System

Abstract

A system is provided.SOLUTION: This system is provided with a means for proposing a dish based on the feeling inputted by the user, a means for enabling the user to select a providing method from self-preparation, delivery and a restaurant for the proposed dish, and a means for displaying a corresponding recipe and a necessary material list when the user selects the self-preparation. A system comprising: means for arranging materials; means for ordering a dish from a nearby affiliated store and arranging delivery when a user selects delivery; means for making a reservation at a nearby affiliated restaurant when a user selects a restaurant; and means for selecting partner information and a donation destination and performing remittance processing when treating another person or donating to a support activity.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In recent years, users have been faced with the challenge of spending a great deal of time and effort when selecting their daily meals. Another issue is that it is difficult for users to find a dish that suits their mood at the time. Furthermore, social issues such as food waste and support for areas with unstable food supplies remain unresolved. The present invention addresses these issues by providing a system that allows users to easily and effectively select and order meals. [Means for solving the problem]

[0005] The present invention provides a system that suggests appropriate dishes based on the mood entered by the user. Specifically, it includes a means for analyzing the mood entered by the user using natural language processing and generating a list of candidate dishes. It also includes a means for allowing the user to select the delivery method from cook-it-yourself, delivery, or restaurant. If cook-it-yourself is selected, the corresponding recipe and a list of necessary ingredients are displayed, allowing the user to arrange for the ingredients. If delivery is selected, the system orders food from a nearby affiliated restaurant and arranges for delivery. If restaurant-based dining is selected, it provides a means for making reservations at a nearby affiliated restaurant. Furthermore, if treating someone or donating to relief efforts, it includes a means for selecting the recipient's information and donation destination and processing the transfer. It also includes a function for adjusting the suggested dishes and ingredients to avoid excess ingredients in order to address the food waste issue.

[0006] "User" refers to an individual or organization that uses this system to select, order, and arrange meals.

[0007] "Mood" refers to information that a user inputs to express their mental state or preferences at that time.

[0008] "Cooking" refers to the ingredients that a user prepares to consume as a meal and the cooking method thereof.

[0009] "Delivery method" refers to the means of delivery of the food selected by the user, and refers to three options: cook it yourself, delivery, or restaurant.

[0010] "Make it yourself" refers to a means for a user to arrange the necessary recipe and ingredients to cook the suggested dish themselves.

[0011] "Delivery" refers to a method in which a user can have the suggested dishes ordered from a nearby affiliated restaurant and delivered to them.

[0012] "Restaurant" refers to a means by which a user can make a reservation at a nearby affiliated restaurant that serves the suggested dishes and enjoy a meal.

[0013] "Natural language processing" refers to a technical method for analyzing text information entered by the user and suggesting appropriate dishes.

[0014] "Food waste" refers to the waste of ingredients and food that is discarded without being consumed properly.

[0015] The "ingredient list" refers to a list of ingredients and seasonings that a user needs when cooking a meal.

[0016] "Money transfer transactions" refers to the movement of money to treat others or to donate to relief efforts.

[0017] "Affiliated store" refers to a restaurant that has a cooperative relationship with this system and is presented to users as a delivery or restaurant option.

[0018] "Reservation" refers to the process by which a user reserves a seat and time in advance to dine at a restaurant.

[0019] "Support activities" refers to efforts to donate and support areas where food is unstable and organizations in need. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] This invention is a system that allows users to easily find a dish that suits their mood at the time, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[0042] Specific embodiments are described below.

[0043] Mood analysis and cooking suggestions

[0044] When a user launches the app and enters their mood for the day, the device sends the text to a server. The server then uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood. The list is then presented to the user via their device, allowing them to select their favorite dish.

[0045] Select delivery method

[0046] When the user selects a dish, the server sends the corresponding delivery method (cook it yourself, delivery, restaurant) to the terminal. The terminal displays the information to the user, who then selects the desired delivery method.

[0047] How to make it yourself

[0048] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[0049] Delivery process

[0050] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[0051] What to do if you're eating at a restaurant

[0052] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[0053] High-value-added features

[0054] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[0055] Addressing the food waste problem

[0056] The system also addresses the issue of food waste, making it possible to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being used.

[0057] Specific examples

[0058] For example, if a user inputs into the app, "I want something a little spicy today," the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[0059] In this way, the present invention is a system that greatly improves user convenience by providing comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments.

[0060] The processing flow will be explained below.

[0061] Step 1:

[0062] The user launches the app and inputs their mood for the day. For example, they might input, "I want to eat something a little spicy today."

[0063] Step 2:

[0064] The terminal receives the user's input and transmits the text data to the server.

[0065] Step 3:

[0066] The server passes the received text data to a natural language processing engine to analyze the user's mood.

[0067] Step 4:

[0068] Based on the analysis results, the server generates a list of dishes that match the user's mood, such as "curry" or "tacos."

[0069] Step 5:

[0070] The server sends the generated list of dish candidates to the terminal.

[0071] Step 6:

[0072] The device displays a list of possible dishes to the user, such as "curry" or "tacos."

[0073] Step 7:

[0074] The user selects "curry" from the displayed food options and taps the "Select" button.

[0075] Step 8:

[0076] The terminal transmits the user's selection to the server.

[0077] Step 9:

[0078] The server generates available delivery methods (make-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[0079] Step 10:

[0080] The device displays options for delivery to the user, such as "make it yourself," "delivery," or "restaurant."

[0081] Step 11:

[0082] The user selects "Delivery" as the delivery method and taps the "Next" button.

[0083] Step 12:

[0084] The terminal transmits the user's selection to the server.

[0085] Step 13:

[0086] The server generates a list of nearby affiliated stores that can provide "curry" and sends it to the terminal.

[0087] Step 14:

[0088] The terminal displays a list of affiliated restaurants to the user. For example, it displays options such as "Curry Restaurant A" and "Curry Restaurant B."

[0089] Step 15:

[0090] The user selects "Curry Restaurant A," checks the order details, and then taps the "Confirm Order" button.

[0091] Step 16:

[0092] The terminal sends the order information to the server.

[0093] Step 17:

[0094] The server processes the order and calculates the estimated delivery time.

[0095] Step 18:

[0096] The server sends the estimated delivery time and order confirmation to the terminal.

[0097] Step 19:

[0098] The terminal notifies the user of the delivery time and order confirmation.

[0099] Building it yourself (another scenario)

[0100] Step 11:

[0101] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[0102] Step 12:

[0103] The terminal transmits the user's selection to the server.

[0104] Step 13:

[0105] The server generates a recipe for "curry" and a list of necessary ingredients, and sends them to the terminal.

[0106] Step 14:

[0107] The terminal displays the recipe and ingredients list to the user.

[0108] Step 15:

[0109] The user taps the "Arrange Materials" button.

[0110] Step 16:

[0111] The terminal sends a material arrangement request to the server.

[0112] Step 17:

[0113] The server generates a list of nearby supermarkets and online supermarkets and sends it to the terminal.

[0114] Step 18:

[0115] The terminal displays a list of supermarkets to the user.

[0116] Step 19:

[0117] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[0118] Step 20:

[0119] The terminal sends the order information to the server.

[0120] Step 21:

[0121] The server processes the order and sends a confirmation message to the terminal.

[0122] Step 22:

[0123] The terminal displays an order confirmation message to the user.

[0124] In this way, this system greatly enhances user convenience by consistently supporting the selection of meals that suit the user's mood, the selection of the delivery method, arrangements, and payment.

[0125] Example 1

[0126] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0127] Conventional meal recommendation systems often lack the functionality to not only suggest dishes that suit the user's mood, but also comprehensively support the selection of how the meal will be served, as well as the specific arrangements and payment procedures. Furthermore, when preparing the meal yourself, the process of preparing ingredients is complicated, which increases the user's workload. Furthermore, these systems do not adequately address the issue of food waste, resulting in excess food. Thus, there is a need for a meal recommendation system that aims to achieve both user convenience and sustainability.

[0128] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0129] In this invention, the server includes: [means for suggesting dishes based on the mood input by the user; [means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant"; and [means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself."] This makes it possible [to suggest dishes based on the mood input by the user, and comprehensively select the delivery method, make specific arrangements, and make payment].

[0130] "User" refers to an end user who uses the system and inputs their mood for the day and the desired delivery method.

[0131] The term "server" refers to an information processing device that receives and processes data entered by a user or a virtual server on a network.

[0132] "Terminal" refers to a device that allows a user to access the system and input their mood, select suggested dishes, and select serving methods.

[0133] "Suggesting" refers to generating and presenting a list of appropriate dishes based on the mood data entered by the user.

[0134] "Delivery method" refers to the means by which users can obtain and consume food, and refers to three methods: cooking it yourself, delivery, or restaurant.

[0135] A "recipe" is a set of instructions for cooking a dish, including the necessary ingredients and steps.

[0136] "Ingredient list" refers to the list of ingredients needed to prepare the selected dish.

[0137] "Arranging ingredients" refers to preparing and ordering the necessary ingredients.

[0138] "Delivery" refers to the delivery of the food selected by the user from a nearby affiliated restaurant via a delivery service.

[0139] "Restaurant" refers to a restaurant that serves the food selected by the user.

[0140] "Affiliated stores" refer to affiliated stores that provide food in cooperation with the system.

[0141] "Order" refers to a request to purchase a dish or ingredients selected by a User.

[0142] "Remittance processing" refers to the procedure for transferring money when a user treats someone else or donates to relief efforts.

[0143] "Natural language processing technology" refers to artificial intelligence technology that analyzes text data and helps it understand its meaning.

[0144] "Food waste" refers to food that is discarded without being consumed.

[0145] The present invention relates to a system that proposes dishes tailored to the user's mood, and handles the selection, arrangement, and payment of the delivery method. This system uses multiple hardware and software components to perform specific data processing and calculations. Specific embodiments are described below.

[0146] System Configuration

[0147] User terminal

[0148] The device on which the user launches the app (smartphone, tablet, PC, etc.)

[0149] Responsible for sending input data and receiving and displaying display content

[0150] server

[0151] Analysis and recommendations using natural language processing technology

[0152] Specific software used for mood analysis: Google (registered trademark) Cloud Natural Language API

[0153] Processing flow

[0154] 1. Mood input

[0155] The user launches the app and enters their mood for the day in text.

[0156] The device transmits the mood data to the server.

[0157] 2. Mood analysis and recipe suggestions

[0158] The server uses natural language processing technology (Google Cloud Natural Language API) to analyze the user's mood.

[0159] The server generates a list of suggested dishes based on the analysis results.

[0160] The terminal displays the recipe list to the user.

[0161] 3. Selection of delivery method

[0162] When the user selects a dish, the server generates the corresponding delivery method (make-yourself, delivery, restaurant).

[0163] The terminal displays the provision methods to the user, and the user selects one.

[0164] If you make it yourself

[0165] The server generates a recipe and a list of ingredients for the selected dish.

[0166] The terminal displays the recipe and ingredients list to the user.

[0167] When a user requests material arrangement, the server generates a list of nearby supermarkets or online supermarkets (for example, the API of an online supermarket).

[0168] When a user orders ingredients, the server processes the order and displays a confirmation message.

[0169] For delivery

[0170] The server generates a list of dishes from nearby partner stores (stores that offer delivery).

[0171] The terminal displays this to the user, who then selects the food and restaurant and places the order.

[0172] The server processes the order and sends an estimated delivery time and order confirmation to the terminal.

[0173] In the case of a restaurant

[0174] The server generates a list of nearby affiliated restaurants.

[0175] The terminal displays this to the user, who then selects a restaurant and enters reservation details.

[0176] The server processes the reservation and sends a confirmation message to the terminal.

[0177] High-value-added features

[0178] If the user chooses to treat others or make a donation, the server generates information about the other person and a list of donation recipients.

[0179] The terminal displays this to the user, and once the remittance amount is set, the server processes the remittance and sends a confirmation message.

[0180] Addressing the food waste problem

[0181] The server adjusts the amount of ingredients based on the user's choice of food and number of people.

[0182] The device displays the adjusted ingredient list to the user, ensuring no excess ingredients are used.

[0183] Specific examples

[0184] For example, if a user inputs into the app, "I want to eat something spicy today," the server analyzes the data and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby affiliated curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the ingredients can be ordered directly.

[0185] Prompt Sentence Examples

[0186] Below are some examples of prompts to input to the generative AI model.

[0187] "User says they want something spicy today. Suggest a dish based on that and offer options for delivery, restaurants, or cook-it-yourself."

[0188] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0189] Step 1:

[0190] The user starts the app and enters their mood for the day in text. This text becomes the input data.

[0191] Step 2:

[0192] The device receives mood data entered by the user and sends the data to the server. The specific operation of the device is to send text data to the server as an HTTP request.

[0193] Step 3:

[0194] The server uses natural language processing technology to analyze the received mood data. This analysis generates a list of dishes that match the user's mood. Using the user's mood text as input data, it performs data calculations using tools such as the Google Cloud Natural Language API, and obtains a list of dishes as output.

[0195] Step 4:

[0196] The server sends the generated dish list to the device. Specifically, it encodes the dish list in JSON format and sends it to the device as an HTTP response.

[0197] Step 5:

[0198] The device receives the recipe list from the server and displays it to the user. The displayed recipe list becomes the output data. The device parses the data and displays it on the user interface.

[0199] Step 6:

[0200] The user selects a favorite dish from the list of dishes. This selection becomes the input data for the next process.

[0201] Step 7:

[0202] Based on the user's food selection, the server generates the corresponding delivery method (cook, delivery, restaurant) and sends it to the terminal. The input is the user's food selection data, and the output is a list of delivery methods.

[0203] Step 8:

[0204] The terminal displays a list of delivery methods to the user, specifically, a delivery method selection screen.

[0205] Step 9:

[0206] The user selects the delivery method (make it yourself, delivery, restaurant). The selected delivery method becomes the input data for the next step.

[0207] If you're making it yourself:

[0208] Step 10:

[0209] The server generates a recipe and a list of ingredients for the selected dish. The input is the user's dish selection data, and the output is the recipe and the list of ingredients.

[0210] Step 11:

[0211] The server sends the recipe and ingredient list to the device, encoding the data in JSON format and sending it as an HTTP response.

[0212] Step 12:

[0213] The terminal displays this to the user. Specifically, the recipe and ingredient list are displayed on the user interface.

[0214] Step 13:

[0215] The user presses the "Arrange materials" button, which becomes the input data for the next step.

[0216] Step 14:

[0217] The terminal sends a material arrangement request to the server. Specifically, the request data is sent as an HTTP request.

[0218] Step 15:

[0219] The server generates a list of nearby supermarkets and online supermarkets, and sends the ordering screen to the terminal. Using the user's location information and material ordering request as input data, it performs data calculations and obtains a supermarket list as output.

[0220] Step 16:

[0221] The terminal displays the super list to the user. Specifically, the terminal displays the order screen.

[0222] Step 17:

[0223] The user orders materials, and the order data becomes the input data for the next step.

[0224] Step 18:

[0225] The server processes the order and sends a confirmation message to the terminal. The order request data is used as input and the order confirmation message is obtained as output.

[0226] For delivery:

[0227] Step 10:

[0228] The server generates a list of dishes available from nearby partner restaurants and sends it to the terminal. The input is the user's food selection data, and the output is a list of dishes available for delivery.

[0229] Step 11:

[0230] The terminal displays this to the user. Specifically, the recipe list is displayed on the user interface.

[0231] Step 12:

[0232] The user selects a specific restaurant and food item and confirms the order. The order data becomes the input data for the next step.

[0233] Step 13:

[0234] The terminal sends the order confirmation data to the server. Specifically, the order data is sent as an HTTP request.

[0235] Step 14:

[0236] The server processes the order, sends the estimated delivery time and order confirmation to the terminal, and notifies the user. The input data is the order data, and the output is the estimated delivery time and order confirmation message.

[0237] If you're eating at a restaurant:

[0238] Step 10:

[0239] The server generates a list of nearby affiliated restaurants and sends it to the terminal. The input data is the user's food selection data, and the output data is the restaurant list.

[0240] Step 11:

[0241] The terminal displays this to the user. As a specific operation, the restaurant list is displayed on the user interface.

[0242] Step 12:

[0243] The user selects a particular restaurant and enters reservation details, which serve as input data for the next step.

[0244] Step 13:

[0245] The terminal sends the reservation details data to the server. Specifically, the reservation data is sent as an HTTP request.

[0246] Step 14:

[0247] The server processes the reservation information and sends a confirmation message to the terminal to notify the user. The reservation details are input and the reservation confirmation message is output.

[0248] (Application example 1)

[0249] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0250] In recent years, users have been demanding a system that allows them to easily and quickly select the meal that best suits their mood that day, and then select the delivery method (cooking, delivery, or restaurant), arrange the meal, and pay for it all at once. However, existing systems that achieve this have issues such as insufficient suggestions for dishes that match the mood, insufficient arrangements and order processing depending on the delivery method, and a lack of high-value-added functions. A system that can effectively solve these issues is needed.

[0251] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0252] In this invention, the server includes a means for suggesting dishes based on the mood input by the user, a means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself." This allows the user to choose a dish that suits their mood that day and comprehensively handle the arrangements and payment according to the selected delivery method. Furthermore, the server also includes a means for ordering food from a nearby affiliated restaurant and arranging delivery if the user selects delivery, a means for making a reservation at a nearby affiliated restaurant if the user selects restaurant, and a means for selecting recipient information and a donation destination and processing a remittance if the user wants to treat someone or donate to a relief effort, thereby providing an even more convenient service.

[0253] The "means for suggesting dishes based on the mood input by the user" is a function for analyzing the mood information input by the user and suggesting suitable dishes based on the analysis results.

[0254] "A means for allowing the user to select the delivery method for the proposed dish from cooking it themselves, delivery, or restaurant" is a function in which the system presents the user with options for delivery methods, allowing the user to select from those options.

[0255] "When the user selects to cook it themselves, a means of displaying the corresponding recipe and a list of ingredients required, and arranging for the ingredients" is a function that, when the user selects to cook a dish themselves, displays the recipe and list of ingredients required for that dish, and even takes them through the process of purchasing the ingredients.

[0256] "Means of ordering food from nearby affiliated stores and arranging delivery when the user selects delivery" refers to a function in which, when the user selects delivery, the system orders food from nearby affiliated stores and arranges for delivery to the specified address.

[0257] "Means for making reservations at nearby affiliated restaurants when a user selects a restaurant" is a function that allows the system to process reservations at nearby affiliated restaurants when a user selects to eat at a restaurant.

[0258] "A means for selecting the recipient and donation destination and carrying out the money transfer process when treating someone or donating to a relief effort" is a function that allows a user to select the recipient and donation destination and carry out the money transfer process when treating someone or donating to a relief effort.

[0259] "Means for analyzing a user's mood input, suggesting dishes based on the analysis results, selecting a specific serving method based on the selected dish, displaying optimal delivery options, and processing the order and notifying the user of the delivery time if the user places an order" refers to a series of functions that analyze mood information entered by a user, suggest dishes based on the results of the analysis, select a serving method according to the dish selected by the user, display delivery options, process the order, and notify the user of the delivery time.

[0260] This invention is a system that allows users to easily find a dish that suits their mood of the day, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[0261] First, the user launches an application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. The server uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood based on the analysis results. The generated list of dishes is presented to the user via the device, from which the user can select their preferred dish.

[0262] Based on the user's choice of food, the server sends the corresponding delivery method (cook, delivery, restaurant) to the device, which then displays it to the user, who can then select the desired delivery method.

[0263] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[0264] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[0265] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[0266] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[0267] Furthermore, this system addresses the issue of food waste by allowing users to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being produced.

[0268] For example, if a user inputs "I want something a little spicy today" into the app, the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry specialty restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[0269] Example prompt: "Right now I'm feeling very relaxed and in the mood for something sweet and warm. Can you suggest a dish that would fit this mood?"

[0270] In this way, the system of the present invention provides comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments, thereby greatly improving user convenience.

[0271] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0272] Step 1:

[0273] The user launches the application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. This sends the user's mood information to the server, which then generates input data for analysis.

[0274] Step 2:

[0275] The server receives the user's mood information and analyzes it using natural language processing technology. The analysis involves breaking down the text data and extracting emotions and keywords. A generative AI model is used to generate a list of dishes that match the user's mood. The analysis results in a list of suggested dishes that match the user's mood.

[0276] Step 3:

[0277] The generated list of suggested dishes is sent from the server to the device. The device then presents this list to the user, allowing the user to visually check the suggested dishes. The user then selects their preferred dish from the presented list. This selection result is then sent back from the device to the server.

[0278] Step 4:

[0279] Based on the user's choice of food, the server generates a corresponding delivery method (cook, delivery, restaurant) for the proposed food and sends it to the device. The device then displays the delivery method options to the user, allowing the user to select the desired delivery method.

