system

Abstract

We provide the system. [Solution] A means of acquiring food inventory data using sensor devices installed in household food storage facilities, A means for transmitting the above inventory data to a data processing device via a network device connected to the monitoring equipment, A means for generating a nutritionally balanced meal plan based on inventory data and user profile data received by a data processing device, A means to identify shortages of supplies based on the generated meal plan and to automatically purchase replenishment items, A means of providing voice guidance to the user regarding the above meal plan and cooking process using an audio information output terminal, A home assistance robot performs the operations described above, providing a means to regularly check the physical inventory of food items, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern dual-income households, especially those with children, it has become a challenge to prepare a nutritionally balanced meal in the busy daily life. In addition to balancing work and childcare, it is difficult to secure time for shopping to prepare daily menus and gather the necessary ingredients. Furthermore, there may not be enough knowledge or information to prepare meals that cater to children's allergies and individual nutritional needs. Therefore, there is a need for support to solve these problems and efficiently maintain a healthy diet.

Means for Solving the Problems

[0005] This invention reduces user effort by acquiring food inventory information using a detection device installed in a home food storage system and transmitting this information to an information processing device via a communication device. The information processing device automatically generates a nutritionally balanced menu based on the received inventory information and the user's profile information. Furthermore, it identifies any missing ingredients from the generated menu and automatically orders them if necessary, saving the user the trouble of shopping. In addition, it provides cooking instructions via voice guidance through a communication terminal, making it possible for even users who are not confident in their cooking skills to cook with ease. This makes it possible to streamline meal preparation and facilitate nutritional management, especially for dual-income households with children, and supports their daily lives.

[0006] A "household food preservation device" is a device that allows for the long-term storage of food within the home by maintaining a constant temperature and humidity.

[0007] A "detection device" is a device that includes sensors to automatically detect the condition of food items inside a storage container and collect that data.

[0008] A "communication device" is a hardware or software mechanism for transmitting data obtained from a detection device to an external system or server.

[0009] An "information processing device" is a computer system that analyzes and processes information based on received data and generates meaningful results as output.

[0010] "Inventory information" refers to data regarding the type, quantity, and expiration date of ingredients in a food storage device.

[0011] "User profile information" refers to personal information about the user, including data such as age and health-related information such as allergies.

[0012] A "nutritionally balanced menu" refers to a meal plan that takes into account the health condition of children and users, and is designed to include the necessary nutrients in an appropriate manner.

[0013] "Automatic replenishment ordering" refers to a user-inactive ordering process that replenishes missing ingredients based on inventory information.

[0014] A "communication terminal" is an electronic device used by a user as an interface to a system, and is used for sending and receiving information.

[0015] "Means of providing voice guidance" refers to software or device functions that provide cooking procedures and information to the user via voice. [Brief explanation of the drawing]

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

Modes for Carrying Out the Invention

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

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

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

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

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

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

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

[0024] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a system for automating food inventory management and healthy meal preparation within the home, and can be implemented with the following configuration.

[0038] overview

[0039] First, a detection device is installed in the food storage unit in the home. This device detects the type and quantity of food items inside the storage unit and transmits this information to a server via a communication device. This communication is conducted over a network.

[0040] Food ingredient data management

[0041] The server stores the inventory information of received ingredients in a database. This makes it possible to always manage the status of ingredients in the home in an up-to-date manner.

[0042] Menu suggestions

[0043] Next, the server analyzes each user's profile information within the household, including age and allergy information, and automatically generates a nutritionally balanced meal plan. The generated meal plan takes into account the user's health condition and daily consumption habits.

[0044] Automated shopping

[0045] The server compares the ingredients required for the proposed menu with inventory data to identify any missing ingredients. The terminal notifies the user of the identified ingredient list, and after user confirmation, automatically orders the necessary ingredients through partnered online stores.

[0046] Cooking support

[0047] During the cooking phase, the device uses voice guidance to direct the user through the cooking procedure based on the menu. Since the user receives voice instructions for each cooking step, they can proceed to the next action without using their hands, allowing them to safely complete the meal regardless of their cooking skills.

[0048] Specific example

[0049] For example, consider a household with an infant where the child's profile is registered and the child has milk or egg allergies. In this household, a detection device collects information about the ingredients in the refrigerator, and if there is little milk left or little food containing eggs, the server suggests a menu that includes alternative ingredients. The server customizes the menu to meet the user's daily nutritional needs, automatically orders ingredients such as almond milk or soy milk if necessary, and provides cooking instructions to the user through voice guidance.

[0050] With this configuration, the present invention significantly reduces the burden of meal preparation and provides efficient and healthy meal support, especially for busy dual-income households.

[0051] The following describes the processing flow.

[0052] Step 1:

[0053] The server periodically receives inventory information from detection devices installed in home food storage systems. This information includes the type, quantity, and expiration date of the food.

[0054] Step 2:

[0055] The server stores the received inventory information in a database and records inventory fluctuations by comparing it with past data.

[0056] Step 3:

[0057] The server retrieves user profile information (e.g., age, weight, allergy information) from the database and begins analysis. Based on this information, it determines each user's nutritional needs.

[0058] Step 4:

[0059] The server automatically generates nutritionally balanced meal plans, taking into account inventory data and the user's nutritional needs. The generated meal plans are optimized based on nutritional standards and inventory status.

[0060] Step 5:

[0061] The terminal notifies the user of the menu retrieved from the server and suggests it to the user. The user can review this menu and request changes if necessary.

[0062] Step 6:

[0063] The server incorporates user feedback to finalize the menu. It also cross-references this with inventory information to identify any missing ingredients.

[0064] Step 7:

[0065] The terminal displays a list of missing ingredients to the user and obtains their approval to proceed with the process of automatically ordering them.

[0066] Step 8:

[0067] The server, upon user approval, automatically places an order for any missing ingredients via the online store's API.

[0068] Step 9:

[0069] The device starts voice guidance at the beginning of cooking, guiding the user through the cooking process step by step. This allows the user to safely proceed with cooking by following the instructions.

[0070] (Example 1)

[0071] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0072] In modern households, managing groceries and preparing healthy meals are crucial challenges. However, the demands of daily life make manual inventory management, creating nutritionally balanced menus, and grocery shopping difficult. There is a need for systems that simplify and streamline these tasks.

[0073] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0074] In this invention, the server includes means for acquiring food inventory information, means for transmitting the inventory information to a computer, and means for generating a nutritionally balanced meal plan. This makes it possible to reduce the burden of managing food supplies in the home and support a healthy diet.

[0075] "Food storage equipment" refers to equipment used to store food items in the home, including refrigerators and pantries.

[0076] A "detection device" is a device installed inside a food storage device to identify the type and quantity of food products, and uses technologies such as RFID tags and barcode readers.

[0077] A "communication device" is a device used to transmit inventory information acquired from a detection device to an external computing device, and it transmits data via a network.

[0078] A "computer system" is a computer system that receives and processes inventory information transmitted from a communication device.

[0079] A "meal plan" is a menu generated with nutritional balance in mind, and is created based on the user's profile information.

[0080] An "external purchasing device" is a device that automatically orders groceries based on a meal plan, and it is linked to the ordering system of an online store.

[0081] A "communication terminal" is a device that provides users with voice guidance on meal planning and cooking instructions, and is equipped with a speaker and microphone.

[0082] The embodiments for carrying out the present invention are described below.

[0083] This system is designed to automate grocery management and healthy meal preparation within the home. The necessary hardware includes "sensing devices" installed in "food storage equipment" such as refrigerators and pantries. These sensing devices use RFID tags or barcode readers to identify the type and quantity of food items. This data is transmitted to a server via a "communication device."

[0084] The server stores received food inventory information in a database and uses it to manage the inventory of individual households. To generate a nutritionally balanced "meal plan," the server uses a "computational device" to analyze the user's profile information (e.g., age, allergies, nutritional goals, etc.) and provides appropriate menus using a generation AI model.

[0085] Based on the generated meal plan, the server identifies any missing groceries and automatically places orders via an "external purchasing device." This includes a function that automatically purchases necessary ingredients using online store APIs. The terminal provides the user with voice guidance on the generated menu and cooking instructions, improving the efficiency of household chores.

[0086] For example, in a family with children, if one child has a dairy allergy, the server will take this into consideration, suggest a dairy-free menu, and order alternative ingredients online if necessary.

[0087] An example of a prompt message might be, "Create a healthy menu for your family this week and list the necessary ingredients." In this way, users can prepare healthy and efficient meals.

[0088] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0089] Step 1:

[0090] The user installs a detection device in their home food storage system. The detection device identifies the type and quantity of food and acquires data using RFID tags or barcode readers. The input is physical data of the food (type, quantity), and the output is digitized inventory information.

[0091] Step 2:

[0092] The communication device transmits inventory information acquired from the detection device to the server. The server receives this digitized inventory information as input and stores it in a database. In this step, data processing is performed to organize and store the type, quantity, and expiration date of the food, and the current inventory status is registered in the database as output.

[0093] Step 3:

[0094] The server receives inventory information stored in the database and user profile information (age, allergies, nutritional goals, etc.) as input, and uses a generative AI model to generate an optimal meal plan. This process analyzes nutritional balance based on the user's health status, and the output is a customized menu plan.

[0095] Step 4:

[0096] The server determines the necessary ingredients based on the generated meal plan and compares them with inventory data. The inputs are the meal plan and inventory data, and the output is a list of missing ingredients. The necessary data calculations include checking inventory availability and listing the shortages.

[0097] Step 5:

[0098] The terminal notifies the user of a list of missing ingredients and asks for confirmation of whether they wish to purchase them. After receiving user approval, the terminal automatically places an online order via an external purchasing device. The inputs are the list of missing ingredients and user approval, and the output is an order confirmation sent.

[0099] Step 6:

[0100] The device guides the user through cooking procedures via voice guidance. The input is a generated menu plan, and the output is voice commands. This process provides specific steps to ensure the user can cook safely and with minimal hands-on effort.

[0101] (Application Example 1)

[0102] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0103] In modern society, there is a growing need for more efficient food management and healthy meal preparation at home. However, for dual-income families and busy individuals, it is difficult to keep track of food inventory and prepare nutritionally balanced meals on a daily basis. In this situation, there is a need for automated support systems that reduce the burden on households and promote health maintenance.

[0104] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0105] In this invention, the server includes means for acquiring food inventory data using sensor devices attached to food storage facilities in the home, means for generating a nutritionally balanced meal plan based on the received inventory data and user profile data by a data processing device, and means for a home support robot to check the physical inventory of food on a daily basis. This makes it possible to always provide the user with the optimal meal while reducing food waste and supporting daily life.

[0106] A "household assistance robot" is an autonomous mechanical device designed to automate household tasks and provide assistance with food management and cooking.

[0107] A "sensor device" is a device that detects a specific physical quantity and converts that information into an electrical signal, and is used to detect the inventory status of food products.

[0108] A "data processing device" is a computer that processes received data and makes specific decisions or suggestions based on the analysis results.

[0109] "Inventory data" refers to information that shows the types and quantities of food ingredients stored in food storage facilities.

[0110] "Profile data" refers to information about individual users, including specific data such as age, allergy information, and nutritional needs.

[0111] A "meal plan" refers to a meal plan designed based on nutritional balance, with menus tailored to the user's health condition and preferences.

[0112] A "voice information output terminal" is a device that provides instructions and information via voice, and is designed to support users in operating the device without relying on their vision.

[0113] "Automating purchasing" means electronically managing the process of automatically ordering and replenishing necessary food and supplies when they are in short supply.

[0114] In the system implementing this invention, a household assistance robot plays a central role. The robot is equipped with multiple sensor devices and periodically acquires food inventory data from the household's food storage facilities. This allows the robot to determine the types and quantities of food items and transmit this information to a server via a network device.

[0115] The server analyzes received inventory data and user profile data using a data processing device. The software used for this analysis includes a data analysis program written in Python, and the data is stored in a database such as MySQL (registered trademark). The server then uses a generative AI model to automatically generate meal plans that take into account the user's nutritional balance. The generated meal plans are then communicated to the user in real time via a voice information output terminal.

[0116] Furthermore, the home support robot regularly checks the physical inventory of groceries, identifies any missing foods as needed, and automatically places orders through partner e-commerce platforms. This allows users to enjoy a healthy diet without worrying about purchasing groceries.

[0117] As a concrete example, a scenario is envisioned where, after checking the stock of tomatoes and cheese in the home, this information is sent to a server, which then suggests a tomato soup recipe that takes nutritional balance into consideration. Based on the suggested recipe, an additional cheese order is automatically placed.

[0118] An example of a prompt for a generative AI model is the following text: "A home assistance robot should create a healthy dinner menu based on the current food inventory and the user's nutritional information. It should suggest a recipe using tomatoes and cheese and provide voice guidance to support the cooking process."

[0119] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0120] Step 1:

[0121] A home assistance robot uses sensor devices within a food storage facility to detect the type and quantity of food items. The input is physical inventory information obtained from the sensor devices, and the output is detected inventory data. This inventory data is converted into a digital format for subsequent processing.

[0122] Step 2:

[0123] The robot transmits the acquired inventory data to the server via a network device. The input is the inventory data obtained in step 1, and the output is the digital information sent to the server. Here, data communication takes place using a network protocol.

