system

Abstract

We provide the system. [Solution] A means of receiving data for inputting ingredient information, A calculation means for saving the entered food information and calculating the expiration date, A recipe generation method that generates optimal cooking suggestions based on stored ingredient information, An information notification means that outputs optimal cooking suggestions and expiration date notifications to the user, A generative AI model that generates optimal cooking suggestions by taking into account user preferences and past consumption data, An online data connection method for linking data with e-commerce sites, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds 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 times, food loss is a serious social problem that causes environmental burden and economic losses. In homes and restaurants, there is a current situation where a lot of food ingredients are wasted due to over-purchasing and insufficient management of food ingredients. In order to address such problems, it is essential to streamline the management of food ingredients, particularly to promote awareness of expiration dates and the appropriate use of food ingredients based on them. However, there is no system in the conventional technology that sufficiently supports this, and much of it is left to the user. Therefore, there is a demand for the provision of an integrated management system for effectively reducing food loss.

Means for Solving the Problems

[0005] To solve this problem, the present invention includes a database means that includes a user interface for inputting food ingredient information and a processor that stores the input food ingredient information and calculates the expiration date. It also includes a generation means for generating an optimal cooking plan based on the stored food ingredient information, and a notification means for outputting the optimal cooking plan and expiration date notification to the user. Furthermore, by including means for automatically generating a purchase list based on food ingredient information and means for calculating and displaying the degree of environmental contribution based on food waste reduction, the present invention provides a system that streamlines overall food ingredient management and allows users to easily reduce food waste.

[0006] "Food ingredient information" refers to data entered by users regarding the name, quantity, purchase date, and expiration date of food items.

[0007] A "user interface" is a set of controls that allows users to input, edit, and display information about food ingredients.

[0008] A "processor" is a device that processes input food ingredient information and performs necessary calculations and data storage.

[0009] A "database system" is a memory system for structurally storing and managing information about ingredients and calculation results.

[0010] A "generation method" refers to a system or algorithm that derives the optimal cooking plan based on stored ingredient information.

[0011] "Notification method" refers to an output method for communicating generated cooking suggestions and expiration date information to the user.

[0012] A "purchase list" is an automatically generated list of ingredients that are currently lacking or that will be needed in the future.

[0013] "Contribution to the environment" is an index that quantitatively evaluates the environmental mitigation effect of reducing food waste. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. <UNK>0000076It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] The embodiments for carrying out the present invention will be described by dividing them into three elements: user, terminal, and server.

[0036] User-side embodiment

[0037] First, after purchasing ingredients, the user opens the application on their device and enters the ingredient information. This information includes the name of the food, purchase date, quantity, and expiration date. This information is processed appropriately on the device, as described below, and then sent to the server. The user also periodically checks the device for optimal cooking suggestions and expiration date information to ensure proper use of the ingredients. Furthermore, the user can prevent waste by referring to the purchase list displayed on the device and purchasing only what is needed.

[0038] Terminal-side embodiment

[0039] The terminal has the function of receiving ingredient information entered by the user and sending it to the server. It also displays the optimal cooking suggestion and expiration date notifications received from the server to the user in an easy-to-understand manner. For example, if ingredient information such as "Tomato, Purchase date: October 1, 2023, Expiration date: October 7, 2023" is entered into the terminal, that information is immediately sent to the server, and necessary notifications are sent to the user as they occur.

[0040] Server-side embodiment

[0041] The server receives ingredient information sent from the terminal and stores it in a database. Based on this information, it calculates the expiration date of the ingredients and prepares to notify the user. Furthermore, the server uses an AI algorithm to generate optimal cooking suggestions to maximize the use of the currently available ingredients. These cooking suggestions are sent to the terminal and provided to the user. In addition, based on the user's ingredient consumption data, the server calculates the effect of reducing food waste as a contribution to the environment and provides feedback. In this way, the server plays a central role in data processing and provides various information in a format that makes it easy for users to take actual action.

[0042] This "mode for carrying out the invention" allows the present invention to efficiently support consumers in reducing food waste and promote environmental contributions.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user enters information about the purchased ingredients into the application on their device. Specifically, they specify the name of the ingredient, the purchase date, and the quantity, and then press the submit button.

[0046] Step 2:

[0047] The terminal formats the entered ingredient information into JSON format and prepares it for transmission to the server. Here, it checks the validity of the data and converts it into a format for communication with the server.

[0048] Step 3:

[0049] The server stores the ingredient information received from the terminal into a database. Before saving, it verifies that the data format is correct and inserts it into the database using an SQL query.

[0050] Step 4:

[0051] The server calculates the expiration date for stored food items and sets a notification schedule. This process calculates the expiration date and prepares a trigger to send a notification at the specified date and time.

[0052] Step 5:

[0053] The server uses AI to generate optimal cooking suggestions based on the user's inventory data. Specifically, it feeds the ingredient list to an AI algorithm to create recipe suggestions and cooking plans.

[0054] Step 6:

[0055] The server sends the generated cooking suggestions and expiration date information to the user's device. An API is used for transmission, appropriately packaging the data before sending it to the device.

[0056] Step 7:

[0057] The device displays notifications and suggestions from the server to the user. Specifically, it displays cooking suggestions and alerts about food items nearing their expiration date on the device's screen.

[0058] Step 8:

[0059] Users take necessary actions based on the information presented by their device. For example, they might prioritize cooking ingredients that are nearing their expiration date, or check their shopping list to help with their shopping.

[0060] (Example 1)

[0061] 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."

[0062] Efficient management and waste reduction are crucial issues in food consumption. However, individual food management by consumers is time-consuming and labor-intensive, and food waste due to expired products is common. These problems also increase unnecessary environmental impacts. Therefore, there is a need for systems that efficiently manage, manage, and consume food to reduce food waste.

[0063] 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.

[0064] In this invention, the server includes an information input / output device for users to input information, an information management means including a calculation device for storing the input information and calculating the period, and a generation device for generating an optimal plan based on the stored information. This enables consumers to efficiently manage and cook ingredients and reduce food waste.

[0065] An "information input / output device for users to input information" is a device that provides an interface for users to input arbitrary information.

[0066] "Information management means including a calculation device for storing input information and calculating a period" refers to a device that records information entered by a user and has a calculation function for calculating a period associated with that information.

[0067] A "generating device that generates optimal proposals based on stored information" is a device that analyzes information recorded in a database and creates the best possible proposal based on the results of that analysis.

[0068] A "notification device that outputs notifications of the optimal plan and timeframe" is a device that appropriately reports the calculated timeframe and generated plan to the user.

[0069] "Information display means for displaying generated proposals" refers to a device for visually showing the proposals created by the generation device to the user.

[0070] A "device that automatically generates lists" is a device that automatically creates a list of newly required items based on stored information and utilizing that information.

[0071] A "device for calculating and displaying the impact based on reductions" is a device that measures the effect of reductions achieved by a specific activity and informs the user of the results.

[0072] This invention is a system that has three elements: a user, a terminal, and a server, and promotes the efficient management and consumption of food. The specific configuration and operation are described below.

[0073] User-side embodiment

[0074] Users use an application installed on their device to manage information about food they have purchased. First, users enter information such as the name of the food item, purchase date, quantity, and expiration date. This data forms the basis for efficient management. Users periodically check their device and refer to cooking suggestions and expiration date information provided by the server. This allows users to minimize waste.

[0075] Terminal-side embodiment

[0076] The device receives information entered by the user and sends it to the server. A standard smartphone or tablet is used for this purpose. The received data is temporarily stored but is transferred to the server as it is received. The device also serves to provide notifications from the server to the user. Specifically, it displays information on ingredients nearing their expiration date and cooking suggestions on the device screen.

[0077] Server-side embodiment

[0078] The server receives ingredient information sent from the terminal and stores it in a database. This process uses a database management system based on SQL. The server utilizes the stored data and generates optimal cooking suggestions using an AI algorithm. At the heart of this system is a generative AI model. The server enhances its contribution to the environment by calculating expiration dates, evaluating food waste reduction, and generating feedback for the user.

[0079] Specific example

[0080] When a user enters ingredient information into their device, such as "Tomatoes, Purchase Date: October 1, 2023, Expiration Date: October 7, 2023," that information is sent to the server. The server takes the expiration date into consideration and suggests "Tomato Sauce Pasta" as an example of a dish using tomatoes.

[0081] Example of a prompt

[0082] "Purchased ingredients: chicken, tomatoes. Please suggest a cooking method."

[0083] In this way, the system provides functions that fully support users in efficiently utilizing ingredients.

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

[0085] Step 1:

[0086] The user enters food information into the application on their device. The input fields include the name of the food item, purchase date, quantity, and expiration date. This information is provided by the user and temporarily stored as digital data on the device. This data is then sent to the server in the next step.

[0087] Step 2:

[0088] The device sends the stored ingredient information to the server. This transmission operation uses network communication (e.g., Wi-Fi or mobile data communication). The transmitted data consists of all the information related to each ingredient and is output from the device.

[0089] Step 3:

[0090] The server receives data sent from the terminal and stores it in a database. Based on the input information, the server calculates the expiration date for each food item. This calculation process calculates the number of days from the purchase date to the expiration date and outputs the number of days remaining until the expiration date.

[0091] Step 4:

[0092] The server generates optimal cooking suggestions using a generative AI model based on stored information. By incorporating ingredient information into prompt messages and inputting it into the AI ​​model, cooking suggestions that maximize the use of ingredients are generated. These generated suggestions are retrieved as output.

[0093] Step 5:

[0094] The server notifies the device of the calculated expiration date and generated cooking suggestions. These notifications are sent to the device as push notifications or in-app notifications. This allows the user to receive instructions on how to use ingredients efficiently.

[0095] Step 6:

[0096] The terminal displays instructions received from the server to the user. A visual interface is used for the display, and the information is organized so that the user can easily understand it. This interface highlights ingredients that are nearing their expiration date and optimal cooking suggestions.

[0097] Step 7:

[0098] Based on the information displayed on the device, users take actions to prevent food waste by cooking and consuming food appropriately. Ultimately, the user's actions based on the information become the output, resulting in the effective use of ingredients.

[0099] (Application Example 1)

[0100] 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."

[0101] Modern consumers are expected to manage their food efficiently and reduce waste. However, keeping track of ingredients, managing expiration dates, and choosing cooking methods that suit their preferences are troublesome and contribute to food loss. A solution to this problem is needed.

[0102] 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.

[0103] In this invention, the server includes a calculation means for storing ingredient information and calculating expiration dates, a recipe generation means for generating optimal cooking suggestions based on the stored information, a generation AI model means that takes into account user preferences and past consumption data, and an online data connection means for linking data with e-commerce sites. This allows consumers to efficiently manage ingredients and reduce food waste while saving the effort of inputting information.

[0104] "Food information" refers to details such as the name, quantity, purchase date, and expiration date of food purchased by consumers.

[0105] A "data receiving means" refers to a method that provides an interface for users to input ingredient information and import that information into the system.

[0106] "Calculation means" refers to a processor that has the function of recording input food information and calculating its expiration date.

[0107] A "recipe generation method" is an algorithm or processing system that creates the most suitable cooking plan for the user based on stored ingredient information.

[0108] "Information notification means" refers to a device or method that provides the user with information on the generated cooking plan and expiration date.

[0109] "Generative AI model means" refers to a model that uses machine learning algorithms to generate cooking suggestions that take into account the user's preferences and past consumption data.

[0110] "Online data connection means" refers to a data linkage function that automatically and seamlessly imports food ingredient information from e-commerce platforms.

[0111] This invention is a system for efficiently managing information on food products purchased by consumers and reducing food waste.

[0112] User actions

[0113] After purchasing groceries, users either enter the information through an application on their device or import it from an e-commerce platform using an online data connection. This information includes the name of the food item, purchase date, quantity, and expiration date.

[0114] Device functions

[0115] The terminal receives ingredient information entered or imported by the user and sends it to the server. It also provides the user with optimal cooking suggestions and expiration date notifications sent from the server. The user can use the terminal to check these notifications and take appropriate action.

[0116] Server Processing

[0117] The server stores ingredient information sent from the terminal and calculates the expiration date using a computational method. Furthermore, by using a generative AI model, it considers the user's past consumption data and preferences to generate optimal cooking suggestions. This generation is done using Python, and the AI ​​model is implemented using Tensorflow® and PyTorch. In addition, Google FI® rebase is used as a database to efficiently store and manage the data.

[0118] Specific examples and prompt statements

[0119] For example, if a user purchases "tomatoes," "chicken," and "pasta" online, that information is automatically registered in the app, and a simple pasta recipe using tomatoes is suggested based on the expiration dates. An example of a prompt used in the generating AI model would be, "Considering the user's preferences and the ingredients purchased, please suggest a recipe suitable for tonight's dinner." In this way, users can use their ingredients efficiently and without waste.

[0120] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0121] Step 1:

[0122] Users enter food information using an application on their device or import food information from an e-commerce platform via an online data connection. The information entered includes the name of the food item, purchase date, quantity, and expiration date. This data is stored on the device.

[0123] Step 2:

[0124] The terminal sends the food information received from the user to the server. The transmitted data includes the name of each food item, the date of purchase, the quantity, and the expiration date. This allows the server to aggregate all food information owned by the user.