[0280] Step 5:

[0281] The user selects the desired delivery method from the options (make it yourself, delivery, restaurant) and selects it on the device. The selection result is sent to the server via the device. The server prepares the next step based on the delivery method selected by the user.

[0282] Step 6 (If you're building it yourself):

[0283] If the user selects "Make it yourself," the server generates a recipe and a list of ingredients for the selected dish and sends them to the device. The device displays this to the user and provides an "Arrange ingredients" button. When the user presses the "Arrange ingredients" button, a request is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for completing ingredient arrangements. Once the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[0284] Step 7 (for delivery):

[0285] If the user selects "Delivery," the server generates a list of dishes available from nearby partner restaurants and sends it to the device. The device presents this list to the user, who then selects a specific restaurant and confirms the order, which is then sent to the server. The server processes the order, calculates the estimated delivery time, and sends a confirmation message to the device.

[0286] Step 8 (for restaurants):

[0287] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The terminal presents this list to the user, who then selects a specific restaurant and enters reservation details, which are then sent to the server. The server processes the reservation information and sends a reservation confirmation to the terminal.

[0288] Step 9 (if giving or donating):

[0289] If the user selects to treat or donate, the server generates a list of recipients and donation recipients and sends it to the terminal. The terminal presents the list to the user, who then selects information and sets the amount to be transferred, and the information is sent to the server. The server then processes the transfer and displays a confirmation message on the terminal.

[0290] This system improves user convenience by suggesting meals that suit the user's mood and providing comprehensive support for arrangements and payment depending on the delivery method.

[0291] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0292] The present invention combines a system that suggests appropriate dishes based on the user's mood with an emotion engine that recognizes the user's emotions. This invention allows for a more precise understanding of the user's emotional state, and allows for the selection of dish suggestions and serving methods based on that understanding.

[0293] Mood and emotion analysis and food suggestions

[0294] The user launches the app and inputs their mood for the day. For example, they might input "I'm feeling depressed today." The device then sends the user's input to the emotion engine, which analyzes the user's input text and recognizes their emotional state.

[0295] The server uses a natural language processing engine to analyze the user's mood, and at the same time, recognizes their emotional state through an emotion engine. For example, when someone says "I'm feeling depressed," the server recognizes the emotion "sad."

[0296] Based on the results of mood and emotion analysis, the server generates a list of recipe suggestions that take into account the user's emotional state, such as suggesting dishes like "warm soup" or "comfort food."

[0297] Select delivery method

[0298] When the user selects their preferred dish from a list of candidate dishes, the server generates a delivery method (cook it yourself, delivery, restaurant) and presents it to the user via their terminal.

[0299] How to make it yourself

[0300] When the user selects "Make it yourself" as the delivery method, the server generates a recipe for the dish and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, the device sends an ingredient arrangement request to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for arrangements. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device. The device then displays the confirmation message to the user.

[0301] Delivery process

[0302] When the user selects "Delivery" as the delivery method, the server generates a list of dishes from nearby partner restaurants and sends it to the terminal. When the user selects a specific restaurant and confirms the order, the terminal sends the order information to the server. The server processes the order and calculates the estimated delivery time. The estimated delivery time and order confirmation information are sent to the terminal and notified to the user.

[0303] Restaurant Processing

[0304] When the user selects "Restaurant" as the delivery method, the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user.

[0305] High-value-added features

[0306] This system also includes functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates information about the recipient and a list of donation recipients and sends them to the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and sends a confirmation message to the terminal. The terminal then displays the confirmation message to the user.

[0307] Addressing the food waste problem

[0308] The system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes suggested, making it possible to avoid excess food.

[0309] Specific examples

[0310] For example, if a user inputs "I'm feeling down today," the server analyzes it and recognizes emotions such as "sad." Based on the user's emotional state, the server suggests "hot soup" or "comfort food." If the user selects "hot soup" and "delivery" as the delivery method, the soup can be ordered from a nearby affiliated store and delivered. If the user selects "make it yourself," the recipe and list of ingredients are displayed, and the user can order the ingredients right away.

[0311] In this way, the present invention comprehensively supports the selection of meals based on the user's mood and emotions, the selection of delivery methods, arrangements, and payment, thereby increasing user convenience and satisfaction.

[0312] The processing flow will be explained below.

[0313] Mood and sentiment analysis and food suggestion processing steps

[0314] Step 1:

[0315] The user launches the app and enters their mood for the day, for example, "I'm feeling depressed today."

[0316] Step 2:

[0317] The terminal sends the user's input to the emotion engine.

[0318] Step 3:

[0319] The emotion engine analyzes the user's input text and recognizes their emotional state. In this case, it recognizes the emotion "sad" from the input "I'm feeling depressed."

[0320] Step 4:

[0321] The terminal transmits the user's input and the emotion engine's recognition results to the server.

[0322] Step 5:

[0323] The server uses a natural language processing engine to analyze the user's mood and also takes into account the results of the emotion engine to generate a list of recipe candidates.

[0324] Step 6:

[0325] The server sends the generated list of dish candidates to the terminal.

[0326] Step 7:

[0327] The device will display a list of food suggestions to the user, such as "hot soup" or "comfort food."

[0328] Step 8:

[0329] The user selects "warm soup" from the displayed food options and taps the "Select" button.

[0330] Delivery Method Selection Process Steps

[0331] Step 9:

[0332] The terminal transmits the user's selection to the server.

[0333] Step 10:

[0334] The server generates available delivery methods (make-it-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[0335] Step 11:

[0336] The device will display options for delivery to the user, such as "Make it yourself," "Delivery," or "Restaurant."

[0337] Specific processing steps if you make it yourself

[0338] Step 12:

[0339] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[0340] Step 13:

[0341] The terminal transmits the user's selection to the server.

[0342] Step 14:

[0343] The server generates a recipe and a list of ingredients for the selected dish and sends them to the terminal.

[0344] Step 15:

[0345] The terminal displays the recipe and ingredients list to the user.

[0346] Step 16:

[0347] The user taps the "Arrange Materials" button.

[0348] Step 17:

[0349] The terminal sends a material arrangement request to the server.

[0350] Step 18:

[0351] The server generates a list of nearby supermarkets and online supermarkets and sends a screen for making arrangements to the terminal.

[0352] Step 19:

[0353] The terminal displays a list of supermarkets to the user.

[0354] Step 20:

[0355] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[0356] Step 21:

[0357] The terminal sends the order information to the server.

[0358] Step 22:

[0359] The server processes the order and sends a confirmation message to the terminal.

[0360] Step 23:

[0361] The terminal displays a confirmation message to the user.

[0362] Specific processing steps for delivery

[0363] Step 12:

[0364] The user selects "Delivery" as the delivery method and taps the "Next" button.

[0365] Step 13:

[0366] The terminal transmits the user's selection to the server.

[0367] Step 14:

[0368] The server generates a list of dishes that can be provided by nearby affiliated stores and transmits it to the terminal.

[0369] Step 15:

[0370] The terminal displays a list of affiliated stores to the user.

[0371] Step 16:

[0372] The user selects a specific store and places an order.

[0373] Step 17:

[0374] The terminal sends the order information to the server.

[0375] Step 18:

[0376] The server processes the order and calculates the estimated delivery time.

[0377] Step 19:

[0378] The server sends the estimated delivery time and order confirmation to the terminal.

[0379] Step 20:

[0380] The terminal notifies the user of the delivery time and order confirmation.

[0381] Specific processing steps for restaurants

[0382] Step 12:

[0383] The user selects "Restaurant" as the delivery method and taps the "Next" button.

[0384] Step 13:

[0385] The terminal transmits the user's selection to the server.

[0386] Step 14:

[0387] The server generates a list of nearby affiliated restaurants and sends it to the terminal.

[0388] Step 15:

[0389] The terminal displays a list of affiliated restaurants to the user.

[0390] Step 16:

[0391] The user selects a particular restaurant and enters reservation details.

[0392] Step 17:

[0393] The terminal transmits the reservation information to the server.

[0394] Step 18:

[0395] The server processes the reservation information and sends a reservation confirmation to the terminal.

[0396] Step 19:

[0397] The terminal displays a reservation confirmation to the user.

[0398] In this way, the system can increase user satisfaction and convenience by performing a consistent process from selection of delivery method, arrangement, and payment based on the user's mood and emotions.

[0399] Example 2

[0400] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0401] In modern society, there is a demand for systems that can enhance user convenience and satisfaction by suggesting meals that suit individual users' moods and emotions and selecting appropriate delivery methods. However, conventional systems have difficulty precisely analyzing users' moods and emotions and selecting optimal meal suggestions and delivery methods based on that analysis. In addition, to address the food waste issue, there is a need for a function that adjusts the amount of food consumed to prevent excess ingredients from being generated.

[0402] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting dishes based on the mood and emotions input by the user, a means for allowing the user to select the delivery method for the suggested dish from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and list of necessary ingredients when the user selects "make it yourself," and arranging for the ingredients. This makes it possible to suggest optimal dishes and select delivery methods based on the user's mood and emotions, and to address the food waste issue.

[0403] "User" refers to an individual or organization that uses the system.

[0404] "Mood" refers to the psychological and emotional state that a user is feeling at that time.

[0405] "Cooking" refers to food prepared using ingredients.

[0406] "Suggestion" refers to the options and ideas the system offers to the user.

[0407] "Delivery method" refers to the method by which the food is provided to the user, including options such as cook-it-yourself, delivery, and restaurant.

[0408] "Cook it yourself" refers to the user cooking the food themselves.

[0409] "Delivery" refers to a service that delivers food.

[0410] "Restaurant" means a food establishment that serves food.

[0411] A "recipe" is a set of instructions that explains how to prepare a dish.

[0412] An "ingredient list" refers to a list of ingredients needed to make a dish.

[0413] "Arrangements" refers to preparing and ordering needed supplies and services.

[0414] "Affiliated stores" refer to stores that provide services in cooperation with the system.

[0415] "Reservation" means applying in advance to use the Service at a specific date and time.

[0416] "Remittance" refers to sending money to another person.

[0417] The "food waste problem" refers to the social and economic problems caused by food ingredients and food going to waste.

[0418] "Natural language processing" refers to the technology that enables computers to understand and process human language.

[0419] "Emotion recognition" refers to the technology of analyzing and recognizing emotions from a user's text or voice.

[0420] The present invention is a system that suggests appropriate dishes based on the user's mood and emotions and provides a method for obtaining these dishes. This system is realized through interactions between a server, a terminal, and a user.

[0421] System configuration

[0422] This system involves the user inputting their mood and emotions, the server analyzing their emotions and suggesting dishes, and various methods of serving dishes.

[0423] 1. User input of mood and emotion

[0424] The user launches the application on their smartphone or other device and inputs their mood or emotion for the day in text. For example, they might say, "I'm feeling depressed today." This input data is then sent from the device to the server.

[0425] 2. Emotion analysis and recipe suggestions by the server

[0426] The server analyzes the received user input data using a natural language processing (NLP) engine and an emotion recognition engine. Specifically, the NLP engine (e.g., GPT-4 (registered trademark) from OpenAI (registered trademark)) analyzes the user's text, and the emotion recognition engine recognizes the user's mood and emotional state.

[0427] For example, if a user inputs "I'm feeling down today," the emotion recognition engine will recognize the emotion as "sad." Based on this analysis, the server will generate a list of food candidates. If the analysis result is "sad," dishes such as "warm soup" and "comfort food" will be suggested.

[0428] 3. Proposal of food serving methods

[0429] Once the user selects their preferred dish from the list of suggested dishes, the server then generates the delivery method (cook it yourself, delivery, restaurant) and sends it to the terminal.

[0430] Implementation of the provision method

[0431] How to make it yourself

[0432] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server then generates a list of nearby supermarkets and online supermarkets and displays an ordering screen on the device. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[0433] Delivery process

[0434] If the user selects "Delivery," the server generates a list of dishes from nearby partner restaurants and sends it to the device. Once the user selects a restaurant and a dish and confirms the order, the device sends the order information to the server. The server processes the order, calculates the estimated delivery time, sends it to the device, and notifies the user.

[0435] Restaurant Processing

[0436] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal to display to the user.

[0437] Addressing the food waste problem

[0438] This system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes it suggests, which helps prevent excess food from being produced.

[0439] Prompt Sentence Examples

[0440] We will build a system that will provide appropriate recipe suggestions in response to input such as "I'm feeling down today," and then suggest a serving method based on that. We will also explain how to handle delivery, restaurants, and home cooking. (The model includes an emotion recognition engine and an NLP engine.)

[0441] Through these functions, the present invention provides optimal recipe suggestions and serving methods based on the user's mood and emotions, greatly improving user convenience and satisfaction.

[0442] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0443] Step 1: Launch the app and enter your mood

[0444] A user launches an application on a smartphone or other device. The app provides the user with a text input field asking, "How are you feeling today?" The user enters "I'm feeling down today" and taps the submit button. This input data is sent from the device to the server. The specific input is text data, and the output is HTTPS communication to the server.

[0445] Step 2: Sentiment Analysis

[0446] The server stores the received user input data and sends it to the emotion engine. The emotion engine (specifically OpenAI's GPT-4) analyzes the input text and recognizes the emotional state. As a result of the analysis, it recognizes an emotion such as "sad" from the text "I'm feeling depressed today." The input is text data, and the output is the recognition result of the emotional state (e.g., "sad").

[0447] Step 3: Generate dish candidates

[0448] The server generates candidate dishes from a recipe database based on the emotion analysis results. In the example above, "warm soup" and "comfort food" are selected as candidate dishes corresponding to the emotion "sad." The server then sends the selected candidate dish list to the device. The input is the recognition result of the emotional state, and the output is a candidate dish list.

[0449] Step 4: Propose delivery method

[0450] The user selects "hot soup" from the list of food candidates. The device sends this selection data to the server. The server then generates options for delivery methods (make it yourself, delivery, restaurant) and sends them to the device. The input is the food selection data, and the output is the delivery method options. When the user selects "delivery" on the device, the device sends that information to the server.

[0451] Step 5: DIY

[0452] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. The device displays the recipe and list of ingredients. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays the ordering screen on the device. When the user orders ingredients, the server processes the order and sends a confirmation message to the device. The input is the "Make it yourself" selection and the ingredient arrangement request, and the output is the recipe, ingredient list, and ingredient order confirmation message.

[0453] Step 6: Processing in case of delivery

[0454] If the user selects "Delivery," the server generates a list of dishes from nearby affiliated restaurants and sends it to the terminal. When the user selects a restaurant and a dish and confirms the order, the terminal sends that information to the server. The server processes the order, calculates the estimated delivery time, and sends it to the terminal along with order confirmation information. The terminal notifies the user of the estimated delivery time and order confirmation information. The input is the "Delivery" selection and order information, and the output is the estimated delivery time and order confirmation information.

[0455] Step 7: Restaurant Case

[0456] If the user selects "Restaurant", the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a particular restaurant and enters reservation details, and the terminal sends that information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user. The input is the "Restaurant" selection and reservation details, and the output is the reservation confirmation information.

[0457] Step 8: Addressing the food waste issue

[0458] This system has the function of appropriately adjusting the amount of dishes and ingredients selected by the user to address the food waste issue. The server analyzes this data and adjusts the amount of dishes and ingredients suggested to avoid excess food. The input is the user's selected data, and the output is the adjusted dish and ingredient suggestions.

[0459] (Application example 2)

[0460] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0461] In modern society, there is a demand for systems to suggest appropriate dishes and determine how they are served based on the user's mood and emotions. However, conventional systems have difficulty accurately understanding the user's emotional state, and are therefore unable to make appropriate dish suggestions based on that. Furthermore, while there is a need to address the issue of food waste, current systems do not adequately consider this point. This calls for the development of new technologies to improve user satisfaction and reduce food waste.

[0462] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: [means for suggesting dishes based on the mood and emotion input by the user; [means for allowing the user to select the delivery method for the suggested dishes from cook-it-yourself, delivery, or restaurant; and [means for analyzing the mood and emotion input by the user using an emotion engine and a natural language processing engine and displaying appropriate delivery dish candidates.] This makes it possible to suggest dishes and select delivery methods that match the user's current emotional state, improving user satisfaction and addressing the issue of food waste.

[0463] "User" refers to an individual user of the system.

[0464] "Mood" refers to a temporary psychological state or emotion that a user has.

[0465] "Emotion" more specifically represents the user's psychological state and refers to an internal reaction based on the mood and state of the day.

[0466] "Cuisine Suggestions" refers to meal options and details provided based on the user's mood and emotions.

[0467] "Delivery method" refers to the means and options for delivering food to the user, including cooking it yourself, delivery, and choosing from a restaurant.

[0468] "Delivery" refers to a service that delivers the selected dish to a location specified by the user.

[0469] "Emotion engine" refers to a technical means for analyzing a user's input text and recognizing its emotional state.

[0470] "Natural language processing engine" refers to a technical means for analyzing text entered by a user and understanding its content.

[0471] "Dish suggestions" refer to suggested meal options based on the user's emotions and moods.

[0472] The "food waste problem" refers to the social and economic problems that arise when food ingredients and food are wasted.

[0473] An "ingredient list" is a list of ingredients needed to make a particular dish.

[0474] This invention is a system that analyzes the mood and emotions input by the user, and based on that, suggests appropriate dishes and selects how to serve them. The system is made up of the following components:

[0475] 1. System Program Configuration

[0476] The system consists of the following main modules:

[0477] Emotion Engine

[0478] Natural Language Processing Engine

[0479] Food suggestion module

[0480] Delivery method selection module

[0481] Order Processing Module

[0482] Emotion Engine

[0483] The emotion engine analyzes the text data entered by the user and recognizes their emotional state. The engine utilizes the TextBlob library in Python to accurately analyze the emotions in the text.

[0484] Natural Language Processing Engine

[0485] The natural language processing engine is used to analyze and understand the mood and emotions input by the user, which allows the system to determine what kind of food is appropriate based on the user's mood.

[0486] Food suggestion module

[0487] The recipe suggestion module suggests multiple recipe options to the user based on data obtained from the emotion engine and natural language processing engine. The user can then select from the suggested dishes to proceed to the next step.

[0488] Delivery method selection module

[0489] The delivery method selection module presents delivery methods for the dish selected by the user, such as cooking it yourself, delivery, or restaurant delivery. Once the user selects a delivery method, the appropriate processing is carried out.

[0490] Order Processing Module

[0491] The order processing module orders food from nearby partner restaurants and arranges delivery if the user selects delivery, and also makes reservations at nearby partner restaurants if the user selects a restaurant.

[0492] 2. System processing method and data calculation

[0493] The hardware used by the system is primarily a smartphone, on which an application is launched and which processes data in conjunction with a server.

[0494] Hardware used

[0495] Smartphone

[0496] Software used

[0497] Python

[0498] Flask

[0499] TextBlob

[0500] Data flow

[0501] 1. The user launches the smartphone app and enters their current mood and a message.

[0502] 2. The entered data is sent to the server, where it is analyzed using an emotion engine and natural language processing engine.

[0503] 3. Based on the analysis results, the server generates a list of candidate dishes and presents it to the user.

[0504] 4. Once the user selects a dish and decides how it will be served, the server uses that information to perform the corresponding process (display recipe, order delivery, make restaurant reservation).

[0505] 3. Specific Examples

[0506] For example, if a user inputs "I'm tired from work today," the system will recognize the emotion as "tired" and suggest food options such as energy drinks and coffee. If the user selects from these options and chooses delivery, the system will order the selected food from a partner restaurant and deliver it to the user's specified location.

[0507] Prompt Sentence Examples

[0508] Please perform sentiment analysis on the following text: "I'm tired from work today."

[0509] Expected emotion: "tired"

[0510] Suggest recipes based on your emotional state:

[0511] Emotional state: "tired"

[0512] Food options: ["Energy Drink", "Coffee"]

[0513] In this way, the present invention realizes appropriate dish suggestions based on the user's mood and emotions, and efficient selection and arrangement of serving methods.

[0514] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0515] Step 1:

[0516] The user starts the smartphone app and inputs their current mood and a message. The input data becomes text data that indicates the user's mood and emotions.

[0517] Input: Text that indicates the user's mood or emotion (e.g., "I'm tired from work today")

[0518] Output: Text data

[0519] Specific operation: The user enters their mood or emotion in text format into the app's input field and presses the send button.

[0520] Step 2:

[0521] The device sends the input text data to the server, which receives the text data and analyzes it using an emotion engine and natural language processing engine.

[0522] Input: Text data

[0523] Output: Analysis results (emotional state)

[0524] Specific operation: The terminal sends text data to the server via an HTTP request, and the server receives the data.

[0525] Step 3:

[0526] The server analyzes the text data using an emotion engine (TextBlob) to recognize the user's emotional state and generates analysis results based on the emotional state.

[0527] Input: Text data

[0528] Output: Emotional state (e.g. "tired")

[0529] What it does: The server uses the TextBlob library to sentiment analyze the text and determine its emotional state: positive, negative, or neutral.

