dish they want to make, for example, "tomatoes," "chicken," and "potatoes," and names the dishes such as "Dish A" and "Dish B."

[0983] Step 2:

[0984] The device receives the information about ingredients and the name of the dish entered by the user and prepares to send it to the system. It also sends specific cooking conditions (e.g., cooking time limits and available cooking equipment) if necessary.

[0985] Step 3:

[0986] The terminal transmits the user-entered data to the server, including the list of ingredients, the name of the dish, and cooking conditions.

[0987] Step 4:

[0988] The server analyzes the received user data and accesses the database to retrieve related recipe information, such as the list of ingredients, quantities, cooking steps, and cooking time for the specified dish.

[0989] Step 5:

[0990] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[0991] Step 6:

[0992] The server then sends the generated optimal cooking instructions to the device. These instructions are structured step by step and are organized in a way that makes them easy for the user to understand.

[0993] Step 7:

[0994] The terminal displays the cooking instructions sent from the server to the user, and the user can proceed with cooking by following these instructions. The instructions are presented in the form of text, images, and, if necessary, video.

[0995] Step 8:

[0996] The user records the amounts of ingredients actually used as they cook, and when cooking is complete, inputs the amounts into the terminal.

[0997] Step 9:

[0998] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[0999] Step 10:

[1000] The server manages food waste based on the collected usage data and suggests optimal ways to use ingredients from next time onwards. Specifically, it analyzes the user's past data and suggests combinations and amounts of ingredients that minimize waste.

[1001] In this way, specific actions at each step support efficient operation of the entire system, helping users to cook without waste.

[1002] Example 1

[1003] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1004] In modern life, it is extremely important for users to cook efficiently and reduce food waste. Conventional recipe provision systems do not optimize cooking procedures when making multiple dishes simultaneously, often resulting in wasted time and effort. Furthermore, they lack a mechanism for recording the amounts of ingredients actually used and using this information for future cooking. This leads to increased food waste. Furthermore, the cooking procedures are not visually easy to understand, which hinders users from cooking smoothly.

[1005] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1006] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for transmitting the generated cooking procedures to a terminal and displaying them to the user in real time, and means for displaying the retrieved recipe information and cooking procedures in visual or video format. This allows the user to efficiently cook multiple dishes simultaneously and follow the visual instructions while cooking, thereby saving time and effort and reducing food waste.

[1007] A "user" refers to a person who inputs ingredients and the name of the dish they want to make in order to create a dish.

[1008] "Terminal" refers to a device that receives information from a user, transmits it to a server, and displays the generated cooking instructions to the user.

[1009] The "server" refers to a device that references a database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[1010] "Ingredients" refers to the substances, such as foods and seasonings, used to create a dish.

[1011] "Dish name" refers to the name of the dish the user wants to make.

[1012] "Recipe information" refers to information such as ingredients needed to prepare a dish, the required amounts, cooking steps, cooking time, etc.

[1013] A "database" refers to a collection of information that stores and manages recipe information, etc.

[1014] An "AI model" refers to an algorithm or program that uses artificial intelligence technology to analyze data and derive optimal solutions.

[1015] A "prompt sentence" refers to a sentence used to input specific instructions or questions to an AI model.

[1016] "Cooking procedure" refers to a series of steps for preparing a dish.

[1017] "Food waste" refers to the amount of food that is not consumed and is discarded.

[1018] "Visual display" refers to presenting information in an intuitive way using diagrams, videos, etc.

[1019] "Real-time display" refers to a display method that provides information immediately when a user performs an operation.

[1020] The system of the present invention processes the information entered by the user about the ingredients to be used in the dish and the name of the dish they want to make, and generates and provides the optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[1021] Hardware and software used

[1022] The system uses a "terminal" that receives user input, a "server" that accesses the database and performs calculations using AI models, and an internal database.

[1023] 1. Terminal: A device such as a smartphone, tablet, or PC. These devices receive user input through a user interface, send it to the server, and display the generated cooking instructions.

[1024] 2. Server: A computer with high-performance computing power and software for running AI models, specifically AI frameworks such as TensorFlow and PyTorch.

[1025] 3. Database: Stores and manages recipe information and user ingredient usage information. Typically, an SQL database or NoSQL database (e.g., MySQL, MongoDB) is used.

[1026] System Operation Overview

[1027] 1. The user inputs the ingredients to be used in the cooking and the name of the dish they wish to make through the terminal interface. For example, they can input "tomatoes, chicken, potatoes" as the ingredients they wish to use and specify "dish A" and "dish B" as the names of the dishes they wish to make. At this time, the user can also input specific cooking conditions (e.g., time limit, available cooking utensils).

[1028] 2. The device sends the information to the server as a data packet, including the ingredients list, the name of the dish, and the cooking instructions.

[1029] 3. The server references its internal database based on the received data and obtains the relevant recipe information (ingredients, required quantities, cooking steps, cooking time).

[1030] 4. The server uses the AI ​​model to generate efficient cooking instructions based on the acquired recipe information, using prompts such as "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?"

[1031] 5. The generated recipes are sent from the server to the device, which displays step-by-step instructions to the user in real time, including diagrams and videos as needed.

[1032] Specific examples

[1033] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[1034] 1. The user enters "tomatoes, chicken, potatoes" as the ingredients to be used in the dish, and specifies "dish A, dish B" as the names of the dishes they want to make.

[1035] 2. The device sends this information to the server.

[1036] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1037] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1038] 5. The server sends the generated instructions to the terminal, which displays them to the user in real time.

[1039] 6. The user follows the instructions to proceed with cooking and inputs the amount of ingredients used after cooking is complete.

[1040] 7. The device sends the usage data to the server, and the server suggests the best way to use ingredients from next time onwards.

[1041] In this way, the system of the present invention supports the user's cooking process, enabling efficient and waste-free cooking, and can also provide specific suggestions for reducing food waste.

[1042] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1043] Step 1:

[1044] The user uses the terminal interface to input the ingredients to be used in cooking and the name of the dish they want to make. For example, if the user inputs "tomatoes, chicken, and potatoes" as the ingredients they want to use and specifies "dish A, dish B" as the names of the dishes they want to make, this information is treated as input data. Subsequent information processing is initiated based on this input.

[1045] Step 2:

[1046] The terminal sends the input data to the server as a data packet. The data sent includes a list of ingredients (e.g., "200g tomatoes, 300g chicken, 400g potatoes"), dish names (e.g., "Dish A, Dish B"), and cooking conditions (e.g., "Can be cooked within 30 minutes"). Based on this information, the server is ready to process and calculate the data.

[1047] Step 3:

[1048] The server references its internal database based on the received data and retrieves the relevant recipe information. For example, it executes a database query to retrieve recipe information (ingredients, quantities, cooking steps, and cooking time) related to "Dish A" and "Dish B." The retrieved recipe information is loaded from the database into computer memory and used in the next step.

[1049] Step 4:

[1050] The server uses an AI model to generate efficient cooking instructions based on the acquired recipe information. The AI ​​model (e.g., TensorFlow, PyTorch) performs processing based on the prompt, "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?" For example, an optimal cooking procedure is generated that includes parallel processing such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken." In this process, the AI ​​model performs data calculations and outputs the optimal procedure.

[1051] Step 5:

[1052] The server then sends the generated cooking instructions to the device. These instructions include step-by-step instructions, as well as diagrams and videos if necessary. For example, they may include specific instructions such as "Step 1: Finely chop the tomatoes (with diagram)" and "Step 2: Boil the potatoes while chopping the tomatoes (with video)."

[1053] Step 6:

[1054] The device displays the received cooking instructions to the user in real time, for example, by using a touchscreen or voice assistant to indicate the next step the user should take, allowing the user to smoothly proceed with cooking while looking at the screen.

[1055] Step 7:

[1056] After cooking is complete, the user inputs the amount of ingredients actually used into the terminal. For example, they might input "tomatoes: 180g, chicken: 250g, potatoes: 350g." This generates actual usage data.

[1057] Step 8:

[1058] The device sends the usage data entered by the user to the server. The server processes this data to manage food waste. For example, it analyzes the data and generates optimal instructions for using ingredients for the next time and beyond (e.g., "Next time, try a recipe that uses only 200g of potatoes").

[1059] Step 9:

[1060] The server sends the generated next cooking suggestion to the device, which displays the suggestion to the user so that the user can use it as a reference when planning their next cooking. This allows the user to use ingredients efficiently and reduce food waste.

[1061] In this way, the system of the present invention includes a series of processing steps that support the user's cooking process and enable efficient and waste-free cooking.

[1062] (Application example 1)

[1063] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1064] The present invention aims to reduce the effort and time users face during the cooking process and reduce food waste by providing an efficient cooking procedure. Another objective of the present invention is to provide a safe and efficient cooking environment in an autonomous vehicle, thereby providing a comfortable dining experience while driving.

[1065] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1066] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for allowing the user to input ingredients and the name of the dish by voice and receive cooking instructions visually or audibly, and means for linking with cooking utensils used in the autonomous vehicle and providing optimal cooking procedures according to the situation, thereby enabling users to cook efficiently and safely even while in an autonomous vehicle and reduce food waste.

[1067] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish they wish to make, and then cooks according to the system's instructions.

[1068] "Ingredients" are the ingredients and seasonings used to create a dish.

[1069] "Dish Name" is the name of the particular dish the user wants to make.

[1070] A "database" is an information storage device that stores related recipe information.

[1071] "Recipe information" refers to detailed information such as ingredients, amounts required, cooking steps, cooking time, etc., for making a particular dish.

[1072] An "optimal cooking procedure" is a series of cooking steps that optimizes the order in which cooking utensils are used and waiting time in order to efficiently prepare multiple dishes.

[1073] "Cooking instructions" are the specific steps and processes for creating a dish.

[1074] "Usage data" refers to data relating to the amount of material actually used by the user.

[1075] "Food waste" refers to the amount of food ingredients and dishes that are discarded unnecessarily.

[1076] "Voice input" is a method in which the user inputs information such as ingredients and the name of a dish using voice through a microphone.

[1077] "Visual instructions" are written or graphic instructions provided to the user through a display.