[0124] Step 3:

[0125] The server manages the received inventory data and user profile data using a data processing device and then begins analysis. The input is inventory data and user profile information, and the output is a nutritionally balanced meal plan as a result of the analysis. Relevant data is searched using database queries, and the meal plan is formulated using a generative AI model.

[0126] Step 4:

[0127] The server generates an optimized meal plan and identifies any missing ingredients based on it. The input is the meal plan obtained in step 3, and the output is a list of ingredients that need to be replenished. If necessary, it automatically generates purchase instructions for supplies using electronic ordering protocols to partner stores.

[0128] Step 5:

[0129] The server transmits the generated meal plan and cooking instructions to a voice information output terminal, providing voice guidance to the user. The input is the meal plan and cooking instructions, and the output is the voice guidance presented to the user. Speech synthesis technology is used to provide step-by-step guidance.

[0130] Step 6:

[0131] The user interacts with a home assistance robot to guide the cooking process. The robot monitors the user's progress in real time and provides feedback as needed. The input is information about the user's cooking progress, and the output is the next instructions or cooking assistance. This allows the robot to continuously provide cooking assistance in the home.

[0132] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0133] This invention incorporates an emotion engine that recognizes the user's emotions into a system that provides food management and nutritionally balanced meal plans for the home, thereby offering more personalized meal support. The aim of this invention is to optimize meal plans and food purchases according to the user's emotional state.

[0134] Integration of emotion recognition

[0135] In this system, the emotion engine is primarily embedded in the terminal and collects emotion data in real time through interaction with the user. When the user prepares food on the terminal or application, the system can estimate their emotions from their facial expressions and tone of voice using sensor devices such as cameras and microphones.

[0136] Data analysis and menu suggestions

[0137] The server analyzes the collected emotional data using an information processing device to determine the user's current emotional state (e.g., stress, happiness, fatigue). Based on this determination, it generates a menu optimized for the user's current state. For example, it suggests a menu using ingredients with relaxing effects for users with high stress levels, thereby improving work efficiency.

[0138] Automatic ordering function

[0139] The server identifies any missing ingredients in the proposed menu by cross-referencing it with inventory data. Based on this information, the terminal considers the user's emotional state and, for example, automatically places an order for highly nutritious foods for a user who needs an energy boost.

[0140] Audio guidance and user interaction

[0141] During the cooking process, the device uses voice guidance to provide appropriate cooking instructions tailored to the user's emotional state. If the user is tired, simpler steps are prioritized; if they are feeling happy, approaches are presented to encourage them to enjoy a more time-consuming cooking experience.

[0142] Specific example

[0143] For example, if a user returns home tired after work and feels the need to refresh, the emotion engine will detect signs of fatigue, and the server will suggest a menu like: "Refreshing Salad with Lemon and Herbs." Furthermore, the necessary ingredients will already be automatically purchased online and prepared. Simultaneously, simple cooking instructions will be provided via voice guidance to help the user prepare the meal quickly.

[0144] Thus, the present invention aims to enrich and improve the health of home eating habits by recognizing the user's emotions in real time and optimizing meal and nutrition management based on those emotions.

[0145] The following describes the processing flow.

[0146] Step 1:

[0147] The device collects emotional data from facial expressions, voice tone, click patterns, and other information through user interaction. It uses sensor devices to estimate the user's emotional state in real time.

[0148] Step 2:

[0149] The server receives emotional data sent from the terminal. Based on the received data, the information processing device analyzes and determines the user's current emotional state.

[0150] Step 3:

[0151] The server uses the analysis results to generate nutritionally balanced meal plans based on the user's emotional state. For example, when the user is feeling stressed, it selects a meal plan that includes ingredients with relaxing properties.

[0152] Step 4:

[0153] The terminal notifies the user of the generated menu and provides specific cooking suggestions. The user can view and review the suggested menu and make adjustments or selections as needed.

[0154] Step 5:

[0155] The server references the household's inventory data based on the selected menu. From this information, it identifies any missing ingredients and determines whether they need to be purchased.

[0156] Step 6:

[0157] The device automatically links with online stores to create a list of missing ingredients and begins preparing an order. It also takes the user's emotional state into consideration and includes suggestions for gathering the necessary nutrients.

[0158] Step 7:

[0159] The server completes the automated order through integration with the online store and sends the order confirmation information to the terminal.

[0160] Step 8:

[0161] The device provides emotionally appropriate voice guidance once the user begins cooking. For example, if the user is tired, it will guide them through concise and efficient steps.

[0162] Step 9:

[0163] Users cook by following the voice guide. They can also receive real-time cooking assistance by asking questions to the guide as needed.

[0164] (Example 2)

[0165] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0166] In modern households, planning nutritionally balanced meals every day is an extremely time-consuming task. Furthermore, providing personalized suggestions that take into account the user's emotional state and allergy information has been considered difficult until now. In addition, automatic replenishment of necessary ingredients and guidance on cooking procedures, which can enrich lives by adapting to individual circumstances, face significant technical hurdles to realization.

[0167] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0168] In this invention, the server includes means for detecting the user's emotional state using sensors and collecting emotional data; means for an information processing device to analyze the collected emotional data and generate an optimal menu based on the user's emotional state; and means for identifying ingredient shortages based on the generated menu and automatically placing orders for replenishment. This enables personalized meal suggestions and nutritional management tailored to the user's emotions and circumstances, making meal planning at home easier.

[0169] A "preservation device" is equipment used to properly store food and ingredients and maintain their freshness.

[0170] A "detection device" is a device used to sense the presence or state of an object and to acquire related information.

[0171] An "information processing device" is a system that receives, analyzes, and processes data, and generates instructions or suggestions based on the results.

[0172] "Users" refer to individuals or organizations that access and use a system or service.

[0173] "Profile information" refers to information that includes personal data about the user, preferences, and past activity history.

[0174] A "communication device" is an electronic device used to send and receive data and information.

[0175] "Emotional state" refers to the user's mental and emotional condition, including states such as stress and happiness.

[0176] A "sensor" is a device that detects physical or environmental phenomena and outputs that information as an electrical signal.

[0177] A "menu" refers to a combination of foods and dishes for a particular meal.

[0178] "Voice guidance" refers to a method of conveying instructions and information to users using voice.

[0179] "Automatic replenishment" is a process that automatically replenishes missing items or materials based on a pre-planned schedule.

[0180] This invention is a system that supports food management and nutritionally balanced menu suggestions in the home, and incorporates an emotion engine that recognizes the user's emotional state. The aim of this system is to improve daily eating habits by providing personalized meal suggestions tailored to the user's individual emotional state.

[0181] First, the device detects the user's facial expressions and voice tone in real time using camera and microphone sensors. This data is analyzed by an emotion engine to determine the user's emotional state. Specifically, standard cameras and microphones are used, and smartphones and tablets with these components are also available.

[0182] Next, the server receives emotional data transmitted from the terminal and analyzes it using an advanced information processing device to determine the user's current emotional state. Here, machine learning algorithms are used to analyze the emotional data, and a menu corresponding to the emotion is generated based on the results. A generative AI model is utilized in this process, suggesting an optimized menu rather than a random one, tailored to the user's emotions.

[0183] For example, if a user feels tired after work and wants to refresh themselves, the emotion engine will detect signs of fatigue, and the server will suggest a menu like a "refreshing salad with lemon and herbs." Furthermore, the necessary ingredients will be automatically purchased online, and simple cooking instructions will be provided via voice guidance from the device.

[0184] An example of an input prompt for the generative AI model would be text in the format of, "Please suggest a refreshing menu for when the user's emotional state is 'tired'."

[0185] This system makes it possible to optimize dietary habits to suit the individual needs and circumstances of each household.

[0186] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0187] Step 1:

[0188] The device uses a camera and microphone to capture the user's facial expressions and voice tone in order to collect information about the user's emotional state. Real-time visual and audio data of the user is acquired as input. Based on this, an emotion engine analyzes the data and estimates the user's emotions (e.g., stress, happiness, fatigue) in real time. The estimated emotional state is obtained as output.

[0189] Step 2:

[0190] The server receives estimated emotion data transmitted from the terminal. It takes emotional state data analyzed by the terminal as input. The server further analyzes this data using an information processing device, uses machine learning algorithms to improve the accuracy of the emotion, and ultimately determines the emotional state. The final emotional state is generated as output.

[0191] Step 3:

[0192] The server uses a generative AI model to generate the optimal menu based on the generated emotional state. The inputs used are the user's emotional state data, profile information, and inventory information. The data is analyzed by the AI ​​model, and a menu corresponding to the emotion is proposed. The output is menu information corresponding to the user's emotion.

[0193] Step 4:

[0194] The server matches the inventory information to identify any missing ingredients based on the menu. It uses the proposed menu and inventory information obtained from storage devices as input. This identifies shortages in the inventory and generates an ingredient order list for automatic replenishment. The output is a list of ingredients that need to be ordered.

[0195] Step 5:

[0196] The device provides suggested menus and corresponding cooking instructions as voice guidance tailored to the user's emotional state. The inputs used are menu information and the user's current emotional state. The voice guidance simplifies or elaborates the cooking instructions, providing the user with the most suitable procedure. The output is a voice notification of the cooking guide.

[0197] (Application Example 2)

[0198] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0199] In modern households, food management and the suggestion of nutritionally balanced menus are considered important, but there is a lack of systems that provide personalized meal support tailored to the emotional state of individual consumers. This problem carries the risk that daily stress and fatigue will influence food choices, ultimately making it difficult to maintain healthy eating habits. The present invention aims to enable the suggestion of a richer diet that takes emotional states into account by proposing optimal menus based on the user's emotional state.

[0200] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0201] In this invention, the server includes means for acquiring food inventory information using a detection device installed in a food storage device in the home, means for collecting emotional data using an emotional recognition device that recognizes the user's emotional state, and means for analyzing the collected emotional data and personalizing the menu based on the analysis results. This makes it possible to suggest a nutritionally balanced menu that reflects the user's emotional state.

[0202] "Household food storage equipment" refers to devices used to store food in the home, and includes refrigerators, pantries, and other similar items.

[0203] A "detection device" is a device installed in a food storage container that is equipped with sensors and cameras to identify the type and quantity of food inside.

[0204] "Inventory information" refers to data obtained by the detection device that shows the type, quantity, and storage condition of food products.

[0205] A "communication device" is hardware used to send and receive data with information processing devices and other devices, and it communicates via internet connections, etc.

[0206] An "information processing device" is a device such as a computer or server used to process and analyze received data.

[0207] "User profile information" refers to personal data about the user, including information such as age, gender, allergy information, and food preferences.

[0208] An "emotion recognition device" is hardware and software used to estimate a user's emotional state, analyzing facial expressions and voice using a camera and microphone.

[0209] "Emotional data" refers to data that quantifies or classifies a user's emotional state as measured by an emotion recognition device.

[0210] A "menu" refers to a systematically planned menu of meals, a meal plan that takes nutritional balance into consideration.

[0211] Personalization is the process of adjusting products and services according to the individual user's characteristics and circumstances.

[0212] "Voice guidance" refers to a function that provides information to users using voice, including automated guides and instructions.

[0213] This system is implemented using hardware such as food storage devices installed in homes, their associated communication devices, and emotion recognition devices. Primarily, sensors are installed within the food storage devices, allowing a detection device to acquire information about the food inventory. This information is then transmitted to an information processing device via a communication device.

[0214] The information processing device generates a nutritionally balanced menu based on received inventory information and user profile information. Furthermore, the user's emotional state is measured in real time by an emotion recognition device, and this data is analyzed by an emotion recognition engine. Based on the results of this analysis, the menu is personalized according to the user's emotions.

[0215] For example, if a user feels the need to refresh themselves, the system can analyze that emotion and suggest a menu using ingredients that have a refreshing effect. In this case, the system automatically identifies any missing ingredients and places an online order for the food.

[0216] Users receive voice guidance on suggested menus and cooking procedures via a communication terminal. This voice guidance is adjusted according to the user's emotional state; for example, simplified cooking procedures are presented when the user is tired.

[0217] For example, if a user prompts, "Please come up with an interesting dish to match my mood today," the system analyzes the request and automatically generates a menu. The generated menu reflects the user's emotional state and can suggest something like "Grilled Herb Chicken and Seasonal Vegetables" for a relaxed dinner. In this way, a personalized dining experience tailored to the user's emotional state is provided.

[0218] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0219] Step 1:

[0220] The server obtains food inventory information using detection devices installed in food storage systems within the home. At this stage, the sensors collect data on the type and quantity of food and transmit this data to the server via a communication device. Based on this input data, the server determines the current food inventory status.

[0221] Step 2:

[0222] The user's emotional state is measured by an emotion recognition device via a communication terminal. Here, the user's facial expressions and voice tone are analyzed using a camera and microphone. This analysis generates emotional data. The server receives this emotional data as input and interprets the user's current emotional state.

[0223] Step 3:

[0224] The server generates nutritionally balanced meal plans based on received inventory information, emotional data, and user profile information. Here, a generative AI model is used to create a personalized meal plan for the user, resulting in individually customized menus. Specifically, data calculations are used to design relaxing menus designed to reduce stress.

[0225] Step 4:

[0226] The server identifies any missing food items based on the generated menu and automatically places online orders. The input here is the menu content, and based on that content, it calculates the necessary ingredients and generates output to place orders on the sales website.