[0530] Step 4:

[0531] The server generates an appropriate dish candidate list using a natural language processing engine based on the emotional state, the dish candidate list including dish options that are suitable for the user's emotional state.

[0532] Input: Emotional state

[0533] Output: List of food candidates (e.g. "energy drink" "coffee")

[0534] Specific operation: The server extracts appropriate dishes from a database of dish candidates according to the emotional state and generates a list.

[0535] Step 5:

[0536] The server sends the generated list of dish candidates to the terminal, which displays it to the user, who then selects a specific dish from the displayed list of dish candidates.

[0537] Input: List of food candidates

[0538] Output: The dish selected by the user

[0539] Specific operation: The device displays a list of candidate dishes on the screen, and the user selects a dish from the list.

[0540] Step 6:

[0541] For the dish selected by the user, the terminal displays a screen for selecting the delivery method (make it yourself, delivery, restaurant), and the user selects one.

[0542] Input: The dish selected by the user

[0543] Output: Delivery method selected by the user

[0544] Specific behavior: A pop-up will appear with options for delivery method, and the user can tap to select it.

[0545] Step 7:

[0546] The server executes the corresponding process based on the delivery method selected by the user. For example, if delivery is selected, the server sends the order to a nearby partner store and arranges for delivery.

[0547] Input: Delivery method selected by the user

[0548] Output: Order details and delivery schedule

[0549] Specific operation: The server sends the order information to the selected store, calculates the estimated delivery time, and displays it on the terminal.

[0550] Step 8:

[0551] The terminal receives the order details and delivery schedule from the server and notifies the user. Once delivery is complete, the user can collect the meal.

[0552] Input: Order details and delivery schedule

[0553] Output: User notified and delivery completed

[0554] Specific operation: The device displays a notification to the user to inform them that the delivery is complete. The user then receives the food from the delivery person.

[0555] In this way, through a series of processing steps, the system efficiently suggests appropriate dishes based on the user's mood and emotions, and how to serve them.

[0556] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0557] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0558] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0559] [Second embodiment]

[0560] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0561] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0562] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0563] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0564] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0565] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0566] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0567] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0568] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0569] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0570] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0571] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0572] This invention is a system that allows users to easily find a dish that suits their mood at the time, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[0573] Specific embodiments are described below.

[0574] Mood analysis and cooking suggestions

[0575] When a user launches the app and enters their mood for the day, the device sends the text to a server. The server then uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood. The list is then presented to the user via their device, allowing them to select their favorite dish.

[0576] Select delivery method

[0577] When the user selects a dish, the server sends the corresponding delivery method (cook it yourself, delivery, restaurant) to the terminal. The terminal displays the information to the user, who then selects the desired delivery method.

[0578] How to make it yourself

[0579] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[0580] Delivery process

[0581] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[0582] What to do if you're eating at a restaurant

[0583] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[0584] High-value-added features

[0585] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[0586] Addressing the food waste problem

[0587] The system also addresses the issue of food waste, making it possible to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being used.

[0588] Specific examples

[0589] For example, if a user inputs into the app, "I want something a little spicy today," the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[0590] In this way, the present invention is a system that greatly improves user convenience by providing comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments.

[0591] The processing flow will be explained below.

[0592] Step 1:

[0593] The user launches the app and inputs their mood for the day. For example, they might input, "I want to eat something a little spicy today."

[0594] Step 2:

[0595] The terminal receives the user's input and transmits the text data to the server.

[0596] Step 3:

[0597] The server passes the received text data to a natural language processing engine to analyze the user's mood.

[0598] Step 4:

[0599] Based on the analysis results, the server generates a list of dishes that match the user's mood, such as "curry" or "tacos."

[0600] Step 5:

[0601] The server sends the generated list of dish candidates to the terminal.

[0602] Step 6:

[0603] The device displays a list of possible dishes to the user, such as "curry" or "tacos."

[0604] Step 7:

[0605] The user selects "curry" from the displayed food options and taps the "Select" button.

[0606] Step 8:

[0607] The terminal transmits the user's selection to the server.

[0608] Step 9:

[0609] The server generates available delivery methods (make-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[0610] Step 10:

[0611] The device displays options for delivery to the user, such as "make it yourself," "delivery," or "restaurant."

[0612] Step 11:

[0613] The user selects "Delivery" as the delivery method and taps the "Next" button.

[0614] Step 12:

[0615] The terminal transmits the user's selection to the server.

[0616] Step 13:

[0617] The server generates a list of nearby affiliated stores that can provide "curry" and sends it to the terminal.

[0618] Step 14:

[0619] The terminal displays a list of affiliated restaurants to the user. For example, it displays options such as "Curry Restaurant A" and "Curry Restaurant B."

[0620] Step 15:

[0621] The user selects "Curry Restaurant A," checks the order details, and then taps the "Confirm Order" button.

[0622] Step 16:

[0623] The terminal sends the order information to the server.

[0624] Step 17:

[0625] The server processes the order and calculates the estimated delivery time.

[0626] Step 18:

[0627] The server sends the estimated delivery time and order confirmation to the terminal.

[0628] Step 19:

[0629] The terminal notifies the user of the delivery time and order confirmation.

[0630] Building it yourself (another scenario)

[0631] Step 11:

[0632] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[0633] Step 12:

[0634] The terminal transmits the user's selection to the server.

[0635] Step 13:

[0636] The server generates a recipe for "curry" and a list of necessary ingredients, and sends them to the terminal.

[0637] Step 14:

[0638] The terminal displays the recipe and ingredients list to the user.

[0639] Step 15:

[0640] The user taps the "Arrange Materials" button.

[0641] Step 16:

[0642] The terminal sends a material arrangement request to the server.

[0643] Step 17:

[0644] The server generates a list of nearby supermarkets and online supermarkets and sends it to the terminal.

[0645] Step 18:

[0646] The terminal displays a list of supermarkets to the user.

[0647] Step 19:

[0648] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[0649] Step 20:

[0650] The terminal sends the order information to the server.

[0651] Step 21:

[0652] The server processes the order and sends a confirmation message to the terminal.

[0653] Step 22:

[0654] The terminal displays an order confirmation message to the user.

[0655] In this way, this system greatly enhances user convenience by consistently supporting the selection of meals that suit the user's mood, the selection of the delivery method, arrangements, and payment.

[0656] Example 1

[0657] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0658] Conventional meal recommendation systems often lack the functionality to not only suggest dishes that suit the user's mood, but also comprehensively support the selection of how the meal will be served, as well as the specific arrangements and payment procedures. Furthermore, when preparing the meal yourself, the process of preparing ingredients is complicated, which increases the user's workload. Furthermore, these systems do not adequately address the issue of food waste, resulting in excess food. Thus, there is a need for a meal recommendation system that aims to achieve both user convenience and sustainability.

[0659] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0660] In this invention, the server includes: [means for suggesting dishes based on the mood input by the user; [means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant"; and [means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself."] This makes it possible [to suggest dishes based on the mood input by the user, and comprehensively select the delivery method, make specific arrangements, and make payment].

[0661] "User" refers to an end user who uses the system and inputs their mood for the day and the desired delivery method.

[0662] The term "server" refers to an information processing device that receives and processes data entered by a user or a virtual server on a network.

[0663] "Terminal" refers to a device that allows a user to access the system and input their mood, select suggested dishes, and select serving methods.

[0664] "Suggesting" refers to generating and presenting a list of appropriate dishes based on the mood data entered by the user.

[0665] "Delivery method" refers to the means by which users can obtain and consume food, and refers to three methods: cooking it yourself, delivery, or restaurant.

[0666] A "recipe" is a set of instructions for cooking a dish, including the necessary ingredients and steps.

[0667] "Ingredient list" refers to the list of ingredients needed to prepare the selected dish.

[0668] "Arranging ingredients" refers to preparing and ordering the necessary ingredients.

[0669] "Delivery" refers to the delivery of the food selected by the user from a nearby affiliated restaurant via a delivery service.

[0670] "Restaurant" refers to a restaurant that serves the food selected by the user.

[0671] "Affiliated stores" refer to affiliated stores that provide food in cooperation with the system.

[0672] "Order" refers to a request to purchase a dish or ingredients selected by a User.

[0673] "Remittance processing" refers to the procedure for transferring money when a user treats someone else or donates to relief efforts.

[0674] "Natural language processing technology" refers to artificial intelligence technology that analyzes text data and helps it understand its meaning.

[0675] "Food waste" refers to food that is discarded without being consumed.

[0676] The present invention relates to a system that proposes dishes tailored to the user's mood, and handles the selection, arrangement, and payment of the delivery method. This system uses multiple hardware and software components to perform specific data processing and calculations. Specific embodiments are described below.

[0677] System Configuration

[0678] User terminal

[0679] The device on which the user launches the app (smartphone, tablet, PC, etc.)

[0680] Responsible for sending input data and receiving and displaying display content

[0681] server

[0682] Analysis and recommendations using natural language processing technology

[0683] Specific software used for mood analysis: Google Cloud Natural Language API

[0684] Processing flow

[0685] 1. Mood input

[0686] The user launches the app and enters their mood for the day in text.

[0687] The device transmits the mood data to the server.

[0688] 2. Mood analysis and recipe suggestions

[0689] The server uses natural language processing technology (Google Cloud Natural Language API) to analyze the user's mood.

[0690] The server generates a list of suggested dishes based on the analysis results.

[0691] The terminal displays the recipe list to the user.

[0692] 3. Selection of delivery method

[0693] When the user selects a dish, the server generates the corresponding delivery method (make-yourself, delivery, restaurant).

[0694] The terminal displays the provision methods to the user, and the user selects one.

[0695] If you make it yourself

[0696] The server generates a recipe and a list of ingredients for the selected dish.

[0697] The terminal displays the recipe and ingredients list to the user.

[0698] When a user requests material arrangement, the server generates a list of nearby supermarkets or online supermarkets (for example, the API of an online supermarket).

[0699] When a user orders ingredients, the server processes the order and displays a confirmation message.

[0700] For delivery

[0701] The server generates a list of dishes from nearby partner stores (stores that offer delivery).

[0702] The terminal displays this to the user, who then selects the food and restaurant and places the order.

[0703] The server processes the order and sends an estimated delivery time and order confirmation to the terminal.

[0704] In the case of a restaurant

[0705] The server generates a list of nearby affiliated restaurants.

[0706] The terminal displays this to the user, who then selects a restaurant and enters reservation details.

[0707] The server processes the reservation and sends a confirmation message to the terminal.

[0708] High-value-added features

[0709] If the user chooses to treat others or make a donation, the server generates information about the other person and a list of donation recipients.

[0710] The terminal displays this to the user, and once the remittance amount is set, the server processes the remittance and sends a confirmation message.

[0711] Addressing the food waste problem

[0712] The server adjusts the amount of ingredients based on the user's choice of food and number of people.

[0713] The device displays the adjusted ingredient list to the user, ensuring no excess ingredients are used.

[0714] Specific examples

[0715] For example, if a user inputs into the app, "I want to eat something spicy today," the server analyzes the data and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby affiliated curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the ingredients can be ordered directly.

[0716] Prompt Sentence Examples

[0717] Below are some examples of prompts to input to the generative AI model.

[0718] "User says they want something spicy today. Suggest a dish based on that and offer options for delivery, restaurants, or cook-it-yourself."

[0719] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0720] Step 1:

[0721] The user starts the app and enters their mood for the day in text. This text becomes the input data.

[0722] Step 2:

[0723] The device receives mood data entered by the user and sends the data to the server. The specific operation of the device is to send text data to the server as an HTTP request.

[0724] Step 3:

[0725] The server uses natural language processing technology to analyze the received mood data. This analysis generates a list of dishes that match the user's mood. Using the user's mood text as input data, it performs data calculations using tools such as the Google Cloud Natural Language API, and obtains a list of dishes as output.

[0726] Step 4:

[0727] The server sends the generated dish list to the device. Specifically, it encodes the dish list in JSON format and sends it to the device as an HTTP response.

[0728] Step 5:

[0729] The device receives the recipe list from the server and displays it to the user. The displayed recipe list becomes the output data. The device parses the data and displays it on the user interface.

[0730] Step 6:

[0731] The user selects a favorite dish from the list of dishes. This selection becomes the input data for the next process.

[0732] Step 7:

[0733] Based on the user's food selection, the server generates the corresponding delivery method (cook, delivery, restaurant) and sends it to the terminal. The input is the user's food selection data, and the output is a list of delivery methods.

[0734] Step 8:

[0735] The terminal displays a list of delivery methods to the user, specifically, a delivery method selection screen.

[0736] Step 9:

[0737] The user selects the delivery method (make it yourself, delivery, restaurant). The selected delivery method becomes the input data for the next step.

[0738] If you're making it yourself:

[0739] Step 10:

[0740] The server generates a recipe and a list of ingredients for the selected dish. The input is the user's dish selection data, and the output is the recipe and the list of ingredients.

[0741] Step 11:

[0742] The server sends the recipe and ingredient list to the device, encoding the data in JSON format and sending it as an HTTP response.

[0743] Step 12:

[0744] The terminal displays this to the user. Specifically, the recipe and ingredient list are displayed on the user interface.

[0745] Step 13:

[0746] The user presses the "Arrange materials" button, which becomes the input data for the next step.

[0747] Step 14:

[0748] The terminal sends a material arrangement request to the server. Specifically, the request data is sent as an HTTP request.

[0749] Step 15:

[0750] The server generates a list of nearby supermarkets and online supermarkets, and sends the ordering screen to the terminal. Using the user's location information and material ordering request as input data, it performs data calculations and obtains a supermarket list as output.

[0751] Step 16:

[0752] The terminal displays the super list to the user. Specifically, the terminal displays the order screen.

[0753] Step 17:

[0754] The user orders materials, and the order data becomes the input data for the next step.

[0755] Step 18:

[0756] The server processes the order and sends a confirmation message to the terminal. The order request data is used as input and the order confirmation message is obtained as output.

[0757] For delivery:

[0758] Step 10:

[0759] The server generates a list of dishes available from nearby partner restaurants and sends it to the terminal. The input is the user's food selection data, and the output is a list of dishes available for delivery.

[0760] Step 11:

[0761] The terminal displays this to the user. Specifically, the recipe list is displayed on the user interface.

[0762] Step 12:

[0763] The user selects a specific restaurant and food item and confirms the order. The order data becomes the input data for the next step.

[0764] Step 13:

[0765] The terminal sends the order confirmation data to the server. Specifically, the order data is sent as an HTTP request.

[0766] Step 14:

[0767] The server processes the order, sends the estimated delivery time and order confirmation to the terminal, and notifies the user. The input data is the order data, and the output is the estimated delivery time and order confirmation message.

[0768] If you're eating at a restaurant:

[0769] Step 10:

[0770] The server generates a list of nearby affiliated restaurants and sends it to the terminal. The input data is the user's food selection data, and the output data is the restaurant list.

[0771] Step 11:

[0772] The terminal displays this to the user. As a specific operation, the restaurant list is displayed on the user interface.

[0773] Step 12:

[0774] The user selects a particular restaurant and enters reservation details, which serve as input data for the next step.

[0775] Step 13:

[0776] The terminal sends the reservation details data to the server. Specifically, the reservation data is sent as an HTTP request.

[0777] Step 14:

[0778] The server processes the reservation information and sends a confirmation message to the terminal to notify the user. The reservation details are input and the reservation confirmation message is output.

[0779] (Application example 1)

[0780] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0781] In recent years, users have been demanding a system that allows them to easily and quickly select the meal that best suits their mood that day, and then select the delivery method (cooking, delivery, or restaurant), arrange the meal, and pay for it all at once. However, existing systems that achieve this have issues such as insufficient suggestions for dishes that match the mood, insufficient arrangements and order processing depending on the delivery method, and a lack of high-value-added functions. A system that can effectively solve these issues is needed.

[0782] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0783] In this invention, the server includes a means for suggesting dishes based on the mood input by the user, a means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself." This allows the user to choose a dish that suits their mood that day and comprehensively handle the arrangements and payment according to the selected delivery method. Furthermore, the server also includes a means for ordering food from a nearby affiliated restaurant and arranging delivery if the user selects delivery, a means for making a reservation at a nearby affiliated restaurant if the user selects restaurant, and a means for selecting recipient information and a donation destination and processing a remittance if the user wants to treat someone or donate to a relief effort, thereby providing an even more convenient service.

[0784] The "means for suggesting dishes based on the mood input by the user" is a function for analyzing the mood information input by the user and suggesting suitable dishes based on the analysis results.

[0785] "A means for allowing the user to select the delivery method for the proposed dish from cooking it themselves, delivery, or restaurant" is a function in which the system presents the user with options for delivery methods, allowing the user to select from those options.

[0786] "When the user selects to cook it themselves, a means of displaying the corresponding recipe and a list of ingredients required, and arranging for the ingredients" is a function that, when the user selects to cook a dish themselves, displays the recipe and list of ingredients required for that dish, and even takes them through the process of purchasing the ingredients.

[0787] "Means of ordering food from nearby affiliated stores and arranging delivery when the user selects delivery" refers to a function in which, when the user selects delivery, the system orders food from nearby affiliated stores and arranges for delivery to the specified address.

[0788] "Means for making reservations at nearby affiliated restaurants when a user selects a restaurant" is a function that allows the system to process reservations at nearby affiliated restaurants when a user selects to eat at a restaurant.

[0789] "A means for selecting the recipient and donation destination and carrying out the money transfer process when treating someone or donating to a relief effort" is a function that allows a user to select the recipient and donation destination and carry out the money transfer process when treating someone or donating to a relief effort.

[0790] "Means for analyzing a user's mood input, suggesting dishes based on the analysis results, selecting a specific serving method based on the selected dish, displaying optimal delivery options, and processing the order and notifying the user of the delivery time if the user places an order" refers to a series of functions that analyze mood information entered by a user, suggest dishes based on the results of the analysis, select a serving method according to the dish selected by the user, display delivery options, process the order, and notify the user of the delivery time.

[0791] This invention is a system that allows users to easily find a dish that suits their mood of the day, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[0792] First, the user launches an application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. The server uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood based on the analysis results. The generated list of dishes is presented to the user via the device, from which the user can select their preferred dish.

[0793] Based on the user's choice of food, the server sends the corresponding delivery method (cook, delivery, restaurant) to the device, which then displays it to the user, who can then select the desired delivery method.

[0794] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[0795] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[0796] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[0797] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[0798] Furthermore, this system addresses the issue of food waste by allowing users to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being produced.

[0799] For example, if a user inputs "I want something a little spicy today" into the app, the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry specialty restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[0800] Example prompt: "Right now I'm feeling very relaxed and in the mood for something sweet and warm. Can you suggest a dish that would fit this mood?"

[0801] In this way, the system of the present invention provides comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments, thereby greatly improving user convenience.

[0802] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0803] Step 1:

[0804] The user launches the application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. This sends the user's mood information to the server, which then generates input data for analysis.

[0805] Step 2:

[0806] The server receives the user's mood information and analyzes it using natural language processing technology. The analysis involves breaking down the text data and extracting emotions and keywords. A generative AI model is used to generate a list of dishes that match the user's mood. The analysis results in a list of suggested dishes that match the user's mood.

[0807] Step 3:

[0808] The generated list of suggested dishes is sent from the server to the device. The device then presents this list to the user, allowing the user to visually check the suggested dishes. The user then selects their preferred dish from the presented list. This selection result is then sent back from the device to the server.

[0809] Step 4:

[0810] Based on the user's choice of food, the server generates a corresponding delivery method (cook, delivery, restaurant) for the proposed food and sends it to the device. The device then displays the delivery method options to the user, allowing the user to select the desired delivery method.

[0811] Step 5:

[0812] The user selects the desired delivery method from the options (make it yourself, delivery, restaurant) and selects it on the device. The selection result is sent to the server via the device. The server prepares the next step based on the delivery method selected by the user.

[0813] Step 6 (If you're building it yourself):

[0814] If the user selects "Make it yourself," the server generates a recipe and a list of ingredients for the selected dish and sends them to the device. The device displays this to the user and provides an "Arrange ingredients" button. When the user presses the "Arrange ingredients" button, a request is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for completing ingredient arrangements. Once the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[0815] Step 7 (for delivery):

[0816] If the user selects "Delivery," the server generates a list of dishes available from nearby partner restaurants and sends it to the device. The device presents this list to the user, who then selects a specific restaurant and confirms the order, which is then sent to the server. The server processes the order, calculates the estimated delivery time, and sends a confirmation message to the device.

[0817] Step 8 (for restaurants):

[0818] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The terminal presents this list to the user, who then selects a specific restaurant and enters reservation details, which are then sent to the server. The server processes the reservation information and sends a reservation confirmation to the terminal.

[0819] Step 9 (if giving or donating):

[0820] If the user selects to treat or donate, the server generates a list of recipients and donation recipients and sends it to the terminal. The terminal presents the list to the user, who then selects information and sets the amount to be transferred, and the information is sent to the server. The server then processes the transfer and displays a confirmation message on the terminal.