[0125] Step 3:

[0126] The server stores the received food information in a Google® Firebase database. Based on the stored data, a calculation tool calculates the expiration date. As a result, the calculated expiration date is added to each data entry and used as the basis for notifications.

[0127] Step 4:

[0128] The server uses a generative AI model based on stored ingredient information and expiration dates to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This algorithm uses TensorFlow and PyTorch models implemented in a Python environment. The generated recipe suggestions are output as prompts for the user to see.

[0129] Step 5:

[0130] The server sends the generated cooking suggestion and expiration date notification to the terminal. The terminal displays this information in a user-friendly format. For example, it might display a notification such as "Simple pasta recipe using tomatoes" and "Tomatoes expire in 3 days."

[0131] Step 6:

[0132] Users check the information notified via their devices and use the cooking suggestions to efficiently utilize ingredients. By checking recipes and taking actions to reduce food waste, users contribute to the environment.

[0133] 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.

[0134] The system incorporating the emotion engine in this invention provides a personalized experience by applying emotion recognition technology to support users in managing their ingredients and reducing food waste.

[0135] User-side embodiment

[0136] Users input ingredient information using an application on their device. During this process, the device's camera and microphone collect information about the user's emotions through their voice and facial expressions. Users can also review suggested cooking methods and notifications displayed on the device and make selections based on their feelings and preferences. Furthermore, they can receive personalized plans tailored to their stress levels and health status, and follow those plans to maintain a healthy diet.

[0137] Terminal-side embodiment

[0138] The device collects ingredient information and emotional data entered by the user and sends it to the server. Emotional data, in particular, is continuously analyzed in real time by an emotion engine. The interface on the device adjusts according to changes in emotions, improving the user experience. Furthermore, received cooking suggestions and shopping lists are displayed to the user as optimal content based on the emotional information.

[0139] Server-side embodiment

[0140] The server integrates ingredient information and emotional data transmitted from the terminal and stores it in a database. The emotional engine analyzes this data and generates cooking suggestions best suited to the user's current emotional state. For example, if the emotional engine determines that the user's stress level is high, it will provide a recipe using foods with relaxing effects. It will also generate a shopping list of ingredients that need to be purchased. This makes it a program that promotes the user's health.

[0141] For example, if a user enters "I'm tired today," the emotion engine analyzes that emotion and suggests a simple, relaxing recipe like "herbal tea and a simple sandwich." If the user is feeling uplifted, it recommends a new, challenging recipe to enrich the user's cooking experience.

[0142] Through the embodiments described above, the system of the present invention realizes dietary support that takes into account the individual emotional state of the user. This system reduces food waste and contributes to a sustainable lifestyle by promoting personalized food management and consumption according to the user's preferences and health condition.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] The user launches the application on their device and begins entering information about the ingredients. As they enter the name, quantity, and purchase date of the ingredients, the device's camera and microphone simultaneously capture the user's facial expressions and voice.

[0146] Step 2:

[0147] The terminal formats the ingredient information entered by the user and sends it to the server along with sentiment data. A secure communication protocol is used for transmission.

[0148] Step 3:

[0149] The server matches the received food information with emotional data and stores it in a database. In addition, the emotion engine analyzes the user's emotional state and identifies stress levels and positive / negative emotions.

[0150] Step 4:

[0151] The server generates optimal cooking suggestions based on analyzed emotional data. For example, if the user is seeking relaxation, the server will suggest menu items with relaxing effects, such as lavender tea.

[0152] Step 5:

[0153] The server sends the generated cooking plan and expiration date information to the terminal. It also simultaneously generates and sends a purchase list tailored to the user's emotional state.

[0154] Step 6:

[0155] The device visually displays received cooking suggestions, expiration date notifications, and shopping lists to the user. This includes emotionally responsive interface design changes.

[0156] Step 7:

[0157] The user checks the information displayed on the device and begins cooking using the ingredients. They can also use the shopping list to consider procuring new ingredients.

[0158] Step 8:

[0159] The server continuously monitors food consumption data and emotional changes, calculates and analyzes the environmental contribution based on food waste reduction, and reports it to the user periodically.

[0160] (Example 2)

[0161] 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".

[0162] This invention aims to efficiently support users in managing their ingredients and reducing food waste, while providing a personalized experience that responds to their emotions. Conventional systems suggest ingredients and recipes without considering the user's emotions, making it difficult to improve the accuracy of suggestions and user satisfaction. Furthermore, there is a need to simultaneously achieve the seemingly contradictory goals of reducing food waste and promoting user health.

[0163] 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.

[0164] In this invention, the server includes means for providing a user interface for inputting ingredient information and emotional information; data storage means including a processor for storing the input ingredient information and emotional information, calculating the expiration date, and analyzing the emotional data; generation means for generating an optimal cooking suggestion based on the stored ingredient information and emotional information; notification means for outputting the generated cooking suggestion and expiration date notification to the user; and adjustment means for dynamically adjusting the user interface based on the user's emotions. This enables personalized ingredient management and cooking suggestions that respond to the user's emotions, efficiently achieving both food waste reduction and health promotion.

[0165] "Ingredient information" refers to data that includes the name, quantity, expiration date, and other related information of the ingredients.

[0166] "Emotional information" refers to data that represents the user's emotional state at any given time, collected from the user's voice, facial expressions, and other sources.

[0167] "User interface" refers to the system's operating screen and input methods for users to input information about ingredients and emotions.

[0168] "Data storage means" refers to means for securely storing food ingredient information and emotional information, and managing them in a format that can be accessed as needed.

[0169] A "generation method" is a process that has the function of automatically creating cooking suggestions that meet the user's needs based on stored data.

[0170] A "notification method" is an output function that provides users with information such as cooking suggestions and expiration dates.

[0171] "Adjustment mechanisms" refer to functions that change the interface design and usability based on the user's emotional state, thereby providing a more comfortable user experience.

[0172] The present invention is a technology that uses emotional information to personalize user ingredient management and food waste reduction. This system exchanges information between a terminal and a server to provide the user with the optimal experience.

[0173] First, users can input ingredient information using a dedicated application installed on their device. Input is done in various ways, including keyboard, voice input, and image recognition using a camera. Emotional information is also collected simultaneously through the user's facial expressions and voice. The hardware used includes cameras, microphones, and sensors. This allows the user's emotional state to be analyzed in real time and transmitted to the server.

[0174] The server integrates received ingredient information and emotional data and records it in a database for data storage. Using a generative AI model, the server generates cooking suggestions that maximize the use of ingredient information, based on the user's emotional state. This generative AI model runs on a workstation and selects the most suitable suggestion from a vast and diverse range of cooking options, based on the user's current emotional state.

[0175] For example, if a user enters "I'm tired today," the server uses an emotion recognition engine to analyze the user's state and suggests a relaxing recipe like "herbal tea and a simple sandwich." The system also automatically generates a shopping list based on missing ingredients, helping users easily replenish their supplies.

[0176] As a concrete example of how this system works, the prompt "Based on the user's emotional data, suggest a recipe for a dish that should be suggested when the user is under high stress" is input to the generating AI model, and the AI ​​determines the suggested recipe.

[0177] The system of the present invention simultaneously reduces food waste and promotes user health by effectively utilizing ingredients and presenting cooking suggestions that are flexibly adjusted according to the user's emotions.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user launches the application on the device and enters information about the ingredients. Specifically, the user enters the name of the ingredient using the keyboard or scans the barcode of the ingredient using the camera function. It is also possible to dictate the information using voice input. During input, the device's camera and microphone record the user's facial expressions and voice, simultaneously collecting emotional information. The entered ingredient information and emotional information are stored on the device and used in the next step.

[0181] Step 2:

[0182] The terminal processes the collected food ingredient information and emotional data and sends it to the server. Specifically, it securely transfers the data using data encryption technology. The server stores the received data in a database. In this process, the food ingredient information is organized and the emotional data is preprocessed, transforming the information into a format that can be used efficiently.

[0183] Step 3:

[0184] The server uses a generative AI model to generate cooking suggestions based on ingredient information and emotional information. Specifically, the generative AI model selects from a vast database of recipes and suggests the recipe best suited to the user's current emotional state. For example, if the server determines that the user is tired, a menu with relaxing effects will be selected. The generated cooking suggestions are then finalized on the server and prepared for the next step.

[0185] Step 4:

[0186] The server sends the generated cooking suggestion and a shopping list of necessary ingredients to the device. Specifically, the server lists the ingredients the user needs to obtain along with the recommended recipe and sends this as a push notification to the device. This notification allows the user to make their selection in the next step.

[0187] Step 5:

[0188] The device notifies the user of received cooking suggestions and shopping lists, allowing the user to make selections. The user can review the suggested recipes and choose the one that best suits their current situation and preferences. The user interface dynamically changes according to their emotions; for example, a clearer and calming interface is provided when the user is under high stress.

[0189] Step 6:

[0190] After cooking according to the recipe, the user enters feedback into their device. Specifically, the user records the ingredients they actually used and their satisfaction with the recipe in the app. The device then sends this feedback back to the server, and the system uses this feedback to improve future suggestions and enhance the user experience.

[0191] (Application Example 2)

[0192] 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."

[0193] Current food management systems are unable to provide personalized meal suggestions that adapt to users' emotions and health conditions, making it difficult to improve user satisfaction. Similarly, food delivery services struggle to offer meal options that consider individual user preferences, failing to deliver the dining experience users desire. Furthermore, there is a growing need to effectively reduce food waste and demonstrate concrete contributions to the environment.

[0194] 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.

[0195] In this invention, the server includes means for providing a human interface for inputting ingredient information, storage means including an information processing device for storing the input ingredient information and calculating the expiration date, generation means for generating an optimal cooking suggestion based on the stored ingredient information and the user's emotional information, communication means for outputting the optimal cooking suggestion and expiration date notification to the user, and analysis means for detecting the user's emotional information and adjusting the suggested content based on it. This makes it possible to concretely demonstrate the provision of meal suggestions tailored to the user's emotions, the reduction of food waste, and contributions to the environment.

[0196] "Food ingredient information" refers to data that users input through a human interface, such as the name, quantity, and expiration date of food items.

[0197] A "human interface" is an interactive system that allows users to input information into a system, and it is a means of exchanging information with other users through screens, keyboards, touch displays, etc.

[0198] An "information processing device" is a device or system that performs various calculations based on input data, such as calculating expiration dates.

[0199] A "storage method" is a structure or device for recording input data and retrieving it for later use.

[0200] "Generating means" refers to a process or apparatus that creates new information, specifically cooking ideas, based on stored data.

[0201] A "means of communication" refers to a system or device that effectively conveys generated information or notifications to the user.

[0202] "Analysis means" refers to a method or system for analyzing information about a user's emotional state and making appropriate adjustments based on the results of that analysis.

[0203] "Emotional information" refers to data that indicates the user's psychological state, and is collected from things like facial expressions and tone of voice.

[0204] The system that implements this application works when a user uses a food delivery application on their smartphone. The application uses the smartphone's camera and microphone to capture the user's facial expressions and voice data. When the user launches the application, the device collects this data and analyzes the emotional data in real time using an emotion recognition engine (Emotion SDK).

[0205] The analyzed sentiment data is sent to the server via an API built with Node.js on the backend. The server uses a database system such as MySQL® to integrate past food history data with current sentiment data and generate a menu optimized for the user. The generated menu is adjusted based on the user's sentiment state and presented to the user via a frontend application developed with React Native.

[0206] For example, if a user expresses a desire to "enjoy a movie in a calm mood," the server can suggest a "relaxing tea and light snack menu." This process allows users to choose a meal that suits their mood and state, resulting in a more satisfying experience.

[0207] An example of a prompt that utilizes emotional data through a generative AI model is: "Consider the user's emotional state and suggest a dinner menu that best suits their mood at the time. If the user is highly fatigued, prioritize menus that can replenish energy." This prompt aims to provide personalized suggestions based on the user's individual state.

[0208] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0209] Step 1:

[0210] The user launches a food delivery application. This activates the smartphone's camera and microphone, setting up an environment for collecting the user's facial expressions and voice. When the user proceeds to the menu screen, this data is collected in real time. The input consists of image data and audio data captured through the camera and microphone.

[0211] Step 2:

[0212] The device sends collected image and audio data to the Emotion SDK for emotion recognition. The emotion recognition engine uses image and audio analysis to estimate the user's emotional state and quantify it. For example, it might be expressed as "70% happiness, 30% fatigue." The output is numerical data indicating the user's emotional state.

[0213] Step 3:

[0214] The device sends estimated emotion data to the backend API. The server retrieves the received emotion state data and the user's eating history data from a MySQL database and integrates them. Based on the integration results, a dataset is generated using Node.js. The input is emotion data and eating history data, and the output is the integrated dataset.

[0215] Step 4:

[0216] The server uses a generative AI model based on the generated dataset to create menus that respond to the user's emotions. The provided prompt text is input into the generative AI model, which generates a menu that suggests the most suitable meal for the user. For example, if the user's "happiness level" is high, a menu suggesting a new experience will be suggested. The output is a list of suggested menus.