[0227] Step 5:

[0228] The device provides the user with a suggested menu and corresponding cooking instructions via voice guidance through communication. The input for this step is the user's emotional state and the chosen menu. This data is then used to output appropriate cooking instructions via voice guidance. Specifically, if the user is feeling fatigued, the device prioritizes providing instructions for easy cooking procedures.

[0229] Step 6:

[0230] The user begins cooking according to the provided voice guidance and enjoys a meal that responds to their emotions. Here, the cooking process is realistic, and the user's actions in completing the actual menu become the output. This process realizes a dining experience based on emotion management and nutritional management.

[0231] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0232] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0233] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0234] [Second Embodiment]

[0235] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0236] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0237] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0238] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0239] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0240] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0241] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0242] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0243] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0244] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0245] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0246] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0247] This invention is a system for automating food inventory management and healthy meal preparation within the home, and can be implemented with the following configuration.

[0248] overview

[0249] First, a detection device is installed in the food storage unit in the home. This device detects the type and quantity of food items inside the storage unit and transmits this information to a server via a communication device. This communication is conducted over a network.

[0250] Food ingredient data management

[0251] The server stores the inventory information of received ingredients in a database. This makes it possible to always manage the status of ingredients in the home in an up-to-date manner.

[0252] Menu suggestions

[0253] Next, the server analyzes each user's profile information within the household, including age and allergy information, and automatically generates a nutritionally balanced meal plan. The generated meal plan takes into account the user's health condition and daily consumption habits.

[0254] Automated shopping

[0255] The server compares the ingredients required for the proposed menu with inventory data to identify any missing ingredients. The terminal notifies the user of the identified ingredients list, and after user confirmation, automatically orders the necessary ingredients through partnered online stores.

[0256] Cooking support

[0257] During the cooking phase, the device uses voice guidance to direct the user through the cooking procedure based on the menu. Since the user is instructed by voice at each cooking step, they can proceed to the next action without using their hands, allowing them to safely complete the meal regardless of their cooking skills.

[0258] Specific example

[0259] For example, consider a household with an infant where the child's profile is registered and the child has milk or egg allergies. In this household, a detection device collects information about the ingredients in the refrigerator, and if there is little milk left or little food containing eggs, the server suggests a menu that includes alternative ingredients. The server customizes the menu to meet the user's daily nutritional needs, automatically orders ingredients such as almond milk or soy milk if necessary, and provides cooking instructions to the user through voice guidance.

[0260] With this configuration, the present invention significantly reduces the burden of meal preparation and provides efficient and healthy meal support, especially for busy dual-income households.

[0261] The following describes the processing flow.

[0262] Step 1:

[0263] The server periodically receives inventory information from detection devices installed in home food storage systems. This information includes the type, quantity, and expiration date of the food.

[0264] Step 2:

[0265] The server stores the received inventory information in a database and records inventory fluctuations by comparing it with past data.

[0266] Step 3:

[0267] The server retrieves user profile information (e.g., age, weight, allergy information) from the database and begins analysis. Based on this information, it determines each user's nutritional needs.

[0268] Step 4:

[0269] The server automatically generates nutritionally balanced meal plans, taking into account inventory data and the user's nutritional needs. The generated meal plans are optimized based on nutritional standards and inventory status.

[0270] Step 5:

[0271] The terminal notifies the user of the menu retrieved from the server and suggests it to the user. The user can review this menu and request changes if necessary.

[0272] Step 6:

[0273] The server incorporates user feedback to finalize the menu. It also cross-references this with inventory information to identify any missing ingredients.

[0274] Step 7:

[0275] The terminal displays a list of missing ingredients to the user and obtains their approval to proceed with the process of automatically ordering them.

[0276] Step 8:

[0277] The server, upon user approval, automatically places an order for any missing ingredients via the online store's API.

[0278] Step 9:

[0279] The device starts voice guidance at the beginning of cooking, guiding the user through the cooking process step by step. This allows the user to safely proceed with cooking by following the instructions.

[0280] (Example 1)

[0281] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0282] In modern households, managing groceries and preparing healthy meals are crucial challenges. However, the demands of daily life make manual inventory management, creating nutritionally balanced menus, and grocery shopping difficult. There is a need for systems that simplify and streamline these tasks.

[0283] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0284] In this invention, the server includes means for acquiring inventory information of food products, means for transmitting the inventory information to a computing device, and means for generating a meal plan with a balanced nutrition. Thereby, it becomes possible to reduce the burden of food product management within a household and support a healthy diet.

[0285] The "food storage device" is equipment used for storing food products within a household, including refrigerators, pantries, and the like.

[0286] The "detection device" is a device installed within a food storage device for identifying the types and quantities of food products, which uses technologies such as RFID tags and barcode readers.

[0287] The "communication device" is a device for transmitting the inventory information acquired from the detection device to an external computing device, which transmits data via a network.

[0288] The "computing device" is a computer system for receiving and processing the inventory information transmitted from the communication device.

[0289] The "meal plan" is a menu generated considering nutritional balance and is created based on the user's profile information.

[0290] The "external purchase device" is a device for automatically ordering the food products lacking based on the meal plan, which cooperates with the ordering system of an online store.

[0291] The "communication terminal" is a device for guiding the user with voice regarding the meal plan and cooking instructions, which is equipped with a speaker and a microphone.

[0292] The embodiments for implementing the present invention will be described below.

[0293] This system is designed to automate grocery management and healthy meal preparation within the home. The necessary hardware includes "sensing devices" installed in "food storage equipment" such as refrigerators and pantries. These sensing devices use RFID tags or barcode readers to identify the type and quantity of food items. This data is transmitted to a server via a "communication device."

[0294] The server stores received food inventory information in a database and uses it to manage the inventory of individual households. To generate a nutritionally balanced "meal plan," the server uses a "computational device" to analyze the user's profile information (e.g., age, allergies, nutritional goals, etc.) and provides appropriate menus using a generation AI model.

[0295] Based on the generated meal plan, the server identifies any missing groceries and automatically places orders via an "external purchasing device." This includes a function that automatically purchases necessary ingredients using online store APIs. The terminal provides the user with voice guidance on the generated menu and cooking instructions, improving the efficiency of household chores.

[0296] For example, in a family with children, if one child has a dairy allergy, the server will take this into consideration, suggest a dairy-free menu, and order alternative ingredients online if necessary.

[0297] An example of a prompt message might be, "Create a healthy menu for your family this week and list the necessary ingredients." In this way, users can prepare healthy and efficient meals.

[0298] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0299] Step 1:

[0300] The user installs a detection device on the food preservation device in the home. The detection device identifies the type and quantity of food and obtains data using an RFID tag or a barcode reader. As input, there is physical data of food (type, quantity), and as output, digitized inventory information is obtained.

[0301] Step 2:

[0302] The communication device transmits the inventory information obtained from the detection device to the server. The server receives this digitized inventory information as input and stores it in the database. In this step, data processing is performed to organize and store the type, quantity, and expiration date of food, and the current status of the inventory is registered in the database as output.

[0303] Step 3:

[0304] The server receives the inventory information stored in the database and the user's profile information (age, allergies, nutritional goals, etc.) as input, and uses a generated AI model to generate an optimal meal plan. In this process, an analysis of the nutritional balance based on the user's health status is performed, and a customized menu plan is obtained as output.

[0305] Step 4:

[0306] The server determines the necessary ingredients based on the generated meal plan and compares them with the inventory data. As input, there is the menu plan and the inventory data, and as output, a list of missing ingredients is created. As the necessary data calculation, the presence or absence of inventory is checked and the shortages are listed up.

[0307] Step 5:

[0308] The terminal notifies the user of the list of missing ingredients and confirms whether to purchase them. After obtaining approval from the user, the terminal automatically places an online order via an external purchasing device. As input, there is the list of missing ingredients and the user's approval, and as output, an order confirmation is sent.

[0309] Step 6:

[0310] The device guides the user through cooking procedures via voice guidance. The input is a generated menu plan, and the output is voice commands. This process provides specific steps to ensure the user can cook safely and with minimal hands-on effort.

[0311] (Application Example 1)

[0312] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0313] In modern society, there is a growing need for more efficient food management and healthy meal preparation at home. However, for dual-income families and busy individuals, it is difficult to keep track of food inventory and prepare nutritionally balanced meals on a daily basis. In this situation, there is a need for automated support systems that reduce the burden on households and promote health maintenance.

[0314] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0315] In this invention, the server includes means for acquiring food inventory data using sensor devices attached to food storage facilities in the home, means for generating a nutritionally balanced meal plan based on the received inventory data and user profile data by a data processing device, and means for a home support robot to check the physical inventory of food on a daily basis. This makes it possible to always provide the user with the optimal meal while reducing food waste and supporting daily life.

[0316] A "household assistance robot" is an autonomous mechanical device designed to automate household tasks and provide assistance with food management and cooking.

[0317] A "sensor device" is a device that detects a specific physical quantity and converts that information into an electrical signal, and is used to detect the inventory status of food products.

[0318] A "data processing device" is a computer that processes received data and makes specific decisions or suggestions based on the analysis results.

[0319] "Inventory data" refers to information that shows the types and quantities of food ingredients stored in food storage facilities.

[0320] "Profile data" refers to information about individual users, including specific data such as age, allergy information, and nutritional needs.

[0321] A "meal plan" refers to a meal plan designed based on nutritional balance, with menus tailored to the user's health condition and preferences.

[0322] A "voice information output terminal" is a device that provides instructions and information via voice, and is designed to support users in operating the device without relying on their vision.

[0323] "Automating purchasing" means electronically managing the process of automatically ordering and replenishing necessary food and supplies when they are in short supply.

[0324] In the system implementing this invention, a household assistance robot plays a central role. The robot is equipped with multiple sensor devices and periodically acquires food inventory data from the household's food storage facilities. This allows the robot to determine the types and quantities of food items and transmit this information to a server via a network device.

[0325] The server analyzes received inventory data and user profile data using a data processing device. The software used for this analysis includes a data analysis program written in Python, and the data is stored in a database such as MySQL. The server then uses a generative AI model to automatically generate meal plans that take into account the user's nutritional balance. The generated meal plans are then communicated to the user in real time via a voice information output terminal.

[0326] Furthermore, the home support robot regularly checks the physical inventory of groceries, identifies any missing foods as needed, and automatically places orders through partner e-commerce platforms. This allows users to enjoy a healthy diet without worrying about purchasing groceries.

[0327] As a concrete example, a scenario is envisioned where, after checking the stock of tomatoes and cheese in the home, this information is sent to a server, which then suggests a tomato soup recipe that takes nutritional balance into consideration. Based on the suggested recipe, an additional cheese order is automatically placed.

[0328] An example of a prompt for a generative AI model is the following text: "A home assistance robot should create a healthy dinner menu based on the current food inventory and the user's nutritional information. It should suggest a recipe using tomatoes and cheese and provide voice guidance to support the cooking process."

[0329] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0330] Step 1:

[0331] A home assistance robot uses sensor devices within a food storage facility to detect the type and quantity of food items. The input is physical inventory information obtained from the sensor devices, and the output is detected inventory data. This inventory data is converted into a digital format for subsequent processing.

[0332] Step 2:

[0333] The robot transmits the acquired inventory data to the server via a network device. The input is the inventory data obtained in step 1, and the output is the digital information sent to the server. Here, data communication takes place using a network protocol.

[0334] Step 3:

[0335] The server manages the received inventory data and user profile data using a data processing device and then begins analysis. The input is inventory data and user profile information, and the output is a nutritionally balanced meal plan as a result of the analysis. Relevant data is searched using database queries, and the meal plan is formulated using a generative AI model.

[0336] Step 4:

[0337] The server generates an optimized meal plan and identifies any missing ingredients based on it. The input is the meal plan obtained in step 3, and the output is a list of ingredients that need to be replenished. If necessary, it automatically generates purchase instructions for supplies using electronic ordering protocols to partner stores.

[0338] Step 5:

[0339] The server transmits the generated meal plan and cooking instructions to a voice information output terminal, providing voice guidance to the user. The input is the meal plan and cooking instructions, and the output is the voice guidance presented to the user. Speech synthesis technology is used to provide step-by-step guidance.

[0340] Step 6:

[0341] The user interacts with a home assistance robot to guide the cooking process. The robot monitors the user's progress in real time and provides feedback as needed. The input is information about the user's cooking progress, and the output is the next instructions or cooking assistance. This allows the robot to continuously provide cooking assistance in the home.

[0342] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0343] This invention incorporates an emotion engine that recognizes the user's emotions into a system that provides food management and nutritionally balanced meal plans for the home, thereby offering more personalized meal support. The aim of this invention is to optimize meal plans and food purchases according to the user's emotional state.

[0344] Integration of emotion recognition

[0345] In this system, the emotion engine is primarily embedded in the terminal and collects emotion data in real time through interaction with the user. When the user prepares food on the terminal or application, the system can estimate their emotions from their facial expressions and tone of voice using sensor devices such as cameras and microphones.

[0346] Data analysis and menu suggestions

[0347] The server analyzes the collected emotional data using an information processing device to determine the user's current emotional state (e.g., stress, happiness, fatigue). Based on this determination, it generates a menu optimized for the user's current state. For example, it suggests a menu using ingredients with relaxing effects for users with high stress levels, thereby improving work efficiency.

[0348] Automatic ordering function

[0349] The server identifies any missing ingredients in the proposed menu by cross-referencing it with inventory data. Based on this information, the terminal considers the user's emotional state and, for example, automatically places an order for highly nutritious foods for a user who needs an energy boost.