[0821] This system improves user convenience by suggesting meals that suit the user's mood and providing comprehensive support for arrangements and payment depending on the delivery method.

[0822] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0823] The present invention combines a system that suggests appropriate dishes based on the user's mood with an emotion engine that recognizes the user's emotions. This invention allows for a more precise understanding of the user's emotional state, and allows for the selection of dish suggestions and serving methods based on that understanding.

[0824] Mood and emotion analysis and food suggestions

[0825] The user launches the app and inputs their mood for the day. For example, they might input "I'm feeling depressed today." The device then sends the user's input to the emotion engine, which analyzes the user's input text and recognizes their emotional state.

[0826] The server uses a natural language processing engine to analyze the user's mood, and at the same time, recognizes their emotional state through an emotion engine. For example, when someone says "I'm feeling depressed," the server recognizes the emotion "sad."

[0827] Based on the results of mood and emotion analysis, the server generates a list of recipe suggestions that take into account the user's emotional state, such as suggesting dishes like "warm soup" or "comfort food."

[0828] Select delivery method

[0829] When the user selects their preferred dish from a list of candidate dishes, the server generates a delivery method (cook it yourself, delivery, restaurant) and presents it to the user via their terminal.

[0830] How to make it yourself

[0831] When the user selects "Make it yourself" as the delivery method, the server generates a recipe for the dish and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, the device sends an ingredient arrangement request to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for arrangements. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device. The device then displays the confirmation message to the user.

[0832] Delivery process

[0833] When the user selects "Delivery" as the delivery method, the server generates a list of dishes from nearby partner restaurants and sends it to the terminal. When the user selects a specific restaurant and confirms the order, the terminal sends the order information to the server. The server processes the order and calculates the estimated delivery time. The estimated delivery time and order confirmation information are sent to the terminal and notified to the user.

[0834] Restaurant Processing

[0835] When the user selects "Restaurant" as the delivery method, the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user.

[0836] High-value-added features

[0837] This system also includes functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates information about the recipient and a list of donation recipients and sends them to the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and sends a confirmation message to the terminal. The terminal then displays the confirmation message to the user.

[0838] Addressing the food waste problem

[0839] The system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes suggested, making it possible to avoid excess food.

[0840] Specific examples

[0841] For example, if a user inputs "I'm feeling down today," the server analyzes it and recognizes emotions such as "sad." Based on the user's emotional state, the server suggests "hot soup" or "comfort food." If the user selects "hot soup" and "delivery" as the delivery method, the soup can be ordered from a nearby affiliated store and delivered. If the user selects "make it yourself," the recipe and list of ingredients are displayed, and the user can order the ingredients right away.

[0842] In this way, the present invention comprehensively supports the selection of meals based on the user's mood and emotions, the selection of delivery methods, arrangements, and payment, thereby increasing user convenience and satisfaction.

[0843] The processing flow will be explained below.

[0844] Mood and sentiment analysis and food suggestion processing steps

[0845] Step 1:

[0846] The user launches the app and enters their mood for the day, for example, "I'm feeling depressed today."

[0847] Step 2:

[0848] The terminal sends the user's input to the emotion engine.

[0849] Step 3:

[0850] The emotion engine analyzes the user's input text and recognizes their emotional state. In this case, it recognizes the emotion "sad" from the input "I'm feeling depressed."

[0851] Step 4:

[0852] The terminal transmits the user's input and the emotion engine's recognition results to the server.

[0853] Step 5:

[0854] The server uses a natural language processing engine to analyze the user's mood and also takes into account the results of the emotion engine to generate a list of recipe candidates.

[0855] Step 6:

[0856] The server sends the generated list of dish candidates to the terminal.

[0857] Step 7:

[0858] The device will display a list of food suggestions to the user, such as "hot soup" or "comfort food."

[0859] Step 8:

[0860] The user selects "warm soup" from the displayed food options and taps the "Select" button.

[0861] Delivery Method Selection Process Steps

[0862] Step 9:

[0863] The terminal transmits the user's selection to the server.

[0864] Step 10:

[0865] The server generates available delivery methods (make-it-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[0866] Step 11:

[0867] The device will display options for delivery to the user, such as "Make it yourself," "Delivery," or "Restaurant."

[0868] Specific processing steps if you make it yourself

[0869] Step 12:

[0870] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[0871] Step 13:

[0872] The terminal transmits the user's selection to the server.

[0873] Step 14:

[0874] The server generates a recipe and a list of ingredients for the selected dish and sends them to the terminal.

[0875] Step 15:

[0876] The terminal displays the recipe and ingredients list to the user.

[0877] Step 16:

[0878] The user taps the "Arrange Materials" button.

[0879] Step 17:

[0880] The terminal sends a material arrangement request to the server.

[0881] Step 18:

[0882] The server generates a list of nearby supermarkets and online supermarkets and sends a screen for making arrangements to the terminal.

[0883] Step 19:

[0884] The terminal displays a list of supermarkets to the user.

[0885] Step 20:

[0886] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[0887] Step 21:

[0888] The terminal sends the order information to the server.

[0889] Step 22:

[0890] The server processes the order and sends a confirmation message to the terminal.

[0891] Step 23:

[0892] The terminal displays a confirmation message to the user.

[0893] Specific processing steps for delivery

[0894] Step 12:

[0895] The user selects "Delivery" as the delivery method and taps the "Next" button.

[0896] Step 13:

[0897] The terminal transmits the user's selection to the server.

[0898] Step 14:

[0899] The server generates a list of dishes that can be provided by nearby affiliated stores and transmits it to the terminal.

[0900] Step 15:

[0901] The terminal displays a list of affiliated stores to the user.

[0902] Step 16:

[0903] The user selects a specific store and places an order.

[0904] Step 17:

[0905] The terminal sends the order information to the server.

[0906] Step 18:

[0907] The server processes the order and calculates the estimated delivery time.

[0908] Step 19:

[0909] The server sends the estimated delivery time and order confirmation to the terminal.

[0910] Step 20:

[0911] The terminal notifies the user of the delivery time and order confirmation.

[0912] Specific processing steps for restaurants

[0913] Step 12:

[0914] The user selects "Restaurant" as the delivery method and taps the "Next" button.

[0915] Step 13:

[0916] The terminal transmits the user's selection to the server.

[0917] Step 14:

[0918] The server generates a list of nearby affiliated restaurants and sends it to the terminal.

[0919] Step 15:

[0920] The terminal displays a list of affiliated restaurants to the user.

[0921] Step 16:

[0922] The user selects a particular restaurant and enters reservation details.

[0923] Step 17:

[0924] The terminal transmits the reservation information to the server.

[0925] Step 18:

[0926] The server processes the reservation information and sends a reservation confirmation to the terminal.

[0927] Step 19:

[0928] The terminal displays a reservation confirmation to the user.

[0929] In this way, the system can increase user satisfaction and convenience by performing a consistent process from selection of delivery method, arrangement, and payment based on the user's mood and emotions.

[0930] Example 2

[0931] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0932] In modern society, there is a demand for systems that can enhance user convenience and satisfaction by suggesting meals that suit individual users' moods and emotions and selecting appropriate delivery methods. However, conventional systems have difficulty precisely analyzing users' moods and emotions and selecting optimal meal suggestions and delivery methods based on that analysis. In addition, to address the food waste issue, there is a need for a function that adjusts the amount of food consumed to prevent excess ingredients from being generated.

[0933] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting dishes based on the mood and emotions input by the user, a means for allowing the user to select the delivery method for the suggested dish from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and list of necessary ingredients when the user selects "make it yourself," and arranging for the ingredients. This makes it possible to suggest optimal dishes and select delivery methods based on the user's mood and emotions, and to address the food waste issue.

[0934] "User" refers to an individual or organization that uses the system.

[0935] "Mood" refers to the psychological and emotional state that a user is feeling at that time.

[0936] "Cooking" refers to food prepared using ingredients.

[0937] "Suggestion" refers to the options and ideas the system offers to the user.

[0938] "Delivery method" refers to the method by which the food is provided to the user, including options such as cook-it-yourself, delivery, and restaurant.

[0939] "Cook it yourself" refers to the user cooking the food themselves.

[0940] "Delivery" refers to a service that delivers food.

[0941] "Restaurant" means a food establishment that serves food.

[0942] A "recipe" is a set of instructions that explains how to prepare a dish.

[0943] An "ingredient list" refers to a list of ingredients needed to make a dish.

[0944] "Arrangements" refers to preparing and ordering needed supplies and services.

[0945] "Affiliated stores" refer to stores that provide services in cooperation with the system.

[0946] "Reservation" means applying in advance to use the Service at a specific date and time.

[0947] "Remittance" refers to sending money to another person.

[0948] The "food waste problem" refers to the social and economic problems caused by food ingredients and food going to waste.

[0949] "Natural language processing" refers to the technology that enables computers to understand and process human language.

[0950] "Emotion recognition" refers to the technology of analyzing and recognizing emotions from a user's text or voice.

[0951] The present invention is a system that suggests appropriate dishes based on the user's mood and emotions and provides a method for obtaining these dishes. This system is realized through interactions between a server, a terminal, and a user.

[0952] System configuration

[0953] This system involves the user inputting their mood and emotions, the server analyzing their emotions and suggesting dishes, and various methods of serving dishes.

[0954] 1. User input of mood and emotion

[0955] The user launches the application on their smartphone or other device and inputs their mood or emotion for the day in text. For example, they might say, "I'm feeling depressed today." This input data is then sent from the device to the server.

[0956] 2. Emotion analysis and recipe suggestions by the server

[0957] The server analyzes the received user input data using a natural language processing (NLP) engine and an emotion recognition engine. Specifically, the NLP engine (e.g., OpenAI's GPT-4) analyzes the user's text, and the emotion recognition engine recognizes the user's mood and emotional state.

[0958] For example, if a user inputs "I'm feeling down today," the emotion recognition engine will recognize the emotion as "sad." Based on this analysis, the server will generate a list of food candidates. If the analysis result is "sad," dishes such as "warm soup" and "comfort food" will be suggested.

[0959] 3. Proposal of food serving methods

[0960] Once the user selects their preferred dish from the list of suggested dishes, the server then generates the delivery method (cook it yourself, delivery, restaurant) and sends it to the terminal.

[0961] Implementation of the provision method

[0962] How to make it yourself

[0963] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server then generates a list of nearby supermarkets and online supermarkets and displays an ordering screen on the device. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[0964] Delivery process

[0965] If the user selects "Delivery," the server generates a list of dishes from nearby partner restaurants and sends it to the device. Once the user selects a restaurant and a dish and confirms the order, the device sends the order information to the server. The server processes the order, calculates the estimated delivery time, sends it to the device, and notifies the user.

[0966] Restaurant Processing

[0967] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal to display to the user.

[0968] Addressing the food waste problem

[0969] This system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes it suggests, which helps prevent excess food from being produced.

[0970] Prompt Sentence Examples

[0971] We will build a system that will provide appropriate recipe suggestions in response to input such as "I'm feeling down today," and then suggest a serving method based on that. We will also explain how to handle delivery, restaurants, and home cooking. (The model includes an emotion recognition engine and an NLP engine.)

[0972] Through these functions, the present invention provides optimal recipe suggestions and serving methods based on the user's mood and emotions, greatly improving user convenience and satisfaction.

[0973] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0974] Step 1: Launch the app and enter your mood

[0975] A user launches an application on a smartphone or other device. The app provides the user with a text input field asking, "How are you feeling today?" The user enters "I'm feeling down today" and taps the submit button. This input data is sent from the device to the server. The specific input is text data, and the output is HTTPS communication to the server.

[0976] Step 2: Sentiment Analysis

[0977] The server stores the received user input data and sends it to the emotion engine. The emotion engine (specifically OpenAI's GPT-4) analyzes the input text and recognizes the emotional state. As a result of the analysis, it recognizes an emotion such as "sad" from the text "I'm feeling depressed today." The input is text data, and the output is the recognition result of the emotional state (e.g., "sad").

[0978] Step 3: Generate dish candidates

[0979] The server generates candidate dishes from a recipe database based on the emotion analysis results. In the example above, "warm soup" and "comfort food" are selected as candidate dishes corresponding to the emotion "sad." The server then sends the selected candidate dish list to the device. The input is the recognition result of the emotional state, and the output is a candidate dish list.

[0980] Step 4: Propose delivery method

[0981] The user selects "hot soup" from the list of food candidates. The device sends this selection data to the server. The server then generates options for delivery methods (make it yourself, delivery, restaurant) and sends them to the device. The input is the food selection data, and the output is the delivery method options. When the user selects "delivery" on the device, the device sends that information to the server.

[0982] Step 5: DIY

[0983] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. The device displays the recipe and list of ingredients. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays the ordering screen on the device. When the user orders ingredients, the server processes the order and sends a confirmation message to the device. The input is the "Make it yourself" selection and the ingredient arrangement request, and the output is the recipe, ingredient list, and ingredient order confirmation message.

[0984] Step 6: Processing in case of delivery

[0985] If the user selects "Delivery," the server generates a list of dishes from nearby affiliated restaurants and sends it to the terminal. When the user selects a restaurant and a dish and confirms the order, the terminal sends that information to the server. The server processes the order, calculates the estimated delivery time, and sends it to the terminal along with order confirmation information. The terminal notifies the user of the estimated delivery time and order confirmation information. The input is the "Delivery" selection and order information, and the output is the estimated delivery time and order confirmation information.

[0986] Step 7: Restaurant Case

[0987] If the user selects "Restaurant", the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a particular restaurant and enters reservation details, and the terminal sends that information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user. The input is the "Restaurant" selection and reservation details, and the output is the reservation confirmation information.

[0988] Step 8: Addressing the food waste issue

[0989] This system has the function of appropriately adjusting the amount of dishes and ingredients selected by the user to address the food waste issue. The server analyzes this data and adjusts the amount of dishes and ingredients suggested to avoid excess food. The input is the user's selected data, and the output is the adjusted dish and ingredient suggestions.

[0990] (Application example 2)

[0991] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0992] In modern society, there is a demand for systems to suggest appropriate dishes and determine how they are served based on the user's mood and emotions. However, conventional systems have difficulty accurately understanding the user's emotional state, and are therefore unable to make appropriate dish suggestions based on that. Furthermore, while there is a need to address the issue of food waste, current systems do not adequately consider this point. This calls for the development of new technologies to improve user satisfaction and reduce food waste.

[0993] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: [means for suggesting dishes based on the mood and emotion input by the user; [means for allowing the user to select the delivery method for the suggested dishes from cook-it-yourself, delivery, or restaurant; and [means for analyzing the mood and emotion input by the user using an emotion engine and a natural language processing engine and displaying appropriate delivery dish candidates.] This makes it possible to suggest dishes and select delivery methods that match the user's current emotional state, improving user satisfaction and addressing the issue of food waste.

[0994] "User" refers to an individual user of the system.

[0995] "Mood" refers to a temporary psychological state or emotion that a user has.

[0996] "Emotion" more specifically represents the user's psychological state and refers to an internal reaction based on the mood and state of the day.

[0997] "Cuisine Suggestions" refers to meal options and details provided based on the user's mood and emotions.

[0998] "Delivery method" refers to the means and options for delivering food to the user, including cooking it yourself, delivery, and choosing from a restaurant.

[0999] "Delivery" refers to a service that delivers the selected dish to a location specified by the user.

[1000] "Emotion engine" refers to a technical means for analyzing a user's input text and recognizing its emotional state.

[1001] "Natural language processing engine" refers to a technical means for analyzing text entered by a user and understanding its content.

[1002] "Dish suggestions" refer to suggested meal options based on the user's emotions and moods.

[1003] The "food waste problem" refers to the social and economic problems that arise when food ingredients and food are wasted.

[1004] An "ingredient list" is a list of ingredients needed to make a particular dish.

[1005] This invention is a system that analyzes the mood and emotions input by the user, and based on that, suggests appropriate dishes and selects how to serve them. The system is made up of the following components:

[1006] 1. System Program Configuration

[1007] The system consists of the following main modules:

[1008] Emotion Engine

[1009] Natural Language Processing Engine

[1010] Food suggestion module

[1011] Delivery method selection module

[1012] Order Processing Module

[1013] Emotion Engine

[1014] The emotion engine analyzes the text data entered by the user and recognizes their emotional state. The engine utilizes the TextBlob library in Python to accurately analyze the emotions in the text.

[1015] Natural Language Processing Engine

[1016] The natural language processing engine is used to analyze and understand the mood and emotions input by the user, which allows the system to determine what kind of food is appropriate based on the user's mood.

[1017] Food suggestion module

[1018] The recipe suggestion module suggests multiple recipe options to the user based on data obtained from the emotion engine and natural language processing engine. The user can then select from the suggested dishes to proceed to the next step.

[1019] Delivery method selection module

[1020] The delivery method selection module presents delivery methods for the dish selected by the user, such as cooking it yourself, delivery, or restaurant delivery. Once the user selects a delivery method, the appropriate processing is carried out.

[1021] Order Processing Module

[1022] The order processing module orders food from nearby partner restaurants and arranges delivery if the user selects delivery, and also makes reservations at nearby partner restaurants if the user selects a restaurant.

[1023] 2. System processing method and data calculation

[1024] The hardware used by the system is primarily a smartphone, on which an application is launched and which processes data in conjunction with a server.

[1025] Hardware used

[1026] Smartphone

[1027] Software used

[1028] Python

[1029] Flask

[1030] TextBlob

[1031] Data flow

[1032] 1. The user launches the smartphone app and enters their current mood and a message.

[1033] 2. The entered data is sent to the server, where it is analyzed using an emotion engine and natural language processing engine.

[1034] 3. Based on the analysis results, the server generates a list of candidate dishes and presents it to the user.

[1035] 4. Once the user selects a dish and decides how it will be served, the server uses that information to perform the corresponding process (display recipe, order delivery, make restaurant reservation).

[1036] 3. Specific Examples

[1037] For example, if a user inputs "I'm tired from work today," the system will recognize the emotion as "tired" and suggest food options such as energy drinks and coffee. If the user selects from these options and chooses delivery, the system will order the selected food from a partner restaurant and deliver it to the user's specified location.

[1038] Prompt Sentence Examples

[1039] Please perform sentiment analysis on the following text: "I'm tired from work today."

[1040] Expected emotion: "tired"

[1041] Suggest recipes based on your emotional state:

[1042] Emotional state: "tired"

[1043] Food options: ["Energy Drink", "Coffee"]

[1044] In this way, the present invention realizes appropriate dish suggestions based on the user's mood and emotions, and efficient selection and arrangement of serving methods.

[1045] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1046] Step 1:

[1047] The user starts the smartphone app and inputs their current mood and a message. The input data becomes text data that indicates the user's mood and emotions.

[1048] Input: Text that indicates the user's mood or emotion (e.g., "I'm tired from work today")

[1049] Output: Text data

[1050] Specific operation: The user enters their mood or emotion in text format into the app's input field and presses the send button.

[1051] Step 2:

[1052] The device sends the input text data to the server, which receives the text data and analyzes it using an emotion engine and natural language processing engine.

[1053] Input: Text data

[1054] Output: Analysis results (emotional state)

[1055] Specific operation: The terminal sends text data to the server via an HTTP request, and the server receives the data.

[1056] Step 3:

[1057] The server analyzes the text data using an emotion engine (TextBlob) to recognize the user's emotional state and generates analysis results based on the emotional state.

[1058] Input: Text data

[1059] Output: Emotional state (e.g. "tired")

[1060] What it does: The server uses the TextBlob library to sentiment analyze the text and determine its emotional state: positive, negative, or neutral.

[1061] Step 4:

[1062] The server generates an appropriate dish candidate list using a natural language processing engine based on the emotional state, the dish candidate list including dish options that are suitable for the user's emotional state.

[1063] Input: Emotional state

[1064] Output: List of food candidates (e.g. "energy drink" "coffee")

[1065] Specific operation: The server extracts appropriate dishes from a database of dish candidates according to the emotional state and generates a list.

[1066] Step 5:

[1067] The server sends the generated list of dish candidates to the terminal, which displays it to the user, who then selects a specific dish from the displayed list of dish candidates.

[1068] Input: List of food candidates

[1069] Output: The dish selected by the user

[1070] Specific operation: The device displays a list of candidate dishes on the screen, and the user selects a dish from the list.

[1071] Step 6:

[1072] For the dish selected by the user, the terminal displays a screen for selecting the delivery method (make it yourself, delivery, restaurant), and the user selects one.

[1073] Input: The dish selected by the user

[1074] Output: Delivery method selected by the user

[1075] Specific behavior: A pop-up will appear with options for delivery method, and the user can tap to select it.

[1076] Step 7:

[1077] The server executes the corresponding process based on the delivery method selected by the user. For example, if delivery is selected, the server sends the order to a nearby partner store and arranges for delivery.