[0217] Step 5:

[0218] The server generates menu suggestions and sends them to the user's device, where the user reviews them in the frontend application. Using a React Native interface, the user is presented with menu suggestions and can choose from the options. Once the selected menu is confirmed, the process proceeds to place the order. The input is a list of menu suggestions, and the output is the menu selected by the user.

[0219] 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.

[0220] 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.

[0221] 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.

[0222] [Second Embodiment]

[0223] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0224] 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.

[0225] 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).

[0226] 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.

[0227] 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.

[0228] 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).

[0229] 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.

[0230] 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.

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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".

[0235] The embodiments for carrying out the present invention will be described by dividing them into three elements: user, terminal, and server.

[0236] User-side embodiment

[0237] First, after purchasing ingredients, the user opens the application on their device and enters the ingredient information. This information includes the name of the food, purchase date, quantity, and expiration date. This information is processed appropriately on the device, as described below, and then sent to the server. The user also periodically checks the device for optimal cooking suggestions and expiration date information to ensure proper use of the ingredients. Furthermore, the user can prevent waste by referring to the purchase list displayed on the device and purchasing only what is needed.

[0238] Terminal-side embodiment

[0239] The terminal has the function of receiving ingredient information entered by the user and sending it to the server. It also displays the optimal cooking suggestion and expiration date notifications received from the server to the user in an easy-to-understand manner. For example, if ingredient information such as "Tomato, Purchase date: October 1, 2023, Expiration date: October 7, 2023" is entered into the terminal, that information is immediately sent to the server, and necessary notifications are sent to the user as they occur.

[0240] Server-side embodiment

[0241] The server receives ingredient information sent from the terminal and stores it in a database. Based on this information, it calculates the expiration date of the ingredients and prepares to notify the user. Furthermore, the server uses an AI algorithm to generate optimal cooking suggestions to maximize the use of the currently available ingredients. These cooking suggestions are sent to the terminal and provided to the user. In addition, based on the user's ingredient consumption data, the server calculates the effect of reducing food waste as a contribution to the environment and provides feedback. In this way, the server plays a central role in data processing and provides various information in a format that makes it easy for users to take actual action.

[0242] This "mode for carrying out the invention" allows the present invention to efficiently support consumers in reducing food waste and promote environmental contributions.

[0243] The following describes the processing flow.

[0244] Step 1:

[0245] The user enters information about the purchased groceries into the application on their device. Specifically, they specify the name of the groceries, the purchase date, and the quantity, and then press the submit button.

[0246] Step 2:

[0247] The terminal formats the entered ingredient information into JSON format and prepares it for transmission to the server. Here, it checks the validity of the data and converts it into a format for communication with the server.

[0248] Step 3:

[0249] The server stores the ingredient information received from the terminal into a database. Before saving, it verifies that the data format is correct and inserts it into the database using an SQL query.

[0250] Step 4:

[0251] The server calculates the expiration date for stored food items and sets a notification schedule. This process calculates the expiration date and prepares a trigger to send a notification at the specified date and time.

[0252] Step 5:

[0253] The server uses AI to generate optimal cooking suggestions based on the user's inventory data. Specifically, it feeds the ingredient list to an AI algorithm to create recipe suggestions and cooking plans.

[0254] Step 6:

[0255] The server sends the generated cooking suggestions and expiration date information to the user's device. An API is used for transmission, appropriately packaging the data before sending it to the device.

[0256] Step 7:

[0257] The device displays notifications and suggestions from the server to the user. Specifically, it displays cooking suggestions and alerts about food items nearing their expiration date on the device's screen.

[0258] Step 8:

[0259] Users take necessary actions based on the information presented by their device. For example, they might prioritize cooking ingredients that are nearing their expiration date, or check their shopping list to help with their shopping.

[0260] (Example 1)

[0261] 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."

[0262] Efficient management and waste reduction are crucial issues in food consumption. However, individual food management by consumers is time-consuming and labor-intensive, and food waste due to expired products is common. These problems also increase unnecessary environmental impacts. Therefore, there is a need for systems that efficiently manage, manage, and consume food to reduce food waste.

[0263] 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.

[0264] In this invention, the server includes an information input / output device for users to input information, an information management means including a calculation device for storing the input information and calculating the period, and a generation device for generating an optimal plan based on the stored information. This enables consumers to efficiently manage and cook ingredients and reduce food waste.

[0265] An "information input / output device for users to input information" is a device that provides an interface for users to input arbitrary information.

[0266] "Information management means including a calculation device for storing input information and calculating a period" refers to a device that records information entered by a user and has a calculation function for calculating a period associated with that information.

[0267] A "generating device that generates optimal proposals based on stored information" is a device that analyzes information recorded in a database and creates the best possible proposal based on the results of that analysis.

[0268] A "notification device that outputs notifications of the optimal plan and timeframe" is a device that appropriately reports the calculated timeframe and generated plan to the user.

[0269] "Information display means for displaying generated proposals" refers to a device for visually showing the proposals created by the generation device to the user.

[0270] A "device that automatically generates lists" is a device that automatically creates a list of newly required items based on stored information and utilizing that information.

[0271] A "device for calculating and displaying the impact based on reductions" is a device that measures the effect of reductions achieved by a specific activity and informs the user of the results.

[0272] This invention is a system that has three elements: a user, a terminal, and a server, and promotes the efficient management and consumption of food. The specific configuration and operation are described below.

[0273] User-side embodiment

[0274] Users use an application installed on their device to manage information about food they have purchased. First, users enter information such as the name of the food item, purchase date, quantity, and expiration date. This data forms the basis for efficient management. Users periodically check their device and refer to cooking suggestions and expiration date information provided by the server. This allows users to minimize waste.

[0275] Terminal-side embodiment

[0276] The device receives information entered by the user and sends it to the server. A standard smartphone or tablet is used for this purpose. The received data is temporarily stored but is transferred to the server as it is received. The device also serves to provide notifications from the server to the user. Specifically, it displays information on ingredients nearing their expiration date and cooking suggestions on the device screen.

[0277] Server-side embodiment

[0278] The server receives ingredient information sent from the terminal and stores it in a database. This process uses a database management system based on SQL. The server utilizes the stored data and generates optimal cooking suggestions using an AI algorithm. At the heart of this system is a generative AI model. The server enhances its contribution to the environment by calculating expiration dates, evaluating food waste reduction, and generating feedback for the user.

[0279] Specific example

[0280] When a user enters ingredient information into their device, such as "Tomatoes, Purchase Date: October 1, 2023, Expiration Date: October 7, 2023," that information is sent to the server. The server takes the expiration date into consideration and suggests "Tomato Sauce Pasta" as an example of a dish using tomatoes.

[0281] Example of a prompt

[0282] "Purchased ingredients: chicken, tomatoes. Please suggest a cooking method."

[0283] In this way, the system provides functions that fully support users in efficiently utilizing ingredients.

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] The user inputs food ingredient information into the application on the terminal. The input items include the name of the food ingredient, purchase date, quantity, and expiration date. This information is provided by the user and temporarily stored as digital data by the terminal. This data is transmitted to the server in the next step.

[0287] Step 2:

[0288] The terminal transmits the stored food ingredient information to the server. Network communication (e.g., Wi-Fi or mobile data communication) is used for this transmission operation. The data to be transmitted is the entire information related to each food ingredient and is in the form output from the terminal.

[0289] Step 3:

[0290] The server receives the data transmitted from the terminal and stores it in the database. Based on the input information, the server calculates the expiration date for each food ingredient. In this calculation process, the number of days from the purchase date to the expiration date is calculated, and the number of days until the expiration date is obtained as the output.

[0291] Step 4:

[0292] The server generates an optimal cooking plan using the AI model generated based on the stored information. By incorporating the food ingredient information into the prompt text and inputting it into the AI model, a cooking plan for maximizing the utilization of the food ingredients is generated. This generated plan is obtained as the output.

[0293] Step 5:

[0294] The server notifies the device of the calculated expiration date and generated cooking suggestions. These notifications are sent to the device as push notifications or in-app notifications. This allows the user to receive instructions on how to use ingredients efficiently.

[0295] Step 6:

[0296] The terminal displays instructions received from the server to the user. A visual interface is used for the display, and the information is organized so that the user can easily understand it. This interface highlights ingredients nearing their expiration date and optimal cooking suggestions.

[0297] Step 7:

[0298] Based on the information displayed on the device, users take actions to prevent food waste by cooking and consuming food appropriately. Ultimately, the user's actions based on the information become the output, resulting in the effective use of ingredients.

[0299] (Application Example 1)

[0300] 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."

[0301] Modern consumers are expected to manage their food efficiently and reduce waste. However, keeping track of ingredients, managing expiration dates, and choosing cooking methods that suit their preferences are troublesome and contribute to food loss. A solution to this problem is needed.

[0302] 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.

[0303] In this invention, the server includes a calculation means for storing food ingredient information and calculating the expiration date, a recipe generation means for generating an optimal cooking plan based on the stored information, a generation AI model means considering the user's preferences and past consumption data, and an online data connection means for data linking with an e-commerce site. As a result, consumers can efficiently manage food ingredients while saving the trouble of input, and reduce food waste.

[0304] "Food ingredient information" refers to details such as the name, quantity, purchase date, and expiration date of the food purchased by the consumer.

[0305] "Data reception means" is a method that provides an interface for the user to input food ingredient information and import the information into the system.

[0306] "Calculation means" refers to a processor that has the function of recording the input food ingredient information and calculating its expiration date.

[0307] "Recipe generation means" is an algorithm or processing system that creates an optimal cooking plan for the user based on the stored food ingredient information.

[0308] "Information notification means" refers to a device or method that provides the generated cooking plan and notice of the expiration date to the user.

[0309] "Generation AI model means" refers to a model that uses machine learning algorithms to generate cooking plans considering the user's preferences and past consumption data.

[0310] "Online data connection means" refers to a data linking function for automatically and seamlessly importing food ingredient information from an e-commerce platform.

[0311] This invention is a system for efficiently managing information on food ingredients purchased by consumers and reducing food waste.

[0312] User operation

[0313] After purchasing groceries, users either enter the information through an application on their device or import it from an e-commerce platform using an online data connection. This information includes the name of the food item, the date of purchase, the quantity, and the expiration date.

[0314] Device functions

[0315] The terminal receives ingredient information entered or imported by the user and sends it to the server. It also provides the user with optimal cooking suggestions and expiration date notifications sent from the server. The user can use the terminal to check these notifications and take appropriate action.

[0316] Server Processing

[0317] The server stores ingredient information sent from the terminal and calculates the expiration date using a computational method. Furthermore, it uses a generative AI model to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This generation process uses Python, implementing the AI ​​model with tools such as TensorFlow and PyTorch. Google Firebase is used as the database to efficiently store and manage the data.

[0318] Specific examples and prompt statements

[0319] For example, if a user purchases "tomatoes," "chicken," and "pasta" online, that information is automatically registered in the app, and a simple pasta recipe using tomatoes is suggested based on the expiration dates. An example of a prompt used in the generating AI model would be, "Considering the user's preferences and the ingredients purchased, please suggest a recipe suitable for tonight's dinner." In this way, users can use their ingredients efficiently and without waste.

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] Users enter food information using an application on their device or import food information from an e-commerce platform via an online data connection. The information entered includes the name of the food item, purchase date, quantity, and expiration date. This data is stored on the device.

[0323] Step 2:

[0324] The terminal sends the food information received from the user to the server. The transmitted data includes the name of each food item, the date of purchase, the quantity, and the expiration date. This allows the server to aggregate all food information owned by the user.

[0325] Step 3:

[0326] The server stores the received food information in a Google Firebase database. Based on the stored data, a calculation tool calculates the expiration date. As a result, the calculated expiration date is added to each data entry and used as the basis for notifications.

[0327] Step 4:

[0328] The server uses a generative AI model based on stored ingredient information and expiration dates to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This algorithm uses TensorFlow and PyTorch models implemented in a Python environment. The generated recipe suggestions are output as prompts for the user to see.

[0329] Step 5:

[0330] The server sends the generated cooking suggestion and expiration date notification to the terminal. The terminal displays this information in a user-friendly format. For example, it might display a notification such as "Simple pasta recipe using tomatoes" and "Tomatoes expire in 3 days."

[0331] Step 6:

[0332] Users check the information notified via their devices and use the cooking suggestions to efficiently utilize ingredients. By checking recipes and taking actions to reduce food waste, users contribute to the environment.

[0333] 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.

[0334] The system incorporating the emotion engine in this invention provides a personalized experience by applying emotion recognition technology to support users in managing their ingredients and reducing food waste.

[0335] User-side embodiment

[0336] Users input ingredient information using an application on their device. During this process, the device's camera and microphone collect information about the user's emotions through their voice and facial expressions. Users can also review suggested cooking methods and notifications displayed on the device and make selections based on their feelings and preferences. Furthermore, they can receive personalized plans tailored to their stress levels and health status, and follow those plans to maintain a healthy diet.

[0337] Terminal-side embodiment

[0338] The device collects ingredient information and emotional data entered by the user and sends it to the server. Emotional data, in particular, is continuously analyzed in real time by an emotion engine. The interface on the device adjusts according to changes in emotions, improving the user experience. Furthermore, received cooking suggestions and shopping lists are displayed to the user as optimal content based on the emotional information.