[1078] "Audio instructions" are audio instructions provided to the user through a speaker.

[1079] An "autonomous vehicle" is a vehicle that drives automatically and is equipped with simple cooking equipment inside.

[1080] "Cooking equipment" refers to equipment and tools used in cooking, including microwave ovens and hot plates.

[1081] A "situation-appropriate cooking procedure" is a cooking procedure that is optimized according to the condition of the cooking utensils and the user's state.

[1082] MODE FOR CARRYING OUT THE INVENTION

[1083] The present invention relates to a system for providing efficient cooking procedures in an autonomous vehicle, as described in detail below.

[1084] 1. System Overview

[1085] The system aims to help users prepare meals comfortably in their autonomous vehicles and is comprised of the following main components:

[1086] An interface that allows users to input ingredients and dish names by voice and receive cooking instructions visually or audibly

[1087] A server that obtains recipe information based on ingredients and dish names and generates optimal cooking instructions

[1088] A device that works with cooking appliances (e.g., microwave ovens, hot plates) installed in autonomous vehicles to provide cooking instructions according to the situation.

[1089] 2. Program Processing

[1090] The main processes in the system program are as follows:

[1091] Hardware and Software

[1092] Smart glasses: A display that shows visual cooking instructions and a microphone for receiving voice commands

[1093] Self-driving vehicles: equipped with cooking appliances (microwave oven, hot plate, etc.)

[1094] Server: Collects recipe information and generates optimal cooking instructions

[1095] Speech recognition engine: Software for processing user voice input

[1096] Network module: Software for data communication between the smart glasses and the server

[1097] Data processing and calculation

[1098] 1. Receiving and Sending User Input

[1099] The user inputs ingredients and the name of the dish by voice.

[1100] The smart glasses' voice recognition engine converts the voice into text data and sends it to the server.

[1101] 2. Obtaining recipe information and generating cooking instructions

[1102] The server retrieves the corresponding recipe information from the database.

[1103] Based on the acquired recipe information, a generative AI model is used to generate optimal cooking procedures.

[1104] If calibration is required, optimize the order in which cooking appliances are used and the waiting time.

[1105] 3. Providing cooking instructions

[1106] The server sends the generated cooking instructions to the smart glasses.

[1107] The smart glasses provide visual or audio instructions to the user.

[1108] 4. Recording usage data

[1109] After cooking, the user inputs the amount of ingredients actually used by voice.

[1110] The smart glasses convert the voice into text data and send this data to a server.

[1111] The server records the usage data received for food waste management and suggests the best way to use ingredients from next time onwards.

[1112] 3. Specific examples

[1113] If a user wants to cook "sauteed chicken" using "tomatoes" and "chicken" in an autonomous vehicle, the system operates as follows:

[1114] 1. The user speaks "tomato, chicken, chicken saute" into the smart glasses.

[1115] 2. The smart glasses convert the speech into text and send it to the server.

[1116] 3. The server retrieves the recipe information and generates efficient cooking instructions, such as "fry the chicken while chopping the tomatoes."

[1117] 4. The server sends the generated instructions to the smart glasses, which then display them to the user.

[1118] 5. After cooking is complete, the user can voice-input the amount of ingredients actually used, and the smart glasses will send that data to the server.

[1119] 6. The server records usage data to manage food waste and suggests optimal ways to use ingredients for future use.

[1120] 4. Examples of prompts

[1121] "Just tell me the ingredients you use in the dish. For example, 'tomatoes, chicken'."

[1122] "Just say the name of the dish you want to make. For example, 'Chicken Sauté'."

[1123] "Say 'Next' to move to the next step."

[1124] "Please tell me the quantities of the ingredients you used. For example, '2 tomatoes, 300g chicken'."

[1125] Thus, the system of the present invention provides a concrete means for efficient and comfortable cooking in an autonomous vehicle.

[1126] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1127] Step 1:

[1128] Input: The user inputs ingredients and dish names by voice through the smart glasses.

[1129] How it works: The smart glasses' voice recognition engine converts the user's speech into text data.

[1130] Output: The converted text data, including ingredients and dish names such as "tomato," "chicken," and "sauteed chicken."

[1131] Step 2:

[1132] Input: Text data sent from the smart glasses to the server.

[1133] Operation: The server searches the database based on the received ingredients and dish name to retrieve related recipe information.

[1134] Output: Retrieved recipe information. For example, detailed information such as ingredients needed for "Sauteed Chicken", required quantities, cooking steps, cooking time, etc.

[1135] Step 3:

[1136] Input: Recipe information retrieved from the database.

[1137] How it works: The server uses generative AI models to generate optimal cooking instructions for efficiently creating multiple dishes.

[1138] Output: Optimal cooking steps. For example, an efficient process such as "fry chicken while chopping tomatoes."

[1139] Step 4:

[1140] Input: The optimal cooking instructions sent by the server.

[1141] How it works: The smart glasses receive the cooking instructions and present them to the user visually or audibly, along with diagrams and videos if needed.

[1142] Output: Cooking instructions that the user can follow in real time, for example, "Cut the tomatoes" on the display.

[1143] Step 5:

[1144] Input: The user inputs the actual amount of ingredients used by voice as the cooking progresses.

[1145] How it works: The smart glasses' voice recognition engine again converts the speech into text data and sends that data to the server.

[1146] Output: Converted text data. For example, usage data such as "2 tomatoes, 300g chicken."

[1147] Step 6:

[1148] Input: Usage data sent from smart glasses.

[1149] How it works: The server manages food waste based on the usage data it receives, and suggests optimal ways to use ingredients from next time onwards.

[1150] Output: Food waste management data that will be useful for your next cooking and suggestions on how to best use ingredients. For example, "Since you used up all the tomatoes this time, use fresh tomatoes next time."

[1151] This will enable users to cook efficiently and safely inside self-driving vehicles and reduce food waste.

[1152] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1153] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[1154] overview

[1155] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[1156] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that recognizes the user's emotions.

[1157] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[1158] System Operation

[1159] Receiving and Sending Information

[1160] The user uses the terminal to input ingredients to be used in cooking and the name of the dish they want to make. For example, they can specify ingredients such as "tomato," "chicken," and "potato," and also specify the name of the dish, such as "Dish A" or "Dish B."

[1161] The terminal acquires the information entered by the user and transmits it to the server along with specific cooking conditions (such as cooking time limits and available cooking utensils) as needed.

[1162] Get recipe information

[1163] The server accesses the database based on the received user data to retrieve relevant recipe information, including the list of ingredients, serving sizes, cooking steps, cooking time, etc., corresponding to the specified dish name.

[1164] Generating optimal cooking procedures

[1165] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" and "mash potatoes while frying chicken."

[1166] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[1167] Procedure adjustment by emotion engine

[1168] The device is equipped with an emotion engine that analyzes the user's voice input and facial expressions to identify emotions. For example, if the user is feeling stressed, the emotion engine will detect this and request the server to adjust the actual procedure.

[1169] The server generates cooking instructions based on the user's emotions based on the information from the emotion engine. For example, if the server determines that the user is under high stress, it suggests instructions that shorten cooking time or are simpler.

[1170] Providing instructions

[1171] The server then sends the generated optimal cooking instructions to the device. The instructions are structured step by step and are organized in a way that makes them easy for users to understand.

[1172] The device displays cooking instructions to the user, who can follow the instructions to proceed with the cooking. The instructions are presented in the form of text, images, and, if necessary, video.

[1173] Recording usage and suggesting next time

[1174] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[1175] The terminal transmits the input usage data to the server.

[1176] The server uses this data to manage food waste and generates suggestions on how to best use ingredients for future purchases.

[1177] Specific examples

[1178] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[1179] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[1180] 2. The device sends this information to the server.

[1181] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1182] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1183] 5. The server sends the generated instructions back to the terminal, which displays them to the user.

[1184] 6. The user follows the cooking instructions. During the cooking process, the device analyzes the user's emotions and adjusts the cooking instructions as necessary.

[1185] 7. After the user has finished cooking, they input the amount of ingredients used into the terminal.

[1186] 8. The device sends the usage data to the server, which then uses this data to suggest the best way to use ingredients for the next time onwards.

[1187] In this way, the system of the present invention supports the cooking process of the user, realizing efficient and waste-free cooking that also takes emotions into consideration.

[1188] The processing flow will be explained below.

[1189] Step 1:

[1190] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make using the terminal interface. For example, they can specify ingredients such as "tomato," "chicken," and "potato" and dish names such as "Dish A" and "Dish B."

[1191] Step 2:

[1192] The device retrieves the ingredients and recipe name entered by the user and prepares all data to be sent to the server, which may also include specific cooking conditions (e.g., cooking time limits and available cooking equipment).

[1193] Step 3:

[1194] The device sends the input information to the server, which includes the ingredients list, the name of the dish, and cooking instructions.

[1195] Step 4:

[1196] The server analyzes the received information and accesses the database to retrieve related recipe information, such as the ingredient list, quantities, cooking steps, and cooking time for the specified dish.

[1197] Step 5:

[1198] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently preparing multiple dishes. For example, it optimizes the process by taking into account the order in which cooking utensils are used and waiting times, such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken."

[1199] Step 6:

[1200] The device analyzes the user's voice input and facial expressions in real time and uses an emotion engine to identify the user's emotions, for example, whether the user is feeling stressed or enjoying cooking.

[1201] Step 7:

[1202] The device uses the emotion engine's results to determine whether the cooking instructions need to be adjusted. For example, if the device determines that the user's stress level is high, it sends that information to the server.

[1203] Step 8:

[1204] The server receives data from the emotion engine and regenerates cooking instructions according to the user's emotions. For example, if the user is under high stress, the instructions are modified to shorten cooking time or provide simpler instructions.

[1205] Step 9:

[1206] The server then sends cooking instructions tailored to the user's emotions to the device, allowing the user to receive detailed support tailored to their emotions.

[1207] Step 10:

[1208] The device displays the adjusted steps to the user, allowing the user to follow the instructions to proceed with the cooking. For example, specific instructions such as "First, cut the tomatoes, then boil the potatoes" are displayed.