[1078] Input: Delivery method selected by the user

[1079] Output: Order details and delivery schedule

[1080] Specific operation: The server sends the order information to the selected store, calculates the estimated delivery time, and displays it on the terminal.

[1081] Step 8:

[1082] The terminal receives the order details and delivery schedule from the server and notifies the user. Once delivery is complete, the user can collect the meal.

[1083] Input: Order details and delivery schedule

[1084] Output: User notified and delivery completed

[1085] Specific operation: The device displays a notification to the user to inform them that the delivery is complete. The user then receives the food from the delivery person.

[1086] In this way, through a series of processing steps, the system efficiently suggests appropriate dishes based on the user's mood and emotions, and how to serve them.

[1087] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1088] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1089] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1090] [Third embodiment]

[1091] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1092] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1093] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1094] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1095] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1096] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1097] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1098] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1099] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1100] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1101] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1102] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1103] This invention is a system that allows users to easily find a dish that suits their mood at the time, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[1104] Specific embodiments are described below.

[1105] Mood analysis and cooking suggestions

[1106] When a user launches the app and enters their mood for the day, the device sends the text to a server. The server then uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood. The list is then presented to the user via their device, allowing them to select their favorite dish.

[1107] Select delivery method

[1108] When the user selects a dish, the server sends the corresponding delivery method (cook it yourself, delivery, restaurant) to the terminal. The terminal displays the information to the user, who then selects the desired delivery method.

[1109] How to make it yourself

[1110] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[1111] Delivery process

[1112] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[1113] What to do if you're eating at a restaurant

[1114] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[1115] High-value-added features

[1116] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[1117] Addressing the food waste problem

[1118] The system also addresses the issue of food waste, making it possible to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being used.

[1119] Specific examples

[1120] For example, if a user inputs into the app, "I want something a little spicy today," the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[1121] In this way, the present invention is a system that greatly improves user convenience by providing comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments.

[1122] The processing flow will be explained below.

[1123] Step 1:

[1124] The user launches the app and inputs their mood for the day. For example, they might input, "I want to eat something a little spicy today."

[1125] Step 2:

[1126] The terminal receives the user's input and transmits the text data to the server.

[1127] Step 3:

[1128] The server passes the received text data to a natural language processing engine to analyze the user's mood.

[1129] Step 4:

[1130] Based on the analysis results, the server generates a list of dishes that match the user's mood, such as "curry" or "tacos."

[1131] Step 5:

[1132] The server sends the generated list of dish candidates to the terminal.

[1133] Step 6:

[1134] The device displays a list of possible dishes to the user, such as "curry" or "tacos."

[1135] Step 7:

[1136] The user selects "curry" from the displayed food options and taps the "Select" button.

[1137] Step 8:

[1138] The terminal transmits the user's selection to the server.

[1139] Step 9:

[1140] The server generates available delivery methods (make-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[1141] Step 10:

[1142] The device displays options for delivery to the user, such as "make it yourself," "delivery," or "restaurant."

[1143] Step 11:

[1144] The user selects "Delivery" as the delivery method and taps the "Next" button.

[1145] Step 12:

[1146] The terminal transmits the user's selection to the server.

[1147] Step 13:

[1148] The server generates a list of nearby affiliated stores that can provide "curry" and sends it to the terminal.

[1149] Step 14:

[1150] The terminal displays a list of affiliated restaurants to the user. For example, it displays options such as "Curry Restaurant A" and "Curry Restaurant B."

[1151] Step 15:

[1152] The user selects "Curry Restaurant A," checks the order details, and then taps the "Confirm Order" button.

[1153] Step 16:

[1154] The terminal sends the order information to the server.

[1155] Step 17:

[1156] The server processes the order and calculates the estimated delivery time.

[1157] Step 18:

[1158] The server sends the estimated delivery time and order confirmation to the terminal.

[1159] Step 19:

[1160] The terminal notifies the user of the delivery time and order confirmation.

[1161] Building it yourself (another scenario)

[1162] Step 11:

[1163] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[1164] Step 12:

[1165] The terminal transmits the user's selection to the server.

[1166] Step 13:

[1167] The server generates a recipe for "curry" and a list of necessary ingredients, and sends them to the terminal.

[1168] Step 14:

[1169] The terminal displays the recipe and ingredients list to the user.

[1170] Step 15:

[1171] The user taps the "Arrange Materials" button.

[1172] Step 16:

[1173] The terminal sends a material arrangement request to the server.

[1174] Step 17:

[1175] The server generates a list of nearby supermarkets and online supermarkets and sends it to the terminal.

[1176] Step 18:

[1177] The terminal displays a list of supermarkets to the user.

[1178] Step 19:

[1179] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[1180] Step 20:

[1181] The terminal sends the order information to the server.

[1182] Step 21:

[1183] The server processes the order and sends a confirmation message to the terminal.

[1184] Step 22:

[1185] The terminal displays an order confirmation message to the user.

[1186] In this way, this system greatly enhances user convenience by consistently supporting the selection of meals that suit the user's mood, the selection of the delivery method, arrangements, and payment.

[1187] Example 1

[1188] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1189] Conventional meal recommendation systems often lack the functionality to not only suggest dishes that suit the user's mood, but also comprehensively support the selection of how the meal will be served, as well as the specific arrangements and payment procedures. Furthermore, when preparing the meal yourself, the process of preparing ingredients is complicated, which increases the user's workload. Furthermore, these systems do not adequately address the issue of food waste, resulting in excess food. Thus, there is a need for a meal recommendation system that aims to achieve both user convenience and sustainability.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1191] In this invention, the server includes: [means for suggesting dishes based on the mood input by the user; [means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant"; and [means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself."] This makes it possible [to suggest dishes based on the mood input by the user, and comprehensively select the delivery method, make specific arrangements, and make payment].

[1192] "User" refers to an end user who uses the system and inputs their mood for the day and the desired delivery method.

[1193] The term "server" refers to an information processing device that receives and processes data entered by a user or a virtual server on a network.

[1194] "Terminal" refers to a device that allows a user to access the system and input their mood, select suggested dishes, and select serving methods.

[1195] "Suggesting" refers to generating and presenting a list of appropriate dishes based on the mood data entered by the user.

[1196] "Delivery method" refers to the means by which users can obtain and consume food, and refers to three methods: cooking it yourself, delivery, or restaurant.

[1197] A "recipe" is a set of instructions for cooking a dish, including the necessary ingredients and steps.

[1198] "Ingredient list" refers to the list of ingredients needed to prepare the selected dish.

[1199] "Arranging ingredients" refers to preparing and ordering the necessary ingredients.

[1200] "Delivery" refers to the delivery of the food selected by the user from a nearby affiliated restaurant via a delivery service.

[1201] "Restaurant" refers to a restaurant that serves the food selected by the user.

[1202] "Affiliated stores" refer to affiliated stores that provide food in cooperation with the system.

[1203] "Order" refers to a request to purchase a dish or ingredients selected by a User.

[1204] "Remittance processing" refers to the procedure for transferring money when a user treats someone else or donates to relief efforts.

[1205] "Natural language processing technology" refers to artificial intelligence technology that analyzes text data and helps it understand its meaning.

[1206] "Food waste" refers to food that is discarded without being consumed.

[1207] The present invention relates to a system that proposes dishes tailored to the user's mood, and handles the selection, arrangement, and payment of the delivery method. This system uses multiple hardware and software components to perform specific data processing and calculations. Specific embodiments are described below.

[1208] System Configuration

[1209] User terminal

[1210] The device on which the user launches the app (smartphone, tablet, PC, etc.)

[1211] Responsible for sending input data and receiving and displaying display content

[1212] server

[1213] Analysis and recommendations using natural language processing technology

[1214] Specific software used for mood analysis: Google Cloud Natural Language API

[1215] Processing flow

[1216] 1. Mood input

[1217] The user launches the app and enters their mood for the day in text.

[1218] The device transmits the mood data to the server.

[1219] 2. Mood analysis and recipe suggestions

[1220] The server uses natural language processing technology (Google Cloud Natural Language API) to analyze the user's mood.

[1221] The server generates a list of suggested dishes based on the analysis results.

[1222] The terminal displays the recipe list to the user.

[1223] 3. Selection of delivery method

[1224] When the user selects a dish, the server generates the corresponding delivery method (make-yourself, delivery, restaurant).

[1225] The terminal displays the provision methods to the user, and the user selects one.

[1226] If you make it yourself

[1227] The server generates a recipe and a list of ingredients for the selected dish.

[1228] The terminal displays the recipe and ingredients list to the user.

[1229] When a user requests material arrangement, the server generates a list of nearby supermarkets or online supermarkets (for example, the API of an online supermarket).

[1230] When a user orders ingredients, the server processes the order and displays a confirmation message.

[1231] For delivery

[1232] The server generates a list of dishes from nearby partner stores (stores that offer delivery).

[1233] The terminal displays this to the user, who then selects the food and restaurant and places the order.

[1234] The server processes the order and sends an estimated delivery time and order confirmation to the terminal.

[1235] In the case of a restaurant

[1236] The server generates a list of nearby affiliated restaurants.

[1237] The terminal displays this to the user, who then selects a restaurant and enters reservation details.

[1238] The server processes the reservation and sends a confirmation message to the terminal.

[1239] High-value-added features

[1240] If the user chooses to treat others or make a donation, the server generates information about the other person and a list of donation recipients.

[1241] The terminal displays this to the user, and once the remittance amount is set, the server processes the remittance and sends a confirmation message.

[1242] Addressing the food waste problem

[1243] The server adjusts the amount of ingredients based on the user's choice of food and number of people.

[1244] The device displays the adjusted ingredient list to the user, ensuring no excess ingredients are used.

[1245] Specific examples

[1246] For example, if a user inputs into the app, "I want to eat something spicy today," the server analyzes the data and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby affiliated curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the ingredients can be ordered directly.

[1247] Prompt Sentence Examples

[1248] Below are some examples of prompts to input to the generative AI model.

[1249] "User says they want something spicy today. Suggest a dish based on that and offer options for delivery, restaurants, or cook-it-yourself."

[1250] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1251] Step 1:

[1252] The user starts the app and enters their mood for the day in text. This text becomes the input data.

[1253] Step 2:

[1254] The device receives mood data entered by the user and sends the data to the server. The specific operation of the device is to send text data to the server as an HTTP request.

[1255] Step 3:

[1256] The server uses natural language processing technology to analyze the received mood data. This analysis generates a list of dishes that match the user's mood. Using the user's mood text as input data, it performs data calculations using tools such as the Google Cloud Natural Language API, and obtains a list of dishes as output.

[1257] Step 4:

[1258] The server sends the generated dish list to the device. Specifically, it encodes the dish list in JSON format and sends it to the device as an HTTP response.

[1259] Step 5:

[1260] The device receives the recipe list from the server and displays it to the user. The displayed recipe list becomes the output data. The device parses the data and displays it on the user interface.

[1261] Step 6:

[1262] The user selects a favorite dish from the list of dishes. This selection becomes the input data for the next process.

[1263] Step 7:

[1264] Based on the user's food selection, the server generates the corresponding delivery method (cook, delivery, restaurant) and sends it to the terminal. The input is the user's food selection data, and the output is a list of delivery methods.

[1265] Step 8:

[1266] The terminal displays a list of delivery methods to the user, specifically, a delivery method selection screen.

[1267] Step 9:

[1268] The user selects the delivery method (make it yourself, delivery, restaurant). The selected delivery method becomes the input data for the next step.

[1269] If you're making it yourself:

[1270] Step 10:

[1271] The server generates a recipe and a list of ingredients for the selected dish. The input is the user's dish selection data, and the output is the recipe and the list of ingredients.

[1272] Step 11:

[1273] The server sends the recipe and ingredient list to the device, encoding the data in JSON format and sending it as an HTTP response.

[1274] Step 12:

[1275] The terminal displays this to the user. Specifically, the recipe and ingredient list are displayed on the user interface.

[1276] Step 13:

[1277] The user presses the "Arrange materials" button, which becomes the input data for the next step.

[1278] Step 14:

[1279] The terminal sends a material arrangement request to the server. Specifically, the request data is sent as an HTTP request.

[1280] Step 15:

[1281] The server generates a list of nearby supermarkets and online supermarkets, and sends the ordering screen to the terminal. Using the user's location information and material ordering request as input data, it performs data calculations and obtains a supermarket list as output.

[1282] Step 16:

[1283] The terminal displays the super list to the user. Specifically, the terminal displays the order screen.

[1284] Step 17:

[1285] The user orders materials, and the order data becomes the input data for the next step.

[1286] Step 18:

[1287] The server processes the order and sends a confirmation message to the terminal. The order request data is used as input and the order confirmation message is obtained as output.

[1288] For delivery:

[1289] Step 10:

[1290] The server generates a list of dishes available from nearby partner restaurants and sends it to the terminal. The input is the user's food selection data, and the output is a list of dishes available for delivery.

[1291] Step 11:

[1292] The terminal displays this to the user. Specifically, the recipe list is displayed on the user interface.

[1293] Step 12:

[1294] The user selects a specific restaurant and food item and confirms the order. The order data becomes the input data for the next step.

[1295] Step 13:

[1296] The terminal sends the order confirmation data to the server. Specifically, the order data is sent as an HTTP request.

[1297] Step 14:

[1298] The server processes the order, sends the estimated delivery time and order confirmation to the terminal, and notifies the user. The input data is the order data, and the output is the estimated delivery time and order confirmation message.

[1299] If you're eating at a restaurant:

[1300] Step 10:

[1301] The server generates a list of nearby affiliated restaurants and sends it to the terminal. The input data is the user's food selection data, and the output data is the restaurant list.

[1302] Step 11:

[1303] The terminal displays this to the user. As a specific operation, the restaurant list is displayed on the user interface.

[1304] Step 12:

[1305] The user selects a particular restaurant and enters reservation details, which serve as input data for the next step.

[1306] Step 13:

[1307] The terminal sends the reservation details data to the server. Specifically, the reservation data is sent as an HTTP request.

[1308] Step 14:

[1309] The server processes the reservation information and sends a confirmation message to the terminal to notify the user. The reservation details are input and the reservation confirmation message is output.

[1310] (Application example 1)

[1311] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1312] In recent years, users have been demanding a system that allows them to easily and quickly select the meal that best suits their mood that day, and then select the delivery method (cooking, delivery, or restaurant), arrange the meal, and pay for it all at once. However, existing systems that achieve this have issues such as insufficient suggestions for dishes that match the mood, insufficient arrangements and order processing depending on the delivery method, and a lack of high-value-added functions. A system that can effectively solve these issues is needed.

[1313] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1314] In this invention, the server includes a means for suggesting dishes based on the mood input by the user, a means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself." This allows the user to choose a dish that suits their mood that day and comprehensively handle the arrangements and payment according to the selected delivery method. Furthermore, the server also includes a means for ordering food from a nearby affiliated restaurant and arranging delivery if the user selects delivery, a means for making a reservation at a nearby affiliated restaurant if the user selects restaurant, and a means for selecting recipient information and a donation destination and processing a remittance if the user wants to treat someone or donate to a relief effort, thereby providing an even more convenient service.

[1315] The "means for suggesting dishes based on the mood input by the user" is a function for analyzing the mood information input by the user and suggesting suitable dishes based on the analysis results.

[1316] "A means for allowing the user to select the delivery method for the proposed dish from cooking it themselves, delivery, or restaurant" is a function in which the system presents the user with options for delivery methods, allowing the user to select from those options.

[1317] "When the user selects to cook it themselves, a means of displaying the corresponding recipe and a list of ingredients required, and arranging for the ingredients" is a function that, when the user selects to cook a dish themselves, displays the recipe and list of ingredients required for that dish, and even takes them through the process of purchasing the ingredients.

[1318] "Means of ordering food from nearby affiliated stores and arranging delivery when the user selects delivery" refers to a function in which, when the user selects delivery, the system orders food from nearby affiliated stores and arranges for delivery to the specified address.

[1319] "Means for making reservations at nearby affiliated restaurants when a user selects a restaurant" is a function that allows the system to process reservations at nearby affiliated restaurants when a user selects to eat at a restaurant.

[1320] "A means for selecting the recipient and donation destination and carrying out the money transfer process when treating someone or donating to a relief effort" is a function that allows a user to select the recipient and donation destination and carry out the money transfer process when treating someone or donating to a relief effort.

[1321] "Means for analyzing a user's mood input, suggesting dishes based on the analysis results, selecting a specific serving method based on the selected dish, displaying optimal delivery options, and processing the order and notifying the user of the delivery time if the user places an order" refers to a series of functions that analyze mood information entered by a user, suggest dishes based on the results of the analysis, select a serving method according to the dish selected by the user, display delivery options, process the order, and notify the user of the delivery time.

[1322] This invention is a system that allows users to easily find a dish that suits their mood of the day, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[1323] First, the user launches an application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. The server uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood based on the analysis results. The generated list of dishes is presented to the user via the device, from which the user can select their preferred dish.

[1324] Based on the user's choice of food, the server sends the corresponding delivery method (cook, delivery, restaurant) to the device, which then displays it to the user, who can then select the desired delivery method.

[1325] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[1326] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[1327] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[1328] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[1329] Furthermore, this system addresses the issue of food waste by allowing users to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being produced.

[1330] For example, if a user inputs "I want something a little spicy today" into the app, the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry specialty restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[1331] Example prompt: "Right now I'm feeling very relaxed and in the mood for something sweet and warm. Can you suggest a dish that would fit this mood?"

[1332] In this way, the system of the present invention provides comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments, thereby greatly improving user convenience.

[1333] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1334] Step 1:

[1335] The user launches the application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. This sends the user's mood information to the server, which then generates input data for analysis.

[1336] Step 2:

[1337] The server receives the user's mood information and analyzes it using natural language processing technology. The analysis involves breaking down the text data and extracting emotions and keywords. A generative AI model is used to generate a list of dishes that match the user's mood. The analysis results in a list of suggested dishes that match the user's mood.

[1338] Step 3:

[1339] The generated list of suggested dishes is sent from the server to the device. The device then presents this list to the user, allowing the user to visually check the suggested dishes. The user then selects their preferred dish from the presented list. This selection result is then sent back from the device to the server.

[1340] Step 4:

[1341] Based on the user's choice of food, the server generates a corresponding delivery method (cook, delivery, restaurant) for the proposed food and sends it to the device. The device then displays the delivery method options to the user, allowing the user to select the desired delivery method.

[1342] Step 5:

[1343] The user selects the desired delivery method from the options (make it yourself, delivery, restaurant) and selects it on the device. The selection result is sent to the server via the device. The server prepares the next step based on the delivery method selected by the user.

[1344] Step 6 (If you're building it yourself):

[1345] If the user selects "Make it yourself," the server generates a recipe and a list of ingredients for the selected dish and sends them to the device. The device displays this to the user and provides an "Arrange ingredients" button. When the user presses the "Arrange ingredients" button, a request is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for completing ingredient arrangements. Once the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[1346] Step 7 (for delivery):

[1347] If the user selects "Delivery," the server generates a list of dishes available from nearby partner restaurants and sends it to the device. The device presents this list to the user, who then selects a specific restaurant and confirms the order, which is then sent to the server. The server processes the order, calculates the estimated delivery time, and sends a confirmation message to the device.

[1348] Step 8 (for restaurants):

[1349] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The terminal presents this list to the user, who then selects a specific restaurant and enters reservation details, which are then sent to the server. The server processes the reservation information and sends a reservation confirmation to the terminal.

[1350] Step 9 (if giving or donating):

[1351] If the user selects to treat or donate, the server generates a list of recipients and donation recipients and sends it to the terminal. The terminal presents the list to the user, who then selects information and sets the amount to be transferred, and the information is sent to the server. The server then processes the transfer and displays a confirmation message on the terminal.

[1352] This system improves user convenience by suggesting meals that suit the user's mood and providing comprehensive support for arrangements and payment depending on the delivery method.

[1353] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1354] The present invention combines a system that suggests appropriate dishes based on the user's mood with an emotion engine that recognizes the user's emotions. This invention allows for a more precise understanding of the user's emotional state, and allows for the selection of dish suggestions and serving methods based on that understanding.

[1355] Mood and emotion analysis and food suggestions

[1356] The user launches the app and inputs their mood for the day. For example, they might input "I'm feeling depressed today." The device then sends the user's input to the emotion engine, which analyzes the user's input text and recognizes their emotional state.

[1357] The server uses a natural language processing engine to analyze the user's mood, and at the same time, recognizes their emotional state through an emotion engine. For example, when someone says "I'm feeling depressed," the server recognizes the emotion "sad."

[1358] Based on the results of mood and emotion analysis, the server generates a list of recipe suggestions that take into account the user's emotional state, such as suggesting dishes like "warm soup" or "comfort food."

[1359] Select delivery method

[1360] When the user selects their preferred dish from a list of candidate dishes, the server generates a delivery method (cook it yourself, delivery, restaurant) and presents it to the user via their terminal.