[0339] Server-side embodiment

[0340] The server integrates ingredient information and emotional data transmitted from the terminal and stores it in a database. The emotional engine analyzes this data and generates cooking suggestions best suited to the user's current emotional state. For example, if the emotional engine determines that the user's stress level is high, it will provide a recipe using foods with relaxing effects. It will also generate a shopping list of ingredients that need to be purchased. This makes it a program that promotes the user's health.

[0341] For example, if a user enters "I'm tired today," the emotion engine analyzes that emotion and suggests a simple, relaxing recipe like "herbal tea and a simple sandwich." If the user is feeling uplifted, it recommends a new, challenging recipe to enrich the user's cooking experience.

[0342] Through the embodiments described above, the system of the present invention realizes dietary support that takes into account the individual emotional state of the user. This system reduces food waste and contributes to a sustainable lifestyle by promoting personalized food management and consumption according to the user's preferences and health condition.

[0343] The following describes the processing flow.

[0344] Step 1:

[0345] The user launches the application on their device and begins entering information about the ingredients. As they enter the name, quantity, and purchase date of the ingredients, the device's camera and microphone simultaneously capture the user's facial expressions and voice.

[0346] Step 2:

[0347] The terminal formats the ingredient information entered by the user and sends it to the server along with sentiment data. A secure communication protocol is used for transmission.

[0348] Step 3:

[0349] The server matches the received food information with emotional data and stores it in a database. In addition, the emotion engine analyzes the user's emotional state and identifies stress levels and positive / negative emotions.

[0350] Step 4:

[0351] The server generates optimal cooking suggestions based on analyzed emotional data. For example, if the user is seeking relaxation, the server will suggest menu items with relaxing effects, such as lavender tea.

[0352] Step 5:

[0353] The server sends the generated cooking plan and expiration date information to the terminal. It also simultaneously generates and sends a purchase list tailored to the user's emotional state.

[0354] Step 6:

[0355] The device visually displays received cooking suggestions, expiration date notifications, and shopping lists to the user. This includes emotionally responsive interface design changes.

[0356] Step 7:

[0357] The user checks the information displayed on the device and begins cooking using the ingredients. They can also use the shopping list to consider procuring new ingredients.

[0358] Step 8:

[0359] The server continuously monitors food consumption data and emotional changes, calculates and analyzes the environmental contribution based on food waste reduction, and reports it to the user periodically.

[0360] (Example 2)

[0361] 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".

[0362] This invention aims to efficiently support users in managing their ingredients and reducing food waste, while providing a personalized experience that responds to their emotions. Conventional systems suggest ingredients and recipes without considering the user's emotions, making it difficult to improve the accuracy of suggestions and user satisfaction. Furthermore, there is a need to simultaneously achieve the seemingly contradictory goals of reducing food waste and promoting user health.

[0363] 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.

[0364] In this invention, the server includes means for providing a user interface for inputting ingredient information and emotional information; data storage means including a processor for storing the input ingredient information and emotional information, calculating the expiration date, and analyzing the emotional data; generation means for generating an optimal cooking suggestion based on the stored ingredient information and emotional information; notification means for outputting the generated cooking suggestion and expiration date notification to the user; and adjustment means for dynamically adjusting the user interface based on the user's emotions. This enables personalized ingredient management and cooking suggestions that respond to the user's emotions, efficiently achieving both food waste reduction and health promotion.

[0365] "Ingredient information" refers to data that includes the name, quantity, expiration date, and other related information of the ingredients.

[0366] "Emotional information" refers to data that represents the user's emotional state at any given time, collected from the user's voice, facial expressions, and other sources.

[0367] "User interface" refers to the system's operating screen and input methods for users to input information about ingredients and emotions.

[0368] "Data storage means" refers to means for securely storing food ingredient information and emotional information, and managing them in a format that can be accessed as needed.

[0369] A "generation method" is a process that has the function of automatically creating cooking suggestions that meet the user's needs based on stored data.

[0370] A "notification method" is an output function that provides users with information such as cooking suggestions and expiration dates.

[0371] "Adjustment mechanisms" refer to functions that change the interface design and usability based on the user's emotional state, thereby providing a more comfortable user experience.

[0372] The present invention is a technology that uses emotional information to personalize user food management and food waste reduction. This system exchanges information between a terminal and a server to provide the user with the optimal experience.

[0373] First, users can input ingredient information using a dedicated application installed on their device. Input is done in various ways, including keyboard, voice input, and image recognition using a camera. Emotional information is also collected simultaneously through the user's facial expressions and voice. The hardware used includes cameras, microphones, and sensors. This allows the user's emotional state to be analyzed in real time and transmitted to the server.

[0374] The server integrates received ingredient information and emotional data and records it in a database for data storage. Using a generative AI model, the server generates cooking suggestions that maximize the use of ingredient information, based on the user's emotional state. This generative AI model runs on a workstation and selects the most suitable suggestion from a vast and diverse range of cooking options, based on the user's current emotional state.

[0375] For example, if a user enters "I'm tired today," the server uses an emotion recognition engine to analyze the user's state and suggests a relaxing recipe like "herbal tea and a simple sandwich." The system also automatically generates a shopping list based on missing ingredients, helping users easily replenish their supplies.

[0376] As a concrete example of how this system works, the prompt "Based on the user's emotional data, suggest a recipe for a dish that should be suggested when the user is under high stress" is input to the generating AI model, and the AI ​​determines the suggested recipe.

[0377] The system of the present invention simultaneously reduces food waste and promotes user health by effectively utilizing ingredients and presenting cooking suggestions that are flexibly adjusted according to the user's emotions.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The user launches the application on the device and enters information about the ingredients. Specifically, the user enters the name of the ingredient using the keyboard or scans the barcode of the ingredient using the camera function. It is also possible to dictate the information using voice input. During input, the device's camera and microphone record the user's facial expressions and voice, simultaneously collecting emotional information. The entered ingredient information and emotional information are stored on the device and used in the next step.

[0381] Step 2:

[0382] The terminal processes the collected food ingredient information and emotional data and sends it to the server. Specifically, it securely transfers the data using data encryption technology. The server stores the received data in a database. In this process, the food ingredient information is organized and the emotional data is preprocessed, transforming the information into a format that can be used efficiently.

[0383] Step 3:

[0384] The server uses a generative AI model to generate cooking suggestions based on ingredient information and emotional information. Specifically, the generative AI model selects from a vast database of recipes and suggests the recipe best suited to the user's current emotional state. For example, if the server determines that the user is tired, a menu with relaxing effects will be selected. The generated cooking suggestions are then finalized on the server and prepared for the next step.

[0385] Step 4:

[0386] The server sends the generated cooking suggestion and a shopping list of necessary ingredients to the device. Specifically, the server lists the ingredients the user needs to obtain along with the recommended recipe and sends this as a push notification to the device. This notification allows the user to make their selection in the next step.

[0387] Step 5:

[0388] The device notifies the user of received cooking suggestions and shopping lists, allowing the user to make selections. The user can review the suggested recipes and choose the one that best suits their current situation and preferences. The user interface dynamically changes according to their emotions; for example, a clearer and calming interface is provided when the user is under high stress.

[0389] Step 6:

[0390] After cooking according to the recipe, the user enters feedback into their device. Specifically, the user records the ingredients they actually used and their satisfaction with the recipe in the app. The device then sends this feedback back to the server, and the system uses this feedback to improve future suggestions and enhance the user experience.

[0391] (Application Example 2)

[0392] 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 as the "terminal".

[0393] Current food management systems are unable to provide personalized meal suggestions that adapt to users' emotions and health conditions, making it difficult to improve user satisfaction. Similarly, food delivery services struggle to offer meal options that consider individual user preferences, failing to deliver the dining experience users desire. Furthermore, there is a growing need to effectively reduce food waste and demonstrate concrete contributions to the environment.

[0394] 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.

[0395] In this invention, the server includes means for providing a human interface for inputting ingredient information, storage means including an information processing device for storing the input ingredient information and calculating the expiration date, generation means for generating an optimal cooking suggestion based on the stored ingredient information and the user's emotional information, communication means for outputting the optimal cooking suggestion and expiration date notification to the user, and analysis means for detecting the user's emotional information and adjusting the suggested content based on it. This makes it possible to concretely demonstrate the provision of meal suggestions tailored to the user's emotions, the reduction of food waste, and contributions to the environment.

[0396] "Food ingredient information" refers to data that users input through a human interface, such as the name, quantity, and expiration date of food items.

[0397] A "human interface" is an interactive system that allows users to input information into a system, and it is a means of exchanging information with other users through screens, keyboards, touch displays, etc.

[0398] An "information processing device" is a device or system that performs various calculations based on input data, such as calculating expiration dates.

[0399] A "storage method" is a structure or device for recording input data and retrieving it for later use.

[0400] "Generating means" refers to a process or apparatus that creates new information, specifically cooking ideas, based on stored data.

[0401] A "means of communication" refers to a system or device that effectively conveys generated information or notifications to the user.

[0402] "Analysis means" refers to a method or system for analyzing information about a user's emotional state and making appropriate adjustments based on the results of that analysis.

[0403] "Emotional information" refers to data that indicates the user's psychological state, and is collected from things like facial expressions and tone of voice.

[0404] The system that implements this application works when a user uses a food delivery application on their smartphone. The application uses the smartphone's camera and microphone to capture the user's facial expressions and voice data. When the user launches the application, the device collects this data and analyzes the emotional data in real time using an emotion recognition engine (Emotion SDK).

[0405] The analyzed sentiment data is sent to the server via an API built with Node.js on the backend. The server uses a database system such as MySQL to integrate past food history data with current sentiment data and generate a menu optimized for the user. The generated menu is adjusted based on the user's sentiment state and presented to the user via a frontend application developed with React Native.

[0406] For example, if a user expresses a desire to "enjoy a movie in a calm mood," the server can suggest a "relaxing tea and light snack menu." This process allows users to choose a meal that suits their mood and state, resulting in a more satisfying experience.

[0407] An example of a prompt that utilizes emotional data through a generative AI model is: "Consider the user's emotional state and suggest a dinner menu that best suits their mood at the time. If the user is highly fatigued, prioritize menus that can replenish energy." This prompt aims to provide personalized suggestions based on the user's individual state.

[0408] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0409] Step 1:

[0410] The user launches a food delivery application. This activates the smartphone's camera and microphone, setting up an environment for collecting the user's facial expressions and voice. When the user proceeds to the menu screen, this data is collected in real time. The input consists of image data and audio data captured through the camera and microphone.

[0411] Step 2:

[0412] The device sends collected image and audio data to the Emotion SDK for emotion recognition. The emotion recognition engine uses image and audio analysis to estimate the user's emotional state and quantify it. For example, it might be expressed as "70% happiness, 30% fatigue." The output is numerical data indicating the user's emotional state.

[0413] Step 3:

[0414] The device sends estimated emotion data to the backend API. The server retrieves the received emotion state data and the user's eating history data from a MySQL database and integrates them. Based on the integration results, a dataset is generated using Node.js. The input is emotion data and eating history data, and the output is the integrated dataset.

[0415] Step 4:

[0416] The server uses a generative AI model based on the generated dataset to create menus that respond to the user's emotions. The provided prompt text is input into the generative AI model, which generates a menu that suggests the most suitable meal for the user. For example, if the user's "happiness level" is high, a menu suggesting a new experience will be suggested. The output is a list of suggested menus.

[0417] Step 5:

[0418] The server generates menu suggestions and sends them to the user's device, where the user reviews them in the frontend application. Using a React Native interface, the user is presented with menu suggestions and can choose from the options. Once the selected menu is confirmed, the process proceeds to place the order. The input is a list of menu suggestions, and the output is the menu selected by the user.

[0419] 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.

[0420] 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.

[0421] 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.

[0422] [Third Embodiment]

[0423] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0424] 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.

[0425] 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).

[0426] 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.

[0427] 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.

[0428] 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).

[0429] 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.

[0430] 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.

[0431] 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.

[0432] 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.

[0433] 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.

[0434] 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".

[0435] The embodiments for carrying out the present invention will be described by dividing them into three elements: user, terminal, and server.

[0436] User-side embodiment

[0437] First, after purchasing ingredients, the user opens the application on their device and enters the ingredient information. This information includes the name of the food, purchase date, quantity, and expiration date. This information is processed appropriately on the device, as described below, and then sent to the server. The user also periodically checks the device for optimal cooking suggestions and expiration date information to ensure proper use of the ingredients. Furthermore, the user can prevent waste by referring to the purchase list displayed on the device and purchasing only what is needed.

[0438] Terminal-side embodiment

[0439] The terminal has the function of receiving ingredient information entered by the user and sending it to the server. It also displays the optimal cooking suggestion and expiration date notifications received from the server to the user in an easy-to-understand manner. For example, if ingredient information such as "Tomato, Purchase date: October 1, 2023, Expiration date: October 7, 2023" is entered into the terminal, that information is immediately sent to the server, and necessary notifications are sent to the user as they occur.