[1209] Step 11:

[1210] The user records the amounts of ingredients actually used while cooking, and inputs the amounts into the terminal when cooking is complete.

[1211] Step 12:

[1212] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[1213] Step 13:

[1214] The server manages food waste based on the collected usage data and generates suggestions on how to best use ingredients from next time onwards, allowing users to reduce waste the next time they cook.

[1215] This series of steps enables the system to provide efficient and waste-free cooking support while responding to the user's real-time emotional state.

[1216] Example 2

[1217] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1218] In today's world, efficiently preparing multiple dishes simultaneously and minimizing food waste are challenges facing many households and restaurants. Furthermore, the lack of adjustments to cooking procedures based on the user's emotions leaves the stress and difficulty experienced by users unresolved. Furthermore, conventional cooking assistance systems lack the functionality to reflect the amount of ingredients used by the user in the next cooking session, resulting in food waste.

[1219] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1220] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for analyzing the user's emotions, means for adjusting the cooking procedures based on the analysis results, means for receiving the amounts of ingredients actually used from the user, and means for managing food waste based on the received usage data and presenting optimal ways to use ingredients for future use. This enables efficient cooking support that takes the user's emotions into consideration, and can provide optimal cooking procedures while reducing food waste.

[1221] A "user" is an entity that uses the system to input ingredients to be used in cooking and the name of the dish they wish to make.

[1222] A "terminal" is a device that receives input from a user, sends it to the server, and displays the generated cooking instructions to the user. It may also include an emotion engine.

[1223] "Server" refers to a combination of hardware and software that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[1224] "Ingredients" refer to the foods or ingredients that a user specifies to make a dish.

[1225] "Dish name" refers to the name of the dish the user wants to make.

[1226] "Recipe information" refers to information such as ingredients, quantities, cooking steps, cooking time, etc.

[1227] A "database" is a digital system that manages and stores data such as recipe information.

[1228] An "AI model" is an algorithm that uses the latest artificial intelligence technology to analyze data and generate optimal cooking instructions.

[1229] An "emotion engine" is a system that analyzes a user's voice and facial expressions to identify their emotions.

[1230] A "cooking recipe" is a set of specific instructions for preparing a dish.

[1231] "Usage amount data" refers to information regarding the amount of ingredients actually used by the user in cooking.

[1232] "Food waste" refers to the waste that occurs when ingredients or food are discarded.

[1233] "Cooking conditions" refers to specific conditions that must be taken into consideration when cooking, such as cooking time and available cooking equipment.

[1234] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[1235] overview

[1236] User Roles

[1237] The user inputs the ingredients to be used and the name of the dish they want to make into the device. For example, they can specify ingredients such as "tomato," "chicken," or "potato," and names of dishes such as "Dish A" or "Dish B." The user simply needs to express naturally using voice and facial expressions any stress or joy they feel while cooking.

[1238] Device Role

[1239] The terminal is a device that receives input from the user, transmits it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that can analyze the user's voice and facial expressions. Examples of such devices include smartphones and tablets.

[1240] Server Roles

[1241] The server refers to the database based on the information sent by the user and uses an AI model (generative AI model) to generate and provide optimal cooking instructions. The server also processes data obtained from the emotion engine and can regenerate cooking instructions according to the user's emotions.

[1242] Hardware and software used

[1243] Both the server and the terminal use hardware with advanced processing capabilities. Specifically, MySQL or PostgreSQL is used as the database management system (DBMS), and machine learning frameworks such as TensorFlow and PyTorch can be used to generate AI models.

[1244] Data processing and calculation

[1245] 1. Receiving and Sending Data

[1246] The user uses the terminal to input ingredients and the name of the dish they want to make. For example, they input "tomatoes, chicken, and potatoes" and "dish A, dish B."

[1247] The device sends this information to the server. Specifically, text data is sent to the server in JSON or XML format.

[1248] 2. Get recipe information

[1249] The server accesses the database based on the information received from the user to retrieve relevant recipe information, including the list of ingredients, quantities, cooking steps, cooking time, etc., corresponding to the specified dish name.

[1250] 3. Generating optimal cooking procedures

[1251] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1252] 4. Procedure adjustment using emotion engine

[1253] The device is equipped with an emotion engine that analyzes the user's voice and facial expressions to identify their emotions, and if the user feels stressed, it requests the server to adjust the cooking instructions.

[1254] Based on this information, the server regenerates the cooking recipe and sends it to the terminal.

[1255] 5. Providing instructions and recording usage

[1256] The device displays the optimal cooking instructions sent from the server to the user, which are provided in the form of text, images, and videos.

[1257] The user follows the cooking procedure and, after cooking is complete, inputs the amounts of ingredients actually used into the terminal.

[1258] The device sends the inputted usage data to the server, which stores and analyzes it to suggest the best way to use ingredients for the next time.

[1259] Specific examples

[1260] For example, if a user wants to make "Dish A using tomatoes and chicken" and "Dish B using potatoes," the following operation will occur.

[1261] 1. The user enters "tomato," "chicken," and "potato" as ingredients and specifies "Dish A" and "Dish B" as dish names.

[1262] 2. The device sends this information to the server.

[1263] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1264] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1265] 5. The device analyzes the user's voice and facial expression data using an emotion engine and sends emotional information to the server as needed.

[1266] 6. The server generates the adjusted procedure again and sends the optimal procedure to the terminal.

[1267] 7. The device displays the optimal cooking procedure to the user, who then follows it to proceed with the cooking.

[1268] 8. After the user has completed cooking, they input the amount of ingredients used into the terminal.

[1269] 9. The device sends the usage data to the server, which stores and analyzes the data to suggest optimal ingredient usage methods for the next time and beyond.

[1270] Prompt Sentence Examples

[1271] The following is an example of input to suggest the optimal procedure for the next time onwards.

[1272] User-entered ingredients: Tomato, Chicken, Potato

[1273] Name of the dish you want to make: Dish A, Dish B

[1274] Cookware restrictions: frying pans, pots

[1275] Cooking time limit: 30 minutes

[1276] User Emotion: Stress (Audio Analysis Results)

[1277] This allows the system to provide optimal cooking procedures according to the user's situation, enabling efficient and waste-free cooking.

[1278] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1279] Step 1:

[1280] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. For example, they input "tomato," "chicken," "potato," and "dish A" and "dish B."

[1281] Input: ingredients and dish name

[1282] Output: Input information (ingredients and dish name)

[1283] Specific action: A user enters data into an input field on a smartphone or tablet and presses the submit button.

[1284] Step 2:

[1285] The device receives input from the user, formats it, and sends it to the server in JSON or XML format.

[1286] Input: Input information (ingredients and dish name)

[1287] Output: Formatted data (JSON or XML format)

[1288] What it does: The device formats the data internally and sends it to a server via the Internet.

[1289] Step 3:

[1290] The server accesses the database based on the data received from the user and obtains the corresponding recipe information.

[1291] Input: Formatted data (ingredients and dish name)

[1292] Output: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[1293] What happens: The server uses an SQL query to retrieve the required information from the database.

[1294] Step 4:

[1295] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information.

[1296] Input: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[1297] Output: Optimal cooking procedure

[1298] Specific operation: The server inputs a prompt sentence into the generative AI model, and the model generates optimal cooking instructions.

[1299] Step 5:

[1300] The terminal analyzes the user's voice and facial expressions and uses an emotion engine to identify the user's emotional state.

[1301] Input: User audio or video data

[1302] Output: User's emotional state (e.g., stressed, relaxed)

[1303] Specific operation: The device uses the camera and microphone to collect the user's voice and facial expression data, which is then analyzed by the emotion engine.

[1304] Step 6:

[1305] The server adjusts the cooking instructions as needed based on information from the emotion engine.

[1306] Input: optimal cooking procedure, user's emotional state

[1307] Output: Adjusted cooking instructions

[1308] What it does: The server re-runs the AI ​​model to generate cooking instructions based on the emotion.

[1309] Step 7:

[1310] The device displays the cooking instructions received from the server to the user. The instructions are provided in the form of text, images, or videos.

[1311] Input: Adjusted cooking instructions

[1312] Output: Cooking instructions displayed to the user

[1313] Specific operation: The device displays cooking instructions on the display.

[1314] Step 8:

[1315] The user proceeds with cooking by following the steps displayed on the terminal.

[1316] Input: User actions, adjusted cooking instructions

[1317] Output: Cooking progress

[1318] Specific Action: The user actually follows the steps using the ingredients and utensils.

[1319] Step 9:

[1320] After cooking is complete, the user inputs the amounts of ingredients actually used into the terminal.

[1321] Input: Amount of material used

[1322] Output: Actual usage data

[1323] Specific actions: The user enters the amount of ingredients used in the input field on the terminal and presses the send button.

[1324] Step 10:

[1325] The terminal transmits the input usage data to the server.

[1326] Input: Actual usage data

[1327] Output: Usage data (JSON or XML format)

[1328] What it does: The device formats the data and sends it to a server over the Internet.

[1329] Step 11:

[1330] The server stores and analyzes the received usage data to suggest optimal food usage methods for the next time and beyond.

[1331] Input: Usage data

[1332] Output: Proposal for optimal ingredient usage

[1333] What it does: The server stores usage data in a database and uses analytical algorithms to generate optimal recommendations.

[1334] (Application example 2)

[1335] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1336] Conventional food delivery services are unable to respond to users' emotions or current situations, resulting in a uniform experience for users, leading to low customer satisfaction. Furthermore, food delivery times and routes are set based on fixed standards, making it difficult to adapt to users' stress and urgent needs. This makes it difficult to provide the delivery experience users expect, resulting in a lack of emotional support in particular.

[1337] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredients to be used in a dish and the name of the dish to be made from the user; means for retrieving related recipe information from a database based on the ingredients and the name of the dish; means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information; means for providing the generated cooking procedures to the user; means for receiving the amounts of ingredients actually used from the user; means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future use; and an emotion engine that recognizes the user's emotions and means for adjusting the cooking procedures based on this emotion engine. This makes it possible to provide an optimal food delivery service that suits the user's emotions and current situation, thereby improving user satisfaction.