[0350] Audio guidance and user interaction

[0351] During the cooking process, the device uses voice guidance to provide appropriate cooking instructions tailored to the user's emotional state. If the user is tired, simpler steps are prioritized; if they are feeling happy, approaches are presented to encourage them to enjoy a more time-consuming cooking experience.

[0352] Specific example

[0353] For example, if a user returns home tired after work and feels the need to refresh, the emotion engine will detect signs of fatigue, and the server will suggest a menu like: "Refreshing Salad with Lemon and Herbs." Furthermore, the necessary ingredients will already be automatically purchased online and prepared. Simultaneously, simple cooking instructions will be provided via voice guidance to help the user prepare the meal quickly.

[0354] Thus, the present invention aims to enrich and improve the health of home eating habits by recognizing the user's emotions in real time and optimizing meal and nutrition management based on those emotions.

[0355] The following describes the processing flow.

[0356] Step 1:

[0357] The device collects emotional data from facial expressions, voice tone, click patterns, and other information through user interaction. It uses sensor devices to estimate the user's emotional state in real time.

[0358] Step 2:

[0359] The server receives emotional data sent from the terminal. Based on the received data, the information processing device analyzes and determines the user's current emotional state.

[0360] Step 3:

[0361] The server uses the analysis results to generate nutritionally balanced meal plans based on the user's emotional state. For example, when the user is feeling stressed, it selects a meal plan that includes ingredients with relaxing properties.

[0362] Step 4:

[0363] The terminal notifies the user of the generated menu and provides specific cooking suggestions. The user can view and review the suggested menu and make adjustments or selections as needed.

[0364] Step 5:

[0365] The server references the household's inventory data based on the selected menu. From this information, it identifies any missing ingredients and determines whether they need to be purchased.

[0366] Step 6:

[0367] The device automatically links with online stores to create a list of missing ingredients and begins preparing an order. It also takes the user's emotional state into consideration and includes suggestions for gathering the necessary nutrients.

[0368] Step 7:

[0369] The server completes the automated order through integration with the online store and sends the order confirmation information to the terminal.

[0370] Step 8:

[0371] The device provides emotionally appropriate voice guidance once the user begins cooking. For example, if the user is tired, it will guide them through concise and efficient steps.

[0372] Step 9:

[0373] Users cook by following the voice guide. They can also receive real-time cooking assistance by asking questions to the guide as needed.

[0374] (Example 2)

[0375] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0376] In modern households, planning nutritionally balanced meals every day is an extremely time-consuming task. Furthermore, providing personalized suggestions that take into account the user's emotional state and allergy information has been considered difficult until now. In addition, automatic replenishment of necessary ingredients and guidance on cooking procedures, which can enrich lives by adapting to individual circumstances, face significant technical hurdles to realization.

[0377] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0378] In this invention, the server includes means for detecting the user's emotional state using sensors and collecting emotional data; means for an information processing device to analyze the collected emotional data and generate an optimal menu based on the user's emotional state; and means for identifying ingredient shortages based on the generated menu and automatically placing orders for replenishment. This enables personalized meal suggestions and nutritional management tailored to the user's emotions and circumstances, making meal planning at home easier.

[0379] A "preservation device" is equipment used to properly store food and ingredients and maintain their freshness.

[0380] A "detection device" is a device used to sense the presence or state of an object and to acquire related information.

[0381] An "information processing device" is a system that receives, analyzes, and processes data, and generates instructions or suggestions based on the results.

[0382] "Users" refer to individuals or organizations that access and use a system or service.

[0383] "Profile information" refers to information that includes personal data about the user, preferences, and past activity history.

[0384] A "communication device" is an electronic device used to send and receive data and information.

[0385] "Emotional state" refers to the user's mental and emotional condition, including states such as stress and happiness.

[0386] A "sensor" is a device that detects physical or environmental phenomena and outputs that information as an electrical signal.

[0387] A "menu" refers to a combination of foods and dishes for a particular meal.

[0388] "Voice guidance" refers to a method of conveying instructions and information to users using voice.

[0389] "Automatic replenishment" is a process that automatically replenishes missing items or materials based on a pre-planned schedule.

[0390] This invention is a system that supports food management and nutritionally balanced menu suggestions in the home, and incorporates an emotion engine that recognizes the user's emotional state. The aim of this system is to improve daily eating habits by providing personalized meal suggestions tailored to the user's individual emotional state.

[0391] First, the device detects the user's facial expressions and voice tone in real time using camera and microphone sensors. This data is analyzed by an emotion engine to determine the user's emotional state. Specifically, standard cameras and microphones are used, and smartphones and tablets with these components are also available.

[0392] Next, the server receives emotional data transmitted from the terminal and analyzes it using an advanced information processing device to determine the user's current emotional state. Here, machine learning algorithms are used to analyze the emotional data, and a menu corresponding to the emotion is generated based on the results. A generative AI model is utilized in this process, suggesting an optimized menu rather than a random one, tailored to the user's emotions.

[0393] For example, if a user feels tired after work and wants to refresh themselves, the emotion engine will detect signs of fatigue, and the server will suggest a menu like a "refreshing salad with lemon and herbs." Furthermore, the necessary ingredients will be automatically purchased online, and simple cooking instructions will be provided via voice guidance from the device.

[0394] An example of an input prompt for the generative AI model would be text in the format of, "Please suggest a refreshing menu for when the user's emotional state is 'tired'."

[0395] This system makes it possible to optimize dietary habits to suit the individual needs and circumstances of each household.

[0396] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0397] Step 1:

[0398] The device uses a camera and microphone to capture the user's facial expressions and voice tone in order to collect information about the user's emotional state. Real-time visual and audio data of the user is acquired as input. Based on this, an emotion engine analyzes the data and estimates the user's emotions (e.g., stress, happiness, fatigue) in real time. The estimated emotional state is obtained as output.

[0399] Step 2:

[0400] The server receives estimated emotion data transmitted from the terminal. It takes emotional state data analyzed by the terminal as input. The server further analyzes this data using an information processing device, uses machine learning algorithms to improve the accuracy of the emotion, and ultimately determines the emotional state. The final emotional state is generated as output.

[0401] Step 3:

[0402] The server uses a generative AI model to generate the optimal menu based on the generated emotional state. The inputs used are the user's emotional state data, profile information, and inventory information. The data is analyzed by the AI ​​model, and a menu corresponding to the emotion is proposed. The output is menu information corresponding to the user's emotion.

[0403] Step 4:

[0404] The server matches the inventory information to identify any missing ingredients based on the menu. It uses the proposed menu and inventory information obtained from storage devices as input. This identifies shortages in the inventory and generates an ingredient order list for automatic replenishment. The output is a list of ingredients that need to be ordered.

[0405] Step 5:

[0406] The device provides suggested menus and corresponding cooking instructions as voice guidance tailored to the user's emotional state. The inputs used are menu information and the user's current emotional state. The voice guidance simplifies or elaborates the cooking instructions, providing the user with the most suitable procedure. The output is a voice notification of the cooking guide.

[0407] (Application Example 2)

[0408] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0409] In modern households, food management and the suggestion of nutritionally balanced menus are considered important, but there is a lack of systems that provide personalized meal support tailored to the emotional state of individual consumers. This problem carries the risk that daily stress and fatigue will influence food choices, ultimately making it difficult to maintain healthy eating habits. The present invention aims to enable the suggestion of a richer diet that takes emotional states into account by proposing optimal menus based on the user's emotional state.

[0410] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0411] In this invention, the server includes means for acquiring food inventory information using a detection device installed in a food storage device in the home, means for collecting emotional data using an emotional recognition device that recognizes the user's emotional state, and means for analyzing the collected emotional data and personalizing the menu based on the analysis results. This makes it possible to suggest a nutritionally balanced menu that reflects the user's emotional state.

[0412] "Household food storage equipment" refers to devices used to store food in the home, and includes refrigerators, pantries, and other similar items.

[0413] A "detection device" is a device installed in a food storage container that is equipped with sensors and cameras to identify the type and quantity of food inside.

[0414] "Inventory information" refers to data obtained by the detection device that shows the type, quantity, and storage condition of food products.

[0415] A "communication device" is hardware used to send and receive data with information processing devices and other devices, and it communicates via internet connections, etc.

[0416] An "information processing device" is a device such as a computer or server used to process and analyze received data.

[0417] "User profile information" refers to personal data about the user, including information such as age, gender, allergy information, and food preferences.

[0418] An "emotion recognition device" is hardware and software used to estimate a user's emotional state, analyzing facial expressions and voice using a camera and microphone.

[0419] "Emotional data" refers to data that quantifies or classifies a user's emotional state as measured by an emotion recognition device.

[0420] A "menu" refers to a systematically planned menu of meals, a meal plan that takes nutritional balance into consideration.

[0421] Personalization is the process of adjusting products and services according to the individual user's characteristics and circumstances.

[0422] "Voice guidance" refers to a function that provides information to users using voice, including automated guides and instructions.

[0423] This system is implemented using hardware such as food storage devices installed in homes, their associated communication devices, and emotion recognition devices. Primarily, sensors are installed within the food storage devices, allowing a detection device to acquire information about the food inventory. This information is then transmitted to an information processing device via a communication device.

[0424] The information processing device generates a nutritionally balanced menu based on received inventory information and user profile information. Furthermore, the user's emotional state is measured in real time by an emotion recognition device, and this data is analyzed by an emotion recognition engine. Based on the results of this analysis, the menu is personalized according to the user's emotions.

[0425] For example, if a user feels the need to refresh themselves, the system can analyze that emotion and suggest a menu using ingredients that have a refreshing effect. In this case, the system automatically identifies any missing ingredients and places an online order for the food.

[0426] Users receive voice guidance on suggested menus and cooking procedures via a communication terminal. This voice guidance is adjusted according to the user's emotional state; for example, simplified cooking procedures are presented when the user is tired.

[0427] For example, if a user prompts, "Please come up with an interesting dish to match my mood today," the system analyzes the request and automatically generates a menu. The generated menu reflects the user's emotional state and can suggest something like "Grilled Herb Chicken and Seasonal Vegetables" for a relaxed dinner. In this way, a personalized dining experience tailored to the user's emotional state is provided.

[0428] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0429] Step 1:

[0430] The server obtains food inventory information using detection devices installed in food storage systems within the home. At this stage, the sensors collect data on the type and quantity of food and transmit this data to the server via a communication device. Based on this input data, the server determines the current food inventory status.

[0431] Step 2:

[0432] The user's emotional state is measured by an emotion recognition device via a communication terminal. Here, the user's facial expressions and voice tone are analyzed using a camera and microphone. This analysis generates emotional data. The server receives this emotional data as input and interprets the user's current emotional state.

[0433] Step 3:

[0434] The server generates nutritionally balanced meal plans based on received inventory information, emotional data, and user profile information. Here, a generative AI model is used to create a personalized meal plan for the user, resulting in individually customized menus. Specifically, data calculations are used to design relaxing menus designed to reduce stress.

[0435] Step 4:

[0436] The server identifies any missing food items based on the generated menu and automatically places online orders. The input here is the menu content, and based on that content, it calculates the necessary ingredients and generates output to place orders on the sales website.

[0437] Step 5:

[0438] The device provides the user with a suggested menu and corresponding cooking instructions via voice guidance through communication. The input for this step is the user's emotional state and the chosen menu. This data is then used to output appropriate cooking instructions via voice guidance. Specifically, if the user is feeling fatigued, the device prioritizes providing instructions for easy cooking procedures.

[0439] Step 6:

[0440] The user begins cooking according to the provided voice guidance and enjoys a meal that responds to their emotions. Here, the cooking process is realistic, and the user's actions in completing the actual menu become the output. This process realizes a dining experience based on emotion management and nutritional management.

[0441] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0442] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0443] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0444] [Third Embodiment]

[0445] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0446] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0447] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0448] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0449] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0450] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0451] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0452] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0453] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0454] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0455] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0456] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0457] This invention is a system for automating food inventory management and healthy meal preparation within the home, and can be implemented with the following configuration.

[0458] overview

[0459] First, a detection device is installed in the food storage unit in the home. This device detects the type and quantity of food items inside the storage unit and transmits this information to a server via a communication device. This communication is conducted over a network.

[0460] Food ingredient data management

[0461] The server stores the inventory information of received ingredients in a database. This makes it possible to always manage the status of ingredients in the home in an up-to-date manner.

[0462] Menu suggestions

[0463] Next, the server analyzes each user's profile information within the household, including age and allergy information, and automatically generates a nutritionally balanced meal plan. The generated meal plan takes into account the user's health condition and daily consumption habits.

[0464] Automated shopping

[0465] The server compares the ingredients required for the proposed menu with inventory data to identify any missing ingredients. The terminal notifies the user of the identified ingredients list, and after user confirmation, automatically orders the necessary ingredients through partnered online stores.

[0466] Cooking support

[0467] During the cooking phase, the device uses voice guidance to direct the user through the cooking procedure based on the menu. Since the user is instructed by voice at each cooking step, they can proceed to the next action without using their hands, allowing them to safely complete the meal regardless of their cooking skills.