[0440] Server-side embodiment

[0441] The server receives ingredient information sent from the terminal and stores it in a database. Based on this information, it calculates the expiration date of the ingredients and prepares to notify the user. Furthermore, the server uses an AI algorithm to generate optimal cooking suggestions to maximize the use of the currently available ingredients. These cooking suggestions are sent to the terminal and provided to the user. In addition, based on the user's ingredient consumption data, the server calculates the effect of reducing food waste as a contribution to the environment and provides feedback. In this way, the server plays a central role in data processing and provides various information in a format that makes it easy for users to take actual action.

[0442] This "mode for carrying out the invention" allows the present invention to efficiently support consumers in reducing food waste and promote environmental contributions.

[0443] The following describes the processing flow.

[0444] Step 1:

[0445] The user enters information about the purchased groceries into the application on their device. Specifically, they specify the name of the groceries, the purchase date, and the quantity, and then press the submit button.

[0446] Step 2:

[0447] The terminal formats the entered ingredient information into JSON format and prepares it for transmission to the server. Here, it checks the validity of the data and converts it into a format for communication with the server.

[0448] Step 3:

[0449] The server stores the ingredient information received from the terminal into a database. Before saving, it verifies that the data format is correct and inserts it into the database using an SQL query.

[0450] Step 4:

[0451] The server calculates the expiration date for stored food items and sets a notification schedule. This process calculates the expiration date and prepares a trigger to send a notification at the specified date and time.

[0452] Step 5:

[0453] The server uses AI to generate optimal cooking suggestions based on the user's inventory data. Specifically, it feeds the ingredient list to an AI algorithm to create recipe suggestions and cooking plans.

[0454] Step 6:

[0455] The server sends the generated cooking suggestions and expiration date information to the user's device. An API is used for transmission, appropriately packaging the data before sending it to the device.

[0456] Step 7:

[0457] The device displays notifications and suggestions from the server to the user. Specifically, it displays cooking suggestions and alerts about food items nearing their expiration date on the device's screen.

[0458] Step 8:

[0459] Users take necessary actions based on the information presented by their device. For example, they might prioritize cooking ingredients that are nearing their expiration date, or check their shopping list to help with their shopping.

[0460] (Example 1)

[0461] 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."

[0462] Efficient management and waste reduction are crucial issues in food consumption. However, individual food management by consumers is time-consuming and labor-intensive, and food waste due to expired products is common. These problems also increase unnecessary environmental impacts. Therefore, there is a need for systems that efficiently manage, manage, and consume food to reduce food waste.

[0463] 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.

[0464] In this invention, the server includes an information input / output device for users to input information, an information management means including a calculation device for storing the input information and calculating the period, and a generation device for generating an optimal plan based on the stored information. This enables consumers to efficiently manage and cook ingredients and reduce food waste.

[0465] An "information input / output device for users to input information" is a device that provides an interface for users to input arbitrary information.

[0466] "Information management means including a calculation device for storing input information and calculating a period" refers to a device that records information entered by a user and has a calculation function for calculating a period associated with that information.

[0467] A "generating device that generates optimal proposals based on stored information" is a device that analyzes information recorded in a database and creates the best possible proposal based on the results of that analysis.

[0468] A "notification device that outputs notifications of the optimal plan and timeframe" is a device that appropriately reports the calculated timeframe and generated plan to the user.

[0469] "Information display means for displaying generated proposals" refers to a device for visually showing the proposals created by the generation device to the user.

[0470] A "device that automatically generates lists" is a device that automatically creates a list of newly required items based on stored information and utilizing that information.

[0471] A "device for calculating and displaying the impact based on reductions" is a device that measures the effect of reductions achieved by a specific activity and informs the user of the results.

[0472] This invention is a system that has three elements: a user, a terminal, and a server, and promotes the efficient management and consumption of food. The specific configuration and operation are described below.

[0473] User-side embodiment

[0474] Users use an application installed on their device to manage information about food they have purchased. First, users enter information such as the name of the food item, purchase date, quantity, and expiration date. This data forms the basis for efficient management. Users periodically check their device and refer to cooking suggestions and expiration date information provided by the server. This allows users to minimize waste.

[0475] Terminal-side embodiment

[0476] The device receives information entered by the user and sends it to the server. A standard smartphone or tablet is used for this purpose. The received data is temporarily stored but is transferred to the server as it is received. The device also serves to provide notifications from the server to the user. Specifically, it displays information on ingredients nearing their expiration date and cooking suggestions on the device screen.

[0477] Server-side embodiment

[0478] The server receives ingredient information sent from the terminal and stores it in a database. This process uses a database management system based on SQL. The server utilizes the stored data and generates optimal cooking suggestions using an AI algorithm. At the heart of this system is a generative AI model. The server enhances its contribution to the environment by calculating expiration dates, evaluating food waste reduction, and generating feedback for the user.

[0479] Specific example

[0480] When a user enters ingredient information into their device, such as "Tomatoes, Purchase Date: October 1, 2023, Expiration Date: October 7, 2023," that information is sent to the server. The server takes the expiration date into consideration and suggests "Tomato Sauce Pasta" as an example of a dish using tomatoes.

[0481] Example of a prompt

[0482] "Purchased ingredients: chicken, tomatoes. Please suggest a cooking method."

[0483] In this way, the system provides functions that fully support users in efficiently utilizing ingredients.

[0484] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0485] Step 1:

[0486] The user enters food information into the application on their device. The input fields include the name of the food item, purchase date, quantity, and expiration date. This information is provided by the user and temporarily stored as digital data on the device. This data is then sent to the server in the next step.

[0487] Step 2:

[0488] The device sends the stored ingredient information to the server. This transmission operation uses network communication (e.g., Wi-Fi or mobile data communication). The transmitted data consists of all the information related to each ingredient and is output from the device.

[0489] Step 3:

[0490] The server receives data sent from the terminal and stores it in a database. Based on the input information, the server calculates the expiration date for each food item. This calculation process calculates the number of days from the purchase date to the expiration date and outputs the number of days remaining until the expiration date.

[0491] Step 4:

[0492] The server generates optimal cooking suggestions using a generative AI model based on stored information. By incorporating ingredient information into prompt messages and inputting it into the AI ​​model, cooking suggestions that maximize the use of ingredients are generated. These generated suggestions are retrieved as output.

[0493] Step 5:

[0494] The server notifies the device of the calculated expiration date and generated cooking suggestions. These notifications are sent to the device as push notifications or in-app notifications. This allows the user to receive instructions on how to use ingredients efficiently.

[0495] Step 6:

[0496] The terminal displays instructions received from the server to the user. A visual interface is used for the display, and the information is organized so that the user can easily understand it. This interface highlights ingredients nearing their expiration date and optimal cooking suggestions.

[0497] Step 7:

[0498] Based on the information displayed on the device, users take actions to prevent food waste by cooking and consuming food appropriately. Ultimately, the user's actions based on the information become the output, resulting in the effective use of ingredients.

[0499] (Application Example 1)

[0500] 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."

[0501] Modern consumers are expected to manage their food efficiently and reduce waste. However, keeping track of ingredients, managing expiration dates, and choosing cooking methods that suit their preferences are troublesome and contribute to food loss. A solution to this problem is needed.

[0502] 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.

[0503] In this invention, the server includes a calculation means for storing ingredient information and calculating expiration dates, a recipe generation means for generating optimal cooking suggestions based on the stored information, a generation AI model means that takes into account user preferences and past consumption data, and an online data connection means for linking data with e-commerce sites. This allows consumers to efficiently manage ingredients and reduce food waste while saving the effort of inputting information.

[0504] "Food information" refers to details such as the name, quantity, purchase date, and expiration date of food purchased by consumers.

[0505] A "data receiving means" refers to a method that provides an interface for users to input ingredient information and import that information into the system.

[0506] "Calculation means" refers to a processor that has the function of recording input food information and calculating its expiration date.

[0507] A "recipe generation method" is an algorithm or processing system that creates the most suitable cooking plan for the user based on stored ingredient information.

[0508] "Information notification means" refers to a device or method that provides the user with information on the generated cooking plan and expiration date.

[0509] "Generative AI model means" refers to a model that uses machine learning algorithms to generate cooking suggestions that take into account the user's preferences and past consumption data.

[0510] "Online data connection means" refers to a data linkage function that automatically and seamlessly imports food ingredient information from e-commerce platforms.

[0511] This invention is a system for efficiently managing information on food products purchased by consumers and reducing food waste.

[0512] User actions

[0513] After purchasing groceries, users either enter the information through an application on their device or import it from an e-commerce platform using an online data connection. This information includes the name of the food item, the date of purchase, the quantity, and the expiration date.

[0514] Device functions

[0515] The terminal receives ingredient information entered or imported by the user and sends it to the server. It also provides the user with optimal cooking suggestions and expiration date notifications sent from the server. The user can use the terminal to check these notifications and take appropriate action.

[0516] Server Processing

[0517] The server stores ingredient information sent from the terminal and calculates the expiration date using a computational method. Furthermore, it uses a generative AI model to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This generation process uses Python, implementing the AI ​​model with tools such as TensorFlow and PyTorch. Google Firebase is used as the database to efficiently store and manage the data.

[0518] Specific examples and prompt statements

[0519] For example, if a user purchases "tomatoes," "chicken," and "pasta" online, that information is automatically registered in the app, and a simple pasta recipe using tomatoes is suggested based on the expiration dates. An example of a prompt used in the generating AI model would be, "Considering the user's preferences and the ingredients purchased, please suggest a recipe suitable for tonight's dinner." In this way, users can use their ingredients efficiently and without waste.

[0520] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0521] Step 1:

[0522] Users enter food information using an application on their device or import food information from an e-commerce platform via an online data connection. The information entered includes the name of the food item, purchase date, quantity, and expiration date. This data is stored on the device.

[0523] Step 2:

[0524] The terminal sends the food information received from the user to the server. The transmitted data includes the name of each food item, the date of purchase, the quantity, and the expiration date. This allows the server to aggregate all food information owned by the user.

[0525] Step 3:

[0526] The server stores the received food information in a Google Firebase database. Based on the stored data, a calculation tool calculates the expiration date. As a result, the calculated expiration date is added to each data entry and used as the basis for notifications.

[0527] Step 4:

[0528] The server uses a generative AI model based on stored ingredient information and expiration dates to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This algorithm uses TensorFlow and PyTorch models implemented in a Python environment. The generated recipe suggestions are output as prompts for the user to see.

[0529] Step 5:

[0530] The server sends the generated cooking suggestion and expiration date notification to the terminal. The terminal displays this information in a user-friendly format. For example, it might display a notification such as "Simple pasta recipe using tomatoes" and "Tomatoes expire in 3 days."

[0531] Step 6:

[0532] Users check the information notified via their devices and use the cooking suggestions to efficiently utilize ingredients. By checking recipes and taking actions to reduce food waste, users contribute to the environment.

[0533] 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.

[0534] The system incorporating the emotion engine in this invention provides a personalized experience by applying emotion recognition technology to support users in managing their ingredients and reducing food waste.

[0535] User-side embodiment

[0536] Users input ingredient information using an application on their device. During this process, the device's camera and microphone collect information about the user's emotions through their voice and facial expressions. Users can also review suggested cooking methods and notifications displayed on the device and make selections based on their feelings and preferences. Furthermore, they can receive personalized plans tailored to their stress levels and health status, and follow those plans to maintain a healthy diet.

[0537] Terminal-side embodiment

[0538] The device collects ingredient information and emotional data entered by the user and sends it to the server. Emotional data, in particular, is continuously analyzed in real time by an emotion engine. The interface on the device adjusts according to changes in emotions, improving the user experience. Furthermore, received cooking suggestions and shopping lists are displayed to the user as optimal content based on the emotional information.

[0539] Server-side embodiment

[0540] The server integrates ingredient information and emotional data transmitted from the terminal and stores it in a database. The emotional engine analyzes this data and generates cooking suggestions best suited to the user's current emotional state. For example, if the emotional engine determines that the user's stress level is high, it will provide a recipe using foods with relaxing effects. It will also generate a shopping list of ingredients that need to be purchased. This makes it a program that promotes the user's health.

[0541] For example, if a user enters "I'm tired today," the emotion engine analyzes that emotion and suggests a simple, relaxing recipe like "herbal tea and a simple sandwich." If the user is feeling uplifted, it recommends a new, challenging recipe to enrich the user's cooking experience.

[0542] Through the embodiments described above, the system of the present invention realizes dietary support that takes into account the individual emotional state of the user. This system reduces food waste and contributes to a sustainable lifestyle by promoting personalized food management and consumption according to the user's preferences and health condition.

[0543] The following describes the processing flow.

[0544] Step 1:

[0545] The user launches the application on their device and begins entering information about the ingredients. As they enter the name, quantity, and purchase date of the ingredients, the device's camera and microphone simultaneously capture the user's facial expressions and voice.

[0546] Step 2:

[0547] The terminal formats the ingredient information entered by the user and sends it to the server along with sentiment data. A secure communication protocol is used for transmission.

[0548] Step 3:

[0549] The server matches the received food information with emotional data and stores it in a database. In addition, the emotion engine analyzes the user's emotional state and identifies stress levels and positive / negative emotions.