[1338] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish that the user wants to make.

[1339] A "terminal" is a device that receives input from a user, transmits it to the server, and displays the generated cooking instructions to the user.

[1340] The "server" is a system that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[1341] An "ingredient" is a food or ingredient used to make a dish.

[1342] "Dish name" is the name of the dish the user wants to make.

[1343] "Recipe information" refers to information stored in a database, such as ingredient lists, quantities, cooking instructions, and cooking times.

[1344] A "database" is a central location where recipe information is stored.

[1345] A "cooking procedure" is a series of tasks or steps to complete a dish.

[1346] The "emotion engine" is a system that identifies emotions by analyzing the user's voice input and facial expressions.

[1347] "Food waste" refers to food that is discarded without being used.

[1348] "Optimization" refers to adjusting processes to efficiently create multiple dishes.

[1349] "Delivery time" is the time it takes for food to be delivered to the user after it is ordered.

[1350] A "delivery route" is the route that food will take when delivered.

[1351] The food delivery system based on this invention consists of a user, a terminal, and a server. The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. The terminal acquires this information and sends it to the server. The server then references a database based on the received information and acquires related recipe information. The recipe information includes a list of ingredients, quantities, cooking steps, cooking time, etc.

[1352] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. This also optimizes the order in which cooking utensils are used and waiting times. The server then sends the generated cooking instructions to the device, which displays them to the user. The user can then proceed with the cooking process by following the displayed instructions.

[1353] Furthermore, the device is equipped with an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. Based on this emotion data, the server can adjust the cooking instructions. For example, if the user is feeling stressed, the server will suggest cooking instructions that shorten cooking time or simplify the process.

[1354] After the user has finished cooking, they input the amount of ingredients they actually used into the device. This data is sent to the server and used to generate recommendations for optimal use of ingredients for future meals, thereby helping to manage food waste.

[1355] The specific processing of this system is realized using programming languages ​​such as Python and AI frameworks (e.g., TensorFlow and PyTorch), and OpenCV and speech recognition APIs are used to recognize emotions.

[1356] Specific examples

[1357] Suppose a user opens a smartphone app and orders tomato pasta. The device's emotion engine determines from the user's tone of voice and facial expression that the user is feeling stressed. The server receives this information, calculates the optimal delivery route while shortening delivery time, and displays it to the user. This system allows the user to receive their food quickly and efficiently without feeling stressed.

[1358] Prompt Sentence Examples

[1359] "The user ordered tomato pasta. The user's voice tone indicates that they are stressed. Based on this emotion, please reduce the delivery time and generate the optimal delivery route. Please keep the estimated delivery time within XX minutes."

[1360] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1361] Step 1:

[1362] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the device. The input information is saved on the device as a list of ingredients (e.g., "tomatoes," "chicken") and the name of the dish (e.g., "tomato pasta").

[1363] Step 2:

[1364] The terminal sends the ingredient list and dish name obtained from the user to the server, where the terminal uses an HTTP request to send the ingredient and dish name data, and the server uses the received information as input for a database query.

[1365] Step 3:

[1366] The server retrieves related recipe information from the database based on the received ingredients and dish name. Specifically, it executes an SQL query on the database to find records with the corresponding dish name. The output is the recipe information (ingredients list, quantities, cooking steps, cooking time, etc.).

[1367] Step 4:

[1368] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. The AI ​​model optimizes the entire cooking process, taking into account the order in which cooking utensils are used and waiting times. At this stage, the generative AI model calculates the cutting order of ingredients, heating times, and processes that can be carried out simultaneously, and outputs efficient cooking instructions.

[1369] Step 5:

[1370] The server sends the generated optimal cooking instructions to the device, again using an HTTP request to return the cooking instruction data to the device, which receives and stores it.

[1371] Step 6:

[1372] The device displays cooking instructions to the user in the form of text, images, and videos, organized for easy understanding by the user. The user then proceeds with the cooking process based on this information.

[1373] Step 7:

[1374] The emotion engine installed on the device analyzes the user's voice and facial expressions to identify their current emotion. Emotion identification is performed in real time using a microphone and camera, OpenCV, and a speech recognition API. The output is the user's emotional state (e.g., "stress").

[1375] Step 8:

[1376] The device transmits the emotion data identified by the emotion engine to the server, which receives this data as input and adjusts the cooking instructions.

[1377] Step 9:

[1378] The server then adjusts the cooking instructions based on the user's emotional state. For example, if the user is feeling stressed, the AI ​​model can be used to generate instructions that shorten cooking time or simplify the process. In this process, the generative AI model receives specific emotional data as input and re-optimizes the instructions based on that data. The adjusted cooking instructions are then generated as output.

[1379] Step 10:

[1380] The server sends the adjusted cooking recipe to the terminal, which then displays the adjusted recipe to the user, allowing the user to proceed with cooking more comfortably.

[1381] Step 11:

[1382] After the user has finished cooking, they input the amount of ingredients they actually used into the device, which is important information for reducing food waste.

[1383] Step 12:

[1384] The device sends usage data to the server, which uses this data to manage food waste and propose optimal ingredient usage methods for future uses. At this stage, the server analyzes the previous usage data and outputs the next recipe proposal and adjusts the ingredient amounts.

[1385] The above steps realize a system that provides optimal food delivery services according to the user's emotions and current situation, thereby improving user satisfaction.

[1386] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1387] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1388] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1389] [Fourth embodiment]

[1390] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1391] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1392] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1393] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1394] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1395] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1396] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1397] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1398] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1399] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1400] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1401] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1402] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1403] The system of the present invention processes the information entered by the user about ingredients to be used in the dish and the name of the dish they want to make, and generates and provides optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[1404] overview

[1405] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[1406] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user.

[1407] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[1408] System Operation

[1409] Receiving and Sending Information

[1410] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make through the terminal interface. For example, they input "tomato," "chicken," and "potato" as the ingredients they want to use, and specify "dish A" and "dish B" as the names of the dishes they want to make.

[1411] The device sends the entered information to the server, including the ingredient list and the name of the dish, as well as any specific cooking conditions (such as time limits and available cooking equipment).

[1412] Get recipe information

[1413] Based on the received user information, the server retrieves related recipe information from its internal database, including detailed recipes for dishes A and B (ingredients, amounts, cooking steps, cooking time, etc.).

[1414] Generating optimal cooking procedures

[1415] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently creating multiple dishes. For example,

[1416] "Boil the potatoes while you chop the tomatoes."

[1417] This includes steps such as "mashing potatoes while frying chicken."

[1418] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[1419] Providing instructions

[1420] The server then sends the generated cooking instructions to the device. The instructions are structured in an easy-to-understand step-by-step format, and include diagrams and videos as needed.

[1421] The terminal displays these steps to the user, allowing them to follow them in real time.

[1422] Recording usage and suggesting next time

[1423] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[1424] The terminal transmits the input usage data to the server.

[1425] The server uses this data to manage food waste and generates suggestions on how to best use ingredients in the future.

[1426] Specific examples

[1427] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[1428] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[1429] 2. The device sends this information to the server.

[1430] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1431] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1432] 5. The server sends the generated procedure to the terminal, which displays it to the user.

[1433] 6. The user follows the instructions to proceed with cooking, and after cooking is complete, enters the amount of ingredients used into the terminal.

[1434] 7. The device sends the usage data to the server, which then uses this data to suggest the optimal way to use ingredients for the next time onwards.

[1435] In this way, the system of the present invention supports the user's cooking process and enables efficient and waste-free cooking.

[1436] The processing flow will be explained below.

[1437] Step 1:

[1438] The user uses the terminal interface to input ingredients and the name of the dish they want to make, for example, "tomatoes," "chicken," and "potatoes," and names the dishes such as "Dish A" and "Dish B."

[1439] Step 2:

[1440] The device receives the information about ingredients and the name of the dish entered by the user and prepares to send it to the system. It also sends specific cooking conditions (e.g., cooking time limits and available cooking equipment) if necessary.

[1441] Step 3:

[1442] The terminal transmits the user-entered data to the server, including the list of ingredients, the name of the dish, and cooking conditions.

[1443] Step 4:

[1444] The server analyzes the received user data and accesses the database to retrieve related recipe information, such as the list of ingredients, quantities, cooking steps, and cooking time for the specified dish.

[1445] Step 5:

[1446] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1447] Step 6:

[1448] The server then sends the generated optimal cooking instructions to the device. These instructions are structured step by step and are organized in a way that makes them easy for the user to understand.

[1449] Step 7:

[1450] The terminal displays the cooking instructions sent from the server to the user, and the user can proceed with cooking by following these instructions. The instructions are presented in the form of text, images, and, if necessary, video.

[1451] Step 8:

[1452] The user records the amounts of ingredients actually used as they cook, and when cooking is complete, inputs the amounts into the terminal.

[1453] Step 9:

[1454] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[1455] Step 10:

[1456] The server manages food waste based on the collected usage data and suggests optimal ways to use ingredients from next time onwards. Specifically, it analyzes the user's past data and suggests combinations and amounts of ingredients that minimize waste.

[1457] In this way, specific actions at each step support efficient operation of the entire system, helping users to cook without waste.

[1458] Example 1

[1459] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1460] In modern life, it is extremely important for users to cook efficiently and reduce food waste. Conventional recipe provision systems do not optimize cooking procedures when making multiple dishes simultaneously, often resulting in wasted time and effort. Furthermore, they lack a mechanism for recording the amounts of ingredients actually used and using this information for future cooking. This leads to increased food waste. Furthermore, the cooking procedures are not visually easy to understand, which hinders users from cooking smoothly.

[1461] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1462] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for transmitting the generated cooking procedures to a terminal and displaying them to the user in real time, and means for displaying the retrieved recipe information and cooking procedures in visual or video format. This allows the user to efficiently cook multiple dishes simultaneously and follow the visual instructions while cooking, thereby saving time and effort and reducing food waste.

[1463] A "user" refers to a person who inputs ingredients and the name of the dish they want to make in order to create a dish.

[1464] "Terminal" refers to a device that receives information from a user, transmits it to a server, and displays the generated cooking instructions to the user.