[1361] How to make it yourself

[1362] When the user selects "Make it yourself" as the delivery method, the server generates a recipe for the dish and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, the device sends an ingredient arrangement request to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for arrangements. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device. The device then displays the confirmation message to the user.

[1363] Delivery process

[1364] When the user selects "Delivery" as the delivery method, the server generates a list of dishes from nearby partner restaurants and sends it to the terminal. When the user selects a specific restaurant and confirms the order, the terminal sends the order information to the server. The server processes the order and calculates the estimated delivery time. The estimated delivery time and order confirmation information are sent to the terminal and notified to the user.

[1365] Restaurant Processing

[1366] When the user selects "Restaurant" as the delivery method, the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user.

[1367] High-value-added features

[1368] This system also includes functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates information about the recipient and a list of donation recipients and sends them to the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and sends a confirmation message to the terminal. The terminal then displays the confirmation message to the user.

[1369] Addressing the food waste problem

[1370] The system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes suggested, making it possible to avoid excess food.

[1371] Specific examples

[1372] For example, if a user inputs "I'm feeling down today," the server analyzes it and recognizes emotions such as "sad." Based on the user's emotional state, the server suggests "hot soup" or "comfort food." If the user selects "hot soup" and "delivery" as the delivery method, the soup can be ordered from a nearby affiliated store and delivered. If the user selects "make it yourself," the recipe and list of ingredients are displayed, and the user can order the ingredients right away.

[1373] In this way, the present invention comprehensively supports the selection of meals based on the user's mood and emotions, the selection of delivery methods, arrangements, and payment, thereby increasing user convenience and satisfaction.

[1374] The processing flow will be explained below.

[1375] Mood and sentiment analysis and food suggestion processing steps

[1376] Step 1:

[1377] The user launches the app and enters their mood for the day, for example, "I'm feeling depressed today."

[1378] Step 2:

[1379] The terminal sends the user's input to the emotion engine.

[1380] Step 3:

[1381] The emotion engine analyzes the user's input text and recognizes their emotional state. In this case, it recognizes the emotion "sad" from the input "I'm feeling depressed."

[1382] Step 4:

[1383] The terminal transmits the user's input and the emotion engine's recognition results to the server.

[1384] Step 5:

[1385] The server uses a natural language processing engine to analyze the user's mood and also takes into account the results of the emotion engine to generate a list of recipe candidates.

[1386] Step 6:

[1387] The server sends the generated list of dish candidates to the terminal.

[1388] Step 7:

[1389] The device will display a list of food suggestions to the user, such as "hot soup" or "comfort food."

[1390] Step 8:

[1391] The user selects "warm soup" from the displayed food options and taps the "Select" button.

[1392] Delivery Method Selection Process Steps

[1393] Step 9:

[1394] The terminal transmits the user's selection to the server.

[1395] Step 10:

[1396] The server generates available delivery methods (make-it-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[1397] Step 11:

[1398] The device will display options for delivery to the user, such as "Make it yourself," "Delivery," or "Restaurant."

[1399] Specific processing steps if you make it yourself

[1400] Step 12:

[1401] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[1402] Step 13:

[1403] The terminal transmits the user's selection to the server.

[1404] Step 14:

[1405] The server generates a recipe and a list of ingredients for the selected dish and sends them to the terminal.

[1406] Step 15:

[1407] The terminal displays the recipe and ingredients list to the user.

[1408] Step 16:

[1409] The user taps the "Arrange Materials" button.

[1410] Step 17:

[1411] The terminal sends a material arrangement request to the server.

[1412] Step 18:

[1413] The server generates a list of nearby supermarkets and online supermarkets and sends a screen for making arrangements to the terminal.

[1414] Step 19:

[1415] The terminal displays a list of supermarkets to the user.

[1416] Step 20:

[1417] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[1418] Step 21:

[1419] The terminal sends the order information to the server.

[1420] Step 22:

[1421] The server processes the order and sends a confirmation message to the terminal.

[1422] Step 23:

[1423] The terminal displays a confirmation message to the user.

[1424] Specific processing steps for delivery

[1425] Step 12:

[1426] The user selects "Delivery" as the delivery method and taps the "Next" button.

[1427] Step 13:

[1428] The terminal transmits the user's selection to the server.

[1429] Step 14:

[1430] The server generates a list of dishes that can be provided by nearby affiliated stores and transmits it to the terminal.

[1431] Step 15:

[1432] The terminal displays a list of affiliated stores to the user.

[1433] Step 16:

[1434] The user selects a specific store and places an order.

[1435] Step 17:

[1436] The terminal sends the order information to the server.

[1437] Step 18:

[1438] The server processes the order and calculates the estimated delivery time.

[1439] Step 19:

[1440] The server sends the estimated delivery time and order confirmation to the terminal.

[1441] Step 20:

[1442] The terminal notifies the user of the delivery time and order confirmation.

[1443] Specific processing steps for restaurants

[1444] Step 12:

[1445] The user selects "Restaurant" as the delivery method and taps the "Next" button.

[1446] Step 13:

[1447] The terminal transmits the user's selection to the server.

[1448] Step 14:

[1449] The server generates a list of nearby affiliated restaurants and sends it to the terminal.

[1450] Step 15:

[1451] The terminal displays a list of affiliated restaurants to the user.

[1452] Step 16:

[1453] The user selects a particular restaurant and enters reservation details.

[1454] Step 17:

[1455] The terminal transmits the reservation information to the server.

[1456] Step 18:

[1457] The server processes the reservation information and sends a reservation confirmation to the terminal.

[1458] Step 19:

[1459] The terminal displays a reservation confirmation to the user.

[1460] In this way, the system can increase user satisfaction and convenience by performing a consistent process from selection of delivery method, arrangement, and payment based on the user's mood and emotions.

[1461] Example 2

[1462] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1463] In modern society, there is a demand for systems that can enhance user convenience and satisfaction by suggesting meals that suit individual users' moods and emotions and selecting appropriate delivery methods. However, conventional systems have difficulty precisely analyzing users' moods and emotions and selecting optimal meal suggestions and delivery methods based on that analysis. In addition, to address the food waste issue, there is a need for a function that adjusts the amount of food consumed to prevent excess ingredients from being generated.

[1464] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting dishes based on the mood and emotions input by the user, a means for allowing the user to select the delivery method for the suggested dish from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and list of necessary ingredients when the user selects "make it yourself," and arranging for the ingredients. This makes it possible to suggest optimal dishes and select delivery methods based on the user's mood and emotions, and to address the food waste issue.

[1465] "User" refers to an individual or organization that uses the system.

[1466] "Mood" refers to the psychological and emotional state that a user is feeling at that time.

[1467] "Cooking" refers to food prepared using ingredients.

[1468] "Suggestion" refers to the options and ideas the system offers to the user.

[1469] "Delivery method" refers to the method by which the food is provided to the user, including options such as cook-it-yourself, delivery, and restaurant.

[1470] "Cook it yourself" refers to the user cooking the food themselves.

[1471] "Delivery" refers to a service that delivers food.

[1472] "Restaurant" means a food establishment that serves food.

[1473] A "recipe" is a set of instructions that explains how to prepare a dish.

[1474] An "ingredient list" refers to a list of ingredients needed to make a dish.

[1475] "Arrangements" refers to preparing and ordering needed supplies and services.

[1476] "Affiliated stores" refer to stores that provide services in cooperation with the system.

[1477] "Reservation" means applying in advance to use the Service at a specific date and time.

[1478] "Remittance" refers to sending money to another person.

[1479] The "food waste problem" refers to the social and economic problems caused by food ingredients and food going to waste.

[1480] "Natural language processing" refers to the technology that enables computers to understand and process human language.

[1481] "Emotion recognition" refers to the technology of analyzing and recognizing emotions from a user's text or voice.

[1482] The present invention is a system that suggests appropriate dishes based on the user's mood and emotions and provides a method for obtaining these dishes. This system is realized through interactions between a server, a terminal, and a user.

[1483] System configuration

[1484] This system involves the user inputting their mood and emotions, the server analyzing their emotions and suggesting dishes, and various methods of serving dishes.

[1485] 1. User input of mood and emotion

[1486] The user launches the application on their smartphone or other device and inputs their mood or emotion for the day in text. For example, they might say, "I'm feeling depressed today." This input data is then sent from the device to the server.

[1487] 2. Emotion analysis and recipe suggestions by the server

[1488] The server analyzes the received user input data using a natural language processing (NLP) engine and an emotion recognition engine. Specifically, the NLP engine (e.g., OpenAI's GPT-4) analyzes the user's text, and the emotion recognition engine recognizes the user's mood and emotional state.

[1489] For example, if a user inputs "I'm feeling down today," the emotion recognition engine will recognize the emotion as "sad." Based on this analysis, the server will generate a list of food candidates. If the analysis result is "sad," dishes such as "warm soup" and "comfort food" will be suggested.

[1490] 3. Proposal of food serving methods

[1491] Once the user selects their preferred dish from the list of suggested dishes, the server then generates the delivery method (cook it yourself, delivery, restaurant) and sends it to the terminal.

[1492] Implementation of the provision method

[1493] How to make it yourself

[1494] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server then generates a list of nearby supermarkets and online supermarkets and displays an ordering screen on the device. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[1495] Delivery process

[1496] If the user selects "Delivery," the server generates a list of dishes from nearby partner restaurants and sends it to the device. Once the user selects a restaurant and a dish and confirms the order, the device sends the order information to the server. The server processes the order, calculates the estimated delivery time, sends it to the device, and notifies the user.

[1497] Restaurant Processing

[1498] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal to display to the user.

[1499] Addressing the food waste problem

[1500] This system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes it suggests, which helps prevent excess food from being produced.

[1501] Prompt Sentence Examples

[1502] We will build a system that will provide appropriate recipe suggestions in response to input such as "I'm feeling down today," and then suggest a serving method based on that. We will also explain how to handle delivery, restaurants, and home cooking. (The model includes an emotion recognition engine and an NLP engine.)

[1503] Through these functions, the present invention provides optimal recipe suggestions and serving methods based on the user's mood and emotions, greatly improving user convenience and satisfaction.

[1504] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1505] Step 1: Launch the app and enter your mood

[1506] A user launches an application on a smartphone or other device. The app provides the user with a text input field asking, "How are you feeling today?" The user enters "I'm feeling down today" and taps the submit button. This input data is sent from the device to the server. The specific input is text data, and the output is HTTPS communication to the server.

[1507] Step 2: Sentiment Analysis

[1508] The server stores the received user input data and sends it to the emotion engine. The emotion engine (specifically OpenAI's GPT-4) analyzes the input text and recognizes the emotional state. As a result of the analysis, it recognizes an emotion such as "sad" from the text "I'm feeling depressed today." The input is text data, and the output is the recognition result of the emotional state (e.g., "sad").

[1509] Step 3: Generate dish candidates

[1510] The server generates candidate dishes from a recipe database based on the emotion analysis results. In the example above, "warm soup" and "comfort food" are selected as candidate dishes corresponding to the emotion "sad." The server then sends the selected candidate dish list to the device. The input is the recognition result of the emotional state, and the output is a candidate dish list.

[1511] Step 4: Propose delivery method

[1512] The user selects "hot soup" from the list of food candidates. The device sends this selection data to the server. The server then generates options for delivery methods (make it yourself, delivery, restaurant) and sends them to the device. The input is the food selection data, and the output is the delivery method options. When the user selects "delivery" on the device, the device sends that information to the server.

[1513] Step 5: DIY

[1514] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. The device displays the recipe and list of ingredients. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays the ordering screen on the device. When the user orders ingredients, the server processes the order and sends a confirmation message to the device. The input is the "Make it yourself" selection and the ingredient arrangement request, and the output is the recipe, ingredient list, and ingredient order confirmation message.

[1515] Step 6: Processing in case of delivery

[1516] If the user selects "Delivery," the server generates a list of dishes from nearby affiliated restaurants and sends it to the terminal. When the user selects a restaurant and a dish and confirms the order, the terminal sends that information to the server. The server processes the order, calculates the estimated delivery time, and sends it to the terminal along with order confirmation information. The terminal notifies the user of the estimated delivery time and order confirmation information. The input is the "Delivery" selection and order information, and the output is the estimated delivery time and order confirmation information.

[1517] Step 7: Restaurant Case

[1518] If the user selects "Restaurant", the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a particular restaurant and enters reservation details, and the terminal sends that information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user. The input is the "Restaurant" selection and reservation details, and the output is the reservation confirmation information.

[1519] Step 8: Addressing the food waste issue

[1520] This system has the function of appropriately adjusting the amount of dishes and ingredients selected by the user to address the food waste issue. The server analyzes this data and adjusts the amount of dishes and ingredients suggested to avoid excess food. The input is the user's selected data, and the output is the adjusted dish and ingredient suggestions.

[1521] (Application example 2)

[1522] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1523] In modern society, there is a demand for systems to suggest appropriate dishes and determine how they are served based on the user's mood and emotions. However, conventional systems have difficulty accurately understanding the user's emotional state, and are therefore unable to make appropriate dish suggestions based on that. Furthermore, while there is a need to address the issue of food waste, current systems do not adequately consider this point. This calls for the development of new technologies to improve user satisfaction and reduce food waste.

[1524] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: [means for suggesting dishes based on the mood and emotion input by the user; [means for allowing the user to select the delivery method for the suggested dishes from cook-it-yourself, delivery, or restaurant; and [means for analyzing the mood and emotion input by the user using an emotion engine and a natural language processing engine and displaying appropriate delivery dish candidates.] This makes it possible to suggest dishes and select delivery methods that match the user's current emotional state, improving user satisfaction and addressing the issue of food waste.

[1525] "User" refers to an individual user of the system.

[1526] "Mood" refers to a temporary psychological state or emotion that a user has.

[1527] "Emotion" more specifically represents the user's psychological state and refers to an internal reaction based on the mood and state of the day.

[1528] "Cuisine Suggestions" refers to meal options and details provided based on the user's mood and emotions.

[1529] "Delivery method" refers to the means and options for delivering food to the user, including cooking it yourself, delivery, and choosing from a restaurant.

[1530] "Delivery" refers to a service that delivers the selected dish to a location specified by the user.

[1531] "Emotion engine" refers to a technical means for analyzing a user's input text and recognizing its emotional state.

[1532] "Natural language processing engine" refers to a technical means for analyzing text entered by a user and understanding its content.

[1533] "Dish suggestions" refer to suggested meal options based on the user's emotions and moods.

[1534] The "food waste problem" refers to the social and economic problems that arise when food ingredients and food are wasted.

[1535] An "ingredient list" is a list of ingredients needed to make a particular dish.

[1536] This invention is a system that analyzes the mood and emotions input by the user, and based on that, suggests appropriate dishes and selects how to serve them. The system is made up of the following components:

[1537] 1. System Program Configuration

[1538] The system consists of the following main modules:

[1539] Emotion Engine

[1540] Natural Language Processing Engine

[1541] Food suggestion module

[1542] Delivery method selection module

[1543] Order Processing Module

[1544] Emotion Engine

[1545] The emotion engine analyzes the text data entered by the user and recognizes their emotional state. The engine utilizes the TextBlob library in Python to accurately analyze the emotions in the text.

[1546] Natural Language Processing Engine

[1547] The natural language processing engine is used to analyze and understand the mood and emotions input by the user, which allows the system to determine what kind of food is appropriate based on the user's mood.

[1548] Food suggestion module

[1549] The recipe suggestion module suggests multiple recipe options to the user based on data obtained from the emotion engine and natural language processing engine. The user can then select from the suggested dishes to proceed to the next step.

[1550] Delivery method selection module

[1551] The delivery method selection module presents delivery methods for the dish selected by the user, such as cooking it yourself, delivery, or restaurant delivery. Once the user selects a delivery method, the appropriate processing is carried out.

[1552] Order Processing Module

[1553] The order processing module orders food from nearby partner restaurants and arranges delivery if the user selects delivery, and also makes reservations at nearby partner restaurants if the user selects a restaurant.

[1554] 2. System processing method and data calculation

[1555] The hardware used by the system is primarily a smartphone, on which an application is launched and which processes data in conjunction with a server.

[1556] Hardware used

[1557] Smartphone

[1558] Software used

[1559] Python

[1560] Flask

[1561] TextBlob

[1562] Data flow

[1563] 1. The user launches the smartphone app and enters their current mood and a message.

[1564] 2. The entered data is sent to the server, where it is analyzed using an emotion engine and natural language processing engine.

[1565] 3. Based on the analysis results, the server generates a list of candidate dishes and presents it to the user.

[1566] 4. Once the user selects a dish and decides how it will be served, the server uses that information to perform the corresponding process (display recipe, order delivery, make restaurant reservation).

[1567] 3. Specific Examples

[1568] For example, if a user inputs "I'm tired from work today," the system will recognize the emotion as "tired" and suggest food options such as energy drinks and coffee. If the user selects from these options and chooses delivery, the system will order the selected food from a partner restaurant and deliver it to the user's specified location.

[1569] Prompt Sentence Examples

[1570] Please perform sentiment analysis on the following text: "I'm tired from work today."

[1571] Expected emotion: "tired"

[1572] Suggest recipes based on your emotional state:

[1573] Emotional state: "tired"

[1574] Food options: ["Energy Drink", "Coffee"]

[1575] In this way, the present invention realizes appropriate dish suggestions based on the user's mood and emotions, and efficient selection and arrangement of serving methods.

[1576] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1577] Step 1:

[1578] The user starts the smartphone app and inputs their current mood and a message. The input data becomes text data that indicates the user's mood and emotions.

[1579] Input: Text that indicates the user's mood or emotion (e.g., "I'm tired from work today")

[1580] Output: Text data

[1581] Specific operation: The user enters their mood or emotion in text format into the app's input field and presses the send button.

[1582] Step 2:

[1583] The device sends the input text data to the server, which receives the text data and analyzes it using an emotion engine and natural language processing engine.

[1584] Input: Text data

[1585] Output: Analysis results (emotional state)

[1586] Specific operation: The terminal sends text data to the server via an HTTP request, and the server receives the data.

[1587] Step 3:

[1588] The server analyzes the text data using an emotion engine (TextBlob) to recognize the user's emotional state and generates analysis results based on the emotional state.

[1589] Input: Text data

[1590] Output: Emotional state (e.g. "tired")

[1591] What it does: The server uses the TextBlob library to sentiment analyze the text and determine its emotional state: positive, negative, or neutral.

[1592] Step 4:

[1593] The server generates an appropriate dish candidate list using a natural language processing engine based on the emotional state, the dish candidate list including dish options that are suitable for the user's emotional state.

[1594] Input: Emotional state

[1595] Output: List of food candidates (e.g. "energy drink" "coffee")

[1596] Specific operation: The server extracts appropriate dishes from a database of dish candidates according to the emotional state and generates a list.

[1597] Step 5:

[1598] The server sends the generated list of dish candidates to the terminal, which displays it to the user, who then selects a specific dish from the displayed list of dish candidates.

[1599] Input: List of food candidates

[1600] Output: The dish selected by the user

[1601] Specific operation: The device displays a list of candidate dishes on the screen, and the user selects a dish from the list.

[1602] Step 6:

[1603] For the dish selected by the user, the terminal displays a screen for selecting the delivery method (make it yourself, delivery, restaurant), and the user selects one.

[1604] Input: The dish selected by the user

[1605] Output: Delivery method selected by the user

[1606] Specific behavior: A pop-up will appear with options for delivery method, and the user can tap to select it.

[1607] Step 7:

[1608] The server executes the corresponding process based on the delivery method selected by the user. For example, if delivery is selected, the server sends the order to a nearby partner store and arranges for delivery.

[1609] Input: Delivery method selected by the user

[1610] Output: Order details and delivery schedule

[1611] Specific operation: The server sends the order information to the selected store, calculates the estimated delivery time, and displays it on the terminal.

[1612] Step 8:

[1613] The terminal receives the order details and delivery schedule from the server and notifies the user. Once delivery is complete, the user can collect the meal.

[1614] Input: Order details and delivery schedule

[1615] Output: User notified and delivery completed

[1616] Specific operation: The device displays a notification to the user to inform them that the delivery is complete. The user then receives the food from the delivery person.

[1617] In this way, through a series of processing steps, the system efficiently suggests appropriate dishes based on the user's mood and emotions, and how to serve them.

[1618] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1619] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1620] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1621] [Fourth embodiment]

[1622] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1623] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1624] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1625] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1626] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1627] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1628] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1629] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1630] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1631] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1632] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1633] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1634] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1635] This invention is a system that allows users to easily find a dish that suits their mood at the time, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[1636] Specific embodiments are described below.

[1637] Mood analysis and cooking suggestions

[1638] When a user launches the app and enters their mood for the day, the device sends the text to a server. The server then uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood. The list is then presented to the user via their device, allowing them to select their favorite dish.