[0550] Step 4:

[0551] The server generates optimal cooking suggestions based on analyzed emotional data. For example, if the user is seeking relaxation, the server will suggest menu items with relaxing effects, such as lavender tea.

[0552] Step 5:

[0553] The server sends the generated cooking plan and expiration date information to the terminal. It also simultaneously generates and sends a purchase list tailored to the user's emotional state.

[0554] Step 6:

[0555] The device visually displays received cooking suggestions, expiration date notifications, and shopping lists to the user. This includes emotionally responsive interface design changes.

[0556] Step 7:

[0557] The user checks the information displayed on the device and begins cooking using the ingredients. They can also use the shopping list to consider procuring new ingredients.

[0558] Step 8:

[0559] The server continuously monitors food consumption data and emotional changes, calculates and analyzes the environmental contribution based on food waste reduction, and reports it to the user periodically.

[0560] (Example 2)

[0561] 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."

[0562] This invention aims to efficiently support users in managing their ingredients and reducing food waste, while providing a personalized experience that responds to their emotions. Conventional systems suggest ingredients and recipes without considering the user's emotions, making it difficult to improve the accuracy of suggestions and user satisfaction. Furthermore, there is a need to simultaneously achieve the seemingly contradictory goals of reducing food waste and promoting user health.

[0563] 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.

[0564] In this invention, the server includes means for providing a user interface for inputting ingredient information and emotional information; data storage means including a processor for storing the input ingredient information and emotional information, calculating the expiration date, and analyzing the emotional data; generation means for generating an optimal cooking suggestion based on the stored ingredient information and emotional information; notification means for outputting the generated cooking suggestion and expiration date notification to the user; and adjustment means for dynamically adjusting the user interface based on the user's emotions. This enables personalized ingredient management and cooking suggestions that respond to the user's emotions, efficiently achieving both food waste reduction and health promotion.

[0565] "Ingredient information" refers to data that includes the name, quantity, expiration date, and other related information of the ingredients.

[0566] "Emotional information" refers to data that represents the user's emotional state at any given time, collected from the user's voice, facial expressions, and other sources.

[0567] "User interface" refers to the system's operating screen and input methods for users to input information about ingredients and emotions.

[0568] "Data storage means" refers to means for securely storing food ingredient information and emotional information, and managing them in a format that can be accessed as needed.

[0569] A "generation method" is a process that has the function of automatically creating cooking suggestions that meet the user's needs based on stored data.

[0570] A "notification method" is an output function that provides users with information such as cooking suggestions and expiration dates.

[0571] "Adjustment mechanisms" refer to functions that change the interface design and usability based on the user's emotional state, thereby providing a more comfortable user experience.

[0572] The present invention is a technology that uses emotional information to personalize user food management and food waste reduction. This system exchanges information between a terminal and a server to provide the user with the optimal experience.

[0573] First, users can input ingredient information using a dedicated application installed on their device. Input is done in various ways, including keyboard, voice input, and image recognition using a camera. Emotional information is also collected simultaneously through the user's facial expressions and voice. The hardware used includes cameras, microphones, and sensors. This allows the user's emotional state to be analyzed in real time and transmitted to the server.

[0574] The server integrates received ingredient information and emotional data and records it in a database for data storage. Using a generative AI model, the server generates cooking suggestions that maximize the use of ingredient information, based on the user's emotional state. This generative AI model runs on a workstation and selects the most suitable suggestion from a vast and diverse range of cooking options, based on the user's current emotional state.

[0575] For example, if a user enters "I'm tired today," the server uses an emotion recognition engine to analyze the user's state and suggests a relaxing recipe like "herbal tea and a simple sandwich." The system also automatically generates a shopping list based on missing ingredients, helping users easily replenish their supplies.

[0576] As a concrete example of how this system works, the prompt "Based on the user's emotional data, suggest a recipe for a dish that should be suggested when the user is under high stress" is input to the generating AI model, and the AI ​​determines the suggested recipe.

[0577] The system of the present invention simultaneously reduces food waste and promotes user health by effectively utilizing ingredients and presenting cooking suggestions that are flexibly adjusted according to the user's emotions.

[0578] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0579] Step 1:

[0580] The user launches the application on the device and enters information about the ingredients. Specifically, the user enters the name of the ingredient using the keyboard or scans the barcode of the ingredient using the camera function. It is also possible to dictate the information using voice input. During input, the device's camera and microphone record the user's facial expressions and voice, simultaneously collecting emotional information. The entered ingredient information and emotional information are stored on the device and used in the next step.

[0581] Step 2:

[0582] The terminal processes the collected food ingredient information and emotional data and sends it to the server. Specifically, it securely transfers the data using data encryption technology. The server stores the received data in a database. In this process, the food ingredient information is organized and the emotional data is preprocessed, transforming the information into a format that can be used efficiently.

[0583] Step 3:

[0584] The server uses a generative AI model to generate cooking suggestions based on ingredient information and emotional information. Specifically, the generative AI model selects from a vast database of recipes and suggests the recipe best suited to the user's current emotional state. For example, if the server determines that the user is tired, a menu with relaxing effects will be selected. The generated cooking suggestions are then finalized on the server and prepared for the next step.

[0585] Step 4:

[0586] The server sends the generated cooking suggestion and a shopping list of necessary ingredients to the device. Specifically, the server lists the ingredients the user needs to obtain along with the recommended recipe and sends this as a push notification to the device. This notification allows the user to make their selection in the next step.

[0587] Step 5:

[0588] The device notifies the user of received cooking suggestions and shopping lists, allowing the user to make selections. The user can review the suggested recipes and choose the one that best suits their current situation and preferences. The user interface dynamically changes according to their emotions; for example, a clearer and calming interface is provided when the user is under high stress.

[0589] Step 6:

[0590] After cooking according to the recipe, the user enters feedback into their device. Specifically, the user records the ingredients they actually used and their satisfaction with the recipe in the app. The device then sends this feedback back to the server, and the system uses this feedback to improve future suggestions and enhance the user experience.

[0591] (Application Example 2)

[0592] 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."

[0593] Current food management systems are unable to provide personalized meal suggestions that adapt to users' emotions and health conditions, making it difficult to improve user satisfaction. Similarly, food delivery services struggle to offer meal options that consider individual user preferences, failing to deliver the dining experience users desire. Furthermore, there is a growing need to effectively reduce food waste and demonstrate concrete contributions to the environment.

[0594] 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.

[0595] In this invention, the server includes means for providing a human interface for inputting ingredient information, storage means including an information processing device for storing the input ingredient information and calculating the expiration date, generation means for generating an optimal cooking suggestion based on the stored ingredient information and the user's emotional information, communication means for outputting the optimal cooking suggestion and expiration date notification to the user, and analysis means for detecting the user's emotional information and adjusting the suggested content based on it. This makes it possible to concretely demonstrate the provision of meal suggestions tailored to the user's emotions, the reduction of food waste, and contributions to the environment.

[0596] "Food ingredient information" refers to data that users input through a human interface, such as the name, quantity, and expiration date of food items.

[0597] A "human interface" is an interactive system that allows users to input information into a system, and it is a means of exchanging information with other users through screens, keyboards, touch displays, etc.

[0598] An "information processing device" is a device or system that performs various calculations based on input data, such as calculating expiration dates.

[0599] A "storage method" is a structure or device for recording input data and retrieving it for later use.

[0600] "Generating means" refers to a process or apparatus that creates new information, specifically cooking ideas, based on stored data.

[0601] A "means of communication" refers to a system or device that effectively conveys generated information or notifications to the user.

[0602] "Analysis means" refers to a method or system for analyzing information about a user's emotional state and making appropriate adjustments based on the results of that analysis.

[0603] "Emotional information" refers to data that indicates the user's psychological state, and is collected from things like facial expressions and tone of voice.

[0604] The system that implements this application works when a user uses a food delivery application on their smartphone. The application uses the smartphone's camera and microphone to capture the user's facial expressions and voice data. When the user launches the application, the device collects this data and analyzes the emotional data in real time using an emotion recognition engine (Emotion SDK).

[0605] The analyzed sentiment data is sent to the server via an API built with Node.js on the backend. The server uses a database system such as MySQL to integrate past food history data with current sentiment data and generate a menu optimized for the user. The generated menu is adjusted based on the user's sentiment state and presented to the user via a frontend application developed with React Native.

[0606] For example, if a user expresses a desire to "enjoy a movie in a calm mood," the server can suggest a "relaxing tea and light snack menu." This process allows users to choose a meal that suits their mood and state, resulting in a more satisfying experience.

[0607] An example of a prompt that utilizes emotional data through a generative AI model is: "Consider the user's emotional state and suggest a dinner menu that best suits their mood at the time. If the user is highly fatigued, prioritize menus that can replenish energy." This prompt aims to provide personalized suggestions based on the user's individual state.

[0608] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0609] Step 1:

[0610] The user launches a food delivery application. This activates the smartphone's camera and microphone, setting up an environment for collecting the user's facial expressions and voice. When the user proceeds to the menu screen, this data is collected in real time. The input consists of image data and audio data captured through the camera and microphone.

[0611] Step 2:

[0612] The device sends collected image and audio data to the Emotion SDK for emotion recognition. The emotion recognition engine uses image and audio analysis to estimate the user's emotional state and quantify it. For example, it might be expressed as "70% happiness, 30% fatigue." The output is numerical data indicating the user's emotional state.

[0613] Step 3:

[0614] The device sends estimated emotion data to the backend API. The server retrieves the received emotion state data and the user's eating history data from a MySQL database and integrates them. Based on the integration results, a dataset is generated using Node.js. The input is emotion data and eating history data, and the output is the integrated dataset.

[0615] Step 4:

[0616] The server uses a generative AI model based on the generated dataset to create menus that respond to the user's emotions. The provided prompt text is input into the generative AI model, which generates a menu that suggests the most suitable meal for the user. For example, if the user's "happiness level" is high, a menu suggesting a new experience will be suggested. The output is a list of suggested menus.

[0617] Step 5:

[0618] The server generates menu suggestions and sends them to the user's device, where the user reviews them in the frontend application. Using a React Native interface, the user is presented with menu suggestions and can choose from the options. Once the selected menu is confirmed, the process proceeds to place the order. The input is a list of menu suggestions, and the output is the menu selected by the user.

[0619] 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.

[0620] 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.

[0621] 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.

[0622] [Fourth Embodiment]

[0623] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0624] 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.

[0625] 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).

[0626] 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.

[0627] 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.

[0628] 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).

[0629] 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.

[0630] 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.

[0631] 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.

[0632] 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.

[0633] 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.

[0634] 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.

[0635] 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".

[0636] The embodiments for carrying out the present invention will be described by dividing them into three elements: user, terminal, and server.

[0637] User-side embodiment

[0638] First, after purchasing ingredients, the user opens the application on their device and enters the ingredient information. This information includes the name of the food, purchase date, quantity, and expiration date. This information is processed appropriately on the device, as described below, and then sent to the server. The user also periodically checks the device for optimal cooking suggestions and expiration date information to ensure proper use of the ingredients. Furthermore, the user can prevent waste by referring to the purchase list displayed on the device and purchasing only what is needed.

[0639] Terminal-side embodiment

[0640] The terminal has the function of receiving ingredient information entered by the user and sending it to the server. It also displays the optimal cooking suggestion and expiration date notifications received from the server to the user in an easy-to-understand manner. For example, if ingredient information such as "Tomato, Purchase date: October 1, 2023, Expiration date: October 7, 2023" is entered into the terminal, that information is immediately sent to the server, and necessary notifications are sent to the user as they occur.

[0641] Server-side embodiment

[0642] The server receives ingredient information sent from the terminal and stores it in a database. Based on this information, it calculates the expiration date of the ingredients and prepares to notify the user. Furthermore, the server uses an AI algorithm to generate optimal cooking suggestions to maximize the use of the currently available ingredients. These cooking suggestions are sent to the terminal and provided to the user. In addition, based on the user's ingredient consumption data, the server calculates the effect of reducing food waste as a contribution to the environment and provides feedback. In this way, the server plays a central role in data processing and provides various information in a format that makes it easy for users to take actual action.

[0643] This "mode for carrying out the invention" allows the present invention to efficiently support consumers in reducing food waste and promote environmental contributions.

[0644] The following describes the processing flow.

[0645] Step 1:

[0646] The user enters information about the purchased groceries into the application on their device. Specifically, they specify the name of the groceries, the purchase date, and the quantity, and then press the submit button.

[0647] Step 2:

[0648] The terminal formats the entered ingredient information into JSON format and prepares it for transmission to the server. Here, it checks the validity of the data and converts it into a format for communication with the server.

[0649] Step 3:

[0650] The server stores the ingredient information received from the terminal into a database. Before saving, it verifies that the data format is correct and inserts it into the database using an SQL query.

[0651] Step 4:

[0652] The server calculates the expiration date for stored food items and sets a notification schedule. This process calculates the expiration date and prepares a trigger to send a notification at the specified date and time.

[0653] Step 5:

[0654] The server uses AI to generate optimal cooking suggestions based on the user's inventory data. Specifically, it feeds the ingredient list to an AI algorithm to create recipe suggestions and cooking plans.