[1465] The "server" refers to a device that references a database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[1466] "Ingredients" refers to the substances, such as foods and seasonings, used to create a dish.

[1467] "Dish name" refers to the name of the dish the user wants to make.

[1468] "Recipe information" refers to information such as ingredients needed to prepare a dish, the required amounts, cooking steps, cooking time, etc.

[1469] A "database" refers to a collection of information that stores and manages recipe information, etc.

[1470] An "AI model" refers to an algorithm or program that uses artificial intelligence technology to analyze data and derive optimal solutions.

[1471] A "prompt sentence" refers to a sentence used to input specific instructions or questions to an AI model.

[1472] "Cooking procedure" refers to a series of steps for preparing a dish.

[1473] "Food waste" refers to the amount of food that is not consumed and is discarded.

[1474] "Visual display" refers to presenting information in an intuitive way using diagrams, videos, etc.

[1475] "Real-time display" refers to a display method that provides information immediately when a user performs an operation.

[1476] The system of the present invention processes the information entered by the user about the ingredients to be used in the dish and the name of the dish they want to make, and generates and provides the optimal cooking instructions. It also records the amount of ingredients actually used by the user and uses this information for future cooking, thereby reducing food waste.

[1477] Hardware and software used

[1478] The system uses a "terminal" that receives user input, a "server" that accesses the database and performs calculations using AI models, and an internal database.

[1479] 1. Terminal: A device such as a smartphone, tablet, or PC. These devices receive user input through a user interface, send it to the server, and display the generated cooking instructions.

[1480] 2. Server: A computer with high-performance computing power and software for running AI models, specifically AI frameworks such as TensorFlow and PyTorch.

[1481] 3. Database: Stores and manages recipe information and user ingredient usage information. Typically, an SQL database or NoSQL database (e.g., MySQL, MongoDB) is used.

[1482] System Operation Overview

[1483] 1. The user inputs the ingredients to be used in the cooking and the name of the dish they wish to make through the terminal interface. For example, they can input "tomatoes, chicken, potatoes" as the ingredients they wish to use and specify "dish A" and "dish B" as the names of the dishes they wish to make. At this time, the user can also input specific cooking conditions (e.g., time limit, available cooking utensils).

[1484] 2. The device sends the information to the server as a data packet, including the ingredients list, the name of the dish, and the cooking instructions.

[1485] 3. The server references its internal database based on the received data and obtains the relevant recipe information (ingredients, required quantities, cooking steps, cooking time).

[1486] 4. The server uses the AI ​​model to generate efficient cooking instructions based on the acquired recipe information, using prompts such as "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?"

[1487] 5. The generated recipes are sent from the server to the device, which displays step-by-step instructions to the user in real time, including diagrams and videos as needed.

[1488] Specific examples

[1489] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[1490] 1. The user enters "tomatoes, chicken, potatoes" as the ingredients to be used in the dish, and specifies "dish A, dish B" as the names of the dishes they want to make.

[1491] 2. The device sends this information to the server.

[1492] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1493] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1494] 5. The server sends the generated instructions to the terminal, which displays them to the user in real time.

[1495] 6. The user follows the instructions to proceed with cooking and inputs the amount of ingredients used after cooking is complete.

[1496] 7. The device sends the usage data to the server, and the server suggests the best way to use ingredients from next time onwards.

[1497] In this way, the system of the present invention supports the user's cooking process, enabling efficient and waste-free cooking, and can also provide specific suggestions for reducing food waste.

[1498] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1499] Step 1:

[1500] The user uses the terminal interface to input the ingredients to be used in cooking and the name of the dish they want to make. For example, if the user inputs "tomatoes, chicken, and potatoes" as the ingredients they want to use and specifies "dish A, dish B" as the names of the dishes they want to make, this information is treated as input data. Subsequent information processing is initiated based on this input.

[1501] Step 2:

[1502] The terminal sends the input data to the server as a data packet. The data sent includes a list of ingredients (e.g., "200g tomatoes, 300g chicken, 400g potatoes"), dish names (e.g., "Dish A, Dish B"), and cooking conditions (e.g., "Can be cooked within 30 minutes"). Based on this information, the server is ready to process and calculate the data.

[1503] Step 3:

[1504] The server references its internal database based on the received data and retrieves the relevant recipe information. For example, it executes a database query to retrieve recipe information (ingredients, quantities, cooking steps, and cooking time) related to "Dish A" and "Dish B." The retrieved recipe information is loaded from the database into computer memory and used in the next step.

[1505] Step 4:

[1506] The server uses an AI model to generate efficient cooking instructions based on the acquired recipe information. The AI ​​model (e.g., TensorFlow, PyTorch) performs processing based on the prompt, "What is the optimal procedure for simultaneously making dish A using tomatoes and chicken and dish B using potatoes?" For example, an optimal cooking procedure is generated that includes parallel processing such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken." In this process, the AI ​​model performs data calculations and outputs the optimal procedure.

[1507] Step 5:

[1508] The server then sends the generated cooking instructions to the device. These instructions include step-by-step instructions, as well as diagrams and videos if necessary. For example, they may include specific instructions such as "Step 1: Finely chop the tomatoes (with diagram)" and "Step 2: Boil the potatoes while chopping the tomatoes (with video)."

[1509] Step 6:

[1510] The device displays the received cooking instructions to the user in real time, for example, by using a touchscreen or voice assistant to indicate the next step the user should take, allowing the user to smoothly proceed with cooking while looking at the screen.

[1511] Step 7:

[1512] After cooking is complete, the user inputs the amount of ingredients actually used into the terminal. For example, they might input "tomatoes: 180g, chicken: 250g, potatoes: 350g." This generates actual usage data.

[1513] Step 8:

[1514] The device sends the usage data entered by the user to the server. The server processes this data to manage food waste. For example, it analyzes the data and generates optimal instructions for using ingredients for the next time and beyond (e.g., "Next time, try a recipe that uses only 200g of potatoes").

[1515] Step 9:

[1516] The server sends the generated next cooking suggestion to the device, which displays the suggestion to the user so that the user can use it as a reference when planning their next cooking. This allows the user to use ingredients efficiently and reduce food waste.

[1517] In this way, the system of the present invention includes a series of processing steps that support the user's cooking process and enable efficient and waste-free cooking.

[1518] (Application example 1)

[1519] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1520] The present invention aims to reduce the effort and time users face during the cooking process and reduce food waste by providing an efficient cooking procedure. Another objective of the present invention is to provide a safe and efficient cooking environment in an autonomous vehicle, thereby providing a comfortable dining experience while driving.

[1521] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1522] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for receiving the amounts of ingredients actually used from the user, means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future meals, means for allowing the user to input ingredients and the name of the dish by voice and receive cooking instructions visually or audibly, and means for linking with cooking utensils used in the autonomous vehicle and providing optimal cooking procedures according to the situation, thereby enabling users to cook efficiently and safely even while in an autonomous vehicle and reduce food waste.

[1523] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish they wish to make, and then cooks according to the system's instructions.

[1524] "Ingredients" are the ingredients and seasonings used to create a dish.

[1525] "Dish Name" is the name of the particular dish the user wants to make.

[1526] A "database" is an information storage device that stores related recipe information.

[1527] "Recipe information" refers to detailed information such as ingredients, amounts required, cooking steps, cooking time, etc., for making a particular dish.

[1528] An "optimal cooking procedure" is a series of cooking steps that optimizes the order in which cooking utensils are used and waiting time in order to efficiently prepare multiple dishes.

[1529] "Cooking instructions" are the specific steps and processes for creating a dish.

[1530] "Usage data" refers to data relating to the amount of material actually used by the user.

[1531] "Food waste" refers to the amount of food ingredients and dishes that are discarded unnecessarily.

[1532] "Voice input" is a method in which the user inputs information such as ingredients and the name of a dish using voice through a microphone.

[1533] "Visual instructions" are written or graphic instructions provided to the user through a display.

[1534] "Audio instructions" are audio instructions provided to the user through a speaker.

[1535] An "autonomous vehicle" is a vehicle that drives automatically and is equipped with simple cooking equipment inside.

[1536] "Cooking equipment" refers to equipment and tools used in cooking, including microwave ovens and hot plates.

[1537] A "situation-appropriate cooking procedure" is a cooking procedure that is optimized according to the condition of the cooking utensils and the user's state.

[1538] MODE FOR CARRYING OUT THE INVENTION

[1539] The present invention relates to a system for providing efficient cooking procedures in an autonomous vehicle, as described in detail below.

[1540] 1. System Overview

[1541] The system aims to help users prepare meals comfortably in their autonomous vehicles and is comprised of the following main components:

[1542] An interface that allows users to input ingredients and dish names by voice and receive cooking instructions visually or audibly

[1543] A server that obtains recipe information based on ingredients and dish names and generates optimal cooking instructions

[1544] A device that works with cooking appliances (e.g., microwave ovens, hot plates) installed in autonomous vehicles to provide cooking instructions according to the situation.

[1545] 2. Program Processing

[1546] The main processes in the system program are as follows:

[1547] Hardware and Software

[1548] Smart glasses: A display that shows visual cooking instructions and a microphone for receiving voice commands

[1549] Self-driving vehicles: equipped with cooking appliances (microwave oven, hot plate, etc.)

[1550] Server: Collects recipe information and generates optimal cooking instructions

[1551] Speech recognition engine: Software for processing user voice input

[1552] Network module: Software for data communication between the smart glasses and the server

[1553] Data processing and calculation

[1554] 1. Receiving and Sending User Input

[1555] The user inputs ingredients and the name of the dish by voice.

[1556] The smart glasses' voice recognition engine converts the voice into text data and sends it to the server.

[1557] 2. Obtaining recipe information and generating cooking instructions

[1558] The server retrieves the corresponding recipe information from the database.

[1559] Based on the acquired recipe information, a generative AI model is used to generate optimal cooking procedures.

[1560] If calibration is required, optimize the order in which cooking appliances are used and the waiting time.

[1561] 3. Providing cooking instructions

[1562] The server sends the generated cooking instructions to the smart glasses.