[1639] Select delivery method

[1640] When the user selects a dish, the server sends the corresponding delivery method (cook it yourself, delivery, restaurant) to the terminal. The terminal displays the information to the user, who then selects the desired delivery method.

[1641] How to make it yourself

[1642] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[1643] Delivery process

[1644] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[1645] What to do if you're eating at a restaurant

[1646] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[1647] High-value-added features

[1648] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[1649] Addressing the food waste problem

[1650] The system also addresses the issue of food waste, making it possible to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being used.

[1651] Specific examples

[1652] For example, if a user inputs into the app, "I want something a little spicy today," the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[1653] In this way, the present invention is a system that greatly improves user convenience by providing comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments.

[1654] The processing flow will be explained below.

[1655] Step 1:

[1656] The user launches the app and inputs their mood for the day. For example, they might input, "I want to eat something a little spicy today."

[1657] Step 2:

[1658] The terminal receives the user's input and transmits the text data to the server.

[1659] Step 3:

[1660] The server passes the received text data to a natural language processing engine to analyze the user's mood.

[1661] Step 4:

[1662] Based on the analysis results, the server generates a list of dishes that match the user's mood, such as "curry" or "tacos."

[1663] Step 5:

[1664] The server sends the generated list of dish candidates to the terminal.

[1665] Step 6:

[1666] The device displays a list of possible dishes to the user, such as "curry" or "tacos."

[1667] Step 7:

[1668] The user selects "curry" from the displayed food options and taps the "Select" button.

[1669] Step 8:

[1670] The terminal transmits the user's selection to the server.

[1671] Step 9:

[1672] The server generates available delivery methods (make-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[1673] Step 10:

[1674] The device displays options for delivery to the user, such as "make it yourself," "delivery," or "restaurant."

[1675] Step 11:

[1676] The user selects "Delivery" as the delivery method and taps the "Next" button.

[1677] Step 12:

[1678] The terminal transmits the user's selection to the server.

[1679] Step 13:

[1680] The server generates a list of nearby affiliated stores that can provide "curry" and sends it to the terminal.

[1681] Step 14:

[1682] The terminal displays a list of affiliated restaurants to the user. For example, it displays options such as "Curry Restaurant A" and "Curry Restaurant B."

[1683] Step 15:

[1684] The user selects "Curry Restaurant A," checks the order details, and then taps the "Confirm Order" button.

[1685] Step 16:

[1686] The terminal sends the order information to the server.

[1687] Step 17:

[1688] The server processes the order and calculates the estimated delivery time.

[1689] Step 18:

[1690] The server sends the estimated delivery time and order confirmation to the terminal.

[1691] Step 19:

[1692] The terminal notifies the user of the delivery time and order confirmation.

[1693] Building it yourself (another scenario)

[1694] Step 11:

[1695] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[1696] Step 12:

[1697] The terminal transmits the user's selection to the server.

[1698] Step 13:

[1699] The server generates a recipe for "curry" and a list of necessary ingredients, and sends them to the terminal.

[1700] Step 14:

[1701] The terminal displays the recipe and ingredients list to the user.

[1702] Step 15:

[1703] The user taps the "Arrange Materials" button.

[1704] Step 16:

[1705] The terminal sends a material arrangement request to the server.

[1706] Step 17:

[1707] The server generates a list of nearby supermarkets and online supermarkets and sends it to the terminal.

[1708] Step 18:

[1709] The terminal displays a list of supermarkets to the user.

[1710] Step 19:

[1711] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[1712] Step 20:

[1713] The terminal sends the order information to the server.

[1714] Step 21:

[1715] The server processes the order and sends a confirmation message to the terminal.

[1716] Step 22:

[1717] The terminal displays an order confirmation message to the user.

[1718] In this way, this system greatly enhances user convenience by consistently supporting the selection of meals that suit the user's mood, the selection of the delivery method, arrangements, and payment.

[1719] Example 1

[1720] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1721] Conventional meal recommendation systems often lack the functionality to not only suggest dishes that suit the user's mood, but also comprehensively support the selection of how the meal will be served, as well as the specific arrangements and payment procedures. Furthermore, when preparing the meal yourself, the process of preparing ingredients is complicated, which increases the user's workload. Furthermore, these systems do not adequately address the issue of food waste, resulting in excess food. Thus, there is a need for a meal recommendation system that aims to achieve both user convenience and sustainability.

[1722] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1723] In this invention, the server includes: [means for suggesting dishes based on the mood input by the user; [means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant"; and [means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself."] This makes it possible [to suggest dishes based on the mood input by the user, and comprehensively select the delivery method, make specific arrangements, and make payment].

[1724] "User" refers to an end user who uses the system and inputs their mood for the day and the desired delivery method.

[1725] The term "server" refers to an information processing device that receives and processes data entered by a user or a virtual server on a network.

[1726] "Terminal" refers to a device that allows a user to access the system and input their mood, select suggested dishes, and select serving methods.

[1727] "Suggesting" refers to generating and presenting a list of appropriate dishes based on the mood data entered by the user.

[1728] "Delivery method" refers to the means by which users can obtain and consume food, and refers to three methods: cooking it yourself, delivery, or restaurant.

[1729] A "recipe" is a set of instructions for cooking a dish, including the necessary ingredients and steps.

[1730] "Ingredient list" refers to the list of ingredients needed to prepare the selected dish.

[1731] "Arranging ingredients" refers to preparing and ordering the necessary ingredients.

[1732] "Delivery" refers to the delivery of the food selected by the user from a nearby affiliated restaurant via a delivery service.

[1733] "Restaurant" refers to a restaurant that serves the food selected by the user.

[1734] "Affiliated stores" refer to affiliated stores that provide food in cooperation with the system.

[1735] "Order" refers to a request to purchase a dish or ingredients selected by a User.

[1736] "Remittance processing" refers to the procedure for transferring money when a user treats someone else or donates to relief efforts.

[1737] "Natural language processing technology" refers to artificial intelligence technology that analyzes text data and helps it understand its meaning.

[1738] "Food waste" refers to food that is discarded without being consumed.

[1739] The present invention relates to a system that proposes dishes tailored to the user's mood, and handles the selection, arrangement, and payment of the delivery method. This system uses multiple hardware and software components to perform specific data processing and calculations. Specific embodiments are described below.

[1740] System Configuration

[1741] User terminal

[1742] The device on which the user launches the app (smartphone, tablet, PC, etc.)

[1743] Responsible for sending input data and receiving and displaying display content

[1744] server

[1745] Analysis and recommendations using natural language processing technology

[1746] Specific software used for mood analysis: Google Cloud Natural Language API

[1747] Processing flow

[1748] 1. Mood input

[1749] The user launches the app and enters their mood for the day in text.

[1750] The device transmits the mood data to the server.

[1751] 2. Mood analysis and recipe suggestions

[1752] The server uses natural language processing technology (Google Cloud Natural Language API) to analyze the user's mood.

[1753] The server generates a list of suggested dishes based on the analysis results.

[1754] The terminal displays the recipe list to the user.

[1755] 3. Selection of delivery method

[1756] When the user selects a dish, the server generates the corresponding delivery method (make-yourself, delivery, restaurant).

[1757] The terminal displays the provision methods to the user, and the user selects one.

[1758] If you make it yourself

[1759] The server generates a recipe and a list of ingredients for the selected dish.

[1760] The terminal displays the recipe and ingredients list to the user.

[1761] When a user requests material arrangement, the server generates a list of nearby supermarkets or online supermarkets (for example, the API of an online supermarket).

[1762] When a user orders ingredients, the server processes the order and displays a confirmation message.

[1763] For delivery

[1764] The server generates a list of dishes from nearby partner stores (stores that offer delivery).

[1765] The terminal displays this to the user, who then selects the food and restaurant and places the order.

[1766] The server processes the order and sends an estimated delivery time and order confirmation to the terminal.

[1767] In the case of a restaurant

[1768] The server generates a list of nearby affiliated restaurants.

[1769] The terminal displays this to the user, who then selects a restaurant and enters reservation details.

[1770] The server processes the reservation and sends a confirmation message to the terminal.

[1771] High-value-added features

[1772] If the user chooses to treat others or make a donation, the server generates information about the other person and a list of donation recipients.

[1773] The terminal displays this to the user, and once the remittance amount is set, the server processes the remittance and sends a confirmation message.

[1774] Addressing the food waste problem

[1775] The server adjusts the amount of ingredients based on the user's choice of food and number of people.

[1776] The device displays the adjusted ingredient list to the user, ensuring no excess ingredients are used.

[1777] Specific examples

[1778] For example, if a user inputs into the app, "I want to eat something spicy today," the server analyzes the data and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby affiliated curry restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the ingredients can be ordered directly.

[1779] Prompt Sentence Examples

[1780] Below are some examples of prompts to input to the generative AI model.

[1781] "User says they want something spicy today. Suggest a dish based on that and offer options for delivery, restaurants, or cook-it-yourself."

[1782] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1783] Step 1:

[1784] The user starts the app and enters their mood for the day in text. This text becomes the input data.

[1785] Step 2:

[1786] The device receives mood data entered by the user and sends the data to the server. The specific operation of the device is to send text data to the server as an HTTP request.

[1787] Step 3:

[1788] The server uses natural language processing technology to analyze the received mood data. This analysis generates a list of dishes that match the user's mood. Using the user's mood text as input data, it performs data calculations using tools such as the Google Cloud Natural Language API, and obtains a list of dishes as output.

[1789] Step 4:

[1790] The server sends the generated dish list to the device. Specifically, it encodes the dish list in JSON format and sends it to the device as an HTTP response.

[1791] Step 5:

[1792] The device receives the recipe list from the server and displays it to the user. The displayed recipe list becomes the output data. The device parses the data and displays it on the user interface.

[1793] Step 6:

[1794] The user selects a favorite dish from the list of dishes. This selection becomes the input data for the next process.

[1795] Step 7:

[1796] Based on the user's food selection, the server generates the corresponding delivery method (cook, delivery, restaurant) and sends it to the terminal. The input is the user's food selection data, and the output is a list of delivery methods.

[1797] Step 8:

[1798] The terminal displays a list of delivery methods to the user, specifically, a delivery method selection screen.

[1799] Step 9:

[1800] The user selects the delivery method (make it yourself, delivery, restaurant). The selected delivery method becomes the input data for the next step.

[1801] If you're making it yourself:

[1802] Step 10:

[1803] The server generates a recipe and a list of ingredients for the selected dish. The input is the user's dish selection data, and the output is the recipe and the list of ingredients.

[1804] Step 11:

[1805] The server sends the recipe and ingredient list to the device, encoding the data in JSON format and sending it as an HTTP response.

[1806] Step 12:

[1807] The terminal displays this to the user. Specifically, the recipe and ingredient list are displayed on the user interface.

[1808] Step 13:

[1809] The user presses the "Arrange materials" button, which becomes the input data for the next step.

[1810] Step 14:

[1811] The terminal sends a material arrangement request to the server. Specifically, the request data is sent as an HTTP request.

[1812] Step 15:

[1813] The server generates a list of nearby supermarkets and online supermarkets, and sends the ordering screen to the terminal. Using the user's location information and material ordering request as input data, it performs data calculations and obtains a supermarket list as output.

[1814] Step 16:

[1815] The terminal displays the super list to the user. Specifically, the terminal displays the order screen.

[1816] Step 17:

[1817] The user orders materials, and the order data becomes the input data for the next step.

[1818] Step 18:

[1819] The server processes the order and sends a confirmation message to the terminal. The order request data is used as input and the order confirmation message is obtained as output.

[1820] For delivery:

[1821] Step 10:

[1822] The server generates a list of dishes available from nearby partner restaurants and sends it to the terminal. The input is the user's food selection data, and the output is a list of dishes available for delivery.

[1823] Step 11:

[1824] The terminal displays this to the user. Specifically, the recipe list is displayed on the user interface.

[1825] Step 12:

[1826] The user selects a specific restaurant and food item and confirms the order. The order data becomes the input data for the next step.

[1827] Step 13:

[1828] The terminal sends the order confirmation data to the server. Specifically, the order data is sent as an HTTP request.

[1829] Step 14:

[1830] The server processes the order, sends the estimated delivery time and order confirmation to the terminal, and notifies the user. The input data is the order data, and the output is the estimated delivery time and order confirmation message.

[1831] If you're eating at a restaurant:

[1832] Step 10:

[1833] The server generates a list of nearby affiliated restaurants and sends it to the terminal. The input data is the user's food selection data, and the output data is the restaurant list.

[1834] Step 11:

[1835] The terminal displays this to the user. As a specific operation, the restaurant list is displayed on the user interface.

[1836] Step 12:

[1837] The user selects a particular restaurant and enters reservation details, which serve as input data for the next step.

[1838] Step 13:

[1839] The terminal sends the reservation details data to the server. Specifically, the reservation data is sent as an HTTP request.

[1840] Step 14:

[1841] The server processes the reservation information and sends a confirmation message to the terminal to notify the user. The reservation details are input and the reservation confirmation message is output.

[1842] (Application example 1)

[1843] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1844] In recent years, users have been demanding a system that allows them to easily and quickly select the meal that best suits their mood that day, and then select the delivery method (cooking, delivery, or restaurant), arrange the meal, and pay for it all at once. However, existing systems that achieve this have issues such as insufficient suggestions for dishes that match the mood, insufficient arrangements and order processing depending on the delivery method, and a lack of high-value-added functions. A system that can effectively solve these issues is needed.

[1845] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1846] In this invention, the server includes a means for suggesting dishes based on the mood input by the user, a means for allowing the user to select the delivery method for the suggested dishes from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and a list of necessary ingredients and arranging for the ingredients if the user selects "make it yourself." This allows the user to choose a dish that suits their mood that day and comprehensively handle the arrangements and payment according to the selected delivery method. Furthermore, the server also includes a means for ordering food from a nearby affiliated restaurant and arranging delivery if the user selects delivery, a means for making a reservation at a nearby affiliated restaurant if the user selects restaurant, and a means for selecting recipient information and a donation destination and processing a remittance if the user wants to treat someone or donate to a relief effort, thereby providing an even more convenient service.

[1847] The "means for suggesting dishes based on the mood input by the user" is a function for analyzing the mood information input by the user and suggesting suitable dishes based on the analysis results.

[1848] "A means for allowing the user to select the delivery method for the proposed dish from cooking it themselves, delivery, or restaurant" is a function in which the system presents the user with options for delivery methods, allowing the user to select from those options.

[1849] "When the user selects to cook it themselves, a means of displaying the corresponding recipe and a list of ingredients required, and arranging for the ingredients" is a function that, when the user selects to cook a dish themselves, displays the recipe and list of ingredients required for that dish, and even takes them through the process of purchasing the ingredients.

[1850] "Means of ordering food from nearby affiliated stores and arranging delivery when the user selects delivery" refers to a function in which, when the user selects delivery, the system orders food from nearby affiliated stores and arranges for delivery to the specified address.

[1851] "Means for making reservations at nearby affiliated restaurants when a user selects a restaurant" is a function that allows the system to process reservations at nearby affiliated restaurants when a user selects to eat at a restaurant.

[1852] "A means for selecting the recipient and donation destination and carrying out the money transfer process when treating someone or donating to a relief effort" is a function that allows a user to select the recipient and donation destination and carry out the money transfer process when treating someone or donating to a relief effort.

[1853] "Means for analyzing a user's mood input, suggesting dishes based on the analysis results, selecting a specific serving method based on the selected dish, displaying optimal delivery options, and processing the order and notifying the user of the delivery time if the user places an order" refers to a series of functions that analyze mood information entered by a user, suggest dishes based on the results of the analysis, select a serving method according to the dish selected by the user, display delivery options, process the order, and notify the user of the delivery time.

[1854] This invention is a system that allows users to easily find a dish that suits their mood of the day, select a delivery method, and comprehensively handle all the necessary arrangements and payments. This system includes means for analyzing the mood entered by the user and suggesting dishes based on that, means for displaying delivery methods corresponding to the selected dish, and means for making specific arrangements and payments based on the delivery method selected by the user.

[1855] First, the user launches an application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. The server uses natural language processing technology to analyze the user's mood and generates a list of dishes that match the mood based on the analysis results. The generated list of dishes is presented to the user via the device, from which the user can select their preferred dish.

[1856] Based on the user's choice of food, the server sends the corresponding delivery method (cook, delivery, restaurant) to the device, which then displays it to the user, who can then select the desired delivery method.

[1857] If the user selects "Make it yourself," the server sends the recipe for the selected dish and a list of the necessary ingredients to the device. The device displays this to the user, and when the user presses the "Arrange ingredients" button, the device sends the request to the server. The server generates a list of nearby supermarkets and online supermarkets, and displays a screen on the device for completing the ingredient arrangement. Once the user selects a supermarket and orders the ingredients, the server processes the order and displays a confirmation message to the user via the device.

[1858] If the user selects "Delivery," the server generates a list of available dishes from nearby partner restaurants and presents it to the user through the terminal. Once the user selects a specific restaurant and confirms the order, the terminal sends that information to the server. The server processes the order, sends an order confirmation to the terminal with an estimated delivery time, and notifies the user.

[1859] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and presents it to the user through the terminal. When the user selects a specific restaurant and enters reservation details, the terminal sends the information to the server. The server processes the reservation information and notifies the user through the terminal of a reservation confirmation.

[1860] This system also has functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates a list of recipients and donation recipients and presents it to the user via the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and displays a confirmation message to the user via the terminal.

[1861] Furthermore, this system addresses the issue of food waste by allowing users to adjust the amount of ingredients and dishes suggested, thereby preventing excess food from being produced.

[1862] For example, if a user inputs "I want something a little spicy today" into the app, the server analyzes it and generates suggestions such as "curry" or "tacos." If the user selects "curry" and then "delivery," they can order food from a nearby curry specialty restaurant and have it delivered. If the user selects "make it yourself," a curry recipe and a list of necessary ingredients are displayed on the device, and the user can then order the ingredients.

[1863] Example prompt: "Right now I'm feeling very relaxed and in the mood for something sweet and warm. Can you suggest a dish that would fit this mood?"

[1864] In this way, the system of the present invention provides comprehensive support from suggesting meals that suit the user's mood to making arrangements and making payments, thereby greatly improving user convenience.

[1865] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1866] Step 1:

[1867] The user launches the application installed on their smartphone and inputs their mood for the day. The input text data is sent to the server via the device. This sends the user's mood information to the server, which then generates input data for analysis.

[1868] Step 2:

[1869] The server receives the user's mood information and analyzes it using natural language processing technology. The analysis involves breaking down the text data and extracting emotions and keywords. A generative AI model is used to generate a list of dishes that match the user's mood. The analysis results in a list of suggested dishes that match the user's mood.

[1870] Step 3:

[1871] The generated list of suggested dishes is sent from the server to the device. The device then presents this list to the user, allowing the user to visually check the suggested dishes. The user then selects their preferred dish from the presented list. This selection result is then sent back from the device to the server.

[1872] Step 4:

[1873] Based on the user's choice of food, the server generates a corresponding delivery method (cook, delivery, restaurant) for the proposed food and sends it to the device. The device then displays the delivery method options to the user, allowing the user to select the desired delivery method.

[1874] Step 5:

[1875] The user selects the desired delivery method from the options (make it yourself, delivery, restaurant) and selects it on the device. The selection result is sent to the server via the device. The server prepares the next step based on the delivery method selected by the user.

[1876] Step 6 (If you're building it yourself):

[1877] If the user selects "Make it yourself," the server generates a recipe and a list of ingredients for the selected dish and sends them to the device. The device displays this to the user and provides an "Arrange ingredients" button. When the user presses the "Arrange ingredients" button, a request is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for completing ingredient arrangements. Once the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[1878] Step 7 (for delivery):

[1879] If the user selects "Delivery," the server generates a list of dishes available from nearby partner restaurants and sends it to the device. The device presents this list to the user, who then selects a specific restaurant and confirms the order, which is then sent to the server. The server processes the order, calculates the estimated delivery time, and sends a confirmation message to the device.

[1880] Step 8 (for restaurants):

[1881] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The terminal presents this list to the user, who then selects a specific restaurant and enters reservation details, which are then sent to the server. The server processes the reservation information and sends a reservation confirmation to the terminal.

[1882] Step 9 (if giving or donating):

[1883] If the user selects to treat or donate, the server generates a list of recipients and donation recipients and sends it to the terminal. The terminal presents the list to the user, who then selects information and sets the amount to be transferred, and the information is sent to the server. The server then processes the transfer and displays a confirmation message on the terminal.

[1884] This system improves user convenience by suggesting meals that suit the user's mood and providing comprehensive support for arrangements and payment depending on the delivery method.

[1885] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1886] The present invention combines a system that suggests appropriate dishes based on the user's mood with an emotion engine that recognizes the user's emotions. This invention allows for a more precise understanding of the user's emotional state, and allows for the selection of dish suggestions and serving methods based on that understanding.