[0655] Step 6:

[0656] The server sends the generated cooking suggestions and expiration date information to the user's device. An API is used for transmission, appropriately packaging the data before sending it to the device.

[0657] Step 7:

[0658] The device displays notifications and suggestions from the server to the user. Specifically, it displays cooking suggestions and alerts about food items nearing their expiration date on the device's screen.

[0659] Step 8:

[0660] Users take necessary actions based on the information presented by their device. For example, they might prioritize cooking ingredients that are nearing their expiration date, or check their shopping list to help with their shopping.

[0661] (Example 1)

[0662] 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".

[0663] Efficient management and waste reduction are crucial issues in food consumption. However, individual food management by consumers is time-consuming and labor-intensive, and food waste due to expired products is common. These problems also increase unnecessary environmental impacts. Therefore, there is a need for systems that efficiently manage, manage, and consume food to reduce food waste.

[0664] 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.

[0665] In this invention, the server includes an information input / output device for users to input information, an information management means including a calculation device for storing the input information and calculating the period, and a generation device for generating an optimal plan based on the stored information. This enables consumers to efficiently manage and cook ingredients and reduce food waste.

[0666] An "information input / output device for users to input information" is a device that provides an interface for users to input arbitrary information.

[0667] "Information management means including a calculation device for storing input information and calculating a period" refers to a device that records information entered by a user and has a calculation function for calculating a period associated with that information.

[0668] A "generating device that generates optimal proposals based on stored information" is a device that analyzes information recorded in a database and creates the best possible proposal based on the results of that analysis.

[0669] A "notification device that outputs notifications of the optimal plan and timeframe" is a device that appropriately reports the calculated timeframe and generated plan to the user.

[0670] "Information display means for displaying generated proposals" refers to a device for visually showing the proposals created by the generation device to the user.

[0671] A "device that automatically generates lists" is a device that automatically creates a list of newly required items based on stored information and utilizing that information.

[0672] A "device for calculating and displaying the impact based on reductions" is a device that measures the effect of reductions achieved by a specific activity and informs the user of the results.

[0673] This invention is a system that has three elements: a user, a terminal, and a server, and promotes the efficient management and consumption of food. The specific configuration and operation are described below.

[0674] User-side embodiment

[0675] Users use an application installed on their device to manage information about food they have purchased. First, users enter information such as the name of the food item, purchase date, quantity, and expiration date. This data forms the basis for efficient management. Users periodically check their device and refer to cooking suggestions and expiration date information provided by the server. This allows users to minimize waste.

[0676] Terminal-side embodiment

[0677] The device receives information entered by the user and sends it to the server. A standard smartphone or tablet is used for this purpose. The received data is temporarily stored but is transferred to the server as it is received. The device also serves to provide notifications from the server to the user. Specifically, it displays information on ingredients nearing their expiration date and cooking suggestions on the device screen.

[0678] Server-side embodiment

[0679] The server receives ingredient information sent from the terminal and stores it in a database. This process uses a database management system based on SQL. The server utilizes the stored data and generates optimal cooking suggestions using an AI algorithm. At the heart of this system is a generative AI model. The server enhances its contribution to the environment by calculating expiration dates, evaluating food waste reduction, and generating feedback for the user.

[0680] Specific example

[0681] When a user enters ingredient information into their device, such as "Tomatoes, Purchase Date: October 1, 2023, Expiration Date: October 7, 2023," that information is sent to the server. The server takes the expiration date into consideration and suggests "Tomato Sauce Pasta" as an example of a dish using tomatoes.

[0682] Example of a prompt

[0683] "Purchased ingredients: chicken, tomatoes. Please suggest a cooking method."

[0684] In this way, the system provides functions that fully support users in efficiently utilizing ingredients.

[0685] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0686] Step 1:

[0687] The user enters food information into the application on their device. The input fields include the name of the food item, purchase date, quantity, and expiration date. This information is provided by the user and temporarily stored as digital data on the device. This data is then sent to the server in the next step.

[0688] Step 2:

[0689] The device sends the stored ingredient information to the server. This transmission operation uses network communication (e.g., Wi-Fi or mobile data communication). The transmitted data consists of all the information related to each ingredient and is output from the device.

[0690] Step 3:

[0691] The server receives data sent from the terminal and stores it in a database. Based on the input information, the server calculates the expiration date for each food item. This calculation process calculates the number of days from the purchase date to the expiration date and outputs the number of days remaining until the expiration date.

[0692] Step 4:

[0693] The server generates optimal cooking suggestions using a generative AI model based on stored information. By incorporating ingredient information into prompt messages and inputting it into the AI ​​model, cooking suggestions that maximize the use of ingredients are generated. These generated suggestions are retrieved as output.

[0694] Step 5:

[0695] The server notifies the device of the calculated expiration date and generated cooking suggestions. These notifications are sent to the device as push notifications or in-app notifications. This allows the user to receive instructions on how to use ingredients efficiently.

[0696] Step 6:

[0697] The terminal displays instructions received from the server to the user. A visual interface is used for the display, and the information is organized so that the user can easily understand it. This interface highlights ingredients nearing their expiration date and optimal cooking suggestions.

[0698] Step 7:

[0699] Based on the information displayed on the device, users take actions to prevent food waste by cooking and consuming food appropriately. Ultimately, the user's actions based on the information become the output, resulting in the effective use of ingredients.

[0700] (Application Example 1)

[0701] 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".

[0702] Modern consumers are expected to manage their food efficiently and reduce waste. However, keeping track of ingredients, managing expiration dates, and choosing cooking methods that suit their preferences are troublesome and contribute to food loss. A solution to this problem is needed.

[0703] 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.

[0704] In this invention, the server includes a calculation means for storing ingredient information and calculating expiration dates, a recipe generation means for generating optimal cooking suggestions based on the stored information, a generation AI model means that takes into account user preferences and past consumption data, and an online data connection means for linking data with e-commerce sites. This allows consumers to efficiently manage ingredients and reduce food waste while saving the effort of inputting information.

[0705] "Food information" refers to details such as the name, quantity, purchase date, and expiration date of food purchased by consumers.

[0706] A "data receiving means" refers to a method that provides an interface for users to input ingredient information and import that information into the system.

[0707] "Calculation means" refers to a processor that has the function of recording input food information and calculating its expiration date.

[0708] A "recipe generation method" is an algorithm or processing system that creates the most suitable cooking plan for the user based on stored ingredient information.

[0709] "Information notification means" refers to a device or method that provides the user with information on the generated cooking plan and expiration date.

[0710] "Generative AI model means" refers to a model that uses machine learning algorithms to generate cooking suggestions that take into account the user's preferences and past consumption data.

[0711] "Online data connection means" refers to a data linkage function that automatically and seamlessly imports food ingredient information from e-commerce platforms.

[0712] This invention is a system for efficiently managing information on food products purchased by consumers and reducing food waste.

[0713] User actions

[0714] After purchasing groceries, users either enter the information through an application on their device or import it from an e-commerce platform using an online data connection. This information includes the name of the food item, the date of purchase, the quantity, and the expiration date.

[0715] Device functions

[0716] The terminal receives ingredient information entered or imported by the user and sends it to the server. It also provides the user with optimal cooking suggestions and expiration date notifications sent from the server. The user can use the terminal to check these notifications and take appropriate action.

[0717] Server Processing

[0718] The server stores ingredient information sent from the terminal and calculates the expiration date using a computational method. Furthermore, it uses a generative AI model to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This generation process uses Python, implementing the AI ​​model with tools such as TensorFlow and PyTorch. Google Firebase is used as the database to efficiently store and manage the data.

[0719] Specific examples and prompt statements

[0720] For example, if a user purchases "tomatoes," "chicken," and "pasta" online, that information is automatically registered in the app, and a simple pasta recipe using tomatoes is suggested based on the expiration dates. An example of a prompt used in the generating AI model would be, "Considering the user's preferences and the ingredients purchased, please suggest a recipe suitable for tonight's dinner." In this way, users can use their ingredients efficiently and without waste.

[0721] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0722] Step 1:

[0723] Users enter food information using an application on their device or import food information from an e-commerce platform via an online data connection. The information entered includes the name of the food item, purchase date, quantity, and expiration date. This data is stored on the device.

[0724] Step 2:

[0725] The terminal sends the food information received from the user to the server. The transmitted data includes the name of each food item, the date of purchase, the quantity, and the expiration date. This allows the server to aggregate all food information owned by the user.

[0726] Step 3:

[0727] The server stores the received food information in a Google Firebase database. Based on the stored data, a calculation tool calculates the expiration date. As a result, the calculated expiration date is added to each data entry and used as the basis for notifications.

[0728] Step 4:

[0729] The server uses a generative AI model based on stored ingredient information and expiration dates to generate optimal cooking suggestions, taking into account the user's past consumption data and preferences. This algorithm uses TensorFlow and PyTorch models implemented in a Python environment. The generated recipe suggestions are output as prompts for the user to see.

[0730] Step 5:

[0731] The server sends the generated cooking suggestion and expiration date notification to the terminal. The terminal displays this information in a user-friendly format. For example, it might display a notification such as "Simple pasta recipe using tomatoes" and "Tomatoes expire in 3 days."

[0732] Step 6:

[0733] Users check the information notified via their devices and use the cooking suggestions to efficiently utilize ingredients. By checking recipes and taking actions to reduce food waste, users contribute to the environment.

[0734] 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.

[0735] The system incorporating the emotion engine in this invention provides a personalized experience by applying emotion recognition technology to support users in managing their ingredients and reducing food waste.

[0736] User-side embodiment

[0737] Users input ingredient information using an application on their device. During this process, the device's camera and microphone collect information about the user's emotions through their voice and facial expressions. Users can also review suggested cooking methods and notifications displayed on the device and make selections based on their feelings and preferences. Furthermore, they can receive personalized plans tailored to their stress levels and health status, and follow those plans to maintain a healthy diet.

[0738] Terminal-side embodiment

[0739] The device collects ingredient information and emotional data entered by the user and sends it to the server. Emotional data, in particular, is continuously analyzed in real time by an emotion engine. The interface on the device adjusts according to changes in emotions, improving the user experience. Furthermore, received cooking suggestions and shopping lists are displayed to the user as optimal content based on the emotional information.

[0740] Server-side embodiment

[0741] The server integrates ingredient information and emotional data transmitted from the terminal and stores it in a database. The emotional engine analyzes this data and generates cooking suggestions best suited to the user's current emotional state. For example, if the emotional engine determines that the user's stress level is high, it will provide a recipe using foods with relaxing effects. It will also generate a shopping list of ingredients that need to be purchased. This makes it a program that promotes the user's health.

[0742] For example, if a user enters "I'm tired today," the emotion engine analyzes that emotion and suggests a simple, relaxing recipe like "herbal tea and a simple sandwich." If the user is feeling uplifted, it recommends a new, challenging recipe to enrich the user's cooking experience.

[0743] Through the embodiments described above, the system of the present invention realizes dietary support that takes into account the individual emotional state of the user. This system reduces food waste and contributes to a sustainable lifestyle by promoting personalized food management and consumption according to the user's preferences and health condition.

[0744] The following describes the processing flow.

[0745] Step 1:

[0746] The user launches the application on their device and begins entering information about the ingredients. As they enter the name, quantity, and purchase date of the ingredients, the device's camera and microphone simultaneously capture the user's facial expressions and voice.

[0747] Step 2:

[0748] The terminal formats the ingredient information entered by the user and sends it to the server along with sentiment data. A secure communication protocol is used for transmission.

[0749] Step 3:

[0750] The server matches the received food information with emotional data and stores it in a database. In addition, the emotion engine analyzes the user's emotional state and identifies stress levels and positive / negative emotions.

[0751] Step 4:

[0752] The server generates optimal cooking suggestions based on analyzed emotional data. For example, if the user is seeking relaxation, the server will suggest menu items with relaxing effects, such as lavender tea.

[0753] Step 5:

[0754] The server sends the generated cooking plan and expiration date information to the terminal. It also simultaneously generates and sends a purchase list tailored to the user's emotional state.

[0755] Step 6:

[0756] The device visually displays received cooking suggestions, expiration date notifications, and shopping lists to the user. This includes emotionally responsive interface design changes.

[0757] Step 7:

[0758] The user checks the information displayed on the device and begins cooking using the ingredients. They can also use the shopping list to consider procuring new ingredients.

[0759] Step 8:

[0760] The server continuously monitors food consumption data and emotional changes, calculates and analyzes the environmental contribution based on food waste reduction, and reports it to the user periodically.

[0761] (Example 2)

[0762] 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".

[0763] This invention aims to efficiently support users in managing their ingredients and reducing food waste, while providing a personalized experience that responds to their emotions. Conventional systems suggest ingredients and recipes without considering the user's emotions, making it difficult to improve the accuracy of suggestions and user satisfaction. Furthermore, there is a need to simultaneously achieve the seemingly contradictory goals of reducing food waste and promoting user health.

[0764] 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.

[0765] In this invention, the server includes means for providing a user interface for inputting ingredient information and emotional information; data storage means including a processor for storing the input ingredient information and emotional information, calculating the expiration date, and analyzing the emotional data; generation means for generating an optimal cooking suggestion based on the stored ingredient information and emotional information; notification means for outputting the generated cooking suggestion and expiration date notification to the user; and adjustment means for dynamically adjusting the user interface based on the user's emotions. This enables personalized ingredient management and cooking suggestions that respond to the user's emotions, efficiently achieving both food waste reduction and health promotion.