[1563] The smart glasses provide visual or audio instructions to the user.

[1564] 4. Recording usage data

[1565] After cooking, the user inputs the amount of ingredients actually used by voice.

[1566] The smart glasses convert the voice into text data and send this data to a server.

[1567] The server records the usage data received for food waste management and suggests the best way to use ingredients from next time onwards.

[1568] 3. Specific examples

[1569] If a user wants to cook "sauteed chicken" using "tomatoes" and "chicken" in an autonomous vehicle, the system operates as follows:

[1570] 1. The user speaks "tomato, chicken, chicken saute" into the smart glasses.

[1571] 2. The smart glasses convert the speech into text and send it to the server.

[1572] 3. The server retrieves the recipe information and generates efficient cooking instructions, such as "fry the chicken while chopping the tomatoes."

[1573] 4. The server sends the generated instructions to the smart glasses, which then display them to the user.

[1574] 5. After cooking is complete, the user can voice-input the amount of ingredients actually used, and the smart glasses will send that data to the server.

[1575] 6. The server records usage data to manage food waste and suggests optimal ways to use ingredients for future use.

[1576] 4. Examples of prompts

[1577] "Just tell me the ingredients you use in the dish. For example, 'tomatoes, chicken'."

[1578] "Just say the name of the dish you want to make. For example, 'Chicken Sauté'."

[1579] "Say 'Next' to move to the next step."

[1580] "Please tell me the quantities of the ingredients you used. For example, '2 tomatoes, 300g chicken'."

[1581] Thus, the system of the present invention provides a concrete means for efficient and comfortable cooking in an autonomous vehicle.

[1582] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1583] Step 1:

[1584] Input: The user inputs ingredients and dish names by voice through the smart glasses.

[1585] How it works: The smart glasses' voice recognition engine converts the user's speech into text data.

[1586] Output: The converted text data, including ingredients and dish names such as "tomato," "chicken," and "sauteed chicken."

[1587] Step 2:

[1588] Input: Text data sent from the smart glasses to the server.

[1589] Operation: The server searches the database based on the received ingredients and dish name to retrieve related recipe information.

[1590] Output: Retrieved recipe information. For example, detailed information such as ingredients needed for "Sauteed Chicken", required quantities, cooking steps, cooking time, etc.

[1591] Step 3:

[1592] Input: Recipe information retrieved from the database.

[1593] How it works: The server uses generative AI models to generate optimal cooking instructions for efficiently creating multiple dishes.

[1594] Output: Optimal cooking steps. For example, an efficient process such as "fry chicken while chopping tomatoes."

[1595] Step 4:

[1596] Input: The optimal cooking instructions sent by the server.

[1597] How it works: The smart glasses receive the cooking instructions and present them to the user visually or audibly, along with diagrams and videos if needed.

[1598] Output: Cooking instructions that the user can follow in real time, for example, "Cut the tomatoes" on the display.

[1599] Step 5:

[1600] Input: The user inputs the actual amount of ingredients used by voice as the cooking progresses.

[1601] How it works: The smart glasses' voice recognition engine again converts the speech into text data and sends that data to the server.

[1602] Output: Converted text data. For example, usage data such as "2 tomatoes, 300g chicken."

[1603] Step 6:

[1604] Input: Usage data sent from smart glasses.

[1605] How it works: The server manages food waste based on the usage data it receives, and suggests optimal ways to use ingredients from next time onwards.

[1606] Output: Food waste management data that will be useful for your next cooking and suggestions on how to best use ingredients. For example, "Since you used up all the tomatoes this time, use fresh tomatoes next time."

[1607] This will enable users to cook efficiently and safely inside self-driving vehicles and reduce food waste.

[1608] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1609] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[1610] overview

[1611] 1. User: The entity that inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal.

[1612] 2. Terminal: A device that receives input from the user, sends it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that recognizes the user's emotions.

[1613] 3. Server: Refers to the database based on information from the user and uses an AI model to generate and provide optimal cooking instructions.

[1614] System Operation

[1615] Receiving and Sending Information

[1616] The user uses the terminal to input ingredients to be used in cooking and the name of the dish they want to make. For example, they can specify ingredients such as "tomato," "chicken," and "potato," and also specify the name of the dish, such as "Dish A" or "Dish B."

[1617] The terminal acquires the information entered by the user and transmits it to the server along with specific cooking conditions (such as cooking time limits and available cooking utensils) as needed.

[1618] Get recipe information

[1619] The server accesses the database based on the received user data to retrieve relevant recipe information, including the list of ingredients, serving sizes, cooking steps, cooking time, etc., corresponding to the specified dish name.

[1620] Generating optimal cooking procedures

[1621] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" and "mash potatoes while frying chicken."

[1622] Optimization includes adjusting the order in which cooking utensils are used and waiting times, ensuring that users can cook smoothly.

[1623] Procedure adjustment by emotion engine

[1624] The device is equipped with an emotion engine that analyzes the user's voice input and facial expressions to identify emotions. For example, if the user is feeling stressed, the emotion engine will detect this and request the server to adjust the actual procedure.

[1625] The server generates cooking instructions based on the user's emotions based on the information from the emotion engine. For example, if the server determines that the user is under high stress, it suggests instructions that shorten cooking time or are simpler.

[1626] Providing instructions

[1627] The server then sends the generated optimal cooking instructions to the device. The instructions are structured step by step and are organized in a way that makes them easy for users to understand.

[1628] The device displays cooking instructions to the user, who can follow the instructions to proceed with the cooking. The instructions are presented in the form of text, images, and, if necessary, video.

[1629] Recording usage and suggesting next time

[1630] After cooking is complete, users enter the actual amounts of ingredients used into the device, which is important information for reducing food waste.

[1631] The terminal transmits the input usage data to the server.

[1632] The server uses this data to manage food waste and generates suggestions on how to best use ingredients for future purchases.

[1633] Specific examples

[1634] For example, a case will be described in which the user wants to make "dish A using tomatoes and chicken" and "dish B using potatoes."

[1635] 1. The user enters "tomatoes," "chicken," and "potatoes" as ingredients to be used in the dish, and specifies "Dish A" and "Dish B" as the names of the dishes they want to make.

[1636] 2. The device sends this information to the server.

[1637] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1638] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1639] 5. The server sends the generated instructions back to the terminal, which displays them to the user.

[1640] 6. The user follows the cooking instructions. During the cooking process, the device analyzes the user's emotions and adjusts the cooking instructions as necessary.

[1641] 7. After the user has finished cooking, they input the amount of ingredients used into the terminal.

[1642] 8. The device sends the usage data to the server, which then uses this data to suggest the best way to use ingredients for the next time onwards.

[1643] In this way, the system of the present invention supports the cooking process of the user, realizing efficient and waste-free cooking that also takes emotions into consideration.

[1644] The processing flow will be explained below.

[1645] Step 1:

[1646] The user inputs the ingredients to be used in the cooking and the name of the dish they want to make using the terminal interface. For example, they can specify ingredients such as "tomato," "chicken," and "potato" and dish names such as "Dish A" and "Dish B."

[1647] Step 2:

[1648] The device retrieves the ingredients and recipe name entered by the user and prepares all data to be sent to the server, which may also include specific cooking conditions (e.g., cooking time limits and available cooking equipment).

[1649] Step 3:

[1650] The device sends the input information to the server, which includes the ingredients list, the name of the dish, and cooking instructions.

[1651] Step 4:

[1652] The server analyzes the received information and accesses the database to retrieve related recipe information, such as the ingredient list, quantities, cooking steps, and cooking time for the specified dish.

[1653] Step 5:

[1654] Based on the acquired recipe information, the server uses an AI model to generate optimal cooking procedures for efficiently preparing multiple dishes. For example, it optimizes the process by taking into account the order in which cooking utensils are used and waiting times, such as "boil potatoes while cutting tomatoes" or "mash potatoes while frying chicken."

[1655] Step 6:

[1656] The device analyzes the user's voice input and facial expressions in real time and uses an emotion engine to identify the user's emotions, for example, whether the user is feeling stressed or enjoying cooking.

[1657] Step 7:

[1658] The device uses the emotion engine's results to determine whether the cooking instructions need to be adjusted. For example, if the device determines that the user's stress level is high, it sends that information to the server.

[1659] Step 8:

[1660] The server receives data from the emotion engine and regenerates cooking instructions according to the user's emotions. For example, if the user is under high stress, the instructions are modified to shorten cooking time or provide simpler instructions.

[1661] Step 9:

[1662] The server then sends cooking instructions tailored to the user's emotions to the device, allowing the user to receive detailed support tailored to their emotions.

[1663] Step 10:

[1664] The device displays the adjusted steps to the user, allowing the user to follow the instructions to proceed with the cooking. For example, specific instructions such as "First, cut the tomatoes, then boil the potatoes" are displayed.

[1665] Step 11:

[1666] The user records the amounts of ingredients actually used while cooking, and inputs the amounts into the terminal when cooking is complete.

[1667] Step 12:

[1668] The device sends the usage data entered by the user to the server, which can then compare actual consumption with the initial estimate.

[1669] Step 13:

[1670] The server manages food waste based on the collected usage data and generates suggestions on how to best use ingredients from next time onwards, allowing users to reduce waste the next time they cook.

[1671] This series of steps enables the system to provide efficient and waste-free cooking support while responding to the user's real-time emotional state.

[1672] Example 2

[1673] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1674] In today's world, efficiently preparing multiple dishes simultaneously and minimizing food waste are challenges facing many households and restaurants. Furthermore, the lack of adjustments to cooking procedures based on the user's emotions leaves the stress and difficulty experienced by users unresolved. Furthermore, conventional cooking assistance systems lack the functionality to reflect the amount of ingredients used by the user in the next cooking session, resulting in food waste.

[1675] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1676] In this invention, the server includes means for receiving ingredients to be used in cooking and the name of the dish to be made from the user, means for retrieving related recipe information from a database based on the ingredients and the name of the dish, means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information, means for providing the generated cooking procedures to the user, means for analyzing the user's emotions, means for adjusting the cooking procedures based on the analysis results, means for receiving the amounts of ingredients actually used from the user, and means for managing food waste based on the received usage data and presenting optimal ways to use ingredients for future use. This enables efficient cooking support that takes the user's emotions into consideration, and can provide optimal cooking procedures while reducing food waste.