[0468] Specific example

[0469] For example, consider a household with an infant where the child's profile is registered and the child has milk or egg allergies. In this household, a detection device collects information about the ingredients in the refrigerator, and if there is little milk left or little food containing eggs, the server suggests a menu that includes alternative ingredients. The server customizes the menu to meet the user's daily nutritional needs, automatically orders ingredients such as almond milk or soy milk if necessary, and provides cooking instructions to the user through voice guidance.

[0470] With this configuration, the present invention significantly reduces the burden of meal preparation and provides efficient and healthy meal support, especially for busy dual-income households.

[0471] The following describes the processing flow.

[0472] Step 1:

[0473] The server periodically receives inventory information from detection devices installed in home food storage systems. This information includes the type, quantity, and expiration date of the food.

[0474] Step 2:

[0475] The server stores the received inventory information in a database and records inventory fluctuations by comparing it with past data.

[0476] Step 3:

[0477] The server retrieves user profile information (e.g., age, weight, allergy information) from the database and begins analysis. Based on this information, it determines each user's nutritional needs.

[0478] Step 4:

[0479] The server automatically generates nutritionally balanced meal plans, taking into account inventory data and the user's nutritional needs. The generated meal plans are optimized based on nutritional standards and inventory status.

[0480] Step 5:

[0481] The terminal notifies the user of the menu retrieved from the server and suggests it to the user. The user can review this menu and request changes if necessary.

[0482] Step 6:

[0483] The server incorporates user feedback to finalize the menu. It also cross-references this with inventory information to identify any missing ingredients.

[0484] Step 7:

[0485] The terminal displays a list of missing ingredients to the user and obtains their approval to proceed with the process of automatically ordering them.

[0486] Step 8:

[0487] The server, upon user approval, automatically places an order for any missing ingredients via the online store's API.

[0488] Step 9:

[0489] The device starts voice guidance at the beginning of cooking, guiding the user through the cooking process step by step. This allows the user to safely proceed with cooking by following the instructions.

[0490] (Example 1)

[0491] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0492] In modern households, managing groceries and preparing healthy meals are crucial challenges. However, the demands of daily life make manual inventory management, creating nutritionally balanced menus, and grocery shopping difficult. There is a need for systems that simplify and streamline these tasks.

[0493] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0494] In this invention, the server includes means for acquiring food inventory information, means for transmitting the inventory information to a computer, and means for generating a nutritionally balanced meal plan. This makes it possible to reduce the burden of managing food supplies in the home and support a healthy diet.

[0495] "Food storage equipment" refers to equipment used to store food items in the home, including refrigerators and pantries.

[0496] A "detection device" is a device installed inside a food storage device to identify the type and quantity of food products, and uses technologies such as RFID tags and barcode readers.

[0497] A "communication device" is a device used to transmit inventory information acquired from a detection device to an external computing device, and it transmits data via a network.

[0498] A "computer system" is a computer system that receives and processes inventory information transmitted from a communication device.

[0499] A "meal plan" is a menu generated with nutritional balance in mind, and is created based on the user's profile information.

[0500] An "external purchasing device" is a device that automatically orders groceries based on a meal plan, and it is linked to the ordering system of an online store.

[0501] A "communication terminal" is a device that provides users with voice guidance on meal planning and cooking instructions, and is equipped with a speaker and microphone.

[0502] The embodiments for carrying out the present invention are described below.

[0503] This system is designed to automate grocery management and healthy meal preparation within the home. The necessary hardware includes "sensing devices" installed in "food storage equipment" such as refrigerators and pantries. These sensing devices use RFID tags or barcode readers to identify the type and quantity of food items. This data is transmitted to a server via a "communication device."

[0504] The server stores received food inventory information in a database and uses it to manage the inventory of individual households. To generate a nutritionally balanced "meal plan," the server uses a "computational device" to analyze the user's profile information (e.g., age, allergies, nutritional goals, etc.) and provides appropriate menus using a generation AI model.

[0505] Based on the generated meal plan, the server identifies any missing groceries and automatically places orders via an "external purchasing device." This includes a function that automatically purchases necessary ingredients using online store APIs. The terminal provides the user with voice guidance on the generated menu and cooking instructions, improving the efficiency of household chores.

[0506] For example, in a family with children, if one child has a dairy allergy, the server will take this into consideration, suggest a dairy-free menu, and order alternative ingredients online if necessary.

[0507] An example of a prompt message might be, "Create a healthy menu for your family this week and list the necessary ingredients." In this way, users can prepare healthy and efficient meals.

[0508] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0509] Step 1:

[0510] The user installs a detection device in their home food storage system. The detection device identifies the type and quantity of food and acquires data using RFID tags or barcode readers. The input is physical data of the food (type, quantity), and the output is digitized inventory information.

[0511] Step 2:

[0512] The communication device transmits inventory information acquired from the detection device to the server. The server receives this digitized inventory information as input and stores it in a database. In this step, data processing is performed to organize and store the type, quantity, and expiration date of the food, and the current inventory status is registered in the database as output.

[0513] Step 3:

[0514] The server receives inventory information stored in the database and user profile information (age, allergies, nutritional goals, etc.) as input, and uses a generative AI model to generate an optimal meal plan. This process analyzes nutritional balance based on the user's health status, and the output is a customized menu plan.

[0515] Step 4:

[0516] The server determines the necessary ingredients based on the generated meal plan and compares them with inventory data. The inputs are the meal plan and inventory data, and the output is a list of missing ingredients. The necessary data calculations include checking inventory availability and listing the shortages.

[0517] Step 5:

[0518] The terminal notifies the user of a list of missing ingredients and asks for confirmation of whether they wish to purchase them. After receiving user approval, the terminal automatically places an online order via an external purchasing device. The inputs are the list of missing ingredients and user approval, and the output is an order confirmation sent.

[0519] Step 6:

[0520] The device guides the user through cooking procedures via voice guidance. The input is a generated menu plan, and the output is voice commands. This process provides specific steps to ensure the user can cook safely and with minimal hands-on effort.

[0521] (Application Example 1)

[0522] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0523] In modern society, there is a growing need for more efficient food management and healthy meal preparation at home. However, for dual-income families and busy individuals, it is difficult to keep track of food inventory and prepare nutritionally balanced meals on a daily basis. In this situation, there is a need for automated support systems that reduce the burden on households and promote health maintenance.

[0524] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0525] In this invention, the server includes means for acquiring food inventory data using sensor devices attached to food storage facilities in the home, means for generating a nutritionally balanced meal plan based on the received inventory data and user profile data by a data processing device, and means for a home support robot to check the physical inventory of food on a daily basis. This makes it possible to always provide the user with the optimal meal while reducing food waste and supporting daily life.

[0526] A "household assistance robot" is an autonomous mechanical device designed to automate household tasks and provide assistance with food management and cooking.

[0527] A "sensor device" is a device that detects a specific physical quantity and converts that information into an electrical signal, and is used to detect the inventory status of food products.

[0528] A "data processing device" is a computer that processes received data and makes specific decisions or suggestions based on the analysis results.

[0529] "Inventory data" refers to information that shows the types and quantities of food ingredients stored in food storage facilities.

[0530] "Profile data" refers to information about individual users, including specific data such as age, allergy information, and nutritional needs.

[0531] A "meal plan" refers to a meal plan designed based on nutritional balance, with menus tailored to the user's health condition and preferences.

[0532] A "voice information output terminal" is a device that provides instructions and information via voice, and is designed to support users in operating the device without relying on their vision.

[0533] "Automating purchasing" means electronically managing the process of automatically ordering and replenishing necessary food and supplies when they are in short supply.

[0534] In the system implementing this invention, a household assistance robot plays a central role. The robot is equipped with multiple sensor devices and periodically acquires food inventory data from the household's food storage facilities. This allows the robot to determine the types and quantities of food items and transmit this information to a server via a network device.

[0535] The server analyzes received inventory data and user profile data using a data processing device. The software used for this analysis includes a data analysis program written in Python, and the data is stored in a database such as MySQL. The server then uses a generative AI model to automatically generate meal plans that take into account the user's nutritional balance. The generated meal plans are then communicated to the user in real time via a voice information output terminal.

[0536] Furthermore, the home support robot regularly checks the physical inventory of groceries, identifies any missing foods as needed, and automatically places orders through partner e-commerce platforms. This allows users to enjoy a healthy diet without worrying about purchasing groceries.

[0537] As a concrete example, a scenario is envisioned where, after checking the stock of tomatoes and cheese in the home, this information is sent to a server, which then suggests a tomato soup recipe that takes nutritional balance into consideration. Based on the suggested recipe, an additional cheese order is automatically placed.

[0538] An example of a prompt for a generative AI model is the following text: "A home assistance robot should create a healthy dinner menu based on the current food inventory and the user's nutritional information. It should suggest a recipe using tomatoes and cheese and provide voice guidance to support the cooking process."

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

[0540] Step 1:

[0541] A home assistance robot uses sensor devices within a food storage facility to detect the type and quantity of food items. The input is physical inventory information obtained from the sensor devices, and the output is detected inventory data. This inventory data is converted into a digital format for subsequent processing.

[0542] Step 2:

[0543] The robot transmits the acquired inventory data to the server via a network device. The input is the inventory data obtained in step 1, and the output is the digital information sent to the server. Here, data communication takes place using a network protocol.

[0544] Step 3:

[0545] The server manages the received inventory data and user profile data using a data processing device and then begins analysis. The input is inventory data and user profile information, and the output is a nutritionally balanced meal plan as a result of the analysis. Relevant data is searched using database queries, and the meal plan is formulated using a generative AI model.

[0546] Step 4:

[0547] The server generates an optimized meal plan and identifies any missing ingredients based on it. The input is the meal plan obtained in step 3, and the output is a list of ingredients that need to be replenished. If necessary, it automatically generates purchase instructions for supplies using electronic ordering protocols to partner stores.

[0548] Step 5:

[0549] The server transmits the generated meal plan and cooking instructions to a voice information output terminal, providing voice guidance to the user. The input is the meal plan and cooking instructions, and the output is the voice guidance presented to the user. Speech synthesis technology is used to provide step-by-step guidance.

[0550] Step 6:

[0551] The user interacts with a home assistance robot to guide the cooking process. The robot monitors the user's progress in real time and provides feedback as needed. The input is information about the user's cooking progress, and the output is the next instructions or cooking assistance. This allows the robot to continuously provide cooking assistance in the home.

[0552] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0553] This invention incorporates an emotion engine that recognizes the user's emotions into a system that provides food management and nutritionally balanced meal plans for the home, thereby offering more personalized meal support. The aim of this invention is to optimize meal plans and food purchases according to the user's emotional state.

[0554] Integration of emotion recognition

[0555] In this system, the emotion engine is primarily embedded in the terminal and collects emotion data in real time through interaction with the user. When the user prepares food on the terminal or application, the system can estimate their emotions from their facial expressions and tone of voice using sensor devices such as cameras and microphones.

[0556] Data analysis and menu suggestions

[0557] The server analyzes the collected emotional data using an information processing device to determine the user's current emotional state (e.g., stress, happiness, fatigue). Based on this determination, it generates a menu optimized for the user's current state. For example, it suggests a menu using ingredients with relaxing effects for users with high stress levels, thereby improving work efficiency.

[0558] Automatic ordering function

[0559] The server identifies any missing ingredients in the proposed menu by cross-referencing it with inventory data. Based on this information, the terminal considers the user's emotional state and, for example, automatically places an order for highly nutritious foods for a user who needs an energy boost.

[0560] Audio guidance and user interaction

[0561] During the cooking process, the device uses voice guidance to provide appropriate cooking instructions tailored to the user's emotional state. If the user is tired, simpler steps are prioritized; if they are feeling happy, approaches are presented to encourage them to enjoy a more time-consuming cooking experience.

[0562] Specific example

[0563] For example, if a user returns home tired after work and feels the need to refresh, the emotion engine will detect signs of fatigue, and the server will suggest a menu like: "Refreshing Salad with Lemon and Herbs." Furthermore, the necessary ingredients will already be automatically purchased online and prepared. Simultaneously, simple cooking instructions will be provided via voice guidance to help the user prepare the meal quickly.

[0564] Thus, the present invention aims to enrich and improve the health of home eating habits by recognizing the user's emotions in real time and optimizing meal and nutrition management based on those emotions.

[0565] The following describes the processing flow.

[0566] Step 1:

[0567] The device collects emotional data from facial expressions, voice tone, click patterns, and other information through user interaction. It uses sensor devices to estimate the user's emotional state in real time.

[0568] Step 2:

[0569] The server receives emotional data sent from the terminal. Based on the received data, the information processing device analyzes and determines the user's current emotional state.

[0570] Step 3:

[0571] The server uses the analysis results to generate nutritionally balanced meal plans based on the user's emotional state. For example, when the user is feeling stressed, it selects a meal plan that includes ingredients with relaxing properties.

[0572] Step 4:

[0573] The terminal notifies the user of the generated menu and provides specific cooking suggestions. The user can view and review the suggested menu and make adjustments or selections as needed.

[0574] Step 5:

[0575] The server references the household's inventory data based on the selected menu. From this information, it identifies any missing ingredients and determines whether they need to be purchased.

[0576] Step 6:

[0577] The device automatically links with online stores to create a list of missing ingredients and begins preparing an order. It also takes the user's emotional state into consideration and includes suggestions for gathering the necessary nutrients.

[0578] Step 7:

[0579] The server completes the automated order through integration with the online store and sends the order confirmation information to the terminal.