[1887] Mood and emotion analysis and food suggestions

[1888] The user launches the app and inputs their mood for the day. For example, they might input "I'm feeling depressed today." The device then sends the user's input to the emotion engine, which analyzes the user's input text and recognizes their emotional state.

[1889] The server uses a natural language processing engine to analyze the user's mood, and at the same time, recognizes their emotional state through an emotion engine. For example, when someone says "I'm feeling depressed," the server recognizes the emotion "sad."

[1890] Based on the results of mood and emotion analysis, the server generates a list of recipe suggestions that take into account the user's emotional state, such as suggesting dishes like "warm soup" or "comfort food."

[1891] Select delivery method

[1892] When the user selects their preferred dish from a list of candidate dishes, the server generates a delivery method (cook it yourself, delivery, restaurant) and presents it to the user via their terminal.

[1893] How to make it yourself

[1894] When the user selects "Make it yourself" as the delivery method, the server generates a recipe for the dish and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, the device sends an ingredient arrangement request to the server. The server generates a list of nearby supermarkets and online supermarkets and displays a screen on the device for arrangements. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device. The device then displays the confirmation message to the user.

[1895] Delivery process

[1896] When the user selects "Delivery" as the delivery method, the server generates a list of dishes from nearby partner restaurants and sends it to the terminal. When the user selects a specific restaurant and confirms the order, the terminal sends the order information to the server. The server processes the order and calculates the estimated delivery time. The estimated delivery time and order confirmation information are sent to the terminal and notified to the user.

[1897] Restaurant Processing

[1898] When the user selects "Restaurant" as the delivery method, the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user.

[1899] High-value-added features

[1900] This system also includes functions for treating others and making donations to relief activities. When a user selects to treat or donate, the server generates information about the recipient and a list of donation recipients and sends them to the terminal. When the user selects information and sets the amount to send, the terminal sends the information to the server, which then processes the transfer and sends a confirmation message to the terminal. The terminal then displays the confirmation message to the user.

[1901] Addressing the food waste problem

[1902] The system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes suggested, making it possible to avoid excess food.

[1903] Specific examples

[1904] For example, if a user inputs "I'm feeling down today," the server analyzes it and recognizes emotions such as "sad." Based on the user's emotional state, the server suggests "hot soup" or "comfort food." If the user selects "hot soup" and "delivery" as the delivery method, the soup can be ordered from a nearby affiliated store and delivered. If the user selects "make it yourself," the recipe and list of ingredients are displayed, and the user can order the ingredients right away.

[1905] In this way, the present invention comprehensively supports the selection of meals based on the user's mood and emotions, the selection of delivery methods, arrangements, and payment, thereby increasing user convenience and satisfaction.

[1906] The processing flow will be explained below.

[1907] Mood and sentiment analysis and food suggestion processing steps

[1908] Step 1:

[1909] The user launches the app and enters their mood for the day, for example, "I'm feeling depressed today."

[1910] Step 2:

[1911] The terminal sends the user's input to the emotion engine.

[1912] Step 3:

[1913] The emotion engine analyzes the user's input text and recognizes their emotional state. In this case, it recognizes the emotion "sad" from the input "I'm feeling depressed."

[1914] Step 4:

[1915] The terminal transmits the user's input and the emotion engine's recognition results to the server.

[1916] Step 5:

[1917] The server uses a natural language processing engine to analyze the user's mood and also takes into account the results of the emotion engine to generate a list of recipe candidates.

[1918] Step 6:

[1919] The server sends the generated list of dish candidates to the terminal.

[1920] Step 7:

[1921] The device will display a list of food suggestions to the user, such as "hot soup" or "comfort food."

[1922] Step 8:

[1923] The user selects "warm soup" from the displayed food options and taps the "Select" button.

[1924] Delivery Method Selection Process Steps

[1925] Step 9:

[1926] The terminal transmits the user's selection to the server.

[1927] Step 10:

[1928] The server generates available delivery methods (make-it-yourself, delivery, restaurant) for the selected dish and sends them to the terminal.

[1929] Step 11:

[1930] The device will display options for delivery to the user, such as "Make it yourself," "Delivery," or "Restaurant."

[1931] Specific processing steps if you make it yourself

[1932] Step 12:

[1933] The user selects "Create it yourself" as the provision method and taps the "Next" button.

[1934] Step 13:

[1935] The terminal transmits the user's selection to the server.

[1936] Step 14:

[1937] The server generates a recipe and a list of ingredients for the selected dish and sends them to the terminal.

[1938] Step 15:

[1939] The terminal displays the recipe and ingredients list to the user.

[1940] Step 16:

[1941] The user taps the "Arrange Materials" button.

[1942] Step 17:

[1943] The terminal sends a material arrangement request to the server.

[1944] Step 18:

[1945] The server generates a list of nearby supermarkets and online supermarkets and sends a screen for making arrangements to the terminal.

[1946] Step 19:

[1947] The terminal displays a list of supermarkets to the user.

[1948] Step 20:

[1949] The user selects a supermarket, orders ingredients, and taps the "Confirm Order" button.

[1950] Step 21:

[1951] The terminal sends the order information to the server.

[1952] Step 22:

[1953] The server processes the order and sends a confirmation message to the terminal.

[1954] Step 23:

[1955] The terminal displays a confirmation message to the user.

[1956] Specific processing steps for delivery

[1957] Step 12:

[1958] The user selects "Delivery" as the delivery method and taps the "Next" button.

[1959] Step 13:

[1960] The terminal transmits the user's selection to the server.

[1961] Step 14:

[1962] The server generates a list of dishes that can be provided by nearby affiliated stores and transmits it to the terminal.

[1963] Step 15:

[1964] The terminal displays a list of affiliated stores to the user.

[1965] Step 16:

[1966] The user selects a specific store and places an order.

[1967] Step 17:

[1968] The terminal sends the order information to the server.

[1969] Step 18:

[1970] The server processes the order and calculates the estimated delivery time.

[1971] Step 19:

[1972] The server sends the estimated delivery time and order confirmation to the terminal.

[1973] Step 20:

[1974] The terminal notifies the user of the delivery time and order confirmation.

[1975] Specific processing steps for restaurants

[1976] Step 12:

[1977] The user selects "Restaurant" as the delivery method and taps the "Next" button.

[1978] Step 13:

[1979] The terminal transmits the user's selection to the server.

[1980] Step 14:

[1981] The server generates a list of nearby affiliated restaurants and sends it to the terminal.

[1982] Step 15:

[1983] The terminal displays a list of affiliated restaurants to the user.

[1984] Step 16:

[1985] The user selects a particular restaurant and enters reservation details.

[1986] Step 17:

[1987] The terminal transmits the reservation information to the server.

[1988] Step 18:

[1989] The server processes the reservation information and sends a reservation confirmation to the terminal.

[1990] Step 19:

[1991] The terminal displays a reservation confirmation to the user.

[1992] In this way, the system can increase user satisfaction and convenience by performing a consistent process from selection of delivery method, arrangement, and payment based on the user's mood and emotions.

[1993] Example 2

[1994] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1995] In modern society, there is a demand for systems that can enhance user convenience and satisfaction by suggesting meals that suit individual users' moods and emotions and selecting appropriate delivery methods. However, conventional systems have difficulty precisely analyzing users' moods and emotions and selecting optimal meal suggestions and delivery methods based on that analysis. In addition, to address the food waste issue, there is a need for a function that adjusts the amount of food consumed to prevent excess ingredients from being generated.

[1996] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for suggesting dishes based on the mood and emotions input by the user, a means for allowing the user to select the delivery method for the suggested dish from "make it yourself," "delivery," or "restaurant," and a means for displaying the corresponding recipe and list of necessary ingredients when the user selects "make it yourself," and arranging for the ingredients. This makes it possible to suggest optimal dishes and select delivery methods based on the user's mood and emotions, and to address the food waste issue.

[1997] "User" refers to an individual or organization that uses the system.

[1998] "Mood" refers to the psychological and emotional state that a user is feeling at that time.

[1999] "Cooking" refers to food prepared using ingredients.

[2000] "Suggestion" refers to the options and ideas the system offers to the user.

[2001] "Delivery method" refers to the method by which the food is provided to the user, including options such as cook-it-yourself, delivery, and restaurant.

[2002] "Cook it yourself" refers to the user cooking the food themselves.

[2003] "Delivery" refers to a service that delivers food.

[2004] "Restaurant" means a food establishment that serves food.

[2005] A "recipe" is a set of instructions that explains how to prepare a dish.

[2006] An "ingredient list" refers to a list of ingredients needed to make a dish.

[2007] "Arrangements" refers to preparing and ordering needed supplies and services.

[2008] "Affiliated stores" refer to stores that provide services in cooperation with the system.

[2009] "Reservation" means applying in advance to use the Service at a specific date and time.

[2010] "Remittance" refers to sending money to another person.

[2011] The "food waste problem" refers to the social and economic problems caused by food ingredients and food going to waste.

[2012] "Natural language processing" refers to the technology that enables computers to understand and process human language.

[2013] "Emotion recognition" refers to the technology of analyzing and recognizing emotions from a user's text or voice.

[2014] The present invention is a system that suggests appropriate dishes based on the user's mood and emotions and provides a method for obtaining these dishes. This system is realized through interactions between a server, a terminal, and a user.

[2015] System configuration

[2016] This system involves the user inputting their mood and emotions, the server analyzing their emotions and suggesting dishes, and various methods of serving dishes.

[2017] 1. User input of mood and emotion

[2018] The user launches the application on their smartphone or other device and inputs their mood or emotion for the day in text. For example, they might say, "I'm feeling depressed today." This input data is then sent from the device to the server.

[2019] 2. Emotion analysis and recipe suggestions by the server

[2020] The server analyzes the received user input data using a natural language processing (NLP) engine and an emotion recognition engine. Specifically, the NLP engine (e.g., OpenAI's GPT-4) analyzes the user's text, and the emotion recognition engine recognizes the user's mood and emotional state.

[2021] For example, if a user inputs "I'm feeling down today," the emotion recognition engine will recognize the emotion as "sad." Based on this analysis, the server will generate a list of food candidates. If the analysis result is "sad," dishes such as "warm soup" and "comfort food" will be suggested.

[2022] 3. Proposal of food serving methods

[2023] Once the user selects their preferred dish from the list of suggested dishes, the server then generates the delivery method (cook it yourself, delivery, restaurant) and sends it to the terminal.

[2024] Implementation of the provision method

[2025] How to make it yourself

[2026] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server then generates a list of nearby supermarkets and online supermarkets and displays an ordering screen on the device. When the user selects a supermarket and orders ingredients, the server processes the order and sends a confirmation message to the device.

[2027] Delivery process

[2028] If the user selects "Delivery," the server generates a list of dishes from nearby partner restaurants and sends it to the device. Once the user selects a restaurant and a dish and confirms the order, the device sends the order information to the server. The server processes the order, calculates the estimated delivery time, sends it to the device, and notifies the user.

[2029] Restaurant Processing

[2030] If the user selects "Restaurant," the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a specific restaurant and enters reservation details, and the terminal sends the reservation information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal to display to the user.

[2031] Addressing the food waste problem

[2032] This system also addresses the issue of food waste, and has a function to adjust the amount of ingredients and dishes it suggests, which helps prevent excess food from being produced.

[2033] Prompt Sentence Examples

[2034] We will build a system that will provide appropriate recipe suggestions in response to input such as "I'm feeling down today," and then suggest a serving method based on that. We will also explain how to handle delivery, restaurants, and home cooking. (The model includes an emotion recognition engine and an NLP engine.)

[2035] Through these functions, the present invention provides optimal recipe suggestions and serving methods based on the user's mood and emotions, greatly improving user convenience and satisfaction.

[2036] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2037] Step 1: Launch the app and enter your mood

[2038] A user launches an application on a smartphone or other device. The app provides the user with a text input field asking, "How are you feeling today?" The user enters "I'm feeling down today" and taps the submit button. This input data is sent from the device to the server. The specific input is text data, and the output is HTTPS communication to the server.

[2039] Step 2: Sentiment Analysis

[2040] The server stores the received user input data and sends it to the emotion engine. The emotion engine (specifically OpenAI's GPT-4) analyzes the input text and recognizes the emotional state. As a result of the analysis, it recognizes an emotion such as "sad" from the text "I'm feeling depressed today." The input is text data, and the output is the recognition result of the emotional state (e.g., "sad").

[2041] Step 3: Generate dish candidates

[2042] The server generates candidate dishes from a recipe database based on the emotion analysis results. In the example above, "warm soup" and "comfort food" are selected as candidate dishes corresponding to the emotion "sad." The server then sends the selected candidate dish list to the device. The input is the recognition result of the emotional state, and the output is a candidate dish list.

[2043] Step 4: Propose delivery method

[2044] The user selects "hot soup" from the list of food candidates. The device sends this selection data to the server. The server then generates options for delivery methods (make it yourself, delivery, restaurant) and sends them to the device. The input is the food selection data, and the output is the delivery method options. When the user selects "delivery" on the device, the device sends that information to the server.

[2045] Step 5: DIY

[2046] If the user selects "Make it yourself," the server generates a corresponding recipe and a list of required ingredients and sends them to the device. The device displays the recipe and list of ingredients. When the user taps the "Arrange ingredients" button, a request to arrange ingredients is sent to the server. The server generates a list of nearby supermarkets and online supermarkets and displays the ordering screen on the device. When the user orders ingredients, the server processes the order and sends a confirmation message to the device. The input is the "Make it yourself" selection and the ingredient arrangement request, and the output is the recipe, ingredient list, and ingredient order confirmation message.

[2047] Step 6: Processing in case of delivery

[2048] If the user selects "Delivery," the server generates a list of dishes from nearby affiliated restaurants and sends it to the terminal. When the user selects a restaurant and a dish and confirms the order, the terminal sends that information to the server. The server processes the order, calculates the estimated delivery time, and sends it to the terminal along with order confirmation information. The terminal notifies the user of the estimated delivery time and order confirmation information. The input is the "Delivery" selection and order information, and the output is the estimated delivery time and order confirmation information.

[2049] Step 7: Restaurant Case

[2050] If the user selects "Restaurant", the server generates a list of nearby affiliated restaurants and sends it to the terminal. The user selects a particular restaurant and enters reservation details, and the terminal sends that information to the server. The server processes the reservation information and sends a reservation confirmation to the terminal. The terminal displays the reservation confirmation to the user. The input is the "Restaurant" selection and reservation details, and the output is the reservation confirmation information.

[2051] Step 8: Addressing the food waste issue

[2052] This system has the function of appropriately adjusting the amount of dishes and ingredients selected by the user to address the food waste issue. The server analyzes this data and adjusts the amount of dishes and ingredients suggested to avoid excess food. The input is the user's selected data, and the output is the adjusted dish and ingredient suggestions.

[2053] (Application example 2)

[2054] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2055] In modern society, there is a demand for systems to suggest appropriate dishes and determine how they are served based on the user's mood and emotions. However, conventional systems have difficulty accurately understanding the user's emotional state, and are therefore unable to make appropriate dish suggestions based on that. Furthermore, while there is a need to address the issue of food waste, current systems do not adequately consider this point. This calls for the development of new technologies to improve user satisfaction and reduce food waste.

[2056] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: [means for suggesting dishes based on the mood and emotion input by the user; [means for allowing the user to select the delivery method for the suggested dishes from cook-it-yourself, delivery, or restaurant; and [means for analyzing the mood and emotion input by the user using an emotion engine and a natural language processing engine and displaying appropriate delivery dish candidates.] This makes it possible to suggest dishes and select delivery methods that match the user's current emotional state, improving user satisfaction and addressing the issue of food waste.

[2057] "User" refers to an individual user of the system.

[2058] "Mood" refers to a temporary psychological state or emotion that a user has.

[2059] "Emotion" more specifically represents the user's psychological state and refers to an internal reaction based on the mood and state of the day.

[2060] "Cuisine Suggestions" refers to meal options and details provided based on the user's mood and emotions.

[2061] "Delivery method" refers to the means and options for delivering food to the user, including cooking it yourself, delivery, and choosing from a restaurant.

[2062] "Delivery" refers to a service that delivers the selected dish to a location specified by the user.

[2063] "Emotion engine" refers to a technical means for analyzing a user's input text and recognizing its emotional state.

[2064] "Natural language processing engine" refers to a technical means for analyzing text entered by a user and understanding its content.

[2065] "Dish suggestions" refer to suggested meal options based on the user's emotions and moods.

[2066] The "food waste problem" refers to the social and economic problems that arise when food ingredients and food are wasted.

[2067] An "ingredient list" is a list of ingredients needed to make a particular dish.

[2068] This invention is a system that analyzes the mood and emotions input by the user, and based on that, suggests appropriate dishes and selects how to serve them. The system is made up of the following components:

[2069] 1. System Program Configuration

[2070] The system consists of the following main modules:

[2071] Emotion Engine

[2072] Natural Language Processing Engine

[2073] Food suggestion module

[2074] Delivery method selection module

[2075] Order Processing Module

[2076] Emotion Engine

[2077] The emotion engine analyzes the text data entered by the user and recognizes their emotional state. The engine utilizes the TextBlob library in Python to accurately analyze the emotions in the text.

[2078] Natural Language Processing Engine

[2079] The natural language processing engine is used to analyze and understand the mood and emotions input by the user, which allows the system to determine what kind of food is appropriate based on the user's mood.

[2080] Food suggestion module

[2081] The recipe suggestion module suggests multiple recipe options to the user based on data obtained from the emotion engine and natural language processing engine. The user can then select from the suggested dishes to proceed to the next step.

[2082] Delivery method selection module

[2083] The delivery method selection module presents delivery methods for the dish selected by the user, such as cooking it yourself, delivery, or restaurant delivery. Once the user selects a delivery method, the appropriate processing is carried out.

[2084] Order Processing Module

[2085] The order processing module orders food from nearby partner restaurants and arranges delivery if the user selects delivery, and also makes reservations at nearby partner restaurants if the user selects a restaurant.

[2086] 2. System processing method and data calculation

[2087] The hardware used by the system is primarily a smartphone, on which an application is launched and which processes data in conjunction with a server.

[2088] Hardware used

[2089] Smartphone

[2090] Software used

[2091] Python

[2092] Flask

[2093] TextBlob

[2094] Data flow

[2095] 1. The user launches the smartphone app and enters their current mood and a message.

[2096] 2. The entered data is sent to the server, where it is analyzed using an emotion engine and natural language processing engine.

[2097] 3. Based on the analysis results, the server generates a list of candidate dishes and presents it to the user.

[2098] 4. Once the user selects a dish and decides how it will be served, the server uses that information to perform the corresponding process (display recipe, order delivery, make restaurant reservation).

[2099] 3. Specific Examples

[2100] For example, if a user inputs "I'm tired from work today," the system will recognize the emotion as "tired" and suggest food options such as energy drinks and coffee. If the user selects from these options and chooses delivery, the system will order the selected food from a partner restaurant and deliver it to the user's specified location.

[2101] Prompt Sentence Examples

[2102] Please perform sentiment analysis on the following text: "I'm tired from work today."

[2103] Expected emotion: "tired"

[2104] Suggest recipes based on your emotional state:

[2105] Emotional state: "tired"

[2106] Food options: ["Energy Drink", "Coffee"]

[2107] In this way, the present invention realizes appropriate dish suggestions based on the user's mood and emotions, and efficient selection and arrangement of serving methods.

[2108] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2109] Step 1:

[2110] The user starts the smartphone app and inputs their current mood and a message. The input data becomes text data that indicates the user's mood and emotions.

[2111] Input: Text that indicates the user's mood or emotion (e.g., "I'm tired from work today")

[2112] Output: Text data

[2113] Specific operation: The user enters their mood or emotion in text format into the app's input field and presses the send button.

[2114] Step 2:

[2115] The device sends the input text data to the server, which receives the text data and analyzes it using an emotion engine and natural language processing engine.

[2116] Input: Text data

[2117] Output: Analysis results (emotional state)

[2118] Specific operation: The terminal sends text data to the server via an HTTP request, and the server receives the data.

[2119] Step 3:

[2120] The server analyzes the text data using an emotion engine (Text...

Claims

1. A means for suggesting dishes based on a mood input by a user; A means for allowing the user to select the delivery method for the proposed dish from among cooking it themselves, delivery, and restaurant; When the user selects "make it yourself," a corresponding recipe and a list of necessary ingredients are displayed, and a means for the user to arrange for the ingredients; If the user selects delivery, a means for ordering food from a nearby partner restaurant and arranging delivery; A means for making a reservation at a nearby affiliated restaurant when the user selects a restaurant; When treating someone or donating to relief activities, a means for selecting the recipient's information and donation destination and processing the remittance; A system including:

2. The system according to claim 1, wherein the system analyzes the mood input by the user using natural language processing and suggests appropriate dishes.

3. The system according to claim 1, which addresses the food waste problem by adjusting the dishes and ingredients suggested to prevent excess food from being produced.

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