[1677] A "user" is an entity that uses the system to input ingredients to be used in cooking and the name of the dish they wish to make.

[1678] A "terminal" is a device that receives input from a user, sends it to the server, and displays the generated cooking instructions to the user. It may also include an emotion engine.

[1679] "Server" refers to a combination of hardware and software that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[1680] "Ingredients" refer to the foods or ingredients that a user specifies to make a dish.

[1681] "Dish name" refers to the name of the dish the user wants to make.

[1682] "Recipe information" refers to information such as ingredients, quantities, cooking steps, cooking time, etc.

[1683] A "database" is a digital system that manages and stores data such as recipe information.

[1684] An "AI model" is an algorithm that uses the latest artificial intelligence technology to analyze data and generate optimal cooking instructions.

[1685] An "emotion engine" is a system that analyzes a user's voice and facial expressions to identify their emotions.

[1686] A "cooking recipe" is a set of specific instructions for preparing a dish.

[1687] "Usage amount data" refers to information regarding the amount of ingredients actually used by the user in cooking.

[1688] "Food waste" refers to the waste that occurs when ingredients or food are discarded.

[1689] "Cooking conditions" refers to specific conditions that must be taken into consideration when cooking, such as cooking time and available cooking equipment.

[1690] The system of the present invention processes the ingredients and the name of the dish entered by the user, and generates and provides optimal cooking instructions. It also combines an emotion engine that recognizes the user's emotions and adjusts the cooking instructions according to the user's emotions, thereby realizing a more user-friendly and approachable cooking support system.

[1691] overview

[1692] User Roles

[1693] The user inputs the ingredients to be used and the name of the dish they want to make into the device. For example, they can specify ingredients such as "tomato," "chicken," or "potato," and names of dishes such as "Dish A" or "Dish B." The user simply needs to express naturally using voice and facial expressions any stress or joy they feel while cooking.

[1694] Device Role

[1695] The terminal is a device that receives input from the user, transmits it to the server, and displays the generated cooking instructions to the user. It also has an emotion engine that can analyze the user's voice and facial expressions. Examples of such devices include smartphones and tablets.

[1696] Server Roles

[1697] The server refers to the database based on the information sent by the user and uses an AI model (generative AI model) to generate and provide optimal cooking instructions. The server also processes data obtained from the emotion engine and can regenerate cooking instructions according to the user's emotions.

[1698] Hardware and software used

[1699] Both the server and the terminal use hardware with advanced processing capabilities. Specifically, MySQL or PostgreSQL is used as the database management system (DBMS), and machine learning frameworks such as TensorFlow and PyTorch can be used to generate AI models.

[1700] Data processing and calculation

[1701] 1. Receiving and Sending Data

[1702] The user uses the terminal to input ingredients and the name of the dish they want to make. For example, they input "tomatoes, chicken, and potatoes" and "dish A, dish B."

[1703] The device sends this information to the server. Specifically, text data is sent to the server in JSON or XML format.

[1704] 2. Get recipe information

[1705] The server accesses the database based on the information received from the user to retrieve relevant recipe information, including the list of ingredients, quantities, cooking steps, cooking time, etc., corresponding to the specified dish name.

[1706] 3. Generating optimal cooking procedures

[1707] The server uses an AI model based on the acquired recipe information to generate optimal cooking steps for efficiently preparing multiple dishes, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1708] 4. Procedure adjustment using emotion engine

[1709] The device is equipped with an emotion engine that analyzes the user's voice and facial expressions to identify their emotions, and if the user feels stressed, it requests the server to adjust the cooking instructions.

[1710] Based on this information, the server regenerates the cooking recipe and sends it to the terminal.

[1711] 5. Providing instructions and recording usage

[1712] The device displays the optimal cooking instructions sent from the server to the user, which are provided in the form of text, images, and videos.

[1713] The user follows the cooking procedure and, after cooking is complete, inputs the amounts of ingredients actually used into the terminal.

[1714] The device sends the inputted usage data to the server, which stores and analyzes it to suggest the best way to use ingredients for the next time.

[1715] Specific examples

[1716] For example, if a user wants to make "Dish A using tomatoes and chicken" and "Dish B using potatoes," the following operation will occur.

[1717] 1. The user enters "tomato," "chicken," and "potato" as ingredients and specifies "Dish A" and "Dish B" as dish names.

[1718] 2. The device sends this information to the server.

[1719] 3. The server retrieves recipe information for "Dish A" and "Dish B" from the database.

[1720] 4. The server uses the AI ​​model to generate optimal cooking instructions, such as "boil potatoes while chopping tomatoes" or "mash potatoes while frying chicken."

[1721] 5. The device analyzes the user's voice and facial expression data using an emotion engine and sends emotional information to the server as needed.

[1722] 6. The server generates the adjusted procedure again and sends the optimal procedure to the terminal.

[1723] 7. The device displays the optimal cooking procedure to the user, who then follows it to proceed with the cooking.

[1724] 8. After the user has completed cooking, they input the amount of ingredients used into the terminal.

[1725] 9. The device sends the usage data to the server, which stores and analyzes the data to suggest optimal ingredient usage methods for the next time and beyond.

[1726] Prompt Sentence Examples

[1727] The following is an example of input to suggest the optimal procedure for the next time onwards.

[1728] User-entered ingredients: Tomato, Chicken, Potato

[1729] Name of the dish you want to make: Dish A, Dish B

[1730] Cookware restrictions: frying pans, pots

[1731] Cooking time limit: 30 minutes

[1732] User Emotion: Stress (Audio Analysis Results)

[1733] This allows the system to provide optimal cooking procedures according to the user's situation, enabling efficient and waste-free cooking.

[1734] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1735] Step 1:

[1736] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. For example, they input "tomato," "chicken," "potato," and "dish A" and "dish B."

[1737] Input: ingredients and dish name

[1738] Output: Input information (ingredients and dish name)

[1739] Specific action: A user enters data into an input field on a smartphone or tablet and presses the submit button.

[1740] Step 2:

[1741] The device receives input from the user, formats it, and sends it to the server in JSON or XML format.

[1742] Input: Input information (ingredients and dish name)

[1743] Output: Formatted data (JSON or XML format)

[1744] What it does: The device formats the data internally and sends it to a server via the Internet.

[1745] Step 3:

[1746] The server accesses the database based on the data received from the user and obtains the corresponding recipe information.

[1747] Input: Formatted data (ingredients and dish name)

[1748] Output: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[1749] What happens: The server uses an SQL query to retrieve the required information from the database.

[1750] Step 4:

[1751] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information.

[1752] Input: Recipe information (ingredients list, amounts, cooking instructions, cooking time)

[1753] Output: Optimal cooking procedure

[1754] Specific operation: The server inputs a prompt sentence into the generative AI model, and the model generates optimal cooking instructions.

[1755] Step 5:

[1756] The terminal analyzes the user's voice and facial expressions and uses an emotion engine to identify the user's emotional state.

[1757] Input: User audio or video data

[1758] Output: User's emotional state (e.g., stressed, relaxed)

[1759] Specific operation: The device uses the camera and microphone to collect the user's voice and facial expression data, which is then analyzed by the emotion engine.

[1760] Step 6:

[1761] The server adjusts the cooking instructions as needed based on information from the emotion engine.

[1762] Input: optimal cooking procedure, user's emotional state

[1763] Output: Adjusted cooking instructions

[1764] What it does: The server re-runs the AI ​​model to generate cooking instructions based on the emotion.

[1765] Step 7:

[1766] The device displays the cooking instructions received from the server to the user. The instructions are provided in the form of text, images, or videos.

[1767] Input: Adjusted cooking instructions

[1768] Output: Cooking instructions displayed to the user

[1769] Specific operation: The device displays cooking instructions on the display.

[1770] Step 8:

[1771] The user proceeds with cooking by following the steps displayed on the terminal.

[1772] Input: User actions, adjusted cooking instructions

[1773] Output: Cooking progress

[1774] Specific Action: The user actually follows the steps using the ingredients and utensils.

[1775] Step 9:

[1776] After cooking is complete, the user inputs the amounts of ingredients actually used into the terminal.

[1777] Input: Amount of material used

[1778] Output: Actual usage data

[1779] Specific actions: The user enters the amount of ingredients used in the input field on the terminal and presses the send button.

[1780] Step 10:

[1781] The terminal transmits the input usage data to the server.

[1782] Input: Actual usage data

[1783] Output: Usage data (JSON or XML format)

[1784] What it does: The device formats the data and sends it to a server over the Internet.

[1785] Step 11:

[1786] The server stores and analyzes the received usage data to suggest optimal food usage methods for the next time and beyond.

[1787] Input: Usage data

[1788] Output: Proposal for optimal ingredient usage

[1789] What it does: The server stores usage data in a database and uses analytical algorithms to generate optimal recommendations.

[1790] (Application example 2)

[1791] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1792] Conventional food delivery services are unable to respond to users' emotions or current situations, resulting in a uniform experience for users, leading to low customer satisfaction. Furthermore, food delivery times and routes are set based on fixed standards, making it difficult to adapt to users' stress and urgent needs. This makes it difficult to provide the delivery experience users expect, resulting in a lack of emotional support in particular.

[1793] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: means for receiving ingredients to be used in a dish and the name of the dish to be made from the user; means for retrieving related recipe information from a database based on the ingredients and the name of the dish; means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the retrieved recipe information; means for providing the generated cooking procedures to the user; means for receiving the amounts of ingredients actually used from the user; means for managing food waste based on the received usage data and suggesting optimal ways to use ingredients for future use; and an emotion engine that recognizes the user's emotions and means for adjusting the cooking procedures based on this emotion engine. This makes it possible to provide an optimal food delivery service that suits the user's emotions and current situation, thereby improving user satisfaction.

[1794] A "user" is an entity that inputs ingredients to be used in cooking and the name of the dish that the user wants to make.