[0580] Step 8:

[0581] The device provides emotionally appropriate voice guidance once the user begins cooking. For example, if the user is tired, it will guide them through concise and efficient steps.

[0582] Step 9:

[0583] Users cook by following the voice guide. They can also receive real-time cooking assistance by asking questions to the guide as needed.

[0584] (Example 2)

[0585] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0586] In modern households, planning nutritionally balanced meals every day is an extremely time-consuming task. Furthermore, providing personalized suggestions that take into account the user's emotional state and allergy information has been considered difficult until now. In addition, automatic replenishment of necessary ingredients and guidance on cooking procedures, which can enrich lives by adapting to individual circumstances, face significant technical hurdles to realization.

[0587] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0588] In this invention, the server includes means for detecting the user's emotional state using sensors and collecting emotional data; means for an information processing device to analyze the collected emotional data and generate an optimal menu based on the user's emotional state; and means for identifying ingredient shortages based on the generated menu and automatically placing orders for replenishment. This enables personalized meal suggestions and nutritional management tailored to the user's emotions and circumstances, making meal planning at home easier.

[0589] A "preservation device" is equipment used to properly store food and ingredients and maintain their freshness.

[0590] A "detection device" is a device used to sense the presence or state of an object and to acquire related information.

[0591] An "information processing device" is a system that receives, analyzes, and processes data, and generates instructions or suggestions based on the results.

[0592] "Users" refer to individuals or organizations that access and use a system or service.

[0593] "Profile information" refers to information that includes personal data about the user, preferences, and past activity history.

[0594] A "communication device" is an electronic device used to send and receive data and information.

[0595] "Emotional state" refers to the user's mental and emotional condition, including states such as stress and happiness.

[0596] A "sensor" is a device that detects physical or environmental phenomena and outputs that information as an electrical signal.

[0597] A "menu" refers to a combination of foods and dishes for a particular meal.

[0598] "Voice guidance" refers to a method of conveying instructions and information to users using voice.

[0599] "Automatic replenishment" is a process that automatically replenishes missing items or materials based on a pre-planned schedule.

[0600] This invention is a system that supports food management and nutritionally balanced menu suggestions in the home, and incorporates an emotion engine that recognizes the user's emotional state. The aim of this system is to improve daily eating habits by providing personalized meal suggestions tailored to the user's individual emotional state.

[0601] First, the device detects the user's facial expressions and voice tone in real time using camera and microphone sensors. This data is analyzed by an emotion engine to determine the user's emotional state. Specifically, standard cameras and microphones are used, and smartphones and tablets with these components are also available.

[0602] Next, the server receives emotional data transmitted from the terminal and analyzes it using an advanced information processing device to determine the user's current emotional state. Here, machine learning algorithms are used to analyze the emotional data, and a menu corresponding to the emotion is generated based on the results. A generative AI model is utilized in this process, suggesting an optimized menu rather than a random one, tailored to the user's emotions.

[0603] For example, if a user feels tired after work and wants to refresh themselves, the emotion engine will detect signs of fatigue, and the server will suggest a menu like a "refreshing salad with lemon and herbs." Furthermore, the necessary ingredients will be automatically purchased online, and simple cooking instructions will be provided via voice guidance from the device.

[0604] An example of an input prompt for the generative AI model would be text in the format of, "Please suggest a refreshing menu for when the user's emotional state is 'tired'."

[0605] This system makes it possible to optimize dietary habits to suit the individual needs and circumstances of each household.

[0606] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0607] Step 1:

[0608] The device uses a camera and microphone to capture the user's facial expressions and voice tone in order to collect information about the user's emotional state. Real-time visual and audio data of the user is acquired as input. Based on this, an emotion engine analyzes the data and estimates the user's emotions (e.g., stress, happiness, fatigue) in real time. The estimated emotional state is obtained as output.

[0609] Step 2:

[0610] The server receives estimated emotion data transmitted from the terminal. It takes emotional state data analyzed by the terminal as input. The server further analyzes this data using an information processing device, uses machine learning algorithms to improve the accuracy of the emotion, and ultimately determines the emotional state. The final emotional state is generated as output.

[0611] Step 3:

[0612] The server uses a generative AI model to generate the optimal menu based on the generated emotional state. The inputs used are the user's emotional state data, profile information, and inventory information. The data is analyzed by the AI ​​model, and a menu corresponding to the emotion is proposed. The output is menu information corresponding to the user's emotion.

[0613] Step 4:

[0614] The server matches the inventory information to identify any missing ingredients based on the menu. It uses the proposed menu and inventory information obtained from storage devices as input. This identifies shortages in the inventory and generates an ingredient order list for automatic replenishment. The output is a list of ingredients that need to be ordered.

[0615] Step 5:

[0616] The device provides suggested menus and corresponding cooking instructions as voice guidance tailored to the user's emotional state. The inputs used are menu information and the user's current emotional state. The voice guidance simplifies or elaborates the cooking instructions, providing the user with the most suitable procedure. The output is a voice notification of the cooking guide.

[0617] (Application Example 2)

[0618] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0619] In modern households, food management and the suggestion of nutritionally balanced menus are considered important, but there is a lack of systems that provide personalized meal support tailored to the emotional state of individual consumers. This problem carries the risk that daily stress and fatigue will influence food choices, ultimately making it difficult to maintain healthy eating habits. The present invention aims to enable the suggestion of a richer diet that takes emotional states into account by proposing optimal menus based on the user's emotional state.

[0620] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0621] In this invention, the server includes means for acquiring food inventory information using a detection device installed in a food storage device in the home, means for collecting emotional data using an emotional recognition device that recognizes the user's emotional state, and means for analyzing the collected emotional data and personalizing the menu based on the analysis results. This makes it possible to suggest a nutritionally balanced menu that reflects the user's emotional state.

[0622] "Household food storage equipment" refers to devices used to store food in the home, and includes refrigerators, pantries, and other similar items.

[0623] A "detection device" is a device installed in a food storage container that is equipped with sensors and cameras to identify the type and quantity of food inside.

[0624] "Inventory information" refers to data obtained by the detection device that shows the type, quantity, and storage condition of food products.

[0625] A "communication device" is hardware used to send and receive data with information processing devices and other devices, and it communicates via internet connections, etc.

[0626] An "information processing device" is a device such as a computer or server used to process and analyze received data.

[0627] "User profile information" refers to personal data about the user, including information such as age, gender, allergy information, and food preferences.

[0628] An "emotion recognition device" is hardware and software used to estimate a user's emotional state, analyzing facial expressions and voice using a camera and microphone.

[0629] "Emotional data" refers to data that quantifies or classifies a user's emotional state as measured by an emotion recognition device.

[0630] A "menu" refers to a systematically planned menu of meals, a meal plan that takes nutritional balance into consideration.

[0631] Personalization is the process of adjusting products and services according to the individual user's characteristics and circumstances.

[0632] "Voice guidance" refers to a function that provides information to users using voice, including automated guides and instructions.

[0633] This system is implemented using hardware such as food storage devices installed in homes, their associated communication devices, and emotion recognition devices. Primarily, sensors are installed within the food storage devices, allowing a detection device to acquire information about the food inventory. This information is then transmitted to an information processing device via a communication device.

[0634] The information processing device generates a nutritionally balanced menu based on received inventory information and user profile information. Furthermore, the user's emotional state is measured in real time by an emotion recognition device, and this data is analyzed by an emotion recognition engine. Based on the results of this analysis, the menu is personalized according to the user's emotions.

[0635] For example, if a user feels the need to refresh themselves, the system can analyze that emotion and suggest a menu using ingredients that have a refreshing effect. In this case, the system automatically identifies any missing ingredients and places an online order for the food.

[0636] Users receive voice guidance on suggested menus and cooking procedures via a communication terminal. This voice guidance is adjusted according to the user's emotional state; for example, simplified cooking procedures are presented when the user is tired.

[0637] For example, if a user prompts, "Please come up with an interesting dish to match my mood today," the system analyzes the request and automatically generates a menu. The generated menu reflects the user's emotional state and can suggest something like "Grilled Herb Chicken and Seasonal Vegetables" for a relaxed dinner. In this way, a personalized dining experience tailored to the user's emotional state is provided.

[0638] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0639] Step 1:

[0640] The server obtains food inventory information using detection devices installed in food storage systems within the home. At this stage, the sensors collect data on the type and quantity of food and transmit this data to the server via a communication device. Based on this input data, the server determines the current food inventory status.

[0641] Step 2:

[0642] The user's emotional state is measured by an emotion recognition device via a communication terminal. Here, the user's facial expressions and voice tone are analyzed using a camera and microphone. This analysis generates emotional data. The server receives this emotional data as input and interprets the user's current emotional state.

[0643] Step 3:

[0644] The server generates nutritionally balanced meal plans based on received inventory information, emotional data, and user profile information. Here, a generative AI model is used to create a personalized meal plan for the user, resulting in individually customized menus. Specifically, data calculations are used to design relaxing menus designed to reduce stress.

[0645] Step 4:

[0646] The server identifies any missing food items based on the generated menu and automatically places online orders. The input here is the menu content, and based on that content, it calculates the necessary ingredients and generates output to place orders on the sales website.

[0647] Step 5:

[0648] The device provides the user with a suggested menu and corresponding cooking instructions via voice guidance through communication. The input for this step is the user's emotional state and the chosen menu. This data is then used to output appropriate cooking instructions via voice guidance. Specifically, if the user is feeling fatigued, the device prioritizes providing instructions for easy cooking procedures.

[0649] Step 6:

[0650] The user begins cooking according to the provided voice guidance and enjoys a meal that responds to their emotions. Here, the cooking process is realistic, and the user's actions in completing the actual menu become the output. This process realizes a dining experience based on emotion management and nutritional management.

[0651] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0652] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0653] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0654] [Fourth Embodiment]

[0655] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0656] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0657] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0658] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0659] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0660] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0661] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0662] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0663] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0664] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0665] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0666] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0667] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0668] This invention is a system for automating food inventory management and healthy meal preparation within the home, and can be implemented with the following configuration.

[0669] overview

[0670] First, a detection device is installed in the food storage unit in the home. This device detects the type and quantity of food items inside the storage unit and transmits this information to a server via a communication device. This communication is conducted over a network.

[0671] Food ingredient data management

[0672] The server stores the inventory information of received ingredients in a database. This makes it possible to always manage the status of ingredients in the home in an up-to-date manner.

[0673] Menu suggestions

[0674] Next, the server analyzes each user's profile information within the household, including age and allergy information, and automatically generates a nutritionally balanced meal plan. The generated meal plan takes into account the user's health condition and daily consumption habits.

[0675] Automated shopping

[0676] The server compares the ingredients required for the proposed menu with inventory data to identify any missing ingredients. The terminal notifies the user of the identified ingredients list, and after user confirmation, automatically orders the necessary ingredients through partnered online stores.

[0677] Cooking support

[0678] During the cooking phase, the device uses voice guidance to direct the user through the cooking procedure based on the menu. Since the user is instructed by voice at each cooking step, they can proceed to the next action without using their hands, allowing them to safely complete the meal regardless of their cooking skills.

[0679] Specific example

[0680] For example, consider a household with an infant where the child's profile is registered and the child has milk or egg allergies. In this household, a detection device collects information about the ingredients in the refrigerator, and if there is little milk left or little food containing eggs, the server suggests a menu that includes alternative ingredients. The server customizes the menu to meet the user's daily nutritional needs, automatically orders ingredients such as almond milk or soy milk if necessary, and provides cooking instructions to the user through voice guidance.

[0681] With this configuration, the present invention significantly reduces the burden of meal preparation and provides efficient and healthy meal support, especially for busy dual-income households.

[0682] The following describes the processing flow.

[0683] Step 1:

[0684] The server periodically receives inventory information from detection devices installed in home food storage systems. This information includes the type, quantity, and expiration date of the food.

[0685] Step 2:

[0686] The server stores the received inventory information in a database and records inventory fluctuations by comparing it with past data.

[0687] Step 3:

[0688] The server retrieves user profile information (e.g., age, weight, allergy information) from the database and begins analysis. Based on this information, it determines each user's nutritional needs.

[0689] Step 4:

[0690] The server automatically generates nutritionally balanced meal plans, taking into account inventory data and the user's nutritional needs. The generated meal plans are optimized based on nutritional standards and inventory status.

[0691] Step 5:

[0692] The terminal notifies the user of the menu retrieved from the server and suggests it to the user. The user can review this menu and request changes if necessary.

[0693] Step 6:

[0694] The server incorporates user feedback to finalize the menu. It also cross-references this with inventory information to identify any missing ingredients.

[0695] Step 7:

[0696] The terminal displays a list of missing ingredients to the user and obtains their approval to proceed with the process of automatically ordering them.

[0697] Step 8:

[0698] The server, upon user approval, automatically places an order for any missing ingredients via the online store's API.

[0699] Step 9:

[0700] The device starts voice guidance at the beginning of cooking, guiding the user through the cooking process step by step. This allows the user to safely proceed with cooking by following the instructions.

[0701] (Example 1)

[0702] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0703] In modern households, managing groceries and preparing healthy meals are crucial challenges. However, the demands of daily life make manual inventory management, creating nutritionally balanced menus, and grocery shopping difficult. There is a need for systems that simplify and streamline these tasks.

[0704] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0705] In this invention, the server includes means for acquiring food inventory information, means for transmitting the inventory information to a computer, and means for generating a nutritionally balanced meal plan. This makes it possible to reduce the burden of managing food supplies in the home and support a healthy diet.