[0766] "Ingredient information" refers to data that includes the name, quantity, expiration date, and other related information of the ingredients.

[0767] "Emotional information" refers to data that represents the user's emotional state at any given time, collected from the user's voice, facial expressions, and other sources.

[0768] "User interface" refers to the system's operating screen and input methods for users to input information about ingredients and emotions.

[0769] "Data storage means" refers to means for securely storing food ingredient information and emotional information, and managing them in a format that can be accessed as needed.

[0770] A "generation method" is a process that has the function of automatically creating cooking suggestions that meet the user's needs based on stored data.

[0771] A "notification method" is an output function that provides users with information such as cooking suggestions and expiration dates.

[0772] "Adjustment mechanisms" refer to functions that change the interface design and usability based on the user's emotional state, thereby providing a more comfortable user experience.

[0773] The present invention is a technology that uses emotional information to personalize user food management and food waste reduction. This system exchanges information between a terminal and a server to provide the user with the optimal experience.

[0774] First, users can input ingredient information using a dedicated application installed on their device. Input is done in various ways, including keyboard, voice input, and image recognition using a camera. Emotional information is also collected simultaneously through the user's facial expressions and voice. The hardware used includes cameras, microphones, and sensors. This allows the user's emotional state to be analyzed in real time and transmitted to the server.

[0775] The server integrates received ingredient information and emotional data and records it in a database for data storage. Using a generative AI model, the server generates cooking suggestions that maximize the use of ingredient information, based on the user's emotional state. This generative AI model runs on a workstation and selects the most suitable suggestion from a vast and diverse range of cooking options, based on the user's current emotional state.

[0776] For example, if a user enters "I'm tired today," the server uses an emotion recognition engine to analyze the user's state and suggests a relaxing recipe like "herbal tea and a simple sandwich." The system also automatically generates a shopping list based on missing ingredients, helping users easily replenish their supplies.

[0777] As a concrete example of how this system works, the prompt "Based on the user's emotional data, suggest a recipe for a dish that should be suggested when the user is under high stress" is input to the generating AI model, and the AI ​​determines the suggested recipe.

[0778] The system of the present invention simultaneously reduces food waste and promotes user health by effectively utilizing ingredients and presenting cooking suggestions that are flexibly adjusted according to the user's emotions.

[0779] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0780] Step 1:

[0781] The user launches the application on the device and enters information about the ingredients. Specifically, the user enters the name of the ingredient using the keyboard or scans the barcode of the ingredient using the camera function. It is also possible to dictate the information using voice input. During input, the device's camera and microphone record the user's facial expressions and voice, simultaneously collecting emotional information. The entered ingredient information and emotional information are stored on the device and used in the next step.

[0782] Step 2:

[0783] The terminal processes the collected food ingredient information and emotional data and sends it to the server. Specifically, it securely transfers the data using data encryption technology. The server stores the received data in a database. In this process, the food ingredient information is organized and the emotional data is preprocessed, transforming the information into a format that can be used efficiently.

[0784] Step 3:

[0785] The server uses a generative AI model to generate cooking suggestions based on ingredient information and emotional information. Specifically, the generative AI model selects from a vast database of recipes and suggests the recipe best suited to the user's current emotional state. For example, if the server determines that the user is tired, a menu with relaxing effects will be selected. The generated cooking suggestions are then finalized on the server and prepared for the next step.

[0786] Step 4:

[0787] The server sends the generated cooking suggestion and a shopping list of necessary ingredients to the device. Specifically, the server lists the ingredients the user needs to obtain along with the recommended recipe and sends this as a push notification to the device. This notification allows the user to make their selection in the next step.

[0788] Step 5:

[0789] The device notifies the user of received cooking suggestions and shopping lists, allowing the user to make selections. The user can review the suggested recipes and choose the one that best suits their current situation and preferences. The user interface dynamically changes according to their emotions; for example, a clearer and calming interface is provided when the user is under high stress.

[0790] Step 6:

[0791] After cooking according to the recipe, the user enters feedback into their device. Specifically, the user records the ingredients they actually used and their satisfaction with the recipe in the app. The device then sends this feedback back to the server, and the system uses this feedback to improve future suggestions and enhance the user experience.

[0792] (Application Example 2)

[0793] 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".

[0794] Current food management systems are unable to provide personalized meal suggestions that adapt to users' emotions and health conditions, making it difficult to improve user satisfaction. Similarly, food delivery services struggle to offer meal options that consider individual user preferences, failing to deliver the dining experience users desire. Furthermore, there is a growing need to effectively reduce food waste and demonstrate concrete contributions to the environment.

[0795] 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.

[0796] In this invention, the server includes means for providing a human interface for inputting ingredient information, storage means including an information processing device for storing the input ingredient information and calculating the expiration date, generation means for generating an optimal cooking suggestion based on the stored ingredient information and the user's emotional information, communication means for outputting the optimal cooking suggestion and expiration date notification to the user, and analysis means for detecting the user's emotional information and adjusting the suggested content based on it. This makes it possible to concretely demonstrate the provision of meal suggestions tailored to the user's emotions, the reduction of food waste, and contributions to the environment.

[0797] "Food ingredient information" refers to data that users input through a human interface, such as the name, quantity, and expiration date of food items.

[0798] A "human interface" is an interactive system that allows users to input information into a system, and it is a means of exchanging information with other users through screens, keyboards, touch displays, etc.

[0799] An "information processing device" is a device or system that performs various calculations based on input data, such as calculating expiration dates.

[0800] A "storage method" is a structure or device for recording input data and retrieving it for later use.

[0801] "Generating means" refers to a process or apparatus that creates new information, specifically cooking ideas, based on stored data.

[0802] A "means of communication" refers to a system or device that effectively conveys generated information or notifications to the user.

[0803] "Analysis means" refers to a method or system for analyzing information about a user's emotional state and making appropriate adjustments based on the results of that analysis.

[0804] "Emotional information" refers to data that indicates the user's psychological state, and is collected from things like facial expressions and tone of voice.

[0805] The system that implements this application works when a user uses a food delivery application on their smartphone. The application uses the smartphone's camera and microphone to capture the user's facial expressions and voice data. When the user launches the application, the device collects this data and analyzes the emotional data in real time using an emotion recognition engine (Emotion SDK).

[0806] The analyzed sentiment data is sent to the server via an API built with Node.js on the backend. The server uses a database system such as MySQL to integrate past food history data with current sentiment data and generate a menu optimized for the user. The generated menu is adjusted based on the user's sentiment state and presented to the user via a frontend application developed with React Native.

[0807] For example, if a user expresses a desire to "enjoy a movie in a calm mood," the server can suggest a "relaxing tea and light snack menu." This process allows users to choose a meal that suits their mood and state, resulting in a more satisfying experience.

[0808] An example of a prompt that utilizes emotional data through a generative AI model is: "Consider the user's emotional state and suggest a dinner menu that best suits their mood at the time. If the user is highly fatigued, prioritize menus that can replenish energy." This prompt aims to provide personalized suggestions based on the user's individual state.

[0809] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0810] Step 1:

[0811] The user launches a food delivery application. This activates the smartphone's camera and microphone, setting up an environment for collecting the user's facial expressions and voice. When the user proceeds to the menu screen, this data is collected in real time. The input consists of image data and audio data captured through the camera and microphone.

[0812] Step 2:

[0813] The device sends collected image and audio data to the Emotion SDK for emotion recognition. The emotion recognition engine uses image and audio analysis to estimate the user's emotional state and quantify it. For example, it might be expressed as "70% happiness, 30% fatigue." The output is numerical data indicating the user's emotional state.

[0814] Step 3:

[0815] The device sends estimated emotion data to the backend API. The server retrieves the received emotion state data and the user's eating history data from a MySQL database and integrates them. Based on the integration results, a dataset is generated using Node.js. The input is emotion data and eating history data, and the output is the integrated dataset.

[0816] Step 4:

[0817] The server uses a generative AI model based on the generated dataset to create menus that respond to the user's emotions. The provided prompt text is input into the generative AI model, which generates a menu that suggests the most suitable meal for the user. For example, if the user's "happiness level" is high, a menu suggesting a new experience will be suggested. The output is a list of suggested menus.

[0818] Step 5:

[0819] The server generates menu suggestions and sends them to the user's device, where the user reviews them in the frontend application. Using a React Native interface, the user is presented with menu suggestions and can choose from the options. Once the selected menu is confirmed, the process proceeds to place the order. The input is a list of menu suggestions, and the output is the menu selected by the user.

[0820] 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.

[0821] 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.

[0822] 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 robot 414.

[0823] 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.

[0824] 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. In the upper and lower directions of the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. Also, the upper side of the concentric circles is where "pleasant" emotions are located, and the lower side is where "unpleasant" emotions are located. In this way, 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.

[0825] 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.

[0826] 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.

[0827] 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.

[0828] 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."

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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.

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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 as being incorporated by reference.

[0841] The following is further disclosed regarding the embodiments described above.

[0842] (Claim 1)

[0843] A means of providing a user interface for inputting ingredient information,

[0844] A database means including a processor that stores input food information and calculates the expiration date,

[0845] A generation method for generating optimal cooking plans based on stored ingredient information,

[0846] A notification means that outputs optimal cooking suggestions and expiration date notifications to the user,

[0847] A system that includes this.

[0848] (Claim 2)

[0849] The system according to claim 1, further comprising a means for automatically generating a purchase list based on ingredient information.

[0850] (Claim 3)

[0851] The system according to claim 1, comprising a means for calculating and displaying the degree of environmental contribution based on food waste reduction.

[0852] "Example 1"

[0853] (Claim 1)

[0854] An information input / output device for users to input information,

[0855] Information management means including a calculation device that stores input information and calculates a period,

[0856] A generation device that generates the optimal plan based on the stored information,

[0857] A notification device that outputs notifications of the optimal plan and timeframe,

[0858] Information display means for displaying the generated proposal,

[0859] A system that includes this.

[0860] (Claim 2)

[0861] The system according to claim 1, further comprising a device for automatically generating a list based on information.

[0862] (Claim 3)

[0863] The system according to claim 1, comprising a device for calculating and displaying the impact based on reductions.

[0864] "Application Example 1"

[0865] (Claim 1)

[0866] A means of receiving data for inputting ingredient information,

[0867] A calculation means for saving the entered food information and calculating the expiration date,

[0868] A recipe generation method that generates optimal cooking suggestions based on stored ingredient information,

[0869] An information notification means that outputs optimal cooking suggestions and expiration date notifications to the user,

[0870] A generative AI model that generates optimal cooking suggestions by taking into account user preferences and past consumption data,

[0871] An online data connection method for linking data with e-commerce sites,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, further comprising an automatic generation means for automatically generating purchase items based on ingredient information.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising a display device for calculating the degree of environmental contribution based on food waste reduction.

[0877] "Example 2 of combining an emotion engine"

[0878] (Claim 1)

[0879] A means for providing a user interface for inputting food ingredient information and emotional information,

[0880] A data storage means including a processor that stores input food ingredient information and emotional information, calculates the expiration date, and analyzes the emotional data,

[0881] A generation means for generating optimal cooking suggestions based on stored ingredient information and emotional information,

[0882] A notification means that outputs the generated cooking suggestion and expiration date notification to the user,

[0883] A means of dynamically adjusting the user interface based on the user's emotions,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, further comprising means for automatically generating a purchase list based on ingredient information and emotional information.

[0887] (Claim 3)

[0888] The system according to claim 1, comprising a means for calculating and displaying the degree of contribution based on food waste reduction and the user's health status.

[0889] "Application example 2 when combining with an emotional engine"

[0890] (Claim 1)

[0891] A means of providing a human interface for inputting ingredient information,

[0892] A storage means including an information processing device that stores input food information and calculates the expiration date,

[0893] A generation method that generates optimal cooking suggestions based on saved ingredient information and user sentiment information,

[0894] A communication method that outputs optimal cooking suggestions and expiration date notifications to the user,

[0895] An analytical means that detects user sentiment information and adjusts the suggested content based on it,

[0896] A system that includes this.

[0897] (Claim 2)

[0898] The system according to claim 1, further comprising means for automatically generating a purchase list based on ingredient information.

[0899] (Claim 3)

[0900] The system according to claim 1, comprising means for calculating and displaying the degree of contribution to the environment based on the reduction of food waste. [Explanation of Symbols]

[0901] 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 receiving data for inputting ingredient information, A calculation means for saving the entered food information and calculating the expiration date, A recipe generation method that generates optimal cooking suggestions based on stored ingredient information, An information notification means that outputs optimal cooking suggestions and expiration date notifications to the user, A generative AI model that generates optimal cooking suggestions by taking into account user preferences and past consumption data, An online data connection method for linking data with e-commerce sites, A system that includes this.

2. The system according to claim 1, further comprising an automatic generation means for automatically generating purchase items based on ingredient information.

3. The system according to claim 1, comprising a display device for calculating the degree of environmental contribution based on food waste reduction.

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