[1795] A "terminal" is a device that receives input from a user, transmits it to the server, and displays the generated cooking instructions to the user.

[1796] The "server" is a system that references a database based on information from users and uses an AI model to generate and provide optimal cooking instructions.

[1797] An "ingredient" is a food or ingredient used to make a dish.

[1798] "Dish name" is the name of the dish the user wants to make.

[1799] "Recipe information" refers to information stored in a database, such as ingredient lists, quantities, cooking instructions, and cooking times.

[1800] A "database" is a central location where recipe information is stored.

[1801] A "cooking procedure" is a series of tasks or steps to complete a dish.

[1802] The "emotion engine" is a system that identifies emotions by analyzing the user's voice input and facial expressions.

[1803] "Food waste" refers to food that is discarded without being used.

[1804] "Optimization" refers to adjusting processes to efficiently create multiple dishes.

[1805] "Delivery time" is the time it takes for food to be delivered to the user after it is ordered.

[1806] A "delivery route" is the route that food will take when delivered.

[1807] The food delivery system based on this invention consists of a user, a terminal, and a server. The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the terminal. The terminal acquires this information and sends it to the server. The server then references a database based on the received information and acquires related recipe information. The recipe information includes a list of ingredients, quantities, cooking steps, cooking time, etc.

[1808] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. This also optimizes the order in which cooking utensils are used and waiting times. The server then sends the generated cooking instructions to the device, which displays them to the user. The user can then proceed with the cooking process by following the displayed instructions.

[1809] Furthermore, the device is equipped with an emotion engine that analyzes the user's voice and facial expressions to recognize their emotions. Based on this emotion data, the server can adjust the cooking instructions. For example, if the user is feeling stressed, the server will suggest cooking instructions that shorten cooking time or simplify the process.

[1810] After the user has finished cooking, they input the amount of ingredients they actually used into the device. This data is sent to the server and used to generate recommendations for optimal use of ingredients for future meals, thereby helping to manage food waste.

[1811] The specific processing of this system is realized using programming languages ​​such as Python and AI frameworks (e.g., TensorFlow and PyTorch), and OpenCV and speech recognition APIs are used to recognize emotions.

[1812] Specific examples

[1813] Suppose a user opens a smartphone app and orders tomato pasta. The device's emotion engine determines from the user's tone of voice and facial expression that the user is feeling stressed. The server receives this information, calculates the optimal delivery route while shortening delivery time, and displays it to the user. This system allows the user to receive their food quickly and efficiently without feeling stressed.

[1814] Prompt Sentence Examples

[1815] "The user ordered tomato pasta. The user's voice tone indicates that they are stressed. Based on this emotion, please reduce the delivery time and generate the optimal delivery route. Please keep the estimated delivery time within XX minutes."

[1816] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1817] Step 1:

[1818] The user inputs the ingredients to be used in cooking and the name of the dish they want to make into the device. The input information is saved on the device as a list of ingredients (e.g., "tomatoes," "chicken") and the name of the dish (e.g., "tomato pasta").

[1819] Step 2:

[1820] The terminal sends the ingredient list and dish name obtained from the user to the server, where the terminal uses an HTTP request to send the ingredient and dish name data, and the server uses the received information as input for a database query.

[1821] Step 3:

[1822] The server retrieves related recipe information from the database based on the received ingredients and dish name. Specifically, it executes an SQL query on the database to find records with the corresponding dish name. The output is the recipe information (ingredients list, quantities, cooking steps, cooking time, etc.).

[1823] Step 4:

[1824] The server uses an AI model to generate optimal cooking instructions based on the acquired recipe information. The AI ​​model optimizes the entire cooking process, taking into account the order in which cooking utensils are used and waiting times. At this stage, the generative AI model calculates the cutting order of ingredients, heating times, and processes that can be carried out simultaneously, and outputs efficient cooking instructions.

[1825] Step 5:

[1826] The server sends the generated optimal cooking instructions to the device, again using an HTTP request to return the cooking instruction data to the device, which receives and stores it.

[1827] Step 6:

[1828] The device displays cooking instructions to the user in the form of text, images, and videos, organized for easy understanding by the user. The user then proceeds with the cooking process based on this information.

[1829] Step 7:

[1830] The emotion engine installed on the device analyzes the user's voice and facial expressions to identify their current emotion. Emotion identification is performed in real time using a microphone and camera, OpenCV, and a speech recognition API. The output is the user's emotional state (e.g., "stress").

[1831] Step 8:

[1832] The device transmits the emotion data identified by the emotion engine to the server, which receives this data as input and adjusts the cooking instructions.

[1833] Step 9:

[1834] The server then adjusts the cooking instructions based on the user's emotional state. For example, if the user is feeling stressed, the AI ​​model can be used to generate instructions that shorten cooking time or simplify the process. In this process, the generative AI model receives specific emotional data as input and re-optimizes the instructions based on that data. The adjusted cooking instructions are then generated as output.

[1835] Step 10:

[1836] The server sends the adjusted cooking recipe to the terminal, which then displays the adjusted recipe to the user, allowing the user to proceed with cooking more comfortably.

[1837] Step 11:

[1838] After the user has finished cooking, they input the amount of ingredients they actually used into the device, which is important information for reducing food waste.

[1839] Step 12:

[1840] The device sends usage data to the server, which uses this data to manage food waste and propose optimal ingredient usage methods for future uses. At this stage, the server analyzes the previous usage data and outputs the next recipe proposal and adjusts the ingredient amounts.

[1841] The above steps realize a system that provides optimal food delivery services according to the user's emotions and current situation, thereby improving user satisfaction.

[1842] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1843] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1844] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1845] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1846] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1847] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1848] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1849] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1850] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1851] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1852] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1853] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1854] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1855] 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.

[1856] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1857] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1858] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1859] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1860] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1861] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1862] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1863] The following is further disclosed regarding the above embodiment.

[1864] (Claim 1)

[1865] A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user;

[1866] means for acquiring related recipe information from a database based on the ingredients and dish name;

[1867] A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information;

[1868] means for providing the generated cooking recipe to a user;

[1869] means for receiving from the user the amount of material actually used;

[1870] A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards.

[1871] A system including:

[1872] (Claim 2)

[1873] The system according to claim 1, wherein the order of use of cooking utensils and waiting time are optimized when generating a cooking procedure based on the acquired recipe information.

[1874] (Claim 3)

[1875] The system of claim 1, which provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by a user.

[1876] "Example 1"

[1877] (Claim 1)

[1878] A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user;

[1879] means for acquiring related recipe information from a database based on the ingredients and dish name;

[1880] A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information;

[1881] means for providing the generated cooking recipe to a user;

[1882] means for receiving from the user the amount of material actually used;

[1883] A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards.

[1884] means for transmitting the generated cooking recipe to a terminal and displaying the recipe to a user in real time;

[1885] means for displaying the retrieved recipe information and cooking instructions in a visual or video format;

[1886] A system including:

[1887] (Claim 2)

[1888] The system according to claim 1, wherein the order of use of cooking utensils and waiting time are optimized when generating a cooking procedure based on the acquired recipe information.

[1889] (Claim 3)

[1890] The system of claim 1, which provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by a user.

[1891] "Application Example 1"

[1892] (Claim 1)

[1893] A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user;

[1894] means for acquiring related recipe information from a database based on the ingredients and dish name;

[1895] A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information;

[1896] means for providing the generated cooking recipe to a user;

[1897] means for receiving from the user the amount of material actually used;

[1898] A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards.

[1899] means for allowing a user to vocally input ingredients and dish names and receive visual or audio cooking instructions;

[1900] A means for linking with cooking appliances for cooking in an autonomous vehicle and providing optimal cooking procedures according to the situation;

[1901] A system including:

[1902] (Claim 2)

[1903] The system according to claim 1, wherein the order of use of cooking utensils and waiting time are optimized when generating a cooking procedure based on the acquired recipe information.

[1904] (Claim 3)

[1905] The system of claim 1, which provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by a user.

[1906] "Example 2: Combining Emotion Engines"

[1907] (Claim 1)

[1908] A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user;

[1909] means for acquiring related recipe information from a database based on the ingredients and dish name;

[1910] A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information;

[1911] means for providing the generated cooking recipe to a user;

[1912] means for analyzing user emotions;

[1913] means for adjusting the cooking procedure based on the analysis results;

[1914] means for receiving from the user the amount of material actually used;

[1915] A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards.

[1916] A system including:

[1917] (Claim 2)

[1918] The system according to claim 1, wherein the order of use of cooking utensils and waiting time are optimized when generating a cooking procedure based on the acquired recipe information.

[1919] (Claim 3)

[1920] The system of claim 1, which provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by a user.

[1921] "Application example 2 when combining emotion engines"

[1922] (Claim 1)

[1923] A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user;

[1924] means for acquiring related recipe information from a database based on the ingredients and dish name;

[1925] A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information;

[1926] means for providing the generated cooking recipe to a user;

[1927] means for receiving from the user the amount of material actually used;

[1928] A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards.

[1929] a means for adjusting cooking instructions based on an emotion engine that recognizes the emotion of a user;

[1930] A system including:

[1931] (Claim 2)

[1932] The system according to claim 1, wherein the order of use of cooking utensils and waiting time are optimized when generating a cooking procedure based on the acquired recipe information.

[1933] (Claim 3)

[1934] The system of claim 1, which provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by a user. [Explanation of symbols]

[1935] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving ingredients to be used in cooking and the name of the dish to be cooked from the user; means for acquiring related recipe information from a database based on the ingredients and dish name; A means for generating optimal cooking procedures for efficiently preparing multiple dishes based on the acquired recipe information; means for providing the generated cooking recipe to a user; means for receiving from the user the amount of material actually used; A method to manage food waste based on the received usage data and suggest optimal ways to use ingredients from next time onwards. A system including:

2. The system according to claim 1, wherein the order of use of cooking utensils and standby time are optimized when generating a cooking procedure based on the acquired recipe information.

3. The system according to claim 1, wherein the system provides a procedure for simultaneously cooking multiple dishes based on cooking conditions input by the user.

Images