[0706] "Food storage equipment" refers to equipment used to store food items in the home, including refrigerators and pantries.

[0707] A "detection device" is a device installed inside a food storage device to identify the type and quantity of food products, and uses technologies such as RFID tags and barcode readers.

[0708] A "communication device" is a device used to transmit inventory information acquired from a detection device to an external computing device, and it transmits data via a network.

[0709] A "computer system" is a computer system that receives and processes inventory information transmitted from a communication device.

[0710] A "meal plan" is a menu generated with nutritional balance in mind, and is created based on the user's profile information.

[0711] An "external purchasing device" is a device that automatically orders groceries based on a meal plan, and it is linked to the ordering system of an online store.

[0712] A "communication terminal" is a device that provides users with voice guidance on meal planning and cooking instructions, and is equipped with a speaker and microphone.

[0713] The embodiments for carrying out the present invention are described below.

[0714] This system is designed to automate grocery management and healthy meal preparation within the home. The necessary hardware includes "sensing devices" installed in "food storage equipment" such as refrigerators and pantries. These sensing devices use RFID tags or barcode readers to identify the type and quantity of food items. This data is transmitted to a server via a "communication device."

[0715] The server stores received food inventory information in a database and uses it to manage the inventory of individual households. To generate a nutritionally balanced "meal plan," the server uses a "computational device" to analyze the user's profile information (e.g., age, allergies, nutritional goals, etc.) and provides appropriate menus using a generation AI model.

[0716] Based on the generated meal plan, the server identifies any missing groceries and automatically places orders via an "external purchasing device." This includes a function that automatically purchases necessary ingredients using online store APIs. The terminal provides the user with voice guidance on the generated menu and cooking instructions, improving the efficiency of household chores.

[0717] For example, in a family with children, if one child has a dairy allergy, the server will take this into consideration, suggest a dairy-free menu, and order alternative ingredients online if necessary.

[0718] An example of a prompt message might be, "Create a healthy menu for your family this week and list the necessary ingredients." In this way, users can prepare healthy and efficient meals.

[0719] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0720] Step 1:

[0721] The user installs a detection device in their home food storage system. The detection device identifies the type and quantity of food and acquires data using RFID tags or barcode readers. The input is physical data of the food (type, quantity), and the output is digitized inventory information.

[0722] Step 2:

[0723] The communication device transmits inventory information acquired from the detection device to the server. The server receives this digitized inventory information as input and stores it in a database. In this step, data processing is performed to organize and store the type, quantity, and expiration date of the food, and the current inventory status is registered in the database as output.

[0724] Step 3:

[0725] The server receives inventory information stored in the database and user profile information (age, allergies, nutritional goals, etc.) as input, and uses a generative AI model to generate an optimal meal plan. This process analyzes nutritional balance based on the user's health status, and the output is a customized menu plan.

[0726] Step 4:

[0727] The server determines the necessary ingredients based on the generated meal plan and compares them with inventory data. The inputs are the meal plan and inventory data, and the output is a list of missing ingredients. The necessary data calculations include checking inventory availability and listing the shortages.

[0728] Step 5:

[0729] The terminal notifies the user of a list of missing ingredients and asks for confirmation of whether they wish to purchase them. After receiving user approval, the terminal automatically places an online order via an external purchasing device. The inputs are the list of missing ingredients and user approval, and the output is an order confirmation sent.

[0730] Step 6:

[0731] The device guides the user through cooking procedures via voice guidance. The input is a generated menu plan, and the output is voice commands. This process provides specific steps to ensure the user can cook safely and with minimal hands-on effort.

[0732] (Application Example 1)

[0733] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0734] In modern society, there is a growing need for more efficient food management and healthy meal preparation at home. However, for dual-income families and busy individuals, it is difficult to keep track of food inventory and prepare nutritionally balanced meals on a daily basis. In this situation, there is a need for automated support systems that reduce the burden on households and promote health maintenance.

[0735] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0736] In this invention, the server includes means for acquiring food inventory data using sensor devices attached to food storage facilities in the home, means for generating a nutritionally balanced meal plan based on the received inventory data and user profile data by a data processing device, and means for a home support robot to check the physical inventory of food on a daily basis. This makes it possible to always provide the user with the optimal meal while reducing food waste and supporting daily life.

[0737] A "household assistance robot" is an autonomous mechanical device designed to automate household tasks and provide assistance with food management and cooking.

[0738] A "sensor device" is a device that detects a specific physical quantity and converts that information into an electrical signal, and is used to detect the inventory status of food products.

[0739] A "data processing device" is a computer that processes received data and makes specific decisions or suggestions based on the analysis results.

[0740] "Inventory data" refers to information that shows the types and quantities of food ingredients stored in food storage facilities.

[0741] "Profile data" refers to information about individual users, including specific data such as age, allergy information, and nutritional needs.

[0742] A "meal plan" refers to a meal plan designed based on nutritional balance, with menus tailored to the user's health condition and preferences.

[0743] A "voice information output terminal" is a device that provides instructions and information via voice, and is designed to support users in operating the device without relying on their vision.

[0744] "Automating purchasing" means electronically managing the process of automatically ordering and replenishing necessary food and supplies when they are in short supply.

[0745] In the system implementing this invention, a household assistance robot plays a central role. The robot is equipped with multiple sensor devices and periodically acquires food inventory data from the household's food storage facilities. This allows the robot to determine the types and quantities of food items and transmit this information to a server via a network device.

[0746] The server analyzes received inventory data and user profile data using a data processing device. The software used for this analysis includes a data analysis program written in Python, and the data is stored in a database such as MySQL. The server then uses a generative AI model to automatically generate meal plans that take into account the user's nutritional balance. The generated meal plans are then communicated to the user in real time via a voice information output terminal.

[0747] Furthermore, the home support robot regularly checks the physical inventory of groceries, identifies any missing foods as needed, and automatically places orders through partner e-commerce platforms. This allows users to enjoy a healthy diet without worrying about purchasing groceries.

[0748] As a concrete example, a scenario is envisioned where, after checking the stock of tomatoes and cheese in the home, this information is sent to a server, which then suggests a tomato soup recipe that takes nutritional balance into consideration. Based on the suggested recipe, an additional cheese order is automatically placed.

[0749] An example of a prompt for a generative AI model is the following text: "A home assistance robot should create a healthy dinner menu based on the current food inventory and the user's nutritional information. It should suggest a recipe using tomatoes and cheese and provide voice guidance to support the cooking process."

[0750] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0751] Step 1:

[0752] A home assistance robot uses sensor devices within a food storage facility to detect the type and quantity of food items. The input is physical inventory information obtained from the sensor devices, and the output is detected inventory data. This inventory data is converted into a digital format for subsequent processing.

[0753] Step 2:

[0754] The robot transmits the acquired inventory data to the server via a network device. The input is the inventory data obtained in step 1, and the output is the digital information sent to the server. Here, data communication takes place using a network protocol.

[0755] Step 3:

[0756] The server manages the received inventory data and user profile data using a data processing device and then begins analysis. The input is inventory data and user profile information, and the output is a nutritionally balanced meal plan as a result of the analysis. Relevant data is searched using database queries, and the meal plan is formulated using a generative AI model.

[0757] Step 4:

[0758] The server generates an optimized meal plan and identifies any missing ingredients based on it. The input is the meal plan obtained in step 3, and the output is a list of ingredients that need to be replenished. If necessary, it automatically generates purchase instructions for supplies using electronic ordering protocols to partner stores.

[0759] Step 5:

[0760] The server transmits the generated meal plan and cooking instructions to a voice information output terminal, providing voice guidance to the user. The input is the meal plan and cooking instructions, and the output is the voice guidance presented to the user. Speech synthesis technology is used to provide step-by-step guidance.

[0761] Step 6:

[0762] The user interacts with a home assistance robot to guide the cooking process. The robot monitors the user's progress in real time and provides feedback as needed. The input is information about the user's cooking progress, and the output is the next instructions or cooking assistance. This allows the robot to continuously provide cooking assistance in the home.

[0763] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0764] This invention incorporates an emotion engine that recognizes the user's emotions into a system that provides food management and nutritionally balanced meal plans for the home, thereby offering more personalized meal support. The aim of this invention is to optimize meal plans and food purchases according to the user's emotional state.

[0765] Integration of emotion recognition

[0766] In this system, the emotion engine is primarily embedded in the terminal and collects emotion data in real time through interaction with the user. When the user prepares food on the terminal or application, the system can estimate their emotions from their facial expressions and tone of voice using sensor devices such as cameras and microphones.

[0767] Data analysis and menu suggestions

[0768] The server analyzes the collected emotional data using an information processing device to determine the user's current emotional state (e.g., stress, happiness, fatigue). Based on this determination, it generates a menu optimized for the user's current state. For example, it suggests a menu using ingredients with relaxing effects for users with high stress levels, thereby improving work efficiency.

[0769] Automatic ordering function

[0770] The server identifies any missing ingredients in the proposed menu by cross-referencing it with inventory data. Based on this information, the terminal considers the user's emotional state and, for example, automatically places an order for highly nutritious foods for a user who needs an energy boost.

[0771] Audio guidance and user interaction

[0772] During the cooking process, the device uses voice guidance to provide appropriate cooking instructions tailored to the user's emotional state. If the user is tired, simpler steps are prioritized; if they are feeling happy, approaches are presented to encourage them to enjoy a more time-consuming cooking experience.

[0773] Specific example

[0774] For example, if a user returns home tired after work and feels the need to refresh, the emotion engine will detect signs of fatigue, and the server will suggest a menu like: "Refreshing Salad with Lemon and Herbs." Furthermore, the necessary ingredients will already be automatically purchased online and prepared. Simultaneously, simple cooking instructions will be provided via voice guidance to help the user prepare the meal quickly.

[0775] Thus, the present invention aims to enrich and improve the health of home eating habits by recognizing the user's emotions in real time and optimizing meal and nutrition management based on those emotions.

[0776] The following describes the processing flow.

[0777] Step 1:

[0778] The device collects emotional data from facial expressions, voice tone, click patterns, and other information through user interaction. It uses sensor devices to estimate the user's emotional state in real time.

[0779] Step 2:

[0780] The server receives emotional data sent from the terminal. Based on the received data, the information processing device analyzes and determines the user's current emotional state.

[0781] Step 3:

[0782] The server uses the analysis results to generate nutritionally balanced meal plans based on the user's emotional state. For example, when the user is feeling stressed, it selects a meal plan that includes ingredients with relaxing properties.

[0783] Step 4:

[0784] The terminal notifies the user of the generated menu and provides specific cooking suggestions. The user can view and review the suggested menu and make adjustments or selections as needed.

[0785] Step 5:

[0786] The server references the household's inventory data based on the selected menu. From this information, it identifies any missing ingredients and determines whether they need to be purchased.

[0787] Step 6:

[0788] The device automatically links with online stores to create a list of missing ingredients and begins preparing an order. It also takes the user's emotional state into consideration and includes suggestions for gathering the necessary nutrients.

[0789] Step 7:

[0790] The server completes the automated order through integration with the online store and sends the order confirmation information to the terminal.

[0791] Step 8:

[0792] The device provides emotionally appropriate voice guidance once the user begins cooking. For example, if the user is tired, it will guide them through concise and efficient steps.

[0793] Step 9:

[0794] Users cook by following the voice guide. They can also receive real-time cooking assistance by asking questions to the guide as needed.

[0795] (Example 2)

[0796] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0797] In modern households, planning nutritionally balanced meals every day is an extremely time-consuming task. Furthermore, providing personalized suggestions that take into account the user's emotional state and allergy information has been considered difficult until now. In addition, automatic replenishment of necessary ingredients and guidance on cooking procedures, which can enrich lives by adapting to individual circumstances, face significant technical hurdles to realization.

[0798] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0799] In this invention, the server includes means for detecting the user's emotional state using sensors and collecting emotional data; means for an information processing device to analyze the collected emotional data and generate an optimal menu based on the user's emotional state; and means for identifying ingredient shortages based on the generated menu and automatically placing orders for replenishment. This enables personalized meal suggestions and nutritional management tailored to the user's emotions and circumstances, making meal planning at home easier.

[0800] A "preservation device" is equipment used to properly store food and ingredients and maintain their freshness.

[0801] A "detection device" is a device used to sense the presence or state of an object and to acquire related information.

[0802] An "information processing device" is a system that receives, analyzes, and processes data, and generates instructions or suggestions based on the results.

[0803] "Users" refer to individuals or organizations that access and use a system or service.

[0804] "Profile information" refers to information that includes personal data about the user, preferences, and past activity history.

[0805] A "communication device" is an electronic device used to send and receive data and information.

[0806] "Emotional state" refers to the user's mental and emotional condition, including states such as stress and happiness.

[0807] A "sensor" is a device that detects physical or environmental phenomena and outputs that information as an electrical signal.

[0808] A "menu" refers to a combination of foods and dishes for a particular meal.

[0809] "Voice guidance" refers to a method of conveying instructions and information to users using voice.

[0810] "Automatic replenishment" is a process that automatically replenishes missing items or materials based on a pre-planned schedule.

[0811] This invention is a system that supports food management and nutritionally balanced menu suggestions in the home, and incorporates an emotion engine that recognizes the user's emotional state. The aim of this system is to improve daily eating habits by providing personalized meal suggestions tailored to the user's individual emotional state.

[0812] First, the device detects the user's facial expressions and voice tone in real time using camera and microphone sensors. This data is analyzed by an emotion engine to determine the user's emotional state. Specifically, standard cameras and microphones are used, and smartphones and tablets with these components are also available.

[0813] Next, the server receives emotional data transmitted from the terminal and analyzes it using an advanced information processing device to determine the user's current emotional state. Here, machine learning algorithms are used to analyze the emotional data, and a menu corresponding to the emotion is generated based on the results. A generative AI model is utilized in this process, suggesting an optimized menu rather than a random one, tailored to the user's emotions.

[0814] For example, if a user feels tired after work and wants to refresh themselves, the emotion engine will detect signs of fatigue, and the server will suggest a menu like a "refreshing salad with lemon and herbs." Furthermore, the necessary ingredients will be automatically purchased online, and simple cooking instructions will be provided via voice guidance from the device.

[0815] An example of an input prompt for the generative AI model would be text in the format of, "Please suggest a refreshing menu for when the user's emotional state is 'tired'."

[0816] This system makes it possible to optimize dietary habits to suit the individual needs and circumstances of each household.

[0817] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0818] Step 1:

[0819] The device uses a camera and microphone to capture the user's facial expressions and voice tone in order to collect information about the user's emotional state. Real-time visual and audio data of the user is acquired as input. Based on this, an emotion engine analyzes the data and estimates the user's emotions (e.g., stress, happiness, fatigue) in real time. The estimated emotional state is obtained as output.

[0820] Step 2:

[0821] The server receives estimated emotion data transmitted from the terminal. It takes emotional state data analyzed by the terminal as input. The server further analyzes this data using an information processing device, uses machine learning algorithms to improve the accuracy of the emotion, and ultimately determines the emotional state. The final emotional state is generated as output.

[0822] Step 3:

[0823] The server uses a generative AI model to generate the optimal menu based on the generated emotional state. The inputs used are the user's emotional state data, profile information, and inventory information. The data is analyzed by the AI ​​model, and a menu corresponding to the emotion is proposed. The output is menu information corresponding to the user's emotion.

[0824] Step 4:

[0825] The server matches the inventory information to identify any missing ingredients based on the menu. It uses the proposed menu and inventory information obtained from storage devices as input. This identifies shortages in the inventory and generates an ingredient order list for automatic replenishment. The output is a list of ingredients that need to be ordered.

[0826] Step 5:

[0827] The device provides suggested menus and corresponding cooking instructions as voice guidance tailored to the user's emotional state. The inputs used are menu information and the user's current emotional state. The voice guidance simplifies or elaborates the cooking instructions, providing the user with the most suitable procedure. The output is a voice notification of the cooking guide.

[0828] (Application Example 2)

[0829] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0830] In modern households, food management and the suggestion of nutritionally balanced menus are considered important, but there is a lack of systems that provide personalized meal support tailored to the emotional state of individual consumers. This problem carries the risk that daily stress and fatigue will influence food choices, ultimately making it difficult to maintain healthy eating habits. The present invention aims to enable the suggestion of a richer diet that takes emotional states into account by proposing optimal menus based on the user's emotional state.

[0831] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0832] In this invention, the server includes means for acquiring food inventory information using a detection device installed in a food storage device in the home, means for collecting emotional data using an emotional recognition device that recognizes the user's emotional state, and means for analyzing the collected emotional data and personalizing the menu based on the analysis results. This makes it possible to suggest a nutritionally balanced menu that reflects the user's emotional state.

[0833] "Household food storage equipment" refers to devices used to store food in the home, and includes refrigerators, pantries, and other similar items.

[0834] A "detection device" is a device installed in a food storage container that is equipped with sensors and cameras to identify the type and quantity of food inside.

[0835] "Inventory information" refers to data obtained by the detection device that shows the type, quantity, and storage condition of food products.

[0836] A "communication device" is hardware used to send and receive data with information processing devices and other devices, and it communicates via internet connections, etc.

[0837] An "information processing device" is a device such as a computer or server used to process and analyze received data.

[0838] "User profile information" refers to personal data about the user, including information such as age, gender, allergy information, and food preferences.

[0839] An "emotion recognition device" is hardware and software used to estimate a user's emotional state, analyzing facial expressions and voice using a camera and microphone.

[0840] "Emotional data" refers to data that quantifies or classifies a user's emotional state as measured by an emotion recognition device.

[0841] A "menu" refers to a systematically planned menu of meals, a meal plan that takes nutritional balance into consideration.

[0842] Personalization is the process of adjusting products and services according to the individual user's characteristics and circumstances.

[0843] "Voice guidance" refers to a function that provides information to users using voice, including automated guides and instructions.

[0844] This system is implemented using hardware such as food storage devices installed in homes, their associated communication devices, and emotion recognition devices. Primarily, sensors are installed within the food storage devices, allowing a detection device to acquire information about the food inventory. This information is then transmitted to an information processing device via a communication device.

[0845] The information processing device generates a nutritionally balanced menu based on received inventory information and user profile information. Furthermore, the user's emotional state is measured in real time by an emotion recognition device, and this data is analyzed by an emotion recognition engine. Based on the results of this analysis, the menu is personalized according to the user's emotions.

[0846] For example, if a user feels the need to refresh themselves, the system can analyze that emotion and suggest a menu using ingredients that have a refreshing effect. In this case, the system automatically identifies any missing ingredients and places an online order for the food.

[0847] Users receive voice guidance on suggested menus and cooking procedures via a communication terminal. This voice guidance is adjusted according to the user's emotional state; for example, simplified cooking procedures are presented when the user is tired.

[0848] For example, if a user prompts, "Please come up with an interesting dish to match my mood today," the system analyzes the request and automatically generates a menu. The generated menu reflects the user's emotional state and can suggest something like "Grilled Herb Chicken and Seasonal Vegetables" for a relaxed dinner. In this way, a personalized dining experience tailored to the user's emotional state is provided.

[0849] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0850] Step 1:

[0851] The server obtains food inventory information using detection devices installed in food storage systems within the home. At this stage, the sensors collect data on the type and quantity of food and transmit this data to the server via a communication device. Based on this input data, the server determines the current food inventory status.

[0852] Step 2:

[0853] The user's emotional state is measured by an emotion recognition device via a communication terminal. Here, the user's facial expressions and voice tone are analyzed using a camera and microphone. This analysis generates emotional data. The server receives this emotional data as input and interprets the user's current emotional state.

[0854] Step 3:

[0855] The server generates nutritionally balanced meal plans based on received inventory information, emotional data, and user profile information. Here, a generative AI model is used to create a personalized meal plan for the user, resulting in individually customized menus. Specifically, data calculations are used to design relaxing menus designed to reduce stress.

[0856] Step 4:

[0857] The server identifies any missing food items based on the generated menu and automatically places online orders. The input here is the menu content, and based on that content, it calculates the necessary ingredients and generates output to place orders on the sales website.

[0858] Step 5:

[0859] The device provides the user with a suggested menu and corresponding cooking instructions via voice guidance through communication. The input for this step is the user's emotional state and the chosen menu. This data is then used to output appropriate cooking instructions via voice guidance. Specifically, if the user is feeling fatigued, the device prioritizes providing instructions for easy cooking procedures.

[0860] Step 6:

[0861] The user begins cooking according to the provided voice guidance and enjoys a meal that responds to their emotions. Here, the cooking process is realistic, and the user's actions in completing the actual menu become the output. This process realizes a dining experience based on emotion management and nutritional management.

[0862] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0863] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0864] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0865] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0866] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0867] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0868] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0869] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0870] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0871] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0872] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0873] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0874] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0875] 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.

[0876] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0877] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0878] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0879] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0880] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0881] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0882] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0883] The following is further disclosed regarding the embodiments described above.

[0884] (Claim 1)

[0885] A means of obtaining food inventory information using a detection device installed in a food storage device in the home,

[0886] A means for transmitting the above-mentioned inventory information to an information processing device via a communication device connected to a monitoring device,

[0887] A means for generating a nutritionally balanced menu based on inventory information received by an information processing device and user profile information,

[0888] A means to identify food shortages based on the generated menu and automatically place orders for replenishment,

[0889] A means of providing the user with voice guidance on the above-mentioned menu and cooking procedures via a communication terminal,

[0890] A system that includes this.

[0891] (Claim 2)

[0892] The system according to claim 1, which recognizes the user's actions and progress in guiding cooking procedures and provides subsequent instructions accordingly.

[0893] (Claim 3)

[0894] The system according to claim 1 that generates a menu that takes into account the user's allergy information.

[0895] "Example 1"

[0896] (Claim 1)

[0897] A means of obtaining food inventory information using a detection device installed in a food storage device in the home,

[0898] A means for transmitting the above-mentioned inventory information to a computing device via a communication device connected to a detection device,

[0899] A means for generating a nutritionally balanced meal plan based on inventory information received by a computing device and user profile information,

[0900] A means for identifying food shortages based on the generated meal plan and automatically placing orders for replenishment through an external purchasing device,

[0901] A means of providing users with voice guidance on the aforementioned meal plan and cooking instructions via a communication terminal,

[0902] A system that includes this.

[0903] (Claim 2)

[0904] The system according to claim 1, which recognizes the user's instructions and progress in providing cooking instructions and gives the next instructions accordingly.

[0905] (Claim 3)

[0906] The system according to claim 1 that generates a meal plan that takes into account the user's allergy information.

[0907] "Application Example 1"

[0908] (Claim 1)

[0909] A means of acquiring food inventory data using sensor devices installed in household food storage facilities,

[0910] A means for transmitting the above inventory data to a data processing device via a network device connected to the monitoring equipment,

[0911] A means for generating a nutritionally balanced meal plan based on inventory data and user profile data received by a data processing device,

[0912] A means to identify shortages of supplies based on the generated meal plan and to automatically purchase replenishment items,

[0913] A means of providing voice guidance to the user regarding the above meal plan and cooking process using an audio information output terminal,

[0914] A home assistance robot performs the operations described above, providing a means to regularly check the physical inventory of food items,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, which recognizes the user's actions and progress in a cooking process guide and provides interactive feedback by a home support robot.

[0918] (Claim 3)

[0919] The system according to claim 1, which generates a meal plan that takes into account the user's allergy data, suggests alternative ingredients as needed, and automates purchasing.

[0920] "Example 2 of combining an emotion engine"

[0921] (Claim 1)

[0922] A means of obtaining material inventory information using a detection device installed in a storage device within the home,

[0923] A means for transmitting the above-mentioned inventory information to an information processing device via a communication device connected to a monitoring device,

[0924] A means for generating a nutritionally balanced menu based on inventory information and user profile information received by an information processing device,

[0925] A means of detecting the user's emotional state via sensors through a terminal and collecting emotional data,

[0926] A means for an information processing device to analyze collected emotional data and generate an optimal menu based on the user's emotional state,

[0927] A means to identify ingredient shortages based on the generated menu and automatically place orders for replenishment,

[0928] A means of providing users with voice guidance on the above-mentioned menu and cooking procedures via a communication terminal,

[0929] A system that includes this.

[0930] (Claim 2)

[0931] The system according to claim 1, which recognizes the user's actions, progress, and emotional state in guiding cooking procedures, and provides subsequent instructions accordingly.

[0932] (Claim 3)

[0933] The system according to claim 1, which generates a menu that takes into account the user's allergy information and emotional state.

[0934] "Application example 2 when combining with an emotional engine"

[0935] (Claim 1)

[0936] A means of obtaining food inventory information using a detection device installed in a food storage device in the home,

[0937] A means for transmitting the above-mentioned inventory information to an information processing device via a communication device connected to a monitoring device,

[0938] A means for generating a nutritionally balanced menu based on inventory information received by an information processing device and user profile information,

[0939] A means for collecting emotional data using an emotion recognition device that recognizes the emotional state of the user,

[0940] A means of analyzing collected emotional data and personalizing menus based on the analysis results,

[0941] A means to identify food shortages based on the generated menu and automatically place orders for replenishment,

[0942] A means of providing voice guidance to the user regarding the above-mentioned menu and cooking procedures according to their emotional state via a communication terminal,

[0943] A system that includes this.

[0944] (Claim 2)

[0945] The system according to claim 1, which, in providing instructions for cooking procedures, recognizes the user's actions and progress, gives the next instructions accordingly, and provides instructions that take into account the user's emotional state.

[0946] (Claim 3)

[0947] The system according to claim 1, which generates a menu that takes into account the user's allergy information and emotional state. [Explanation of Symbols]

[0948] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of acquiring food inventory data using sensor devices installed in household food storage facilities, A means for transmitting the above inventory data to a data processing device via a network device connected to the monitoring equipment, A means for generating a nutritionally balanced meal plan based on inventory data and user profile data received by a data processing device, A means to identify shortages of supplies based on the generated meal plan and to automatically purchase replenishment items, A means of providing voice guidance to the user regarding the above meal plan and cooking process using an audio information output terminal, A home assistance robot performs the operations described above, providing a means to regularly check the physical inventory of food items, A system that includes this.

2. The system according to claim 1, which recognizes the user's operations and progress in a cooking process guide and provides interactive feedback by a home support robot.

3. The system according to claim 1, which generates a meal plan that takes into account the user's allergy data, suggests alternative ingredients as needed, and automates purchasing.

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